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Blog Posts from the team at Budgeting Solutions

Separating out the wheat from the chaff can be challenging and sometimes the right facts are hard to find.  Our blogs contain a wealth of information gathered from many years of experience by our consultants dealing with everyday issues in projects on client sites.

They may provide clear insight on particular problems or act as a launching pad to clarify your thoughts on issues with how to deliver robust performance management solutions.

Main Posts

The 'Budgeting Solutions Way' To Remote Working

Posted by James Salmon at 4/5/2020 4:30:46 PM

Since our inception in 2005, remote working has always occurred and in some circumstances, the norm. 

Given the unprecedented environment we are now operating in, it means that we are working to a 100% remote offering across numerous project kick-offs and live customer engagements. Through our continued use of remote working we utilise a number of reliable technology platforms that make the experience seamless. 

Below we have outlined some of our implementation methodology principles: 

Foundation Phase:

Prior to project kick-off we will be gathering requirements, outlining the model design, defining the user stories and planning the sprint schedule. The User Story definitions (requirements gathering) are typically seen as the most critical part of the entire project.

Define the key stakeholders & subject matter experts (SME) to be present during the different functional sessions and then agree on a series of remote workshops, via video conferencing facilities, reasonable in length, communicating a clear agenda for that workshop along with expected outcomes. If lengthy sessions are required given stakeholder availability, then ensure you schedule adequate ‘breaks’ in order to gather thoughts and get some space between sessions. We promote this to help stimulate process design if nothing else, but also to simply take a breather.  Following these process workshops, we would ask that you write up the user stories offline and then play these back in a wrap up session to the project team. We are available to support in the drafting of user stories as required.

 As always, before moving to implementation, the user stories must be prioritised, measured and arranged into sprints. Ensure consensus between parties on the project plan and that they are signed off before starting the build, as normal. Model design is then underway and communicated to the internal SME’s. 

Implementation Phase:

In many instances, the implementation phase can be more efficiently run remotely than on-site; having less distractions working remotely than on customer site. The key watch-out being engagement during daily scrum meetings, sprint reviews, sprint retrospectives, PMO & Steering Committee meetings which will now be run entirely remotely. Daily virtual/video stand-ups will take place at the start of each day outlining what was done yesterday, what will be done today and any risks or blocking actions stopping that day’s tasks. You should consider a wrap up call at the end of each day. These in-day sessions can be simple 10-15 minute video calls but important to ensure everyone is clear and aligned on their roles & expectations for that day.

 Agree the audience of each meeting in advance and ensure everyone has access to the chosen remote working platform so that you don’t eat into critical meeting time worrying about IT issues.  Streamline your scrums as best you can, consider giving a short timeslot to each member of the scrum team and create separate sessions for anything needing a longer discussion but not the entire audience. The Model Building team will remain in constant communication throughout a working day with a blend of group chat and virtual meetings. 


At this stage it is critical we establish who the testers will be and to communicate what is expected from them before commencing. Throughout the testing it is vital model builders are available and communication channels are clear. As a team we agree and nominate at UAT lead to consolidate all defects and playback to the project team – these discussions are more appropriate with a small audience. 


The key objectives of the Deployment phase are to; get buy-in from the end users, ensure the new Planning Analytics lands successfully and secure a return on investment for the customer. As a natural by-product of the project approach you should be well on your way to delivering on these goals however there are still some remaining tasks to aid in the deployment phase which are mostly delivered remotely in any case:

  • Develop communication plan for the end-users
  • Develop and agree training plan for end users and model builders
  • Handover and discussion of model maintenance and process documentation
  • Gather user feedback as we transition to Go-Live
  • Document, agree and implement on user feedback

Any engagement can have its own unique challenges and client preferences, but we have been fortunate enough to learn the common threats throughout our 15 years in business. 

Whilst we all are dealing in truly unique circumstances, we believe at Budgeting Solutions we are extremely well equipped to continue our successful delivery of IBM Planning Analytics across our new and existing customers. 

Our track record of successfully delivering on remote projects is strong and we look forward to working together as we mitigate this shifting landscape. 

CFOs See Tech Grabbing Larger Share of a Shrinking Budget

Posted by James Salmon at 4/3/2020 8:55:35 AM

Is this the year the straw breaks the camel’s back?

Each year, it seems as if finance is asked to do more with less. This year will be no different, according to the 2020 Finance Key Issues research from The Hackett Group. Most finance executives expect to see a 3.4% decline, on average, in finance’s operating budget. At the same, other parts of the organization continue to expect finance to provide more value to them.

The five biggest enterprise “asks” of finance in 2020, all of which were ranked as highly important by a majority of executives, were:

  • Support enterprise cost-efficiency improvement
  • Support enterprise growth strategies
  • Enable/augment enterprise analytics capability
  • Enable enterprise digital transformation
  • Support enterprise customer-centricity

“Management expectations in the coming year may outstrip finance’s resources,” said The Hackett Group.

The high expectations are helping to drive an increase of 5% to 10% in the share of the finance operating budget dedicated to technology. The uptick is the first in 10 years, said The Hackett Group. “Our research shows that executives are setting aggressive year-over-year targets for digital technologies’ adoption.”

Study respondents projected a rise of 26% in the adoption of data visualization tools, 24% in RPA implementations, 20% in migration to next-gen cloud-based core finance applications, and an 18% increase in the adoption of advanced analytics solutions.

“Our data shows strong growth in the adoption of cloud-based core finance applications,” said Nilly Essaides, senior research director, finance & EPM, The Hackett Group.  “And the encouraging news is that more than 70% of the finance functions that have adopted cloud-based solutions have been able to realize or exceed their business [objectives].”

The realization of business objectives, however, was slightly lower in robotic process automation (68%) and business process management tools (60%). Adoption of RPA is still mainly at a small scale or pilot stage, 69% of executives indicated, which could partly account for the lower percentage of companies that have realized their business objectives thus far.

In the area of analytics, while companies have plowed ahead with large-scale data visualization deployments, only 12% of organizations are deploying advanced analytics on a large scale. And among those that have deployed it, almost half (47%) said the deployment had fallen short of expectations.

According to Essaides, “Without advanced analytics, management cannot make fully informed decisions or make them quickly. So, there’s a tremendous need for finance to improve its data and analytics competencies, adopt new tools, and enhance the business value it provides directly.”

So, what are the surveyed organizations doing to improve finance’s analytics capabilities? The top five strategies executives said they were taking were:

  • Developing analytics’ competencies internally
  • Providing self-service analytics tools
  • Expanding the use of data visualization solutions
  • Increasing internal and external analytics training resources
  • Enhancing data quality and accessiblity

The most concerning aspect of that list was the “low prioritization finance has placed on human capital, including upskilling and reskilling of staff,” Essaides said. “It isn’t even on the top-10 list of overall finance issues for 2020. This suggests that not only does finance need to address the skills needed for the future, but it must also clearly design how services will be executed along with defining both new and old roles within finance to deliver on business expectations.”

The Hackett Group’s study, “Balancing Cost Reduction with Adding Value,” is based on results gathered from nearly 200 executives in finance, HR, IT, and procurement at a global set of midsize and large enterprises.

Early use of AI for finance focused on operations, analytics

Posted by James Salmon at 12/2/2020 8:16:15 AM

CFOs are automating repetitive processes in accounts payable and reporting; widespread use of AI in finance is not likely in the near term. Here's a look at the issues.

Using AI for finance processes has been a compelling idea for years, and it's not hard to find companies that are really doing it.

Machine learning, natural language processing (NLP) and intelligent chatbots are taking over much of the tedious work of accounting, reporting and auditing. They're even performing basic financial analysis and decision-making that used to be unique to humans. But several experts agreed that AI for finance departments is still in the early adoption phase.

Companies are either piloting AI or using it for narrow purposes, said Adrian Tay, managing director of finance and CFO services at Deloitte Consulting. Most are working to identify use cases that will enable them to deploy AI more broadly.

"One CFO recently shared with me that he understood AI at a high level but lacked the time and expertise to really implement a full AI strategy," said Jack McCullough, president of the CFO Leadership Council, an association of senior financial executives, in an email. "[AI for finance] is certainly the love child of analysts, but CFOs in total are not thinking about it."

The long-term potential sounds promising, however.

"We're at the front end of a long and sustained rate of adoption that is going to build over the next three or four years," said Robert Kugel, senior vice president and research director at Ventana Research.

The best AI use cases

Anecdotal evidence suggests AI excels at financial processes that involve repetitive operations on large volumes of data.

"It will eliminate the need for people to do a lot of the boring, repetitive work that they're doing today," Kugel said. "It will make it possible for systems to wrap themselves around the habits and requirements of the user, as opposed to the user having to adapt how they work within the limitations of technology."

Data quality will also improve and, with it, the quality of analytics as AI gets better at flagging errors for people to correct, Kugel said.

AI is also helping with tedious accounts payable tasks, such as confirming that goods were received and that an invoice contains the right items, Tay said. Companies that use automated payments are deploying machine learning to scan payment patterns for deviations.

"If the machine learning algorithm tells them that the probability of the goods having been received and everything being good with that specific invoice, they'll pay that immediately," Tay said.

The software can also look for outliers from the usual spending patterns by vendor, product and region, he said.

Risk sensing is another early use of AI for finance departments. Companies use it to scan news for threats to critical suppliers, he said.

Early deployments of AI for the finance department

A number of organisations have started using AI for finance, though it is challenging to get them to talk. Vendors and system integrators are willing to name some, though.

PwC, for example, reported that client Microsoft uses machine learning and intelligent process automation (IPA) in analytics that performs real-time reviews of sales to ensure resellers comply with the Foreign Corrupt Practices Act. The software can flag potential corruption risks by identifying relationships and anomalies in individual sales.

At financial company Citigroup, employees developed robotic process automation (RPA), data visualization and NLP tools to automate processes such as financial reporting and generate management commentary on financial results.

Some PwC clients are using AI to make the analytics produced by financial planning and analysis (FP&A) departments more predictive or prescriptive, said Bob Woods, partner at PwC.

"We're seeing a lot of work around particular sales forecasts, external forecasts [and] demand forecasts," he said.

Many clients start by using RPA to move information, transform it at the data layer and then add AI or some form of analytics to produce insights (see sidebar). The AI takes on much of the grunt work so FP&A workers can concentrate on analysis.

Meanwhile, the role of AI for finance workers in controlling and compliance is to automate risk prediction, controls and account reconciliation.

"Many companies have multiple environments that they're trying to bring together and reconcile to get comfort with the data before they start using it for predictive forecasting," Woods said.

Tax professionals, which need specialized skills to keep up with country regulatory requirements, are also early users of AI for finance, he said. AI quickly transforms the data they need and makes it more reliable.

There are other areas where using AI for finance shows promise.

"More and more companies and CFOs are starting to take a look at machine learning and AI to help with forecasting," Tay said. "They're also using that to help their employees in the initial problems of baseline budgets, which are typically a very intensive task."

Some companies use NLP-equipped bots to answer questions, such as a person's expenses for the year and whether they were paid.

"Reporting is also another big area in terms of natural language generation, automating some of the initial insights by using the machine versus the analysts writing it up themselves," Tay said.

NLP also enables searching of finance data as machine learning takes over some of the data management of analysts. It can also read and analyse contracts that can number in the thousands.

Many experts think this ability of AI to spot discrepancies in huge databases is tailor-made for the auditing services of the Big Four accounting firms: Deloitte, EY, KPMG and PwC.

 "It can actually scan through and identify terms or conditions or things that we have trained it to look for and highlight those for an auditor," said Will Bible, partner in the audit and assurance practice at Deloitte US. "The auditor can follow up and review and understand the context around those items. It definitely provides the first pass that accelerates and expands how much our auditors can cover," he said.

It’s Time to Upgrade Your Financial Analytics

Posted by James Salmon at 15/1/2020 10:59:45 AM

FP&A leaders under pressure to deliver more timely and accurate analysis should focus on 4 key areas to upgrade their financial analytics capabilities.

The ability to turn around insightful analysis in a timely manner is key to being seen as a trusted business partner. In a world of digital transformation and constant disruption, analysis must keep pace with queries that will change midstream and anticipate questions that have yet to be asked, but should be. To meet these challenges, assess the current state of financial analytics processes.

"Mature reporting processes move beyond simple “board books” toward a more comprehensive “playbook"

“Traditional finance organizations weren’t designed to answer the types of questions that a digital business consistently asks them,” says Christopher Iervolino, Managing VP at Gartner.

Applications must enable a more flexible and collaborative approach with business partners. To that end, says Iervolino, application leaders should first assess their current maturity in four key areas, so they can plot a roadmap for each:

  • Planning and budgeting
  • Integrated financial planning
  • Management and performance reporting
  • Forecasting and modeling


Heavy use of Excel is a good indicator of an immature budgeting process. More mature processes rely less on spreadsheets, and favor purpose-built FP&A solutions that provide access to common databases, manage data scenarios and related workflows, and ensure transparency.


Immature financial planning capabilities often resemble a shadow budget process, with iterative reporting that can take nine months or more to produce results — by which time the results are often outdated or irrelevant. Other earmarks of immaturity are simplistic reports, scarce analytics and a lack of (or visibility into) business-value insights.

"Maturity in integrated financial planning (IFP) is a binary measure: you either have it or you don’t"

“Higher levels of maturity are characterized by a focus on business drivers that impact the financial line items,” says John E. Van Decker, VP Analyst at Gartner. “The level of detail used must be appropriate to test a hypothesis (“what if”) in a way that has business relevance. For example, this may include planning at low product SKU or customer levels, even if it requires tens of thousands of planning elements.”


Most finance departments are just beginning on the path to maturity in integrated financial planning (IFP). Finance departments that struggle to generate business insights in a timely and accurate manner from high-level financial data can rarely support an IFP program.  


By contrast, higher levels of maturity in IFP translate into increased collaboration with other business domains — and greater business influence. For example, a mature IFP program can target specific financial-planning objectives in outside business areas and generate fresh insights for its sales team.


Relatively immature FP&A functions routinely struggle with answering the “why” behind the numbers. In these departments, spreadsheet-based deliverables often focus solely on accounting numbers, and lack many (or any) outside inputs and analytics, making it difficult to generate any insight.


"Less mature FP&A capabilities typically rely on traditional planning and budgeting tools for forecasting and modelling capabilities"


More mature performance reporting takes a holistic approach to answering the “why” behind financial results. Key to the mature state is the ability to capture and integrate a wide variety of data from different sources — from enterprise resource planning tools and FP&A systems to the disparate Microsoft Office files that inevitably float around various outside departments.


Mature reporting processes move beyond simple “board books” toward a more comprehensive “playbook” that incorporates a variety of data, builds a narrative around it and ultimately generates actionable insights.


Less mature FP&A capabilities typically rely on traditional planning and budgeting tools for forecasting and modeling capabilities. These tools tend to be static, and can’t cope with highly complex business environments.


Greater maturity in these areas is marked by the ability to provide faster and more predictive analytics, adjustments “on the fly,” and an emphasis on high performance through leveraging in-memory computing (IMC) and advanced analytics.  


Read more: 3 Steps to Implement Rolling Forecasts


Once application leaders have assessed the current maturity of these key FP&A processes, they can more ably develop roadmaps for upgrades that will ensure that FP&A can understand the questions their business partners are asking today and will likely need to answer in the future. As solutions enabled by artificial intelligence begin to enter the workplace, finance will become an increasingly tech-enabled field.


This article has been updated from the original, published on April 6, 2018, to reflect new events, conditions or research.


How top companies excel with digital and analytics

Posted by James Salmon at 14/1/2020 10:16:27 AM

One of our colleagues recently came across this article from McKinsey and we thought it would be worth sharing with you. 

You'll find the link to the article below:


Happy reading! 

Do we need a specific financial consolidation solution?

Posted by James Salmon at 27/9/2019 5:29:01 PM

In pure accounting terms, financial consolidation is a formal, standardised set of accounting entries which is used to combine the results of several companies in a group that have common ownership.

Typically, this formal process is undertaken at least once a year for the Statutory year-end. However, an organisation can also choose to follow the same process at each month-end when producing its management accounts.

The range of accounting entries and the corresponding notes to the accounts that might be required could easily fill a medium-sized book. There are accountants that just specialise in Consolidation and it can be a complex topic.

For the majority of organisations, these entries can be whittled down to a handful of key topics and it's these which we will focus on here.

Key Considerations for a Financial Consolidation Solution

The key things to consider in deciding if you need a specific financial consolidation tool

The size of the group and the significance of the trading entities.

Most groups will have both companies that trade or companies that act as a group or holding entities. Trading companies carry out the business of the organisation. Holding/group companies typically don’t trade, but handle financing and loans and hold shares in other (trading) companies.

Consider whether the companies are all 100% owned by the group, or whether third parties hold minority interests. The larger the group and the more minority interests there are, the more likely formal consolidation is necessary in monthly accounting.

  • If a group is acquisitive, and/or shareholding percentages change frequently, then again formal monthly consolidation is more likely.
  • Another significant factor is Currency. In order to consolidate across companies with different currencies, a formal translation process is needed. Each company’s results are converted to the group currency, but the currency rates used vary between the P&L and the Balance Sheet (and sometimes other accounts within them). This creates a difference (the Cumulative Translation Amount “CTA”), which needs to be calculated during the translation. Companies with several currencies almost always consolidate each month-end, in some form or other.



Incidentally, Translation for consolidation should not be confused with Transaction gains and losses. We have had many an entertaining whiteboard session explaining the difference.

Inter-Company Trading

When it comes to the need for a formal tool, in our view, the most significant factor is whether you have Inter-company Trading. If one group company sells to another, but from a ‘whole group’ perspective no “real” external sale has taken place, this trade must be eliminated when considering the group results.

If there is significant trading between group companies, then eliminating this each month becomes material enough to consolidate. If the transactions are simply group loans, recharges or interest, it is less significant. Real trading of goods and services is what is seen as significant.

All these considerations will affect a CFO’s decision whether Accounting for Consolidation is needed for accurate monthly management information. Assuming that it is needed at some level, it doesn’t follow that additional tools are needed.

Somewhat confusingly, the process of consolidation does not necessarily need specialist consolidation tools. In the tool we use, IBM Planning Analytics, many consolidations can be achieved within the standard functions, without bolting on the specific Consolidation module.

Specific Consolidation Tool - IBM Cognos Controller

Much of the functionality needed to consolidate can be found in IBM Planning Analytics, formerly known as IBM Cognos TM1. The scalability and flexibility of the solution means Planning Analytics can be tailored to the specific use case of the client.  

IBM Cognos Controller is only needed where complexity increases. If there are minority interests across the group, or the group is very acquisitive, then the Consolidation module has functions to handle this. Similarly, there is a powerful Inter-company Trading Elimination engine to cope with higher inter-company trading volumes. If sub-consolidations are required at different levels in the group structure, again we recommend the Consolidation module.

Going further, some group consolidations can get very intricate. Areas such as the sale of fixed assets between group companies, for instance, can become very involved. If this sort of detail is required, then a specialist consolidation tool like IBM Cognos Controller should be considered. This will be dedicated to handling the most complex situations, but of course, will lack the wider planning and reporting capability of IBM Planning Analytics.

Considerations for your Consolidation Build

Serious consideration should be given to the consultants that implement your consolidation system. Number one is that they understand consolidation from an accountants’ perspective. It is very difficult to build a system if you don’t understand the rules you are configuring for. Not all consultants have accounting qualifications, and not all accountants understand consolidation. Don’t be afraid to ask that your implementation team has the right mix of skills.

In our experience, the majority of Group organisations do not need a full Consolidation module. In a lot of cases a simple aggregation of results, with currency translation, meets a customer’s requirements. Its all a question of materiality and what the most sensitive factors in any one group are. As ever, figuring out the most relevant and critical information to allow good management decisions are what drive the final choice.

The Business Case: Spreadsheets To Performance Management

Posted by James Salmon at 21/8/2019 2:00:23 PM

The process of identifying an opportunity for change through to implementation is not a linear one, rather a cycle during which you will periodically repeat on yourself to re-qualify certain aspects of a project plan.

We’re finding increasing numbers of prospective clients engaging a partner at the earliest step of that journey. An opportunity has been identified but there is minimal, if any analysis of the opportunity, no selection criteria, no mission statement, and someone needs to sign the cheque.

Like it or not, spreadsheets remain a virtually cost free tool-set, resourcing aside, so the justification for capital expenditure needs to be a strong one.

The ROI of a performance management tool vs. offline spreadsheet models will be evident to the business stakeholder of change; elimination of spreadsheet errors, rapid response times, collaboration, faster reaction to business changes, greater insight into performance management. We get it, but the powers that be will require more. Your business case will need to be fully considered, well focused, resilient, practical and cost-effective.

Stage 1 – Analysis of Opportunity:

You have identified an opportunity to improve your current processes. Document a formal analysis of your strengths and weaknesses, and of the opportunities and threats that you face. Look a little deeper into the risk factor. This helps you to spot process risks, weaknesses in your organization, and identify the risks to which you are currently exposed.

From this you can plan to neutralise those risks through migration. Do you have the ability to produce a rolling forecast? What’s stopping you? Does that have a negative effect on the organisation? Keep it simple but get it down on paper.

Stage 2 – Identify the aim of your Plan:

The next step is to decide precisely what the aim of your plan is in the form of a Vision/Mission statement. Deciding and defining an aim sharpens the focus of your plan, and helps you to avoid wasting effort on irrelevant side issues.

Vision Statement: To have 100% confidence in the information we are deploying for business critical decision-making. To make the right information available in the hands of the right people, and to have the informative resource to respond fast enough to changing forecasts and budgets.

The mission statement gives concrete expression to the Vision statement, explaining how it is to be achieved. Again, keep it simple. Budget, Rolling Forecast, Scenario Planning, 3YP, rolling Actual updates – by Week, by Company, Product Category, Channel.

Stage 3 – Exploring the Options / Selecting the Best Option:

By now, you should have a clear objective so go out and explore the options. That may come as a surprise to hear me say but trust me, if the use case is on point the cream will naturally rise to the top.

Some of you may have heard us to discuss and offer a free ‘Proof of Concept’. This is something you won’t often see from other vendors, an opportunity to have complete exposure to the product prior to any commitment - warts and all. Sample your live data, dimensions & formulae.

Be mindful of pretty features like dashboarding, KPI’s, etc. Although key features of any EPM tool, they should not deflect focus from the aim of the plan. Remember, what problems are we really trying to solve: Drill-down, pivot-ability, integration, scalability, agile planning, self-service analytics, etc.

Stage 4 – Project Planning:

By the time you start detailed planning, you should have a good picture of where you are, what you want to achieve and the options available to you. You may have selected one option as the most likely to yield results.

Detailed planning is the process of working out the most efficient and effective way of achieving the aim you have pre-defined. It is the process of determining who will do what, when, where, how and why, and at what cost.

Focus on Gantt Charts or Critical Path Analysis techniques when working out priorities, deadlines and the allocation of resources. While you are concentrating on the actions that need to be performed, ensure that you also think about the control mechanisms to monitor performance, toll gates, etc. These will include activities like reporting, quality assurance, cost control, etc. that are needed to spot and correct any deviations from the plan.

A standard development plan will focus around: Project Scope & Initiation, User Requirement Analysis, Design, Build, Testing, Deployment & Stabilisation.

Stage 5 - Evaluation of the Plan and its Impact:

You have iteratively evaluated the plan to make sure it will be a worthwhile venture so it’s now decision time. Be sure to have sufficient factual back-up: Cost/Benefit analysis, Plus/Minus/Interesting chart, Force Field analysis.

In the majority of cases you will have a good idea of the final outcome, in others perhaps not and if holes are to be picked in the proposal then simply return to an earlier stage and either improve the plan or make a different one.

Start SMALL, start SLOW, start SMART. Offer confidence and prove the concept by focusing on early and often wins.

Look to win over the hearts and minds of key business stakeholders and empower your internal workforce, after all they will underpin the success of any migration by not returning to the spreadsheet at the first sign of trouble.

A business analyst should not spend the majority of his/her time collecting or churning data rather analysing the data to improve the performance of the business; Performance Management!!

Better Data = Better Decisions = Better Performance. Everyone wins.

The IBM Planning Analytics Roadmap 2019

Posted by James Salmon at 22/7/2019 9:14:12 AM

This guest post is written by Ronnie Rich, Senior Offering Manager for IBM Planning Analytics.

IBM Planning Analytics has a diverse, worldwide community of customers, and more are joining every day. Today, we are sharing a quick introduction for those new customers as well as a reminder for those who have been with us a long time about where to find answers to questions and resources to stay current on the latest news.

Let’s start with the product roadmap. Roadmaps provide valuable guidance for any journey, especially when you’re planning the future of your software deployment. A few weeks ago we presented our latest product roadmap at the Think 2019 conference in San Francisco.

In a session titled What’s New with IBM Planning Analytics Workspace, we highlighted the latest innovations and functionality in IBM Planning Analytics Workspace as well as upcoming innovations for IBM Planning Analytics for Microsoft Excel, IBM Planning Analytics Modelling, and IBM Planning Analytics Administration.

Here’s a small sample of the new capabilities and functionality we covered:

  • Action buttons: You can now configure IBM Planning Analytics Workspace to run a TurboIntegrator process with the click of a button. You can create prompts to ask for parameter values when the process is executed or configure default parameter values to run the process without prompting.
  • Administration enhancements: Monitor and administer your TM1® databases in IBM Planning Analytics Workspace Local using the IBM Planning Analytics Administration agent.
  • More efficient modelling: We’ve made it easier to get data into your models with drag-and-drop import of Dimensions and Attributes, as well as data from file. We also added efficiency tools like Rules Tracing, Autocompletion in Editors, and a Time Dimension Wizard.

You can find the roadmap for IBM Planning Analytics and other solutions in the IBM Analytics Roadmaps web page.

IBM Planning Analytics and its predecessor, IBM TM1, are long-time favourites of the finance crowd, who use it for essential budgeting and forecasting as well as sophisticated financial planning and analysis. It can meet the challenges of enormous data volumes, like Ancestry.com’s “super-cube” of 51 quintillion cells and large numbers of users, like the 6,000 at Germany’s national railroad, Deutsche Bahn.

But for years innovative organisations have been using the solution in a variety of non-finance use cases, such as supply chain planningsales planning, and workforce planning. And people are finding more ways to use it every day. Along with different use cases, IBM Planning Analytics offers deployment on cloud or on-premises. We’re proud of the fact that, with IBM, customers get to choose the deployment method that fits their needs.

Putting Analytics and AI in Context for Better Outcomes

Posted by James Salmon at 18/7/2019 11:25:37 AM

How do organisations really gain value from analytics? Deliver results and drive change at your enterprise using these experts' advice.

One of the errors of traditional business intelligence (BI) has been its standalone, passive relationship to human decisions and business processes. A BI report or dashboard delivers information, but how that information is connected to the decisions and actions that users need to take is often unclear and unstated. The information may or may not be relevant; it could even be out of date or misleading. As analytics applications expand beyond specialists, organisations need to ensure that data insights are better connected to what humans and automated applications and services will do with them.

This issue was discussed extensively at the recent TDWI Solution Summit in Coronado, CA, which focused on the theme of "strategies for delivering results with analytics and data science." In his keynote, James Taylor, cochair of the Summit and CEO of Decision Management Solutions, offered the clearest context for analytics: the decision.

Rather than dive immediately into collecting often ill-defined requirements for developing analytics models and algorithms, Taylor suggested that an organisation should identify decision points in its business processes, customer engagement, and strategy development and think about how these decisions could be improved. This approach will naturally link analytics to business goals. For example, an organisation could look at whether changes in decisions about pricing, claims handling, and service renewals could increase customer satisfaction.

Although many organisations are looking at how to use artificial intelligence (AI) and process management technologies to automate decisions, in most cases decisions are formulated and executed with considerable human involvement.

In his talk at the Summit, Rob Horrobin, AVP of Advanced Analytics and Planning at Pacific Life Insurance, drove home that organisations have to balance people, process, and technology aspects if they are to achieve good outcomes applying analytics to real-world situations. He recommended that organisations composing data science teams to develop analytics models and algorithms should ensure that they include personnel with domain expertise, communications skills, and an understanding of the user experience.

Embedded Analytics and Recommendations Systems

In the technology realm, we are seeing exciting developments in the use of AI to provide prescriptive insights in the form of recommendations to users of BI tools and other applications. For users of BI tools, AI can provide recommendations about which data sets to use in predictive analytics. The software can be smart enough to understand, for example, that the user is trying to examine the effectiveness of marketing campaigns across channels and therefore should include a source that has relevant customer behaviour data. AI can even take things a step further by not waiting for user actions and instead applying machine learning to automatically find patterns in big data and deliver answers to users that are relevant to their roles and responsibilities.

In some ways, the trend toward AI-driven recommendations represents the next generation of embedded BI and analytics. Organisations have long had an interest in bridging the gap between BI and analytics tools on the one side and business applications on the other. Traditionally, users have had to step out of their CRM, ERP, or other business application environments to get the full functionality of a BI or analytics solution. Embedded versions of BI and analytics tools have tended to be primitive, offering simple reporting-oriented dashboards, alerts, and limited query capabilities.

Although the limitations can be frustrating to power users, the simplicity is appropriate for the majority of business application users who typically do not want to climb the learning curve of a more complex BI or analytics solution just to consume information. With AI-driven recommendations and information delivery, organisations can still keep things simple but allow users to tap richer sources of data and learn answers to questions they may not have thought to ask.

Some modern BI solutions use AI to discover and surface simple visualisations of information relevant to the user's decision. An example is MicroStrategy's HyperIntelligence, part of the company's 2019 release, which offers "hover over" insights that pop up as users look at forms, files of customer information, or other business application interfaces. Competing solutions such as ThoughtSpot help nontechnical users explore data related to their decisions through natural language searches. AI can enable such systems to learn from user behaviour and data characteristics to shorten the path to relevant, accurate answers, including presenting the insights in the form of alert messages as users are involved in business processes.

AI-Driven Performance Management

Performance management has long been a way to tighten the connection between BI reports, dashboards, and alerts and users' roles and areas of accountability. Using key performance indicators (KPIs) and other metrics, organisations can communicate strategic corporate objectives, sometimes as part of the implementation of business performance methodologies, to guide decisions and actions.

AI can drive improved understanding of metrics by bringing relevant information to users automatically rather than waiting for them to write a query. Organisations can also use AI-based features in solutions to develop recommended actions. For example, an organisation may use these recommendations to address problems in processes and behaviour that are causing customer satisfaction metrics to fall below corporate objectives.

Performance management depends on data quality and consistency. If users cannot trust the data, they will not trust the KPIs and other metrics. Data quality, data cataloging, and other data management solutions are using AI to help organisations accelerate the improvement of data quality through quicker discovery of discrepancies, anomalies, and inconsistencies across sources.

Analytics in Context: Essential to Achieving Success

As many speakers at the TDWI Solution Summit pointed out, most organisations invest in analytics and AI to drive change. They want to use data effectively to make better decisions, improve customer engagement, and run processes and operations smarter and more efficiently. However, these initiatives will fall short if AI and analytics development is not well integrated with how humans make decisions and take actions.

Prescriptive, AI-driven recommendations will misfire if their development does not take into account how human decision makers will employ them, whether users can trust the underlying data behind them, and whether the recommendations are relevant to the outcomes they are trying to achieve. Organisations that take these human factors into consideration will be able to move beyond the limitations of traditional embedded BI systems.

5 tips for better board reporting

Posted by James Salmon at 18/7/2019 11:21:21 AM

As a finance leader, you’re intimately familiar with your company’s data and KPIs. But guess what? Most of your board members aren’t—and they don’t want or need that level of detail. What do they want? Like your CEO, board members are searching for trusted, strategic deputies who can provide high-level, holistic insight that helps them navigate the swirling currents of today’s business world.

Luckily, top finance executives have a great vantage point from which to fill this role. Here are five tips to ensure you make the most of your time at the front of the room.

Tip one: put yourself in their shoes

Who are the members? Typically, they’re not financial experts and aren’t involved with your company’s day-to-day operations. They may serve on as many as four or five other boards. Moreover, since the 2008 crash, they’ve come under increasing scrutiny and are held to ever-higher standards, even as the pace and complexity of business increases.

As you craft your presentation, keep this vantage point in mind. You don’t need to wow board members with your intricate grasp of the material; you need to give them the information they require.

Tip two: be transparent

As a finance leader, your most valuable asset to the board is your objectivity. You have no axe to grind; you’re not spinning anything; you’re certainly not making the sales forecast look rosier than it is. The most helpful thing you can do is to report bad news as soon as possible in a straightforward way. Conversely, if performance is improving, the board needs to see updated forecasts ASAP, too. Skip the impulse to leave the forecast where it is and present numbers you think the company can beat. The board is always happiest with the most updated, most honest and most objective data available.

On a higher level, transparency also relates to the crispness of the overall message you present. Delivering a message informed by a single source of truth, rather than an overwhelming ream of data, stops the debate over whose numbers are correct and refocuses the discussion on insights and action. In short, it speeds and improves decision-making.

Tip three: provide context

Board members need to quickly grasp your company’s big picture, rather than a snapshot of performance at a moment in time. You can help them get there by covering where the company has been, how it’s performing now and where it’s going in the future. In other words, consider showing them four to eight quarters of past performance, the current quarter’s numbers and four quarters of your latest forecast. That allows the board members to quickly and comprehensively understand how the company is doing.

Tip four: be consistent

Nothing annoys the board more than when your presentation’s data points change from one meeting to the next.  Winnow down the key performance indicators you choose to share the same way, every time. Say you monitor about 250 KPIs internally, ranging from sales metrics to marketing productivity, before you even get to the financial details. When you present to the board, cut the KPIs you share to about 20. Make sure you choose ones that are clearly defined and meaningful to the specific areas you’re covering.

Tip five: know your role

This can be tricky, because executives can have different perspectives on the role of a financial leader. The bottom line, though, is that you’re often the only non-board member who attends the meetings. That means it’s better to keep a low profile and refrain from debating issues, taking sides or inserting unsolicited opinions. Remember: If you do your job—reporting the financial information as objectively and accurately as possible while adding valuable context—board members are going to ask for your view anyway.

IBM Planning Analytics receives top ranks in world’s largest planning survey

Posted by James Salmon at 29/5/2019 9:27:01 AM

Before making any major purchase decision, most of us read reviews to learn about the experiences of other users and get an understanding of a product from the perspective of the marketplace. This is especially important for when evaluating options for a major investment like planning software.

Our team is proud to say that IBM is included in The Planning Survey 19, the annual report from the Business Application Research Center (BARC). BARC is a leading European consulting firm specialising in business software. Their annual survey is based on findings from the world‘s largest and most comprehensive survey of planning software users.

IBM Planning Analytics received high marks again this year, as it was top-ranked in 22 key performance indicators (KPIs) including performance satisfaction, user experience, and product satisfaction. In addition, IBM was named a leader in 17 more KPIs, across five different peer groups.

The BARC results reflect five key attributes that are vital to organisations choosing planning software. Here’s what those attributes mean for our customers.

When it comes to scale, IBM scores high marks—the proof is top rankings in product satisfaction, performance satisfaction and flexibility. When advanced capabilities can scale beyond individual power users or small teams, the business benefits are likewise magnified. The BARC report noted that IBM Planning Analytics is used “in thousands of implementations worldwide, from small-scale departmental scenarios with just a few users and small data volumes to installations with thousands of users.” The report finds the high “performance satisfaction” ranking especially impressive, given how large many of the IBM Planning Analytics deployments are—a testament to the product’s highly capable in-memory database.

…IBM has invested heavily in scalability and performance improvements in recent versions of the product, which is a major differentiator to rival products...”

Microsoft Excel is one of most pervasive applications across the business world. IBM Planning Analytics for Microsoft Excel enables users to hit the ground running. BARC observed that “the Planning Analytics Excel front end offers easy-to-use capabilities for creating content (e.g., modelling, templates) in a familiar environment and publishing it to the web.”

In spite of Excel’s ubiquity, of course, it does have its limitations. The BARC report noted that “Planning Analytics users have far fewer complaints than Excel users. Common issues in planning projects such as missing key product features (e.g., for planning), inflexibility and handling of large numbers of users or large data volumes do not seem to be a problem for Planning Analytics users.”

Virtually all planning and performance management processes involve some analysis and reporting. The BARC report noted that “Besides planning functionality, [IBM Planning Analytics] offers good ad-hoc reporting and OLAP [online analytical processing] analysis capabilities for end users. Reporting and analysis generally takes place in Excel using native-Excel functionality and is therefore easy to use.” IBM Planning Analytics provides out-of-the-box reporting capabilities, so there’s no need to license software from another vendor. Users can take advantage of a broad range of performance reporting, monitoring, dashboarding and scorecarding capabilities.

A key complement to IBM Planning Analytics reporting capabilities is its ability to provide easy access to both the reports and the supporting data. BARC observed that “at the push of a button, results can be published in the Planning Analytics web client and are available in a browser. In this way, decentralised users can access reports or dashboards (e.g., on planning results) anywhere via the web.”

In addition, IBM Planning Analytics has a “single tenant” data tier. This is built by design and with the customer in mind. It means that a customer’s critical business data is stored separately from other customers and each customer has dedicated resources. This means that users will not be slowed down by other customers. No doubt this feature also contributes to high performance satisfaction marks for IBM Planning Analytics.

Flexibility is “a prominent reason why companies choose to buy IBM Planning Analytics.” It provides “a flexible development environment for creating individual planning applications on different aggregation levels (operational as well as strategic) across various planning topics (e.g., sales, HR or financials) and industries.”

In addition to providing the foundation for integrated planning across the organisation, we understand the importance of giving customers the option to decide which deployment is best for them. And they don’t have to compromise on functionality. The same line of code is used for both on-premises and on-cloud versions. So no matter which deployment, you can get the same product and functionality.

“Outstanding piece of software, which is very flexible and agile and which has a broad variety of potential usage.” – survey respondent

Given the 22 top category rankings from this year’s BARC report, it’s not surprising that the product has received a very high recommendation rate. As in BARC reports of years past, IBM Planning Analytics has consistently been a leader in "user experience" which accounts for the fact that "87 percent of respondents are ‘somewhat satisfied’ or ‘very satisfied,” a major reason behind its recommendation rate of 81 percent."

These are just a few of the key highlights from the Planning Survey 2019. Get more details about the survey methodology and why customers are highly satisfied with IBM Planning Analytics by reading the full report. And explore how IBM Planning Analytics can advance your business here.

FP&A Digital Transformation: Balancing Risk & Outcomes

Posted by James Salmon at 28/5/2019 2:36:32 PM

When embracing better-practice, balancing risk to return can be complex and choosing a path that delivers high business value, with minimum disruption is not always easy.

Whether saving costs or improving revenue, FP&A digital transformation projects must provide strong gains in productivity and effectiveness. If you have been through sluggish ERP and CRM implementations, you may have seen how far projects can go wayward before they stop draining time (and money) and start being useful.

IBM conducted a global Survey with ACCA and discovered only 35% of organisations have a digital transformation road-map in place. There are many reasons. One challenge is when leadership don’t have technical knowledge – a reason why technical projects can fail. Another is under-thinking the people aspect – change is a process, not an event. A third reason is not knowing where to start. This is where I look at below.

The best finance teams I’ve worked with apply very simple principals, even in complex transformation projects. The CFOs understand that the result must be embraced by both the leadership team and other departments to be successful. Here are pragmatic approaches for successful initiatives that think big, start small and consistently deliver value:

Don’t Boil the Ocean

Aim for rapid results that achieve business outcomes early – no drawn-out ‘big bang’. Instead, short projects (or ‘sprints’) that iteratively deliver value and create the momentum for change – and allow time for learning. Learn while doing – it’s more than new technical skills. To operate differently from today, your team need new thinking and new approaches – so they need to be ready, and have the space, to learn. One organisation I worked with had very broad goals for optimising supply chain planning, inventory analysis, executive reporting, integrated business planning across HR, Operations, Sales, and along Supply Chain.

Most existing processes were manual, which meant they were running as fast as they could to stand still. Some teams spent 30% of their month just adjusting forecasts, while others took 20 working days to deliver static report packs that showed the ‘what’ but didn’t explain the ‘why’. They stood to gain a lot by digital Finance Transformation.

 Initially they captured a long wish-list from every stakeholder. The risk was that the project would experience ‘death by committee’ trying to please everyone (some team members even though they needed a new ERP – another 5 years of headache). In any event we needed to define the problem before jumping into solution mode. So, when our team began working with them, we started by confirming the business outcomes they sought, from the CEO down. They circulated a high-level concept paper: less structured than a business case, this was critical to get early engagement and buy-in from different departments. It became the lens through which we could understand and assess how specific requests supported achieving this overall goal.

We agreed on the success metrics, and then began to distil each area’s needs and prioritise by comparing complexity to the potential business benefits – looking for quick-wins and tipping-point activities that would critically free-up time in finance to come up for air (i.e. free up time) and start to work on higher-value activities.

Next, we looked across their requirements for commonalities. Actual and forecast sales numbers, for example, were used by a range of processes (sales were quite important it seemed) so if we got one reliable version of the truth on these, it could immediately be used by different teams, even while we were getting on to their specific requirements.

This approach meant they avoided the risk of waiting 6-12 months to get any result. Instead, every additional deliverable added value of what they’d already achieved, as they removed silos and began to collaborate in a common and cohesive approach, while addressing specific departmental needs.

Minimise Disruption – Make it Easy for the Business

While the end-goal of transformation is to do just that – a transformation, that doesn’t mean everyone must start from scratch. Transformation is good in theory, but in practice, many people will be comfortable with the status quo and prefer not to change. The best measure of success is if people and teams actively embrace any new approach you introduce.

For example, if you currently have a steam-driven budgeting process, first get the house in order. According to Mckinsey, a consultancy, 70% of Finance processes can be fully automated. So, streamline your process to free-up time while retaining what business users are familiar. This minimises change-management and makes it easier for other departments to embrace.

An organisation I worked with, re-engineered their integrated planning process, with driver-based models that automatically calculated and consolidated all their information and at the same time strengthened governance through security and data privacy, and audit.

It was sophisticated and immediately meant FP&A was more productive and enabled them to quickly run scenarios and recut plans through the planning cycles.

For end users, however, they decided to run the first new budget cycle keeping the same familiar spreadsheet planning and reporting templates. This is not unique – in the IBM ACCA survey, 75% of organisations said Excel is still main technology skill set in the Office of the CFO. Users were happy with them as they’d refined them over the years.


It was low-risk and required minimal training. This meant they finished the project more quickly, just in time for the next budget cycle.

The difference was the spreadsheets were directly connected to the new planning models, which meant they had the best of the both worlds – a robust and highly efficient planning process with more confidence in their numbers, combined with something familiar and easy for so business users continued to work comfortably at their own speed. This minimised the risk of them rejecting all of Finance’s efforts.

Better practice with Finance Digital Transformation means starting small, delivering quickly towards the big goal. You get your brightest people engaged on high-value activities to retain the best talent. In my next post, we cover how being flexible helps ensure your initiatives stay relevant and how to forge a reliable partnership with IT to align with technology strategy.

Seizing the benefits of Lean-Agile methodologies

Posted by James Salmon at 28/5/2019 2:30:33 PM

This is the first in a series of three blogs that discusses the role of Lean-Agile methodologies in the implementation and scaling of enterprise-wide planning technologies.

Business agility—how quickly a company can adapt to market changes and consumer demand—is a cornerstone of product and platform development. As a catalyst that turns decisions from reactive to proactive, it can translate into the difference between success and failure in dynamic business environments.

What’s more, as products become increasingly software-driven and converged, the most successful enterprises are those that not only innovate, but also expand upon innovation throughout the entire organization—rapidly and with ease. Companies with long product planning phases, high R&D and overhead costs, and limited ability for change must pivot now, or simply get left behind.

 The way forward: employing Lean-Agile methodologies.

 Lean-Agile methodologies are a unique hybrid of both Lean and Agile software development approaches. They’ve been heralded for fostering the development of next-generation products and platforms, including Anaplan’s Connected Planning platform, which summons agile-inspired principles.

 Lean-Agile approaches are not exclusive to software development alone. In fact, organizations can use agile-inspired principles to adopt, implement, and sustain new planning models and enterprise technologies. For these implementations to work at scale, companies must be able to synchronize the various technology delivery frequencies involved in getting a product or platform to market.

What’s needed is an organization-wide approach that breaks through traditional silos and is championed by leadership.

 In this three-part blog series, we take a closer look at Lean-Agile methodologies to understand their business benefits and how they can successfully be employed at scale during (and after) the implementation of enterprise planning technology.


Lean-Agile methodologies: What are they and why they matter

Lean-Agile methodologies are rooted in the underlying principles of both Agile and Lean development approaches. Agile methodology combines values and principles that encourage better ways of developing software—centering on individuals and interactions, capable technology, customer collaboration, and embracing change.

Lean Product Development (LPD) is an approach that addresses challenges in product development, such as a lack of innovation. Its approach focuses on reducing long development cycles and high development and production costs. Adopting an LPD approach helps businesses strive for continuous innovation and iteration.

In turn, Lean-Agile methodologies fuse principles of both approaches. It focuses on a respect for people and culture, flow of work, innovation, and a quest for relentless improvement. Its implementation and application have been so successful in product and platform engineering that many enterprises are keen to scale these methodologies throughout their broader (respective) organisations—from marketing and sales departments to human resources, accounting, purchasing, and other teams.

When used outside the realm of product development, the application of Lean-Agile methodologies can help businesses make continuous, incremental changes to internal processes that drive ongoing operational improvements and deliver higher efficiencies.

The combination of Lean thinking and the Agile Manifesto ultimately summon what has been termed the Lean-Agile Mindset. In effect, Lean and Agile complement each other to yield better results in the shortest sustainable time with the highest level of delivery.


The business benefits of Lean-Agile approaches

The business benefits of Lean-Agile methodologies are now well-established and will be discussed in greater detail in subsequent blog posts in this series. They include:

  • Accelerated time-to-market
  • Increased implementation transparency and visibility
  • Reduced risk and costs from testing early (and often)
  • Improved ability to address unclear or evolving requirements
  • Improved collaboration through alignment of management, IT, and vendor teams



Scaling Lean-Agile methodologies

Disruption, uncertainty, and a seemingly omnipresent need to evolve business models are no longer vague corporate expectations—they’re realities for virtually all enterprises. Adopting Lean-Agile approaches across business operations allow cross-functional teams to act quickly, exhaust fewer resources, work more collaboratively, and deliver results that pack a greater punch.

However, large-scale employment of these methodologies is often daunting, but very necessary and common for industries such as software, aerospace and defence, automotive, and others where large solutions—not portfolio governance—is a primary concern. Successfully scaling Lean-Agile entails a focus on agile technology implementations and the ability to extend those applications—through capable tech platforms—throughout the entire enterprise.

In subsequent posts in this series, we’ll dive deeper into the business benefits that leaders can realise through today’s best-of-breed planning technology. 

4 steps to improve your business reporting process

Posted by James Salmon at 28/5/2019 2:25:01 PM

Late nights. Working over the weekend. Learning the names of every barista within a quarter-mile radius of the office. If you’re in charge of creating financial reports, you don’t need me to tell you how much work it takes to keep information updated and accurate.

That’s because you’re likely logging into multiple systems to pull information while working with incredibly large amounts of data. The more systems and data, the more effort it takes to model and analyse for presentation.

At the same time, all this data is more valuable than ever. When done well, financial reports can provide insights into the past, present, and future, helping the entire company manage volatility, navigate organisational complexity, meet compliance requirements, and drive the direction of operations. As a result, financial reports have never been more necessary to run the company or more in demand by your boss.

So how can you make reporting more efficient, more effective, and less reliant on espresso? Here are four steps you can take to improve your process.


Step 1. Centralise your data

It might sound scary, but without a central data system you’ll waste countless hours dealing with multiple source systems to pull information. And it’s only going to get worse. Industry experts predict that the digital universe is going to double in size every two years, growing from 4.4 trillion gigabytes in 2013 to 44 trillion gigabytes by 2020. As businesses introduce more and more systems to track every last bit of data, you’re going to simply run out of time if you keep trying to pull all that information separately and manually.


Step 2. Tailor your message

Not everyone speaks accountant. Your reports aren’t always going to be read by finance professionals. You need to understand the needs of your audience and create reports appropriately. That way, the reporting process becomes a strategic conversation instead of just a wall of numbers. For example, operational leaders might want detailed metrics on their unit, while executives may require a higher-level summary of the entire business. The more you can provide relevant information, the more value your reports will provide.


Step 3. Get visual

Ask any toddler at bedtime: Stories are always better with pictures. It’s no different in reporting. Data visualisation, like charts and graphs, is crucial to good analysis. When you visualise your raw numbers, your audience can see the story the numbers are telling while easily spotting potential problems or outliers. Not only is a picture worth a thousand words, but it can help you understand the worth of a thousand numbers.


Step 4. Enable self-service reporting

If you had a nickel for every time you had to pull a report for another department, finance would be the most well-funded department in the company. According to the IMA, more than 90% of controllers provide operational data while more than 80% are being used to source business performance and customer data. Sure, you’re happy to help, but pulling reports for everyone else means less time to work on your own valuable strategic activities. By enabling self-service reporting and dashboards, the finance department can take its time back while empowering other departments to get the data they need in seconds instead of waiting for weeks.

3 reasons to upgrade from IBM Cognos TM1 to IBM Planning Analytics Local

Posted by James Salmon at 21/5/2019 1:02:50 PM

1. Workspace

The first big reason to upgrade can be found in Workspace, the user interface that is the new face of the Cognos TM1/IBM Planning Analytics solution. Workspace is attractive on several levels. The interface is a highly visual, freeform design with over 25 charts, scorecards, images, shapes, text, and videos.  Quick searching and Snap Commands give it a natural-language-like feel.

Moreover, Workspace is data rich. You can combine data from any cube from any Cognos TM1 database into a single view, using a new viewer, websheets, charts, or cell widgets. There’s no time-wasting data conversion process at all. Workspace coordinates three forms of data selectors–tile, list and slider–so you can intuitively filter your data rich “Books,” using buttons that allow them to navigate across content, carrying context with them as appropriate.

Workspace supports analysis, reporting, and writeback. With the highly interactive viewer, it’s easy to navigate a multidimensional cube and convert “data exploration” into a chart. Then, you can use this chart to present and share results with others. It’s also easy for business users – both report authors and consumers—to create highly interactive Workspace Books. Finally, Workspace is mobile, so you can work with Workspace Books on your iPad.

2. Hierarchies

The new “Hierarchies” capability is a paradigm-changing analysis feature for Cognos TM1 users. In today’s data rich environment, we all want to explore our data using “attributes” that describe the many characteristics of our customers, products, projects, programs, financial instruments and more. With the Hierarchies capability, you’re not limited to the traditional definition of your cubes for analysis.

Leveraging attribute data in the form of ”virtual dimensions” extends that definition using data from the time the cube was created or anytime after – and does it seamlessly. Further, you can see the intersections of several Hierarchies of the same dimension. You are then able to drill into the data to find data points never before possible. Implementing the Hierarchies capability is a natural process, with little setup and an intuitive process. You can also use Hierarchies for dimension re-organisations and versioning.

3. IBM Planning Analytics for Excel (PAx)

With the IBM Planning Analytics for Excel (PAx) feature, you get Microsoft Excel access to the Cognos TM1 database with superior performance over wide-area networks. PAx has several integration points with Workspace and both environments share a common user experience, Cube Viewer, and Set Editor. PAx has four models of interaction to satisfy all Excel user modes:

Exploration for slice/dice/pivot analysis

Quick Reports for fast worksheet design

Dynamic Reports for row interactivity (zero suppression, expand, collapse)

Custom Report for highly formatted forms and reports.

Also, all the reports you create in PAx can be published for websheet consumption in Workspace. And these are just some of the many features of PAx that will delight Excel junkies.

Is IBM Planning Analytics Local right for you?

These are the most important reasons why we think you should consider upgrading your Cognos TM1 implementation to the new, on-premises version of IBM Planning Analytics. And please note that, in spite of the solution’s new name, the upgrade process is not really a migration. You can simply install and go, using your current model and mode of operation.

We think Cognos TM1 users around the world will like the direction we’re going with the IBM Planning Analytics Local. We also hope that the improvements we’ve made reflect the desires of those users and directly enhance the value of the software they use every day. We take pains to listen and learn from our customers and our goal is to consolidate capabilities and present a unified Web, Excel, and mobile experience for all the diverse roles of Cognos TM1 users.

Your planning app should go beyond just automating spreadsheets

Posted by James Salmon at 25/2/2019 3:36:09 PM

Selecting a new planning app can be an arduous task. You see lots of flashy demos, sales presentations and “cool” looking features. They all look the same right?

Well, that may be the true, but when you peel back the onion and take a closer look, there are some significant differences between the different vendor solutions.

If I were to say to you that your planning system would force you to combine your cost center and account dimensions into a single dimension by concatenating all of the cost center and account codes, you’d think I was crazy, right? If you knew in advance that it worked that way, you would never buy it, correct? Unfortunately, some solutions don’t reveal their shortcomings until after they’re implemented.

Acquiring a new planning application is a journey. Ideally, your new planning app is not just a great spreadsheet automation tool, but is also an enabler which can unlock a whole series of capabilities that were unthinkable in the spreadsheet world. Examples include: rolling forecasts, driver-based planning, linking operations to finance and predictive forecasting, to name but a few. The ultimate goal is an organisation in which plans for Finance, Operations, Sales, HR and a range of other essential functions can be created on a single, integrated platform, where planning is pervasive throughout the organisation and the organisation is constantly aligning resources to seize new opportunities.

With that said, it is important that you select the right planning platform which can support you on the above journey — even if your initial goal is simply to automate your spreadsheets.

There are certain attributes of planning system engines that are absolutely essential for a serious planning system. A few that come to mind are:

  • An in-memory calculation engine for performance
  • A multi-cube architecture for flexibility
  • A sparsity engine to handle enterprise-class data volumes

Beyond these basics, other blog articles by IBM offer more suggestions on things to consider:

The moral of the story is that a little extra care in your due diligence will benefit you when you’re choosing a planning application. 

Multidimensional analysis in finance — because the business world isn’t flat

Posted by James Salmon at 1/2/2019 1:25:42 PM

Analysing data is one of the core functions of many business professionals, especially in finance, where financial planning and analysis (FP&A) is one of the more fun and interesting duties of the job. As markets and business practices have evolved and the volume and variety of data has grown, the complexity of business analysis has also increased — leading the way to multidimensional analysis.

Why multidimensional? Because the business world isn’t flat — two-dimensional — like the rows and columns on a spreadsheet. It’s multidimensional, so it takes multidimensional analysis to examine performance in all of its complexity, particularly when analysing year-end results and planning for the year ahead. That often means working with very large data cubes, sometimes containing billions of data points, to represent products, customers, and the multitude of variables that define a business.

Customers and competitors on every continent

Paradoxically enough, one of the reasons that multidimensional analysis is so essential is that in some ways, to borrow the metaphor of author Thomas Friedman, the business world actually is flat. Friedman’s famous best-seller on globalisation, The World Is Flat, described how the world’s economy has evolved into a far more level playing field for commerce than it had been in decades past. Businesses today can find customers — and competitors — on virtually every continent. And every insight gleaned from in-depth analysis could reveal a performance gap or a competitive advantage that is key to a major market opportunity.

In this environment, analysts need the best possible techniques and tools. That’s why we’d like you to know about a free webinar we’re presenting on Friday, May 17th, at 11:00 a.m.

Multidimensional analysis: user and vendor perspectives

In this webinar we will explain:

  • How examining large, historical, and future-oriented data sets gives you practical insights to help you meet performance targets, seize opportunities to grow business, and address the inevitable setbacks with agility
  • Why analysing data in its full multidimensional complexity provides a deeper understanding of the causes and effects of business results
  • How a personalised “sandbox” environment lets users compare best-case, worst-case, and most-likely-case scenarios, and model alternative courses of action
  • How the “hierarchies” capability (an IBM Planning Analytics exclusive) enables analysts to perform more granular analysis by using “attributes” to model variables such as products, customers, regions, and sales channels in real time
  • As the complexity of analysis has increased, so have the rewards. So please join us to learn how modern planning solutions drive smarter, data-driven decision making and enable organisations to wring more value from their planning and analysis processes.

We look forward to you joining us.

Webinar: Budgeting, Forecasting & Planning in 2019 - May 17th - 11am

(Register now and even if you can't attend we will send you the recording!)

How to reduce the time spent in finance meetings

Posted by James Salmon at 3/12/2018 12:22:15 PM

CFOs know better than anyone that time is money. So why do they waste so much of it in meetings?

More than half of finance teams average nine or more hours each week in meetings, according to a survey of CFOs, and 25% sit through a whopping 13+ hours.

The wrong way to provide financial data

The problem is that because finance teams have access to information and metrics across the organisation, they serve as the gatekeepers to data. When you’re the information gatekeeper, you often become the information sherpa, too. In traditional organisations, this becomes a huge time suck, because finance executives have to guide their colleagues through masses of spreadsheets, addressing the confusion and doubts that proliferate in a disjointed system.

Traditionally, they’ve gathered PowerPoint slides from various departments and shoehorned them into a huge deck to present to the executive team. The slides are invariably a never-before-seen mishmash, with information taken from multiple spreadsheets, that leave attendees questioning data and trying to understand formulas. Every number is explored, and assumption is challenged, which—let’s face it—rarely makes a big difference in the final budget.

As a result of these marathon meetings, CFOs often feel trapped, spending almost all their time looking in the rear-view mirror, which leaves precious little time to focus on the road ahead. And because they waste time that should be devoted to financial strategy discussion, those meetings also waste a stomach-turning amount of money: Some $37 billion goes down the drain every year during unproductive meetings.

Cloud-based finance tools help solve problems

Transitioning to a cloud-based financial tool can immediately help plug this cash haemorrhage. With easily navigable dashboards, cloud-based finance tools provide a single source of truth that eliminates confusion and uncertainty.

When you use a cloud-based finance tool, everybody sees updated numbers ahead of time and can toggle back and forth between an original financial plan and the current version. As a result, everyone comes to the table more prepared. That eliminates the whole “How did you reach this number?” discussion that gobbles up a tremendous amount of time, and quickly elevates meeting conversation from basic explanation to higher-level financial strategy discussion.

Financial Performance Management tools also make it plain to see what was shared at previous meetings, so historical comparisons are quick and painless. As a result, financial planning meetings can be short but incredibly effective.

Together, this transparency and the creation of a single source of truth make non-finance execs far more efficient in understanding the data. This autonomy, in turn, frees up FP&A professionals to contribute higher-level strategy insight. And that’s critical, because the CFO role has transformed: Today’s finance leaders must provide forward-looking vision in addition to accurate financial forecasts. Most CFOs have seen their level of strategic influence increase as they take on concerns beyond number-crunching, an Accenture survey found.

Active planning with cloud-based finance software, then, presents a win for everyone: It’s fast, it’s easy, it’s powerful, and it accelerates decision-making by providing clear, accurate information. That lets CFOs step into their rightful role as strategic advisors—and gets everyone out of that conference room ASAP.

Find out more about how active planning can help you save time and money—and become more strategic in your financial meetings.

IBM Cognos Analytics 11.1 Raised the Bar

Posted by James Salmon at 23/10/2018 11:06:30 AM

IBM just released Cognos Analytics 11.1, which in my opinion raises the bar on self-service, discovery and easy to use analytics.  They innovated with the introduction of artificial intelligence (AI), machine learning (ML) and deep exploration in an intuitive, guided interface.

As part of the early adopter program, I explored and will share some of these innovative capabilities.

The Best Cognos Analytics 11.1 Capabilities

1. True AI-driven BI

With the constantly increasing adoption of data science and discovery also came the need to integrate the insights it delivers with an intuitive consumption experience.  Many niche vendors provided capability to insert R, Python or other statistical functions into its visualizations but fell short on the interaction with the user.  In contrast, thanks to the integration of the Watson Analytics ‘smarts’ (which should be deprecated in mid-2019), Cognos Analytics 11.1 now orchestrates a set of new features intended to empower users with real data exploration.  They can augment their visualizations with advanced analytics and deep-dive into their data with the guidance of AI.

This innovation is led by a simple optional ‘Explore’ module, accessed from either the welcome portal or a visualization, and launches a ‘card’ interface.  From there, the user is shown a diagram that detects the correlation and strength of each field, as a starting point for the discovery.  It even suggests the best starting visualization for displaying such correlation.

Also, each visualization introduces the user to a few common advanced analytics insights, either via:

  • ‘Details’, suggests patterns and other detected insights that may not be obvious at first look.  Clicking on a suggestion adds a new ‘card’ with a way to look at the data.
  • ‘Insights’, adds contextual statistics to the charts.  Fields such as average and meaningful differences.
  • ‘Badges’, presents contextual target-driver relationships and weight, associated with predictive strength.  Including the best supportive way to visualize it, such as decision tree, heat map, correlation, sunburst, or rules list.
  • ‘Compare’,  bring cards side by side to compare data points, whether they are common or unique.

This concept of cards (also taken from Watson Analytics), is very effective with user engagement in a workflow, or ‘thought process’.  Users can always go back to a previous card and further explore, or modify the content as more insights are discovered.  Cognos Analytics already had storytelling in its previous version, and the explore ‘deck’ can be easily exported as a story starting point.

2. Enhanced data preparation for analytics 

With every ‘data wrangler’ comes the need to prepare the data in order to support a specific use case.  However, most of the enterprise reporting platforms have been cautious with this capability as it may conflict with its governance culture.

In its initial release, Cognos Analytics introduced the data module: a web-based, simple modeling interface intended for power users or casual admins to connect, map, and associate data sources.  However, some necessary key features were missing.  Now they are available in this version and include:

  • Data security: modules can implement data level security (currently available for relational data sources only).
  • Data Wrangling and cleansing features, such as splitting columns
  • Support for uploading multiple excel sheets, split into ‘tables’
  • Support for relative time and comparative date handling using lookup to a calendar table (many calendar formats provided)
  • Append data sets (note: data sets are an efficient way to support dashboards with a flat, columnar file to ensure interactive performance)
  • SQL-based tables and assisted expression editor
  • Multi-grain column dependencies (equivalent to determinants in previous generation)

3. Enhanced Dashboarding

Previous releases of Cognos Analytics delivered dashboards using a self-service interface.  As a result, it was highly interactive, but a little too simple and limited for some use cases which needed more granularity.  Cognos Analytics 11.1 adds many new features to help deliver more flexible and detailed dashboards and effectively leverage real estate.

  • Font and value format/control (long awaited)
  • Custom palettes to ensure associated categories are displayed in same color
  • Advanced analytics and statistical visualizations
  • Show data for individual widgets
  • The long awaited ‘lasso’ on maps and other correlation charts: allow user to select an area of data points as filter
  • AI assistant: innovative feature using natural language.  Examples: ‘show me the data available’, or ‘show me the revenue for the product line’.  The assistant suggests visualization best suited for the context requested
  • Collaboration: IBM has partnered with Slack, a teamwork collaboration platform, that easily integrates across devices and browsers. Once configured, users can share content and comments in direct messaging

4. What about Report Authoring? 

Report authoring has always been a strength of the Cognos Analytics platform.  In this release, distributing operational reports is enhanced with features to optimize productivity such as: 

  • Addition of smart layout and grid/snap tools
  • Navigation UI for quick access to contractual tools and properties
  • Copy / paste any report part into a dashboard
  • Reusable styles
  • Custom color palettes
  • New visualisations, such as river, waterfall, Marimekko and floating charts 


Cognos Analytics 11.1 May Now Have the Upper Hand

The competitive market of business intelligence and analytics opened opportunities for both ‘niche’ vendors and enterprise platforms.  In addition, the adoption of data science and advanced analytics evolved separately until now.  With this promising new generation of  Cognos Analytics, it confirms that you can have it ‘both ways’.  It innovates by adding guided exploration and suggestive insights to the user experience, all in an integrated and easy to use interface.  Certainly this is an efficient way to introduce advanced analytics to the more casual user, while assisting the business analysts in discovering insights and stories about their data.

Get to the why with the all new IBM Cognos Analytics

Posted by James Salmon at 18/10/2018 12:39:10 PM

IBM Cognos Analytics latest version 11.1 has definitely caused a stir within the Business Intelligence marketplace; take a look at the videos below to learn what all the hype is about. 

We are just creating content for a webinar series that will start just before Christmas, if you would like us to get you registered please email james.salmon@budgetingsolutions.co.uk

Get to the why with the all new Cognos Analytics: 


What's new in IBM Cognos Analytics dashboarding? 


What's new in IBM Cognos Analytics data exploration? 


What's new in IBM Cognos Analytics reporting? 


Rolling forecasts — Aberdeen offers more reasons to adopt a proven best practice

Posted by James Salmon at 25/9/2018 11:01:01 AM

We’ve talked before about using rolling forecasts, noting that they “facilitate more informed decision-making in areas such as pricing, product mix, capital allocations, and organisational staffing levels.” But are rolling forecasts a new idea? Hardly. Rolling forecasts are a well-established best practice in performance management. In fact, the value of the process has been recognised by innovative companies for more than a decade.

In one of the foundational books on modern performance managementBeyond Budgeting: How Managers Can Break Free from the Annual Performance Trap, authors Jeremy Hope and Robin Fraser outline at length the principles behind rolling forecasts. They offer numerous case studies in how managing with a continually refreshed planning cycle can alter the culture of management for the better.

Now, a new knowledge brief from the Aberdeen Group identifies more of the benefits of rolling forecasts and offers recommendations for how an organization can implement them to best effect. In You Can’t Afford to be Static: Rolling with the Punches in Forecasting, Aberdeen research analysts observe that rolling forecasts can:

  • Give decision makers insight into the dynamics affecting revenue and expense
  • Enable decision makers to “better judge the impact any decision will have on the bottom line”
  • Improve the accuracy of forecasted and budgeted revenue by roughly 14%
  • Improve operational speed and performance
  • Enable companies to continually optimize the flow of discretionary investments

To gain these benefits, Aberdeen says that forecasts must draw on information from outside the walls of the organization. It’s now “glaringly apparent,” they say, that organizations must consider “external changes within their industry and aberrations in the overall economy” if they are to execute their business strategies successfully. In addition, Aberdeen recommends that organizations integrate financial and non-financial data, continually evaluate business drivers, and put forecasting at the center of the management process.

Timeliness of information is vital to the success of rolling forecasts. Aberdeen, however, points out that speed is only one of the advantages. “The value of a rolling forecast is not simply in being able to understand your financials in real time,” they explain. The greater benefit comes from the insight that rolling forecasts provide into the relationships between finance and operations. “The significance of a rolling forecast is that it gives decision makers insight into the dynamics of revenue and expense, and their related drivers.”

What happens when all that timely information informs a faster process? Ideally, it enables the organization to run like the proverbial well-oiled machine. Hope and Fraser give one example taken from a global car manufacturer.

“One forecast dovetails into another like cogs in a wheel. These forecasts form the core information for the monthly meetings, the development programs, and the strategy reviews. Managers build competence in sketching the future, and within that future lie the opportunities and threats that traditional budget-driven processes fail to see until it’s too late.” 

Suffice it to say that rolling forecasts have great potential and a great business pedigree. Like any process change that affects institutional culture, adoption is likely to be gradual. But the results are worth it. Read the Aberdeen knowledge brief, You Can’t Afford to be Static: Rolling with the Punches in Forecasting, to learn why this is one proven best practice that you shouldn’t postpone adopting.

Is your planning application promoting bad behaviour by your finance team?

Posted by James Salmon at 17/9/2018 2:35:17 PM

There is a trend in the performance management space to move away from the traditional spreadsheet-based planning application to a browser-based solution. This is, of course, a welcome move, as it automates a process which is very manual and error-prone. The business benefits of this new approach are well documented — reductions in cycle time, more confidence in the numbers, more time for analysis, etc. There are many.

In an earlier post on things to consider when selecting a planning application, I discussed some of the problems that can hinder reporting and analysis with these applications. One of the issues is the lack of spreadsheet integration and “owned by finance” reporting capabilities.

Finance users love their spreadsheets! They are very easy to use and extremely flexible. They also have very powerful, flexible and pixel-perfect reporting capabilities. You get lots of control and options for formatting (cell by cell), alignment, charts and printing (“fit to page,” for example). We all know that our finance executives have very specific requirements for their reports — fonts, underlines, column spacing and so on. Spreadsheets make it easy to meet their needs in this area.

This is where browser-only performance management applications fall down. Their lack of reporting flexibility may encourage poor behavior — the type of behavior that you were trying to get away from. Imagine being presented with an ad hoc reporting task. Finance executives require an answer to a question in their preferred highly-formatted report style. With a browser-only performance management solution, you may be tempted to copy and paste the data from the browser into a spreadsheet or perform a “data pull” into a .csv file and then manipulate the data in the spreadsheet using VLOOKUPs and SUMIFs. As we well know, any time you cut and paste data in that manner, it introduces the possibility of error that always comes with manual processes. Not the kind of data management behavior that we want to force people into by leaving them no alternative.

The approach taken by IBM Planning Analytics is different. The software provides an extremely powerful and flexible spreadsheet capability alongside sophisticated browser-based capabilities. Each of these sets of features augments the other so that users get the best of both worlds. Because the tool is fully integrated with the underlying database, users benefit from centralized definitions, business rules and security, which also keeps auditors, compliance officers and IT happy.

Meanwhile, though, end users can analyze and report on the data in the spreadsheet environment that they are most familiar with. That gives them the tools they need to meet tight reporting deadlines and satisfy even the most exacting formatting requirements of their executives. Thanks to this combination of features, Planning Analytics delivers uncompromising performance while discouraging the poor behavior described above.

Would you like some hands-on experience with IBM Planning Analytics so you can learn about more of its capabilities? Register for our free demonstration

In the market for a new planning system? - some important things to consider

Posted by James Salmon at 7/9/2018 9:32:58 AM

Selecting a new planning application can be an arduous task. Lots of flashy demos, sales presentations and “cool” looking features. They all look the same right?

Well, that may be the true, but when you peel back the onion and take a closer look, there are some significant differences between the different vendor solutions.

If I was to say to you that your planning system forces you to combine your cost center and account dimensions into a single dimension by concatenating all of the cost center and account codes, you would think that I was crazy, right? If you knew that in advance, you would never buy it, correct?

Acquiring a new planning application is a journey. It is not just a great spreadsheet automation tool, but it is also an enabler which can unlock a whole series of capabilities that were unthinkable in the spreadsheet world. Examples include; Rolling forecasts, Driver based planning, linking operations to finance and predictive forecasting to name but a few. The ultimate goal is an organization which plans on a single, integrated platform, where planning is pervasive throughout the organization and where the organization is constantly aligning resources to opportunity.

With that said, it is important that you select the right planning platform which can support the above journey – even if your initial goal is simply to automate spreadsheets.

There are certain attributes of planning system engines that are absolutely essential for a serious planning system. An in-memory calculation engine for performance, a multi-cube architecture for flexibility and a sparsity engine for enterprise class data volumes. 

Beyond these basics, here are some suggestions on things to consider;





Digital Disruption: disrupt or be disrupted

Posted by James Salmon at 15/8/2018 9:20:35 AM

There is no question that digital disruption is impacting businesses across all industry sectors, but as more new start-ups break through and disrupt markets, what can established businesses do to protect market share and withstand the threat posed by digital disruption?

We have seen many companies fade and fold as a result of digital disruption, but rather than dwelling on the threat of disruption it’s time for established organisations to look at the opportunities presented by the increasingly digitised world we live in.

Technology is impacting customer behaviour and the world around us. Business models are changing and it’s time to adapt and transform for business survival. By thinking outside the box, embracing new digital technologies and focusing on innovation, established businesses can not only position themselves for success today but into the future as well.

Reasons businesses may fail in the face of digital disruption

  1. Slow Decision Cycle - Technology cycles are becoming shorter than corporate decision cycles and organisa­tions are finding it increasingly difficult to keep up with the rapid pace of change.

  2. Complacency About Business Models - Companies cling on to their old successful business models for too long. While Black­berry continued to focus on its lead product, which it thought was untouchable in the enterprise mobile segment, Apple continued to innovate and reinvent what a mobile phone could be.

  3. Fear Of Cannibalising Existing Business - Companies are reluctant to go to market with innovative new offerings for fear of cannibalising existing business. Kodak failed to commercialise its patents for digital photography, and, instead, other firms such as Fuji licensed and commercialised it. “Kodak continued to focus and invest in film-based technologies in the 1980s and 1990s while Fuji was systematically extracting itself from film-based photography and shifting massive resources to new and unproven digital technology.” - Rita McGrath, Professor at Columbia Business School.  

  4. Lower Margins In The Transition - Lower margins in digital business often puts companies off. The newspaper industry was so largely dependent on traditional advertising revenue it was a big leap for news­papers to transition to digital where the rates are a fraction of what they are on print.

  5. Key Resources Unaligned To Opportunities - Organisations try to retro-fit new opportunities into existing organisational structures. Political challenges also present hurdles to successful innovation.

Digital is shaping the way the world operates today and, in order to serve customers better, businesses must understand how to leverage digital to innovate and better serve them.

Indeed, new start-ups and budding entrepreneurs are leveraging digital technologies to build uber-successful businesses that are delivering on and exceeding customer expectations. However these digital technologies also present golden opportunities for established organisations to transform their businesses and become disruptors themselves.

Every business today needs to be a digital business. Digitalisation is not about how you incorporate technology into your organisation, it’s about how you use technology to create new opportunities for your business, ensuring your company serves the customer of today and tomorrow.

Digital presents businesses of all sizes with opportunities to innovate, retain and capture more market share in current markets, enter new arenas and streamline the way their organisation currently works – systems and processes are becoming faster, smarter and waste-free with the help of new technologies.

Think outside the box, look at how your customers are behaving and get to know them, then look at how you can leverage digital technologies to meet their needs and exceed expectations.

This is all possible, but what is required is for businesses to act now and embrace and leverage innovation.

CFO Tips to Improve Financial Planning and Analysis

Posted by James Salmon at 3/8/2018 12:51:46 PM

FP&A professionals can spend less time to deliver more financial planning and analysis to business partners.

Ninety percent of CFOs report that they try to meet all demands for finance support, but this goal isn’t just ambitious — it’s impossible. The demands placed on finance teams have grown as business partners increasingly rely on finance for insightful, actionable analytic support to help them make strategic decisions.

If finance tries to meet every demand, including those that add little value, the quality of the analysis will suffer and strain limited resources.

Saying no is hard, and corporate finance leaders feel this dilemma with their business partners just like IT and other departments.

“Most financial planning and analysis (FP&A) departments still don’t follow the practice of saying no,” says Johanna Robinson, finance practice leader at CEB, now Gartner. “In fact, 90% of CFOs report that they strive to meet all demands for finance support requests made of their finance team.”

Teach employees how to make trade-offs

Although this seems like a simple concept, teams struggle to apply this in their daily work. To help determine where you can most effectively make trade-offs, use an established set of criteria to help employees know when to provide in-depth analytic support and when to scale back. Not only does this allow for the most important analytic requests to take precedence, but also helps your employees better prioritize their time.

“Most finance teams have a limited knowledge about analysis being done outside the function”

The CFO of one major bank uses principled criteria to prioritize when a finance team will spring into action to support a business request. The same criteria provides cover to earn time back for the most important requests by allowing the team to say “no” more often. The tiered system is developed through a set of both finance and non-finance criteria. Businesses with the highest growth potential receive customized support, while finance guides lower tiers to self-serve models. The result has been positive momentum in educating business partners on the difference between wants and needs.

Remove duplicative efforts

While getting comfortable with saying no is important, finance must also have a high degree of certainty that it is focusing on the correct areas. This is made all the more difficult as business units and other departments build out their own analytics, complete with conflicting, duplicative, and incompatible data and reports.

Most finance teams have a limited knowledge about analysis being done outside the function, which can lead to unnecessary or duplicated work. In addition, business stakeholders don’t know where to look for a particular analytic request, which wastes everyone’s time.

Currently, only 22% of FP&A teams have defined their analytic role relative to other analytic groups within the company. Ultimately, each department adds its own expertise to the analytic mix. Defining these contributions will help eliminate duplications of work and reduce the analytic burden on finance teams.

One telecom company decided to cut through the noise by proactively partnering with business units to design joint analysis areas that combine the strengths of each team into one unified report that both sides can endorse. Finance recognizes that marketing analytics will be superior in measuring customer attitudes, while it takes the lead in running ROI figures. This leads to less duplication and frustration and a better business impact from FP&A’s strengths.

“Although each approach varies, they share a common characteristic: Less overall service to yield a higher quality of support.”

Redefine finance roles

With the outgrowth of analytics, some CFOs have explored centralizing the analytic portion of decision support. In fact, 72% of organizations intend to centralize analytics by 2020. The benefits of such a move include leveraging scarce talent, improving efficiency and using data science to provide a deeper level of insight. However, many CFOs worry that such centralization will lead to a loss of influence and business acumen.

To combat this, a major manufacturing company uses a “hub and spoke” model to counter these risks. The hub in this case is the data scientist, who conducts deep analysis and partners with IT and analytics teams. The spokes — who are qualitative financial analysts — take these analyses and recommend them to the business units. The end result is a model that better protects the data scientist’s time while still providing business-specific viewpoints through FP&A analysts who serve as interpreters.

Different Planning Methods for FP&A

Posted by James Salmon at 16/7/2018 11:58:36 AM

In this article we will look at the different methods an organisation can use to set direction. 

Planning Methods

Planning involves many kinds of methods that help managers make decisions. It goes without saying that any planning system must be able to handle both financial and KPI information, it must be able to model the different business structures (products, departments, customer groupings) and possess good reporting and charting capabilities. It should also be able to report data from both a financial viewpoint as well as a strategy view through dashboards and strategy maps, as well as be multi-user that allows secure access to people with different roles.

On top of this, a planning system must also possess a range of specific capabilities whose purpose is to helps an organization prepare for the ‘unexpected’. These capabilities include:

  • Driver-based Planning.
  • Initiative planning.
  • Scenario Planning.
  • Contingency Planning.

Driver-based Planning

Driver-based planning is used to predict future values based on trends and relationships between different measures such as costs, revenues and KPIs. By entering a number into certain accounts known as ‘drivers’, the model will then calculate related information.

Drivers are set by taking a target measure (e.g. revenue or some other ‘outcome’) and establishing what directly impacts its value. For those items, we then establish what impacts them – and so on. Measures at the end of the chain are known as ‘drivers’. Where possible, ‘Drivers’ need to be validated against past behaviour

For example, the drivers of Net Profit could include price per unit, unit cost, No. of visits and sales conversion rate. By entering data into these measures, the model is able to calculate Net profit.

These models also recognise constraints such as production volume and that at certain levels cost and revenue profiles may change e.g. the impact of discounts, late delivery penalties, or that more staff will be needed which will cause a step change in values. They also recognise that there is nearly always a time-lag between the driver and the result it supports. Driver-based models are good for modelling the relationships between activities and can be used to quickly generate future outcomes, but without the time, effort and politics involved in setting these values.

However, these models only work for a certain measure such as costs/revenues that can be directly related to drivers. Other measures such as overheads will be required to get the full picture. Also, they do not take into account unpredictable external influences such as the weather and they can only model what has happened in the past, which may not be a reliable indicator of the future in a volatile market or where product life cycles are relatively short.
Initiative planning.

Initiative planning recognises that it is the impact of specific actions that can help manage a change to the organic growth of an organization. Initiatives are in effect a project that details:

  •  An action to be performed
  • The department(s) involved in its delivery
  • The person responsible for overall delivery
  • The reason(s) why they are being performed and the measure of success
  • The timescale in which it is to be actioned along with defined start /end dates
  • Milestones through which the status of implementation can be monitored.
  • Resources that will be required.

Initiatives can be linked to drivers such as in the driver-planning model described above.

The difference in this planning model is that initiatives can be combined in different combinations and they can be moved back and forwards in time to see how they impact overall results. For example, if we delay initiative three by 2 months, what would be the impact on revenue and costs? Or, what if we dropped initiative two, could we bring forward initiatives four and five?

It is only by doing this kind of analysis, that the best use of resources for a given set of constraints can be determined.
Scenario Planning

Scenario planning can be used to assess different combinations of drivers and/or initiatives so that a choice can be made as to which achieves the best outcome in both the short and long-term, that is the most affordable and has the lowest risk. David Axson in his book on ‘Best Practices in Planning and Performance Management’ comments that: “Planning is not about developing a singular view of the future: one of the most valuable elements of any planning activity is the ability to factor in the impact of risk on assumptions, initiatives and targeted results. A scenario is a story that describes a possible future. It identifies significant events, the main actors, and their motivations, and it conveys how the world functions.”

Scenarios can include entering a range of driver values, trying out multiple combinations of initiatives and looking at the impact of a change to organization structures. The end result is to allow the side-by-side comparison of these scenarios, showing outcomes, any assumptions made as well as details of changes being proposed.
Contingency Planning

Contingency planning is similar to scenario planning, however, its purpose is to review the impact of a number of ‘What if?’ situations on current and forecast performance. For example, what would be the impact on profitability if raw materials were to rise by an unexpected 5%, or if the sales forecast was out by more than 10%?

Contingency models evaluate the outcome of these events and then allow managers to prepare a series of responses or initiatives that would mitigate or take advantage of such an event. Their aim is to help the organization prepare a ‘backup’ plan that can be implemented quickly.
Linking Plans to Budgets

Budgeting is concerned with resourcing a chosen scenario for a given business environment. Budgets should consist of three parts:

  • The resources required keeping the business going for the predicted business environment assuming no changes to the way the business operates. Some of this can be derived from driver-based planning models.
  • The resources required for chosen strategic initiatives to change/improve the operation of the business model. This can be set through initiative / scenario planning models.
  • Other resources not covered by the previous two parts. This will typically be manually entered or fed from supporting systems.

Together, the three parts make up the complete budget for future periods. Although most organisations conduct this process on an annual basis, there is no reason why it can’t operate on a continuous basis as advocated by the Beyond Budgeting movement.

Understanding Real-Time Business Intelligence

Posted by James Salmon at 5/7/2018 10:46:03 AM

Today’s business intelligence is mobile and agile. Here’s a look at basics of real-time business intelligence.

In today’s competitive business world, the company with the best intelligence techniques usually succeeds. Whether you’re an established company or a start-up, every company can adopt real-time business intelligence tools to make crucial decisions in a short period of time and access data in one place within fractions of seconds.

Business intelligence refers to the technology that collects, analyses and presents data. It includes a variety of applications used to analyse the business information and techniques for several activities in one central location. Real-time business intelligence tools produce analytics and gives exact information your business to make high-quality business decisions.

What does real-time business intelligence provide? 

Real-time business intelligence software turns raw data to insights a business can use to access the right information in short period of time. Companies use real-time business intelligence tools to improve decisions and to find the new business opportunities. Business intelligence is also used to identify cost-cutting ideas, uncover business opportunities and react quickly in delivering data and give powerful insights.

Business intelligence platforms can help enterprises accomplish the following:

Provide the best decision support system for users.

Improve business plans and gives quick at-a-glance insight.

Offer data for use in reporting and analysis.

Discover new market opportunities, identify hidden behavioural trends.

Increase business performance and operational efficiency.

Self-service BI software.

Compared to traditional analytics BI techniques, self-service business intelligence provides features and techniques to analyse data quickly. The self-service search-driven analytics BI gives you access to direct information and more benefits for the end-user without relying on IT. That is, even nontechnical people can do more with their data without being dependent on others for the analysis.

These business intelligence solutions are usually created to be user-friendly and fast so that anyone with admin access can analyse data, make decisions, plan and forecast on their own. Most of the organisation uses BI software to uncover flawed business processes are in a much better position.

Big data and BI software

Big data is widely deployed in most of the organisation, but it remains difficult to analyse the huge amount of data in short period of time. Given this volume of data, one of the crucial component of business intelligence software is scalability, which is essential to the success of companies in a wide range of industries.

Business executives and managers can easily analyse huge amounts of data to make better decisions faster and can discover hidden parts of the business through data analysis dashboards. Real-time BI dashboard tools let you find, and analyse data before you invest money in new projects and opportunities.

Business Intelligence Analytics

Real-time business intelligence software provides within fractions of seconds data that can be analysed through performance review dashboards. This is designed to enhance business collaboration, recover from business problems by giving deeper insights of the business.

There are many types of business intelligence analytics software available today, which are mostly designed to empower nontechnical business users to manipulate and interact with data to satisfy their own information requirements. The business analytics dashboard gives deeper analytics to the users to interact with data to satisfy their own information requirements as soon as possible.

BI on handled devices

Nowadays, you can access most business intelligence applications from any mobile device, allowing you a view of business data in real-time or near real-time. As hand-held device such as smartphones and tablets continue to overtake the enterprise, real-time business intelligence analytics keeps everyone connected to the organisation and offers new ways to engage customers with short period of time.

Real-time business intelligence software lets you make decisions using key performance indicator dashboard tools. No more waiting to analyse business data – and the better.

Are spreadsheets really the best tools for financial planning and forecasting?

Posted by James Salmon at 15/6/2018 9:22:29 AM

If you’re not relying on predictive demand planning to increase the accuracy of your financial forecasting, you’re not alone.

More than 45 percent of 1,500 CFOs surveyed by IBM say they’re not ready to call it quits with spreadsheets. Unfortunately, spreadsheet-based processes are laborious, inconsistent and can lead to numerous pitfalls. So why supplement your planning process with a fully automated, analytics-driven solution to manage a multi-billion-dollar business?

Jim Collins, performance management strategy executive at IBM, gives these three reasons: to be able trust the information, to reduce the potential for errors and to ensure departments are collaborating. Collins spent years in the CFO seat himself. Predictive analytics serve to make sales professionals more efficient, improve forecast accuracy and reduce inventory shortfalls while maximizing inventory availability.

Companies such as Huffy Bicycles and Mueller Co. have made the switch and are enjoying an improved planning process that enables them to deliver more insight and maximize product availability for their customers.

Take another example, McCormick & Company, which manufactures spices, herbs, and flavorings for retail, commercial, and industrial markets. The company didn’t have any visibility on the total impact of the changing price of nutmeg. Thanks to predictive analytics, McCormick was able to predict commodity pricing and saw impact not only on cost to company but allowed them to look at production scheduling, size and timing of buys to see significant savings.

Learn more in this webinar about how predictive technologies (not spreadsheets) can improve the accuracy of your own planning and forecasting.

3 Smart Moves for a Smooth Cloud Transition

Posted by James Salmon at 17/5/2018 5:02:09 PM

For FP&A, the cloud appears to have finally reached the tipping point. More and more organisations are realising the transformative potential of the cloud to enhance budgeting and planning, while also driving better business results.

Although finance is one of the last departments in the enterprise to go cloud, the shift is on, according to Gartner, who disclosed they are no longer covering non-cloud solutions in their latest report.  In fact, companies like SAP aren’t even included in the report, as they didn’t make the move to cloud fast enough.

And CFOs agree. According to a recent CFO Survey, finance leaders expect technologies to increasingly reside in the cloud. CFOs estimate that 33% of their IT infrastructure is software as a service today, and they forecast this to grow to 60% of their infrastructure in four years.

The bottom line: With a few exceptions, the key question facing CFOs and FP&A leaders is fast becoming not if you are moving to the cloud, but when you are doing it.

Yet committing to a cloud transition is only the first step. It’s essential to take key actions to help ensure a smooth transition and position your team and the broader organisation to reap the full benefits that a cloud solution can offer. Here are three smart moves that provide the foundation for success.

Assess your current state: The legwork you do leading up to your migration can go a long way toward ensuring a smoother, more productive future in the cloud. Think of the old mantra: “It’s hard to know where you are going if you don’t know where you’ve been.”

Obviously, the key to your pre-migration assessment is to identify the systems, technology, and processes currently being used to manage and analyse financial and operations data at your organisation. It’s also important to get a clear snapshot of the data itself. Where is it being housed? Is data siloed? Is there general agreement on what is the core data for your organisation?

This assessment will help create a benchmark from which to measure your progress, while also ensuring the cloud system you deploy has the functionality, capacity, and capabilities to deliver the most value.

Further, a detailed assessment of your current state has additional benefits. For instance, it should provide reassurance to your executive sponsor and the leadership team that the necessary research has been done and the potential benefits clearly identified. The assessment also helps identify processes or technology that are currently delivering value and might have a place in the post-cloud environment.

Educate and inform: Those already well-versed in cloud know its many benefits. For FP&A, the cloud frees teams from the drudgery of static planning and enables the fast, easy, and powerful capabilities of active planning. Yet even the best technology and most seamless deployment cannot be successful if you don’t get buy-in from everyone from the executives to the admins. In short, to be successful you need more than just a cloud transition strategy for the technical and logistical aspects of moving from an Excel environment or a legacy system to the cloud. You also need a cloud migration strategy to effectively communicate the benefits, and you need to provide adequate training to get partners from throughout the organisation understanding and leveraging the cloud technology.

It’s human nature for people to focus on “what’s in it for me” when faced with change. Yet once business partners grasp that a cloud platform can provide on-demand, self-service access to customisable dashboards, then you have a much easier sell. Ultimately, moving to the cloud should be positioned as not just an FP&A project, but rather an advancement that offers benefits to the whole organisation through more efficiency, better collaboration, and stronger business results.

Don’t declare victory early: If you accurately assess your current state and have effectively communicated the benefits of the cloud, you should move through the first phase of your transition with real momentum. From there, the key is to sustain it. It’s important to continue to promote the benefits of the cloud as an opportunity to adopt active planning that can enhance efficiency and create a competitive edge. For instance, once a cloud platform is established you can move toward a single source of truth—one set of data for the entire company. You can also leverage forecasting and modeling capabilities that offer value to business partners by providing insight on everything from managing headcount to more effectively tracking sales and inventory.

Taking your time and phasing your transition in ways that continuously build on the foundational benefits of the cloud will build an army of advocates, while also positioning FP&A as collaborative strategic partners as opposed to order takers and number crunchers. By making it clear from the start that a full cloud transition takes time and is most successful when executed in a phased approach, you buy yourself time to ensure that the migration is successful and offers the best opportunity for strong ROI.

Ultimately, by taking a well-planned, strategic approach, you can dramatically improve the chances that your transition to the cloud goes smoothly and delivers the maximum value to your business.

10 Must-Read FP&A Stories from 2017

Posted by James Salmon at 10/1/2018 3:49:42 PM

From the growing move toward making finance a strategic business partner to the challenges of addressing new revenue recognition standards, FP&A managers and practitioners had plenty on their plates in 2017—and have myriad challenges and opportunities ahead of them.

With that, enjoy our list!

The Wall Street Journal sparked a lively debate with this story on companies such as P.F. Chang’s and others pushing to reduce how much their finance teams rely on Excel for financial planning, analysis, and reporting. The article and its subsequent aftermath, which prompted widespread industry response, along with a blog penned by Adaptive Insights CEO Tom Bogan, highlighted how many companies are turning to new, cloud-based technologies for more strategic and efficient FP&A work. Read the story.

As the talent war heats up, what skills do FP&A pros need to compete? Writing on LinkedIn, Tom Hood, the CEO of the Maryland Association of CPAs, highlights the top seven competencies that are most in demand. Topping the list: strategic thinking, communications, and tech-savvy know-how with data analytics. Read the story.

With the increasing complexity of business, the demand for FP&A specialists who have a specific expertise or skill set is on the rise. IBM’s Business Analytics blog projects the trend will only continue as senior executives and decision-makers look to FP&A for more forward-looking insights as opposed to merely historical data. Read the story.

FP&A today is growing more attractive to many accounting professionals. However, for accountants interested in making the move to FP&A, many questions remain—particularly, what experience and expertise can they bring to their new role, and which new skills do they need to acquire? Accountexnetwork.com breaks down the challenges and opportunities. Read the story.

To compete in today’s fast-changing business environment, companies need competitive strategies—strategies that are supported by robust planning. Digitalist Magazinefocused on three red flags that signal your planning process might need a course correct. Read the story.

Does your organization often confuse planning with forecasting? Strategic Finance Magazine says it’s a common problem that can create headaches for FP&A. Here’s a breakdown of how the two processes differ and how to explain those differences to business partners. Read the story.

Done right, FP&A can drive real business value. We stick with Strategic Finance for a deep dive into best practices for FP&A and the impact that adhering to them can have on business performance. Read the story.

FP&A can play a pivotal role in helping to drive company growth. Yet adding maximum value requires understanding expectations and being aware that those expectations can differ from company to company. Afponline.org breaks down what FP&A should know to help its companies grow. Read the story.

Boring finance? Not so much anymore. CFO.com notes “it’s quickly getting more interesting” as advancing technology is reducing the drudgery of manual tasks and replacing them with dynamic planning and analysis tools. Read the story.

Recognising the limitations of Excel, Tampa Bay Rays CFO turned to the cloud to manage his FP&A function. He shares his story in Fortune, highlighting a need for collaborative scenario planning that Excel just can’t handle. Read the story.

Evaluating CPM/FP&A System: Nine Key Areas for Consideration

Posted by James Salmon at 29/12/2017 1:56:37 PM


There are many software products that claim to support CPM, but often they only support some aspects, for example financial planning and reporting. One of the issues is that the term CPM is synonymous with budgeting, forecasting and management reporting which by itself cannot provide a complete solution.  

Similarly, some vendors have multiple products covering different parts of CPM. For example, many have a scorecard application that they deem suitable for strategy management; a separate solution for collecting budgets and forecasts; and yet another for reporting and analysis. In the context of this framework, these multiple solutions can only work if they are truly integrated and can be made to operate as a single system. Without this level of integration system maintenance becomes an unbearable nightmare that cannot suitably adapt to the dynamics of the economic environment.

It is worth pointing out that CPM from a vendor’s point of view is a mature market and most have similar capabilities. For organisations looking for discreet planning, budgeting, forecasting and reporting solutions, there is a wide range of choice with vendors offering good solutions. But for organisations wanting to implement a complete CPM solution it is easy to be misled on what product suites can and can't do. 

This evaluation section of the framework outlines the key areas to be investigated so that those evaluating solutions can accurately assess whether the products selected will meet their planned and future needs of CPM. 

One area not covered in this evaluation is a detailed assessment of the technology that underpins a CPM solution, whether that is SQL, OLAP, ROLAP, or In-memory BI. One of the reasons is that having a common technology platform or a system built on a leading ‘open’ database is no guarantee that the vendor has an integrated solution or that it will perform. Solutions should be assessed on their ability to solve a business problem over a period of time. The choice of technology should be up to the vendor to provide the best application they can for the price being offered and that from a customer point of view gives the best return on its investment. 

The evaluation areas here are primarily concerned with a product's capability to meet the CPM framework discussed in this document. They include: 

  1. Data Model – the kind of data that the model can hold
  2. Dimensions, Members and Structures – the way in which dimensions and dimension members are managed
  3. Functionality – the functions required to support each process within
  4. CPM Reporting capability – the types of reports required to support decision-making
  5. Workflow – how users are led and directed through CPM processes
  6. Audit capabilities – how data and structure changes can be tracked and reported
  7. Affordability – how to assess the cost of ownership
  8. Vendor Ability – how to assess the commitment and expertise of a vendor
  9. Demonstrations – what things to look for and test in a workshop session 

1. Data Model 

At the heart of every CPM system is a data model that stores information relating to: 

  • Strategy and the organisational objectives being supported
  • The business environment in which it operates 
  • The way that business value is generated
  • How financial resources have been allocated
  • Forecasts on where the business is heading, and
  • Financial results that have been/will be achieved

Each type of data is different and contains both structured (e.g. numbers) and unstructured (e.g. text) information that is held at different levels of granularity and for different time periods. Some data will be required on a monthly basis while other – for example forecasts involving contracts – are better handled by assigning a date. This means that if the date changes, then the system should know how to roll this up into the appropriate reporting time period. For organisations that deal in seasons, for example retail, the ability to define time as a span between specific dates is important, while results would still need to be accumulated on traditional monthly basis. All these requirements means that a single multi-dimensional model cannot (without serious compromises) meet the different needs of CPM, and yet this data still needs to be bought together if performance is to be planned and managed.

Things to look for

  • Ability to hold multiple data sets with different levels of granularity, dimensions and member combinations to support strategy, tactical plans, budgets, forecasts, management reports and risk. 
  • Ability to define and accumulate time in multiple ways. 
  • Ability to store data at a day level, with the system aggregating data into the right time hierarchies for reporting. 
  • Able to define and hold individual initiatives with associated dimensions and members, along with flexible start and end dates. 
  • Ability to attach unstructured data – comments, notes, documents, responsibility – with any data item. 
  • Ability to combine different data types for reporting and analysis, along with any unstructured data. 
  • Ability to define financial accounts as to type e.g. Debit/Credit, Balance Sheet, P&L, Statistical, etc. This information is used to ensure data rolls up through time and other dimension hierarchies correctly and that variances respect natural sign conventions. 
  • Ability to define statistical accounts/measures so that any assigned calculations take place in the correct order and at the appropriate level in a hierarchy. 

2. Dimensions, Members and Structures 

Much of the data within a CPM model will be organised as hierarchical structures e.g. organisation; strategy, product families. Many members will be common across different CPM data sets and so any change in definition should automatically be applied to related sets. 

Hierarchies change with time, but in order to preserve historic reports, original structures need to be retained. For assessing potential changes, the CPM system should allow alternative structures that can be used to report the impact of change, should that change be adopted.  

Finally, hierarchies are not the only way to select and analyse data. The ability to use attributes where members are selected and grouped according to a range of ‘tags’ assigned to them is an important capability. For example: 

  • Members in the account dimension can have attributes that identify them as being measures of success, resource, risk, etc.
  • Members in the strategy dimension can have attributes that identify whether they are objectives, themes, initiatives, etc.
  • Product hierarchy members can have attributes that denote colour, or whether the product is ‘new’. These attributes can then be used to create an alternative grouping of members, irrespective of where they fit in their respective hierarchy.

Things to look for:

  • Master data management of dimensions and members. It should be possible to apply a change in a member and have it automatically update any data set where it is used 
  • Ability to hold ‘cause and effect’ structures for strategy modelling. These should allow data to be accumulated to multiple parents according to the methodology being used (e.g. what is the total cost of all initiatives supporting objective A), as well as by organisational unit, etc. 
  • Structure changes that are time stamped with previous versions being held 
  • Ability to consolidate and compare the impact of different structure versions for reporting and analysis purposes 
  • Ability to assign and analyse data by multiple attributes and not just by a dimensions’ physical structure. 

3. Functionality 

Functionality can be split into two areas – that which is common to all areas of CPM and that which is specific to a particular CPM process. With the latter, a capability to support a specific process may well be useful in other processes. Reporting capabilities are covered in section 5.5. Here are the things to look for in a CPM solution: 

Common functionality: 

  • Ability to convert local currency data into base currency(ies). This should be a true financial conversion supporting multiple rate types (e.g. opening rate, average rate, closing rate); detection and posting of exchange gain/losses; and the ability to choose from multiple rate versions (e.g. actual, budget, forecast) 
  • Consolidation of data from ‘leaf-node’ members into hierarchical groups
  • Ability to load data from external systems including the mapping of account and department codes into the appropriate CPM data set members
  • Ability to delete data from a CPM data set
  •  Ability to copy data between periods, versions and other combinations of dimensions and members
  • Full security system that automatically restricts users access to functionality and specific areas of data 
  • Ability to present data entry screens to users along with restricted areas that cannot be changed
  • Ability to support multi-languages for both help and setup information
  • Ability to support web, social media, and mobile access

Strategic planning specific functionality: 

  • Supports the methodology being used by the organisation e.g. Balanced Scorecard, Performance Prism, Six Sigma, etc. This means that the system uses the same terminology as defined by the methodology.
  • Ability to set up ‘strategy maps’ that show cause and effect and allows senior managers to define, for example, themes and objectives; to allocate measures of success, implementation and resources.
  • Support for ‘Driver-based’ planning where entering a few key data items generates related data such as a summary P&L. 

Tactical planning specific functionality: 

  • Ability for users to add initiatives that support defined strategies, comprising of combinations of dimensions and members that describe a course of action. 
  • Ability to assess combinations of initiatives in terms of resources consumed and their impact on corporate goals. 
  • Ability to ‘Time shift’ initiatives i.e. to change their start and end data which then causes all associated data to be ‘moved’ in time.
  • Ability to ‘approve’ and ‘reject’ and ‘lock’ initiatives from change
  • Ability to select initiative combinations based on their ability to optimise resources to meet a specific goal
  • Ability to hold combinations of initiatives as different versions of a contingency plan. These do not consolidate with other data and can be ‘re-called’ as required.  

Financial planning specific functionality:

  • Ability to perform a ‘Top-down’ spread where a single number can be allocated back from a top- level node through to leaf-nodes in a hierarchy. It should be possible to ‘exclude’ members during the spreading process.
  • Ability to spread data across members of a dimension according to a range of profiles. It should be possible to exclude members when carrying out the spread.
  • Ability to perform allocations according to set rules that can be invoked by an administrator
  • Ability to define an approval process with appropriate levels of data locking.

Forecasting specific functionality: 

  •  Ability to hold data by contract, project and status 
  • Ability to perform time-series analysis and use results to predict future periods

Risk Management specific functionality:

  • Ability to hold 'risk' and 'impact' factors
  • Ability to calculate risk profile
  • Ability to conduct 'What if?' analyses without affecting data held
  • Ability to hold contingency plans that can be invoked when risk materialises 

Statutory reporting specific functionality:

  • Ability to collect, match and eliminate ‘intercompany’ information 
  • Ability to store ownership data that can be used to adjust results for minority or joint ownership interests 
  • Ability to eliminate third party ownerships
  • Ability to support ad-hoc and recurring journals that ensure Balance Sheet integrity
  • Audit trail and reporting
  • Ability to analyse statutory impact over more than a one year time horizon.
  • XBRL support

4.  Reporting Capability 

Reporting occurs throughout all CPM processes, while the Management reporting process brings together a range of information that determines whether the plan is on track and what decisions can be taken to improve performance.

Things to look for: 

  • Ability to create dynamic Strategy maps. I.e. as initiatives are added, the system should be able to position that initiative within the strategy map without having to redefine the report.
  • Interactive Dashboards / strategy maps. i.e. users should be able to select ‘off-grid’ members such as the time period being shown or the department for which data is being shown.
  • Ability to generate Financial statements and accepted layouts / formatting
  • Ability to generate variances that respect Debit/Credit and account type (e.g. Balance Sheet, P&L, Statistical) assignments.
  • Ability to ‘drill-back’ to underlying detail/source systems from which the results were produced.
  • Ability to automatically match common dimensions and members from multiple data sets for the purpose of generating a report.
  • Ability to bring any information including unstructured data, from any data set and place it anywhere on a page.
  • Ability to perform simple calculations between multiple data sets on a page.
  • Ability to change common dimension member selections from one place where multiple data sets are on a page.
  • Ability to generate charts that are linked to reported data sets. 
  • Ability to sort / group data according to content, dimension member and assigned attributes
  • Ability to omit rows/columns where combinations return ‘blank’ data.
  • Ability to set up ‘key-words’ that can then be used to drive the content of a report. E.g. Current Month, Current Year – can be set in one place that is then used to generate report content for that setting.
  • Ability to group different types of reports into books that can be run as a single action. These respect user security and will omit any data/pages the user is not allowed to access.
  • Ability to access data securely from a spreadsheet 
  • Ability to create pdf, Word, Web and other output formats
  • Ability to deliver content via Mobile devices

Alerting capabilities

  • Ability to alert users/managers when a specific variance has been exceeded 
  • Ability to request a response to an alert 
  • Ability to chase up users who have not responded to an alert 
  • Ability to review all alerts to determine: Which areas generate the most alerts, the status of response to alerts; how quickly users respond to alerts 

5. Workflow 

Workflow relates to the way users are directed through the different tasks involved in a process. There are two types of process: 

  • Structured processes are those that are followed through a specific task e.g. budgeting. It’s structured in that the activities, the people involved and the timescales are known in advance. 
  • Unstructured processes are those that occur when an event or an exception are encountered. In this case the particular activities to be triggered and the people involved are only known when the exception occurs. 

Structured processes can be dealt with through menus but it does requires users to know where to look and to choose the right option. This can make it hard in creating an efficient process as there is no way to prioritise options for specific users. 

Unstructured processes cannot be realistically handled by menus and will require dynamic workflow capabilities to trigger activities as and when they arise. As these activities are completed they themselves will trigger other activities to be carried out. For example, a sales forecast that is 10% outside of a limit, may trigger a request for more information and confirmation of the levels expected. When this is approved it could trigger re-planning by the factory, or an action by marketing to increase advertising spend. These will then have a knock-on effect onto other departments. 

Both types of process should be supported if CPM is to become a continuous, efficient process aimed at managing corporate performance. 

Things to look for: 

  • Ability to define tasks i.e. discreet pieces of work such as enter data, load data, run consolidation, run report, etc. 
  • Ability to combine tasks into sub-processes that are automatically configured for individual users 
  • Automatic generation of “To do” lists that are specific for each user and contains the work to be done, the deadline and any approval process 
  • Automatic warning of task deadlinesAutomatic escalation of non-action on a taskAutomatic triggering of tasks based on dates, an alert, exceptions or events Overview of active processes/tasks, highlighting deadlines and status Ability to ‘unwind’ a task or series of tasks with full audit trails. 

6.  Audit Capabilities 

The ability to audit any plan or result is a key requirement of any corporate system if the numbers shown are to be trusted. This includes collecting comments on what the numbers actually mean as well as how they were gathered and transformed.

Things to look for: 

  • Audit trail on structure changes. All changes should be date-stamped along with the user making the change. Ideally there should be provision for storing comments on why the change was made. 
  • Historic results should remain with historic structures for audit purposes, however it should be possible to consolidate historic data with newer structures for comparative purposes that do not overwrite historic results.
  • Audit trail on processes. It should be possible to review all planning tasks and activities over a period of time. This can help identify bottlenecks that can improve process times in the future and help document the way in which decisions were made.
  • Audit trail on all data changes. It should be possible to track how each number was entered; any adjustments and transformations it went through; and how it consolidated into any total. All changes should be time and date stamped, along with user details and the process activity that changed it. As with structure changes, there should be a provision for storing comments on changes that are then available in reports.

7.  Affordability 

This area of the evaluation considers all the costs involved from initial purchase, through implementation and to the resulting systems’ on-going cost. It also looks at the expertise required to setup and maintain the system, and what else an organisation may have to purchase in order to realise their vision for a complete CPM solution. 

Things to look for: 

  • The initial purchase cost
  • The cost of increasing the number of users
  • The length and cost of training for an administrator and end user
  • Estimate of implementation cost
  • On-going software maintenance cos
  • Other things that need to be purchased to make the solution complete
  • The level of expertise to use and maintain the resulting system.
  • Does the system provide ‘Best practice’ templates, to kick-start an application
  • Can ‘users extend the application for their own local reporting purposes. 

8. Vendor Ability 

This looks at the vendor’s commitment to CPM and the maturity of the product. Maturity can be both a blessing and a curse – Mature products can offer a large reference base but also may be coming to the end of their life, which then may require an upgrade or redevelopment cost. 

Things to look for: 

  • How CPM fits into the future of the company
  • The other products the company sells and supports, and how much is dedicated to the CPM application being sold.
  • Other products the vendor may have that seem to compete with the solution being proposed
  • How long the product has been around and where will it be in 5 to 10 years time.
  • The level of business expertise they can offer in helping redesign processes and metrics
  • The level of technical expertise to implement the solution
  • The financially stability of the company providing the solution.
  • The experience and capability of the company installing the system 

9. Demonstration Workshop 

So far the software evaluation has focused on capabilities that can be viewed in isolation to each other. However, to support CPM these capabilities must be delivered in a seamless way so that the solution operates as single application. The only way this can be properly evaluated is by performing a number of scenarios that cross different processes. This is the purpose of the demonstration workshop. 

It is unlikely this can be accomplished without some planning from the vendor and so the scenarios to be evaluated should be communicated in advance and covered in detail during an interactive workshop. The aim is to gauge the levels of integration that exist and the effort required to maintain them. 

Strategic Planning scenarios 

  • Create a strategy map showing actual measures for the current and target measures for the next 3 years 
  • Define a new objective. Set targets for success and the limit on resources that can be consumed by supporting initiatives.
  • Show how the new objective updates the strategy map 

Tactical Planning scenarios

  • Combine a number of initiatives to review the resources they would consume if approved.
  • Review initiatives by start date
  • Delaying an initiative by 7 weeks: Show the impact of this delay on planned resources 

Financial Planning scenarios 

  • Show how the system directs departments through the planning process.
  • Show how a top level strategic financial goal is spread down to individual departments as a target
  • Move a business unit between divisions and compare the impact on plans.
  • Show how a department has its plans approved.
  • Show how to create an alternative version of the budget which has a different departmental structure

Forecasting scenarios

  • Show how potential sales contracts and/or projects are recorded.
  • Change the status of a potential future contract (e.g. from tentative to approved) and how that updates the overall forecast
  • Change the date of a potential future contract and how that updates the timing of the overall forecast
  • Show how to add a new product, associated forecast data and how this updates the overall forecast
  • Show how the system handles issues such as when a forecast misses a future target 

Management reporting scenarios

  • Show how the system handles the mapping and import of actual data
  • Show how actual results updates:

             o Comparison with strategic plan (i.e. updates the strategy map)

             o Comparison with tactical plan

             o Comparison with budget / forecast 

  • Show how to report the impact of initiatives on    the achievement    of strategic goals
  • Show report that sorts initiatives according to    overspend against budget
  • Show how to create a report that combines strategic goals, initiative status vs. budget
  • Show basic financial statements: Balance Sheet, P&L, Cash Flow    


The aim of this framework has been to clarify the purpose of a CPM system; ways in which it can be implemented; how it relates to supporting BI/Reporting applications; and how to evaluate CPM software solutions. 

It outlines an ideal implementation although it is unlikely that a company will ever implement it in this way. However, it provides a goal for an IT systems strategy that will genuinely help managers and executives manage performance. 

By adopting such a framework, organisations will realise a number of high-level benefits it provides, including: 

  • A single, consistent framework by which the whole organisation manages performance
  • Focus on the things that are critical to the organisation as a whole
  • Reports and analyses that tells the story of ‘what and why’
  • Information in context that links strategy with resources and monitors the effectiveness of processes
  • A documented audit trail that shows the decision-making process
  • A mechanism by which IT projects can be assessed and placed in the context of improving decision-making. 

Three Ways Your Spreadsheets Are Slowing You Down

Posted by James Salmon at 5/12/2017 5:15:46 PM

Make no mistake: Decades-old spreadsheets are not built to handle the complexities of modern, fast-paced businesses. They’re great personal productivity tools, but can present major accuracy issues when shared across multiple users and locations.

So for all of you spreadsheet jockeys out there, here are three ways that Excel-based processes could be slowing you down, and what to do instead.

1. You can’t effectively audit a spreadsheet over time.

Heavy reliance on spreadsheets to support crucial financial processes is detrimental for a variety of reasons. First and foremost, spreadsheets are extremely vulnerable to human error. Just one incorrect number or formula can bring your professional credibility into question. And because you can’t audit spreadsheets, you might not even know when the formula changed, who changed it, or how long it’s been broken. Since spreadsheets require manual entry, they’re just not scalable—and finance leaders within fast-paced businesses don’t have time to waste on manual tasks.

They need a quick and accurate process through which to provide real-time information to business decision-makers. With the advancement of cloud technology, finance teams are turning to systems that can provide a single source of truth for actuals, budgets, and forecasts that complement their spreadsheets. This allows for stronger, smoother, and smarter processes, and the end result is more time for analysis and strategising.

2. A timely, actionable, and reliable system of rolling forecasts is important, yet cumbersome within a spreadsheet-based system.

A rolling forecast system is more than just an option for the modern finance leader—it’s a way of life. Traditional financial budgeting processes just don’t cut it anymore, as finance professionals need real-time information and actionable insights to help propel the business forward. Budgets are often outdated at the start of the year, whereas rolling forecasts adjust to what’s actually happening with your business and market. A growing company needs a tool and process that enables leaders to quickly identify performance trends and needed course corrections. Rolling forecasts allow businesses to extend beyond the annual planning wall and proactively manage the future.

3. Incorporating dashboards into your management reporting packages is a tedious process using Excel, yet it’s the best way to identify areas of strength and improvement.

Most managers can look at a bar chart and make an accurate assessment of the data and trends. But you can’t always do that with a set of numbers. In fact, you can hardly ever glance at a 1,000-plus cell spreadsheet and tell much of anything. But telling the story behind the numbers is critical to informing predictable forecasts that drive change. That’s where visual analytics dashboards come in.

Given that not every department is as inherently number-oriented as finance, dashboards provide an intuitive visual representation that helps managers make decisions based on accurate accounts of historical performance and projected trends. You can customise the information to reflect the most relevant drivers to each cross-functional department, and include ratios to help provide context and meaning.

The key is to present the KPIs that matter most without cluttering dashboards with too many details. When you can make dashboards relevant to departmental managers, you’re empowering them to analyse the information and make better, faster decisions within their area—which are ultimately reflected within the business’ bottom line.

Introducing Cognos Analytics 11.0.8

Posted by James Salmon at 10/11/2017 4:38:44 PM

The Cognos Analytics team has been hard at work on new enhancements, and I am thrilled to announce that release 8 (11.0.8) is now generally available. This release tackles a lot of those small, but significant, enhancements that will help you and your users get the most out of this smart business intelligence and analytics solution.

IBM's large installed base of customers will be happy to know that in this release IBM focused on addressing some of your top Requests for Enhancements (RFE), so rest assured that IBM appreciate (and are listening to) your feedback. IBM also addressed some items that will make it easier to administer and manage your BI and analytics environment. Finally, IBM continue to enhance existing capabilities, for example, adding latitude/longitude support in mapping for reporting.

The enhancements touch all aspects of Cognos Analytics, but they are all focused on reducing the time it takes to get things done and making visualisations easier to understand. These enhancements mean Cognos Analytics 11.0.8 is:

Faster and more precise for dashboard and report creation

  • Addition of latitude and longitude layer in reporting
  • More output options for reports with the ability to save and output a report as XML format
  • Support the viewing experience your users want with the ability to select the Default run action per report (latest saved output, always run the report with the latest data, open in edit mode)

Tailor-made to meet your needs – so you can customise your experience

  • Upload custom images with Image library extension in reporting (on premise and on cloud)

Designed to make your data work for you with faster data preparation

  • Ability to select from multiple connections to a data source with support for ambiguous data connections (either multiple connections to the same data source or multiple sign-ons to the same data source) for data modules and dashboard
  • Faster data set creation with support for Design mode in data set editor

Better visibility and control of your BI and Analytics environment

  • Easy tracking of dashboard usage with support for auditing
  • Keep track of all of your scheduled reports with support for Manage my schedules and activities

Want a quick overview of the cool new features in R8? Watch Kevin as he takes you through the highlights in the What’s new in R8 demo video.

IBM “top-ranked” in 20 KPIs in BARC survey, including usability

Posted by James Salmon at 27/10/2017 4:10:33 PM

The Business Application Research Center (BARC) recently examined solutions for planning, budgeting and forecasting in what it called “the world‘s largest and most comprehensive survey of planning software users.” BARC reported on its findings in The Planning Survey 17.

In the BARC survey, IBM Planning Analytics was “top ranked” in 20 different KPIs, including planning functionality, business value, flexibility, product satisfaction and more. BARC found that “convincing performance” was one of the main reasons why customers chose Planning Analytics: “Its in-memory database is clearly capable of handling large data volumes as well as large numbers of users, leading to a top rank in all of its peer groups, outpacing other big competitors…”

But again, usability KPIs are those that probably mean the most to users and IBM Planning Analytics was top ranked in customer satisfaction and ease of use. BARC said, “With its Excel user interface, customers confirm that Planning Analytics is easy to use, compared to other software generalist’s tools. As a result, IBM is top-ranked for ease of use in [its] peer group.” No wonder that “83 percent [of Planning Analytics customers] say they would probably or definitely recommend Planning Analytics to other companies.”

Read BARC’s The Planning Survey 17.

Why not take a look at Planning Analytics for yourself?

Forrester evaluates enterprise BI platforms based on differentiation: Where does IBM fall?

Posted by James Salmon at 4/10/2017 9:55:20 AM

A couple of weeks ago, Forrester released The Forrester Wave™: Enterprise BI Platforms With Majority On-Premises Deployments, Q3 2017. They redefined the enterprise BI market into two areas: majority on-premises and majority on the cloud (a report for cloud was also published). Vendors appear in only one report. Taking a novel approach, Forrester evaluated vendors based on differentiation rather than on querying, reporting and data visualization, which they describe as “table stakes.” I’m proud to announce that based on this redefinition and rigorous criteria, IBM was named a leader.

In the report, Forrester explained why they redefined the market: “BI technology (along with all related ones, such as big data and artificial intelligence) has evolved at lightning speed over the last two years.” Recent changes in BI platforms blur the lines between static reports and interactive visualization, so the two are not separate categories anymore. And, although Forrester split vendors between on-premises and cloud, they noted that cloud really isn’t a separate segment, as the vendors in this report also offer cloud deployments.

Forrester looked at all the vendors with more than 50% of their revenue from on-premises BI sales with an eye to current offering, strategy and market presence. In their summary of the 22 criteria used to evaluate vendors of enterprise BI platforms with majority on premises, they focused on differentiation, specifically in the following areas:

  • “Actionable and suggestive BI”
  • Advanced analytics
  • Connectors to business applications and integration with competing BI platforms
  • Data catalog and data governance features
  • Data preparation and profiling
  • “Data visualization certification by an objective third party”
  • Advanced geospatial analytics such as geofencing
  • Hadoop and Spark-based architecture
  • “On-chip computing”
  • Compliance and certification with standards bodies
  • Read and write capabilities


In the report, Forrester writes, “IBM offers a broad and comprehensive BI platform with a touch of AI.” They note that the integration of “long-time BI market-leader” Cognos Analytics with SPSS offers predictive analytics and that “a shot of AI” is provided by Watson Analytics. “Knowledge gaps (or ‘I don’t know what I don’t know’) are a significant missed opportunity in many BI environments, and that’s precisely what Watson Analytics addresses.” Forrester adds that after getting insight without having to know the questions to ask, users can turn it into “comprehensive descriptive and predictive BI applications using Cognos Analytics and SPSS.”

A key factor in any Forrester evaluation or report is what clients have to say. So, what did our clients tell them about us? “Client references gave IBM high scores for quick time-to-value, scalability, stability, security, cloud/hybrid architecture, extensibility, and frequency of upgrades.”

In the report, Forrester noted that “insights-driven businesses will take $1.8 trillion from their competitors that are still running their companies by data.” IBM is committed to ensuring that insight (and not data alone) is the basis for business decisions and understanding performance. After all, the basic premise of IBM business analytics solutions—Cognos Analytics, Watson Analytics, Planning Analytics, and SPSS—is insight to action. Data might be one of the most valuable resources in the 21  century. But, as we have demonstrated in other posts for this blog, insufficient analysis can lead to erroneous conclusions, some of which can have far-reaching effects. To be recognized by Forrester as a leader in delivering BI, which is a “key enabler of insights-driven businesses,” is gratifying.

The report is useful for anyone who is evaluating enterprise BI platforms and wants a detailed explanation of how BI has evolved. All 15 enterprise BI platforms are thoughtfully reviewed. To learn more and get the full details of how IBM scored in each of the 22 criteria, download the report.

How do forecasts differ from budgets?

Posted by James Salmon at 28/9/2017 1:45:52 PM

If we update our view of the future more frequently and don’t confine it to the financial year it is obvious that this will be more useful than traditional annual budgets based on the financial year.

So, you might think, forecasts are like budgets but done more frequently – right? Wrong.

Forecasts and budgets are fundamentally different animals, and a failure to recognise this is the cause of many of the problems people have in implementing forecasting processes that deliver value.

The best way to think about forecasts is that they are future actuals. Whereas actuals inform you about what has happened given what you did in the past, forecasts are an attempt to work out what will happen in the future given what you have done and what you plan to do.

You can’t change what you did in the past but you can change your plans…and this is the reason why you produce forecasts. They enable you to determine if and how you need to change your plans to achieve the outcome you want.

To achieve this a forecast needs to be an honest reflection of your expectations. What it can’t be is a way of setting goals or budgets, because these reflect your aspirations. If you try to use forecasts in this way there are only three possible outcomes:

1.      You will get bad forecasts

2.      You will get bad targets or budgets

3.      You will get bad targets and bad forecasts

Indeed, forecasts on have value if you can change your plans in order to achieve the outcome that you want. And since this might mean reallocating resources, forecasts are in opposition to traditional fixed budgeting rather than a handy uncontroversial add on to the process.

And that’s not the only reason why forecasting and budgeting make uncomfortable bed fellows.

Traditionally variance analysis is used to manage performance back to budget and in this world a negative deviation from budget is bad. In a world of forecasting, however, gaps are good, because it is the existence of gaps that tell you that you need to do something different.

Imagine that you are in a sailing boat. You know where you want to go and before you set out you made a plan of how you are going to get there based upon certain assumptions about the wind, tides and so on.

But very often when you are sailing – just like in the world of business – the assumptions that you originally made were wrong because you had no experience of the waters that you were sailing into. Or perhaps conditions changed after you set out. In these circumstances, in order to get where you want to go you have to plot a new course, the first step of which will involve working out where you will end up if you carry on doing what you planned to do.

This forecast may well tell you that you are going to end up hitting some rocks or in some other bad place. This is useful knowledge. This is why you forecast. Your forecast is telling you that you need to do something different.

At this point the appropriate response of the captain to the navigator should be ‘thank you for telling me. What do I need to do differently?’

In business however, because people have been trained to think that differences are bad, forecasts that show adverse outcomes are often greeted with words like ‘this is unacceptable’ or ‘you must try harder’. And worse, when forecasts change to reflect changing circumstances, we often hear ‘last month you said x but know you say y. Do you know what you are doing?’

If this is what happens people pretty soon learn that although you say you want a forecast what you really are asking for is reconfirmation of the budgeted numbers. And if this happens, whatever it says at the top of the piece of paper on which it is written, it is NOT a forecast at all, and everyone has wasted their time. Worse it might have engendered a false sense of security and you may be about to stray into dangerous waters without knowing it.

So forecasting – done well – is much more than a minor modification to traditional processes performed to provide flexibility that the annual process doesn’t possess. It is truly subversive because it demands a change in many other processes and more importantly the mindset that underpins the traditional model of performance management.

Getting the mindset right is probably the most important and difficult challenge that has to be addresses when introducing forecasting into an organisation, but it is not the only one.

Traditional Budgeting: what are the alternatives?

Posted by James Salmon at 31/8/2017 10:50:12 AM

It is difficult to defend traditional budgeting, so even those who worry about not having budgets don’t try to. Instead they argue that the problems are not with budgeting - it is to do with the way that they are produced. We don’t need to change budgeting; we just need to do it better.

Better Budgeting

Although the words are often bandied around it is sometimes difficult to work out what ‘Better Budgeting’ actually means, but it seems to involve doing the same things slightly more efficiently and more frequently with the hope that people will behave better.

Sceptics might view this as doing the wrong things righter.

Another option directly addresses the source of one of the major problems of traditional budgeting – the tendency to take last years actual as the starting point for negotiations on budgets. This has a ratchet like effect on costs – they only go up – and reinforces the sense of entitlement that budget holders feel.

Zero Based Budgeting

To counter this Zero Based Budgeting requires participants to justify every item of cost from first principles every year. The methodology first came to prominence in the mid 1970’s when the Carter administration tried to apply it to Federal budgets, but it quickly fell out of fashion.

More recently it has made a comeback as it has been used aggressively by the people running the acquisition vehicles that have created two predatory giants of the CPG sector: AB InBev and Kraft Heinz. The model is simple: use debt to buy a big company and quickly consolidate its operations and strip out discretionary costs to fund the next big acquisition.

The problem is that in solving one problem with traditional budgeting it makes other problems more acute. It is inevitably more bureaucratic and costly, takes longer and so is less flexible. It also supercharges the annual negotiation process since the stakes are so high.

So it is not difficult to see why it fell out of fashion first time round. And is it also easy to see why it is attractive if you want to see a quick financial return and you are not too worried about the long term. Cynics might argue that you don’t need a large and complex process to say ‘no’ to everyone in your business that wants to hire extra people or make any investments.

Rolling Forecasts

Those who are highly sensitive to the lack of flexibility of traditional budgeting often see rolling forecasts as the answer. If we update our view of the future more frequently and don’t confine it to the financial year it is obvious that this will be more useful than traditional annual budgets based on the financial year.

So they invest in driver or activity based modelling capabilities to help them produce forecasts more efficiently and quickly, which is clearly a ‘good thing’. But while this might be part of the solution they eventually come to realise that rolling forecasts on their own cannot be the solution.

This is because forecasts do just one job – they create an expectation of the future – whereas budgets do many more. Budgets are based on expectations but they are also used to set aspirations (targets), allocate resources and to provide a basis for measurement (variance analysis) and the co-ordination of activities.

If alternative processes for these other jobs are not created one of two things will happen.

Either the budget – or all its problems – will still be needed failing that the roles previously performed by the budget will be loaded onto the rolling forecast. So instead of being a light touch, agile, single purpose process the rolling forecast mutates into a rolling budget and we are back where we started…or worse.

The final alternative to traditional budgeting is founded on this key insight. In order to manage an organisation we still need to set aspirations, forecast likely future outcomes, allocate resources and measure and co-ordinate activities across the organisation. Before we can abolish budgeting we first need to find better ways to do those jobs that it performs.

Beyond Budgeting

The name given to this movement is descriptive but unfortunately in some people’s minds it conjures up a nihilistic vision of chaos, but I believe these fears are misplaced. Control (in the non-pejorative sense of the word) is key to Beyond Budgeting – it is simple exercised in a different way, using different tools. The ends are is the same, but the means differ.

From this it will be clear that Beyond Budgeting is based on the objective of helping organisations to continuously sense its environment and quickly adapt to changes in it.

You should also get the sense that it is not an ‘all or nothing’ idea. It provides a list of ingredients that you can used to bake a better performance management ‘cake’ than the stodgy budgeting one that you are normally forced to eat at a set time each year.

But you can’t combine the Beyond Budgeting ingredients randomly - you need a recipe.

Rolling Forecasting is the New Annual Budgeting

Posted by at 15/8/2017 3:21:53 PM

While increasing economic uncertainty is leading to increased aversion to risk among CFOs, accepting change and uncertainty as a daily norm can help reduce the chance of storms when it comes to an organisation's future. Just like weather forecasting, financial forecasts have become much more accurate with the rise of technology to support real-time data. Unlike weather forecasts though, rolling forecasting for financial professionals can be used to influence the future and bring successful outcomes for organisations. This dynamic financial strategy is the future of budgeting for companies of all sizes if they want to convert strategy into execution.

Rolling Forecasts Roll with the Punches

Often, organisational leaders make the mistake of putting the emphasis on predicting the future rather than changing it. This sets up a mindset for failure if the predicted outcome doesn't materialise. It won’t allow them to convert strategy into execution either. But a rolling forecast poses a new framework that rolls with changes taking place now and can help CFOs make better, more relevant, strategy driven decisions.

Rolling forecasts:

  • Are dynamic and adapt well to change
  • Can pinpoint hits and misses in the budget
  • Produce clear ownership and reduce silos
  • Focus on actual business operations rather than financial variance
  • Chart a forecast for success instead of being a mandatory exercise
  • Enable organisational leaders to compare strategic objectives and actual predictions

A Financial Strategy That Adapts to Change

A rolling forecast doesn't limit an organisation the way a traditional fiscal year does. Instead of having a set 12-month budget period (or longer), a rolling forecast replaces the previous month with a new one tacked on at the end of the period. This keeps the budget fresh and relevant because it's not just using a mandatory period but instead being updated with real-time data. CFOs can use this to the organisation's advantage by creating forecasts that act as living documents rather than static fiscal year plans. The emphasis moves from countdown status to the ability to make timely tweaks as they're needed.

Rolling forecasts give organisations:

  • Accuracy through relevancy: Modifications can be made immediately instead of having to wait until the yearly budgeting meeting.
  • Agility through flexibility: Time-sensitive decisions don't have to wait until the decision is no longer important or relevant.
  • Drive instead of ride: Driver-based predictions mean CFOs can take the driver's seat instead of just looking in a rear view mirror or disclosing predictions.

Key Factors to Consider When Making the Change

Financial data needs to be readily available for rolling forecasts to work. Automated processes and integrated systems, like those utilising the cloud, make this strategy exponentially easier and more efficient. For example, data gleaned from customers can be more realistic than management predictions because managers will do what they can to align budgets with wants instead of needs. Integrated data will show the actual needs and any shortfalls that weren't previously identified.

Companies that are transitioning from a traditional, fiscal year budget strategy will need to determine when they want to evaluate performance. Because rolling forecasts ditch the idea of a single yearly evaluation, organisations that are accustomed to annual mindsets will need to convert the thought process to a more frequent timetable. Deciding on the frequency ahead of time will ease this process and drive success.

Just as important as frequency of evaluations, KPIs should also be clearly identified and derived from strategic objectives prior to a rolling forecast "rollout." Standardising how performance is evaluated will align the forecasting models consistently and help consolidate forecasts. This can be especially helpful in the transition from a traditional fiscal year strategy so as not to overwhelm managers who may see the change as a full-blown yearly report that has to be performed every month. Identifying KPIs avoids that problem and reduces unnecessary stress while also compiling what's needed.

Change isn't always easy, but in the long run it can mean the difference between failure and success, the difference between looking back and driving forward. Using a rolling forecast helps leave failure in the past where it belongs, leaving a horizon full of future success.

Alternatively we are running a webinar in a couple of weeks time which will be of interest. 

Replacing the Annual Budget with Rolling Forecasts – Sept 7th 2017.

To register or find out more click here.

10 Tips to Improve Rolling Forecasts

Posted by James Salmon at 25/7/2017 2:09:08 PM

Register to our Replacing the Annual Budget with Rolling Forecasts webinar – 27th July – 2:00pm to 2:30pm here: https://goo.gl/HK1WQR

To thrive as a business, you need to be able to predict your future earnings and expenses, so you can make smarter business decisions.

Yet, while financial forecasting is imperative to the success of businesses, accurate financial forecasts are difficult to create. So, how does a high-growth, dynamic business create accurate forecasts for their company, without exhausting their time and resources in the process?

Why are Rolling Forecasts so Important?

Rolling forecasts provide the agility needed to adapt to consumer trends.

Rolling forecasts can more effectively meet the needs for high-growth businesses because they provide a flexible framework that is routinely updated, so all variables and industry changes can continually be accounted for.

10 Best Practices for Rolling Forecasts

Here is a list of the best practices for rolling forecasts that will enable enterprises to reduce the time and effort of forecasting, while increasing accuracy.

1. Don't rely exclusively on Excel. Excel isn't collaborative enough to sufficiently generate accurate forecasts, and it doesn't provide the flexibility needed for dynamic industries. Instead, your company needs a system that will factor in variables, enable fast iterations to the forecast, and serve as a baseline for future forecasts. Collecting data via Excel requires too much time and effort while being prone to errors, resulting in tedious budget cycles and inaccurate forecasts.

2. Outline your goals. The core objectives of forecasting are to establish a clear view of your company's financial future to help inform business decisions, as well as to understand the potential impact of those decisions prior to implementing them. Your company should consider your primary goals with the forecast, so you can understand the drivers behind each objective and create better-focused plans.

3. Settle on duration. Determining the appropriate duration will largely depend on the needs and goals of your company. Consider whether quarterly forecasting is sufficient or if monthly forecasts are needed. How far out should your forecasts project - 12 months, 15 months, 18 months?  The growth rate and industry fluctuations of your business can help to determine the best durations for your company.

4. Choose your comparison periods. Comparisons for rolling forecasts can be trickier than with static budgets. You need to provide annual comparisons, comparing year to date (YTD) this year to last year, as well as comparing each month of the rolling forecast to the actual results from that month. While it sounds labor-intensive, EPM software can greatly simplify the process, making it much more efficient to accomplish.

5. Determine what is driving the revenue and expenses of your business. To ensure accuracy, rolling forecasts need to be driver-based, so you can gain the flexibility and agility needed to respond to internal or external fluctuations, update the budget quickly, or generate alternate forecasts.

6. Separate capital and strategic projects from your forecast. Capital and strategic projects don't typically fit into the timeframe of rolling forecasts because they can often last over multiple years. Additionally, they contain a number of variables, which could result in increasing or decreasing the budget for those projects as needed. As such, they should be planned separately from the forecast, while being integrated into the overall plan.

7. Start small and incrementally phase-in new departments. Rolling forecasting can be challenging to implement initially, so it's best to start small. Begin with just a couple of departments, and as those departments establish a solid routine, you can phase-in more departments.

8. Use the rolling forecast as a baseline. The rolling forecast should be a baseline for future budgets. It can provide the framework needed to model what-if scenarios, adjust values, and plan for future circumstances.

9. Integrate your forecasts into your strategic plans. By integrating your rolling forecasts and strategic plans together, you can connect company finances with the overall goals of the organisation, providing a much clearer picture of the business.

10. Consider external factors and variables that will impact forecasting. There are countless external factors that can negatively or positively impact forecasts, all of which should be considered in advance. Rely on external market trends and indicators to determine the primary external factors that are driving your business.

For high-growth businesses, static budgets cannot provide the agility and flexibility needed to ensure optimal allocation of resources. Rolling forecasts can provide the agility needed to update planning assumptions regularly, better insights into the financial impact of decisions, and create a clearer vision of the financial future of your company. Excel fails to provide the tools and versatility that enable efficient and accurate rolling forecasts.

Analytics and the cloud: The Internet of Things

Posted by James Salmon at 20/7/2017 12:59:28 PM

Managing the growth of a connected world to gain new insights

Sensors are driving the explosion of data

Stop for a moment to consider where sensors act all around you. People can run entire businesses from their phones, vehicles are filled with diagnostic and climate control devices, homes have smart utility controls and meters, factories are becoming sensor-enabled as they automate, airplanes have a vast array of sensors to monitor flight performance, communities have sensors to manage traffic flow when road lights switch on. The list is already endless.

Data collected from connected devices is increasingly integrated with analytics to tackle a variety of problems such as:

  • Home Health Monitoring – track patient's vitals and their movements around the home, and raise alerts to family/physicians/hospital if abnormal events take place.
  • Energy Monitoring – at a macro level, utilities can improve national grid effectiveness and power generation; at a micro level, home devices can be powered down or placed on standby when not in use.
  • Asset Management – monitor the health of devices in factories or difficult-to-service locations (i.e. mines, remote wind farms); analyse data and provide diagnostics on devices to predict failure and build predictive maintenance schedules accordingly.
  • Safer Driving - connect vehicles to understand road traffic, monitor performance of both car and driver, to offer lower insurance premiums for safe drivers, drive innovation toward more efficient and even driverless cars.
  • Logistics - track packages and containers, provide estimated arrival times to customers, identify staff distribution centers where workloads are greatest
  • Environmental - leverage weather and air quality sensors to predict when pollution may cause issues at city hotspots, monitor changes in water levels, localise and track data to finer grained geographical areas for greater accuracy in local forecasts
  • Building IoT solutions to enable analytics - When building solutions to use all the data available there are multiple considerations, that together, introduce unique issues with IoT solutions.
  • Velocity – Data is normally moving in real time and needs analysing as such. – Streaming solutions to identify changes to data patterns can be used in feedback loops to change the operation of devices. For example, a switch could be activated to release pressure, based upon a sensor's data that starts to show untypical readings or pressure fluctuations. If done in real time, this can potentially prevent a serious fault in a gas or oil pipeline.
  • Volume – IoT solutions may bring a variety of different data together from video, audio, vibration, temperature, pressure, humidity and more. All of these data sources need to be managed and derived data must be analysed appropriately. This can result in huge amounts of data processing, a genuine Big Data use case.
  • Location – Sensors can be anywhere, and are often mobile. Networks can be complex and their capabilities need to be carefully considered. At the edge of the network where instability may occur due to environmental issues, fault tolerance needs building in. The need to aggregate data or build analytics close to the edge to reduce the load at any central point could be called for. This infers building intelligence close to sensors to either in dedicated devices (think of a raspberry Pi) or within the devices themselves.
  • Standards – Currently there are many ways that data sensors can communicate to a central point. Bluetooth or Bluetooth Low Energy, Wi-Fi or 2G,3G,4G are all common. All are useful and need to be managed across an IoT solution. It may be that Blue Tooth Low Energy (BTLE) is used at the edge to connect multiple devices to an interim ‘aggregator’ and then that device uses Wi-Fi to send data onto the central systems.
  • Cloud – The core systems that are used to analyse IoT derived data are located in the cloud. The demand for resources will vary over time and the processing requirements to model, predict, simulate and visualise the stored history can all be managed from a single point.
  • Integration – IoT solutions often need much more than just sensor based data to become useful. Reports from engineers held in content management systems, ERP (scheduling), and Asset Management systems all within the enterprise may also need to be brought in. This requires integration across all system components.
  • Security and Privacy – Maintaining the security of a set of devices that are distributed geographically, potentially using differing standards and networks is not easy. Being able to prove that such solutions and private and secure where they need to be may be the hardest problem in any IoT solution to solve.


The IoT landscape has some very interesting challenges indeed. There are potentially millions of sensors that must be managed with intelligence built in to control flow of data, local analytics is needed close to devices themselves, error management and feedback to physically control the ‘things’ the devices monitor if the devices themselves are capable of such are a few of the opportunities when we build an IoT solution.

IoT analytics in the cloud

All the data resulting from the output of these devices should flow into a cloud based solution for analysis. Thus, the cloud becomes the “brains” of an IoT solution. The cloud enables action to be taken with the gathered data including simple reporting, predictive modelling, simulation of differing outcomes to test hypotheses, and closed loop systems that communicate with devices to stop failing processes and/or automatically fix problems.

The cloud holds all historical information from the sensors, and can integrate it with data from traditional systems such as ERP, asset management and other forms of data. An IoT solution embodies all forms of systems—Systems of Record, Systems of Engagement, Systems of Automation—to deliver insight to the business.

What does an IoT architecture look like?

I’ve drawn upon work already completed by the IBM cloud architecture team to show the principle components of a IoT Reference Architecture. Primary areas of the architecture are:

  • User Layer – the primary actors in the system, whether a user or application makes use of the IoT system.
  • Proximity Network – the layer of the architecture that manages the sensors themselves, and provides connection to the things they monitor and with the public network.
  • Public Network – links devices to provider cloud services. Other services to augment the sensor data could be fed in here, including data from government open data sources, weather data providers, social media etc.
  • Provider Cloud – the layer that holds the core services that make use of data gathered from the previous layer. Here is where data can be transformed and analysed to offer insights.
  • Enterprise Network – the final part of the solution is the existing data location within the business’s enterprise, for example ERP or asset management.


In conclusion

IoT has opened up a new range of analytics to manage data from a multiplicity of sources that 10 years ago wouldn’t have been considered. The advent of low power sensors, and their ease of use coupled with having lifetimes of several years before replacement, means nearly anything we consider will one day be instrumented. The continual upsurge in data and the need to make sense of it all creates demand for storage and systems, and resulting costs, that can be managed best in the cloud.

Only by linking data that we might not consider will we truly understand more about the variables that prevent processes from working as optimally as is possible. Analytics sited on the cloud is the ideal platform. It is on demand and can be operated as a managed service with continual development and easy roll-out of new services. This allows new ways of processing data to be brought to bear. Platforms such as Spark will enable developers to test out new ideas quickly and share them with others in a collaborative manner.

The IoT market continues to evolve to meet the demands of growth, but as it matures in the next 3-5 years’ leaders and followers will emerge. The leaders will not only have to be able to handle the complexity of connecting literally millions of devices in a secure, managed manner, they must also be capable of analysing all of the assembled data in real time and historically, whilst merging additional data from other cloud-based and enterprise sources.

IBM is well positioned to do this with the legacy of middleware for connectivity, established cloud based services, a rich history of analytical solutions, security platforms that are world leading, and our partnerships with other like-minded companies.

Time to move away from Annual Budgets to Rolling Forecasts?

Posted by James Salmon at 13/7/2017 3:11:41 PM

Companies often spend weeks or months developing an annual plan or budget, but by the time they’re finished, the market has changed and the budget has become obsolete. There’s a better way: rolling forecasts.

Instead of being once-a-year exercises, rolling forecasts happen on a regular cadence. Unlike budgets that may have hundreds or thousands of line items, they focus on key business drivers. And rather than focusing on the past, rolling forecasts act as early warning systems when you’ve drifted off course.

We’ve identified five steps to launch rolling forecasts successfully at your organisation:

1. Use a dedicated application—don’t try to perform them with spreadsheets. 

The multiple versions required by good rolling forecasts to create different scenarios are extremely difficult to perform and manage with spreadsheets.

2. Model your course on drivers, not details.

Your annual budget lists thousands of line items, but you need to perform rolling forecasts at a much higher level. Focus on significant business drivers such as risk, profit, and working capital.

3. Use rolling forecasts to sound out multiple what-if scenarios. 

Look for a tool that lets you change a few key assumptions and drivers and instantly see their effect on the overall plan, such as the impact a price change has on headcounts and cash.

4. Scrub your forecasting process of bias—don’t link it to targets, measures or rewards.

Rolling forecasts are a strategic management tool, not an evaluation tool. Let managers forecast based on real business demands and the real business environment.

5. Choose the right forecasting horizon for your industry. 

A best practice is to forecast at least four to eight quarters past the current quarter’s actuals. But there’s no hard-and-fast guideline for the time interval included in a rolling forecast. It depends on your industry, your business needs, and how long it takes to make decisions.

But let’s say you aren’t convinced about the need for rolling forecasts in the first place. There are several compelling reasons for giving them a try:

  • They enable agile responses to changing market conditions
  • They optimise decision-making for better planning
  • They identify future performance gaps
  • They help senior executives manage performance expectations
  • They shorten long planning cycles with a more efficient model—and direct the extra time toward more strategic activities


That’s not to say that implementing this approach will be smooth sailing. Some people fear that they will take the focus away from company goals. But in fact, rolling forecasts ensure that these goals are realistic because you’re continually updating your plan and tracking performance against them.

For example, say your annual budget was £100 million. If rolling forecasts indicate that you’re going to fall short of that figure due to external headwinds, you can work to get management’s buy-in for a more realistic outcome and make decisions to change your investment levels or key priorities.

3 Questions You Need to Answer for Agile Finance

Posted by James Salmon at 7/7/2017 4:11:37 PM

What’s the most important quality a finance team needs to succeed in the digital age?

What are attributes essential to helping finance achieve more influence within the business?

What’s the most important benefit of cloud applications in the digital age?

These are three important questions that finance teams are asking themselves. They came to the fore in the recently published AICPA research, Agile Finance Revealed: The New Operating Model for Modern Finance. The research found that agile finance teams share three major characteristics:

1.    Greater efficiency through automation

2.    Better information to predict the future

3.    More influence to drive business outcomes 

The results of our informal poll indicated that finance teams are eager for more agility and that one particular element of the new operating model is top of mind for them.

By a wide margin, the majority of respondents chose “Better information through advanced analytics” as the most essential element of the new finance operating model. This outcome dovetails with our own experience as we conducted the research: Finance teams are hungry for more information and analysis, so that they can make more informed recommendations about where the business should go next.

One reason finance teams want the ability to make these recommendations is that they see it as an opportunity to increase their own influence and stature within the business. This is borne out by the responses to our next question: 

The majority of respondents felt that the ability to provide “forward-looking analysis to identify new revenue growth opportunity” was the most important attribute a finance team could have when it comes to influencing better outcomes for the business. This is in line with our findings that CFOs are increasingly seen as the “copilot of the business” along with the CEO. Better analysis—and, more importantly, better recommendations based on that analysis—naturally leads to more influence.

One surprise was that “mitigating risk” was seen by our audience as an important attribute for influencing better business outcomes—more important than identifying and measuring the intangible drivers of business value. This indicates that finance teams still see the traditional responsibility of “risk avoidance” as an important part of their jobs, despite (or perhaps because of) the changes and uncertainties brought on by the digital economy.

Adjusting to the Pace of Digital Change

The rapidly changing shifts of the digital age weigh heavily on the minds of finance teams. When considering the benefits of cloud-based finance applications, more than half of respondents felt the greatest benefit came from the flexibility the cloud provides to change and improve the operating model when the need arises: 

In an era where new business models are springing up almost overnight, and new players can enter the field from any corner, finance teams recognise the importance of being able to rapidly shift gears to respond to new market conditions. This is where they see the biggest benefit of cloud applications.

Aspiring to Drive Revenue Growth

In one of the most important outcomes of the AICPA research, we found that businesses with agile finance teams were significantly more likely to achieve positive revenue growth: 89% of organisations with agile finance teams reported positive growth, vs. 63% of those with non-agile finance teams. These numbers indicate that finance can not only make an accounting of a company’s wealth but actually drive it.

When it comes to influence, positive financial results have the greatest potential impact on a CFO’s continued ability to lead, guide, and act as copilot of the business.

Budgeting Solutions awarded supplier status on G-Cloud 9

Posted by James Salmon at 30/5/2017 1:13:17 PM

We're delighted to announce that Budgeting Solutions has been awarded Supplier status on G-Cloud 9 - the procurement framework which is part of the UK Government's Digital Marketplace.

G-Cloud 9 provides Public Sector organisations with an easy solution for sourcing specialists for Cloud-related projects. Our successful application to be a G-Cloud 9 supplier means that we can now offer our Cloud Software and Cloud Support services to a much wider range of organisations including; central government, local government, health, education, devolved administrations, emergency services, defence and not-for-profit organisations.

How CFOs Implement Advanced Analytics: 5 Best Practices

Posted by James Salmon at 10/2/2017 5:11:00 PM

How to make the most out of your company's data

Today’s corporate agendas revolve around the staggering amount of data available and the advanced analytics needed to gather, interpret and use such data. When it comes to Big Data and Advanced Analytics, things can get really tricky for a company not making the best of them.

A recent McKinsey report shows that businesses which are not able to leverage Big Data and which fail to achieve performing data management also witness an average of 14% in lost revenues per year. Surprisingly, oil companies, life sciences, and consumer goods make the top three industries where big data and advanced analytics are poorly managed, thus leading to financial losses.

As opposed to the McKinsey report, a study coming from MIT and Harvard Business School shows that companies focusing on big data management and advanced analysis witness an increase in revenue of up to 6% in comparison to companies not injecting big data into their financial and operational strategies.

But what are Big Data (BD) and Advanced Analytics (AA) when we refer to financial management and good practices? A broad description of BD defines it as being:

·         Massive in volume and complexity, scaling up to multiple terabytes or even petabytes

·         Unstructured and diverse

·         Widely distributed both on the outside of the organisation and inside the organisation

·         Fast moving and fast changing, needing perpetual sourcing and transmission.

In order to be able to source, understand and use BD, Advanced Analytics comes as a set of tools and techniques which are hard (if not impossible) to replicate with traditional analytics methods in size, accuracy, scale or scope.

Advanced Analytics go beyond simple regression or predictive models, using “new analytic methods” such as the study of social media buzz, data-mining, and others. The advantage of AA when it comes to predictions, however, is that (if used correctly) they can achieve higher levels of accuracy due to the larger data sample sizes.

AA strategies are based on tools and instruments helping CFOs improve the company’s performance on multiple levels. Let’s see today how CFOs implement AA and what good practices examples you can look into to adopt and adapt for your company.

1. Viewing the Budget in 360°

Using Big Data and Advanced Analytics can surely help a company stay ahead of the competition and get better at operations, financial management, sales forecasting, and consumer retention and so on. Optimising data and analysis can help the CFO tackle with complex business rules, market shifts, and economic constraints. Thus, they become able to simultaneously evaluate them all and make better decisions.

However, before investing in AA frameworks, hardware, and data scientists, the CFO needs also to use BD to assess the company’s capability of implementing a BD and AA-centered approach.

While advanced analytics help the CFO translate business opportunities and constraints into mathematical formulas, charts and prediction models to create more accurate budgets and scenarios, the main issue is the company’s internal financial and managing architecture able to sustain the shift to the AA approach.

Such an endeavour can take years and needs a stellar coordination with all the departments in the company.

However, if the company is able to take the first steps towards such paradigm, CFOs need to pay attention to their environment and understand how to implement good practices.

2. Choosing the Right Data and Using it Creatively

All managers and CFOs are literally bombarded with data they sometimes deem unimportant. Other times they have access to the entire information they need, but don’t know where to look for it. The best practice in using advanced analytics on BD is finding the data in your environment and creatively choosing its sources. Given the fact that now we have massive amounts of unstructured information coming from new sources like social media and machine sensors, CFOs can become creative in picking the data sources and using them to improve working capital, resource allocation strategies, the management of costs, risks, human resources and revenues.

One example is of Sears Holding wanting to improve its promotions, personalised offers to customers and generate greater sales values.

But processing information coming from three sub-brands to tailor relevant and revenue-generating promotions in the traditional manner took around eight weeks, which was counterproductive for the company. Instead, Sears Holding switched to BD analysis using Hadoop cluster analysis (together with servers and software) to process the data and create revenue-generating, comprehensive and reliable product promotions in a week.

Other companies use social media, weather forecasts, electronic shipping records, customer surveys results, clients’ feedback and ratings.

3. Building Prediction Models

Prediction models are an instrument CFOs have been using traditionally to identify trends and patterns in market shifts, consumer behaviour, and business performance. However, in the AA framework, prediction models should be constructed not starting with the data but with the identified business opportunities/weaknesses and with determining how the model can actually improve performance.

This shift in paradigm for CFOs can help them narrow the gap between strategic and operational decisions covering business levels that are not traditionally in the hands of the financial manager: supply chain optimisation, customer retention, social media marketing planning, sales- and finance-linked forecasting, new product introduction profitability, customer satisfaction and so on.

For instance, instead of creating a complex product pricing strategy based on traditional data (historical sales data, price elasticity, market responses, competitors’ responses and so on), a company can develop a prediction model starting with the identification of factors that affect their sales. Then, they can determine what data and what model would best deliver the necessary insights for them to make price-related decisions.

What companies need to keep in mind when building models, however, is that they need to keep things simple, as models using 30-40 variables may exhaust its resources.

4. Changing the Company Culture

The CEO and the CFO may agree on using advanced analytics and complex models, but this doesn’t mean the employees will effectively use them in the front rows of operations. It is possible that while the CFO focuses on using AA to optimise the returns on advertising and marketing campaigns, the marketing team disregards the model, has little knowledge of how to correctly implement it or simply uses a different approach to decision making.

When using AA and tapping into big data, one of the best practices of a CFO is not only to implement new models but also make an impact on the company’s culture and practices changes. Granted, such approach is not a traditional one for a CFO, but in this day and age, one needs to think ahead and overpass the boundaries of the job description. Company culture change in relationship with AA can be achieved through a series of steps:

  •          Before implementing AA, the CFO needs to come up with an analytics tool that can be used by all departments at all levels. Speaking the same language and being on the same page (from human resources to online marketers) eases the company’s switch to using advanced analytics and prediction models.
  •          Complex software running through dozens of terabytes of data won’t surely make front row workers’ lives easier. One approach is embedding big data and complex analytics in simple and usable tools for the people working with such data minute by minute. As a CFO, it is your duty to optimise the company’s workforce performance and cut costs. Instead of worrying about the employee’s wasted time and resources to operate with complex data, it is cheaper and faster to use specialised IT companies to turn AA into simple, manageable tools.
  •          Invest in the employees’ big data literacy and management. All CFOs know it is cheaper and faster to train your employees than be faced with employee turnover just because the front row workers can’t handle the tools and techniques you have them operate with.


5. The Use of Crowdsourcing to Boost Forecasting Accuracy

CFOs typically have cross-views on the entire organisation, keeping tight relationships with all departments, meaning they have a broad view of all employees’ capabilities and departments’ best resources. Crowdsourcing is usually a sourcing model in which organisations use contributions from individuals to obtain ideas or services. However, when using Big Data we mentioned that it can be found both internally and externally.

A good practice when it comes to AA is internal crowdsourcing, meaning using the company’s employees’ skills and expertise to improve sales, fix prices, tailor promotions and generate revenue.

There is at least one excellent example of how a company can leverage on its internal data, employees’ wisdom, skills and expertise and prediction models to improve sales forecasts’ accuracy: Henkel. A practice used by Google and Microsoft, crowdsourcing in Henkel took the form of an employees’ vote on the next quarter sales for a batch of selected products.

The technique resulted in 22% improved sales forecast accuracy and the identification of experts within the company who perpetually registered high levels of forecast accuracy. Needless to say, identifying experts within a company and matching them to the right organisational position is profitable from all points of view.

Another example is that of Deutsche Telekom using employee’s evaluations of product concepts. Such an approach led to a very quick sales forecasting analysis which was reliable (a 84% correlation with a parallel consumer survey) and which was very low cost, allowing the company to save 90%.

Big Data and Advanced Analytics are still in their newborn years, offering endless possibilities for companies to use every single piece of information (inside and outside the organisation) to better structure their business on all levels. In this framework, it is likely to witness major shifts in the roles and responsibilities of CFOs in the years to come.

Top Trends In Finance 2017

Posted by James Salmon at 31/1/2017 5:35:24 PM

The year just gone has, with a few notable exceptions, been a difficult one, and the phrase ‘unprecedented time of uncertainty’ has almost become cliché. As a CFO, your main priority is ensuring the financial stability of your company regardless of market conditions, and the apparent inability of anyone to predict anything has made this a greater challenge than ever before.

In 2017, world events are likely to continue to confuse and panic again in equal measure.The Italian banks are at breaking point, the French elections could see one of Europe’s leading powers fall under the control of a far-right party, and article 50 is likely to be triggered, beginning the process of the UK exiting the EU.

 There are, however, reasons for the CFO to be optimistic about what 2017 holds. Donald Trump, for all his flaws, will likely cut corporation tax significantly, providing a timely boost for business, while technological advancements should also mean that finance leaders are better positioned to cope and drive growth.

Rolling Forecasts

According to a new survey by consulting firm Kaufman Hall, agility is a top priority for CFOs in 2017, yet many are still struggling to achieve it.1 Less than 23% of respondents to the survey said they are very confident about their company’s ability to overcome unforeseen business obstacles, citing outdated FP&A tools and processes as the primary cause.

 This push for agility will see continuous forecasting take on an even more important role next year. In Kaufman Hall’s survey, 38% of respondents said their company now uses rolling forecasts, up from 33% from the same period a year ago and 25% in 2014 and popularity is likely to increase exponentially next year as companies begin to realise the benefits. A recent survey by Aberdeen Group saw 71% of top-performing organisations who responded say they mitigated against risks related to volatile business conditions by continuously updating forecasts to better reflect current business conditions, and those seeking to emulate them should do the same.


Cybersecurity remains a pressing concern for organizations of all sizes. In 2016 alone, 2.2 million patient records were taken from 21st Century Oncology, 1.5 million Verizon Enterprise Solutions customer records were stolen, and nearly 150 million accounts leaked from major email providers including Hotmail, Yahoo, and Gmail.

Such is the threat posed by hackers; the past year has seen cyber security increasingly fall under the purview of the CFO. A recent Grant Thornton survey of 912 CFOs found that 38% of respondents identified the CFO as the position most often responsible for cybersecurity, while 44% of finance leaders said they felt the most significant concern for their organisation today is cybersecurity and 57% said undetected breaches were what worried them the most.

The logic behind giving the CFO oversight of cybersecurity is clear. They control some of the most sensitive and important data found within organisations, spanning revenues, profits, investments, and acquisitions. AICPA Vice President of CGMA External Relations, Ash Noah, notes that: ‘The finance function has a unique view into the complexities of the business, as well as an in-depth understanding of the industry, markets and risk climate, yielding important insights for a company’s strategic direction. As the finance function continues to evolve to become more business-centric, it’s critical for finance executives, from the CFO down, to play a driving role in preparing for and addressing potential cyber-risks for the long-term growth of the company.’

CFOs’ Skill-sets Expand…

In a recent interview with us, Ian Swanson, CFO of Delicato Family Vineyards noted: ‘The greatest challenges facing leaders today are the many non-financial aspects of the job. No longer is it enough to put an annual plan together and then report out income statement and cash flow variances month-to-month. You have to understand the entire business as well as the CEO; its strategy, its capabilities, the competitive landscape, its strengths and weaknesses, as well as the impact of changing regulations and new technologies. Helping the organisation manage its way through this changing landscape and keeping all of the stakeholders apprised is much more of the job than it has ever been before, and I only see the demands increasing.’

His words are reinforced by EY’s DNA of the CFO survey, which spoke to 769 finance leaders. Respondents to the survey found that number crunching is no longer the be-all and end-all of the CFO’s role,1 with skills that can help inspire and generate loyalty such as empathy, innovation and imagination becoming equally important.

…And They Begin To Look More At Non-Financials

Not only are CFOs looking to embrace skills outside of their normal wheelhouse, they are also looking at information external to the finance function. According to Adaptive insights, 76% of CFOs report that their finance teams are tracking some non-financial KPIs today, and 46% of CFOs anticipate that number will rise in the next two years.


The Internet of Things (IoT) has been threatening to explode for a number of years now. Estimates for the number of connected devices on the market range from 20.8 billion by 2020 (Gartner) to 28 billion by 2021 (Ericsson).

The central challenge facing CFOs today is measuring and monitoring business performance in a timely fashion to ensure their organisation can respond to events in an agile fashion and exploit every opportunity possible without too great an exposure to risk. The IoT will make it significantly easier for CFOs to do this, with data flowing into billing, enterprise resource planning, and accounting systems in real time. This will change the way that forecasting and audits are carried out, providing real-time visibility around transactions and making risks easier to pinpoint - ultimately, leading to better decision-making.

Zero-Based Budgeting

The last few years have seen a dramatic resurgence in the popularity of zero-based budgeting (ZBB), a budgeting method first popularized in the 1970s under President Jimmy Carter in which budgets are prepared from scratch with a zero-base rather than based on historic data. The number of publicly-traded US companies mentioning the term in their earnings calls increasing from 14 to 90 between 2013 and 2015, and some of the world’s largest organisations have now implemented ZBB - including Unilever, KraftHeinz, Coca-Cola and Mondelez, all of whom have reported significant cost reductions as a result.

ZBB is particularly well suited to an uncertain world, and is likely to continue to grow in popularity so long as uncertainty in the business climate continues. According to global management consulting firm McKinsey & Company, a well-implemented zero-based budget can save large corporations 10-25%, sometimes as early as six months of implementation, and while it is time-consuming, it is likely to remain in trend for the next year at least.


Peter Wollmert, EY global and EMEIA Financial Accounting and Advisory Services (FAAS) leader, recently noted that: ‘CFOs worldwide are struggling to make the most of the increased volume and speed of data available to them. Many are encumbered by legacy systems that do not allow reporting teams to extract forward-looking insight from large, fast-changing data sets. The result is an increasing expectation gap between what boards now look for from corporate reporting, and what CFOs can deliver. Until reporting catches up with technological advancements it will continue to be compromised.’

Making sense of this huge amount of data is the central challenge facing CFOs, and the next year will see them employ machine learning and AI to a greater deal in order to cope. In a recent IBM report, 38% of CFOs surveyed said that AI would be one of the technologies most likely to transform their enterprises within the next few years. In another report by the World Economic Forum, ‘Technological Tipping Points’, which asked 800 executives when they thought that ’30% of corporate audits would be performed by AI’, 75% said 2025. CFOs will have to review various aspects of their organisations and put in place a strategy to help best exploit AI to maintain their competitive edge, ensure they keep costs down, and increase their profits. They must also look at areas where AI could prove a risk, and where competitors may adopt it and outflank them. People often talk about how AI will cause mass unemployment, but for CFOs who fail to plan, it won’t be the machines that have rendered them redundant, they’ll have done it to themselves.

What is a KPI and why are they so important?

Posted by James Salmon at 18/1/2017 11:21:19 AM

Key Performance Indicators (KPIs) are the backbone of business. They are the used by managers, leaders, and executives to help them understand whether their business is on the right track for success, and, if it’s not,  more easily identify where to make improvements and focus more attention.

For public sector organisations, KPIs confirm standards they need to meet to gain budgets.

The aim of a KPI is to bring about improvement.

But with the amount of data that businesses and organisations generate, it is important to choose the right measures and indicators. With that in mind, KPIs must be aligned with the overall company strategy and objectives.

Get them right and business performance will improve.

Get them wrong and you can drive behavioural change that focuses on delivering results on a specific measurement that has no overall positive impact on the business.

But really, what is a KPI?

Firstly it’s critical to understand the difference between a measure, a metric, and a KPI. Just because you can measure it doesn’t make it a metric. And just because it is a metric, that doesn’t automatically make it a KPI.

But you do need to be able to measure it. And everybody within you organisation needs to measure it in the same way.

Converting Metrics into KPIs

The easiest way to understand a KPI is that they build on each other. KPIs derive from metrics, which are created out of measurements.

A measurement can be number of customers, number of sales, or total revenue. But until you start making comparisons, they are simply numbers.

A metric is typically a combination of two or more measures, so number of customers over time, or total revenue over time. Metrics illustrate whether the values are good or bad and can help with financial forecasting and bench-marking.

A metric becomes a KPI when it is put in the context of a particular organisation or industry. A KPI adds meat to the detail, so ratios and percentages often make better KPIs than just the number of things in a group.

What makes a good KPI, and how many should you have?

Overall, an organisation should have no more than 5-6 KPIs developed at an executive or leadership level, although each department will have their own.

KPIs give executives the chance to communicate the mission and focus of the organisation to investors, team members, and other stakeholders. As KPIs filter through the organisation, they must grab employees’ attention to make sure that everyone is moving together in the right direction and delivering value to the business.

Departments, and even individuals within an organisation, may have their own KPIs. But it is important that they understand the context of what they are being measured against and how it fits within the broader business strategy and goals.

The KPIs that a company or organisation measures will vary depending on the type of business and industry, its customers, and its staff. However, they are likely to include some of the following:

  • Net profit
  • Net Promoter Score
  • Customer engagement
  • Customer complaints
  • Market share
  • Share of voice
  • Carbon footprint
  • Supply chain miles
  • Waste recycling rate
  • Employee satisfaction
  • Staff churn
  • Return on investment (ROI)

Once you have defined your business’ goals and strategy, identifying and aligning the KPIs for your business will be much simpler.

We run a comprehensive webinar schedule throughout the year taking a look at many of the topics mentioned within this article therefore please take a look at our latest offerings and feel free to register for as many as you like!

Big Data Meets Business Analytics

Posted by James Salmon at 30/12/2015 1:48:53 PM

Identifying retail pain points

Before you can harness the power of information; you first need to understand the specific problems you hope your data insights will solve. The overarching challenge for many retailers is to cost efficiently provide a seamless, omni-channel shopping experience — an experience geared toward consumers who interact with your brand online, in a store, over the phone, by using a mobile device, at a kiosk, from a catalogue, or all the above — to your customers. Your goal is to provide the right product, at the right price, in the right place, and at the right time. But many obstacles are in your path. When you drill down into this challenge, for example, you have to determine what consumers want and work the dynamics of supply and demand to deliver on those expectations in real time. Ultimately, you need the best tools available to win customer and brand loyalty, while avoiding unnecessary costs.

Asking the critical questions every day, retailers are taking steps to increase their efficiency, improve their customer experiences, and develop smarter retailing strategies. Retailers who don’t enter this race will be left behind. To find out if your organisation is working smarter in retail, start by asking some critical questions:

  • To what extent do your employees have access to the information they need at the time and place they need it?
  • With which suppliers have you moved beyond cooperation to constructive collaboration?
  • Which of your operational processes are able to adapt and respond quickly to changing marketplace demands?
  • How much value are you getting out of the information stored across your organisation? How much external information do you leverage in your strategy and decision making?
  • How well do you know your customers’ preferences?

 Extracting meaning from the mountains

Data pours in from multiple systems, channels, and regions around the clock. The challenge is how to consolidate, organize, and extract meaning from the various data sources to inform decision making and enable productivity and agility in the face of multi-faceted market demands. Business Analytics has the keys you need to unlock the mysteries hidden deep within your data and empowers your organisation to spot trends and discover underlying causes and issues. Today’s Business Analytics tools offer flexible, user-friendly reporting, analysis, modeling, predictive, and planning capabilities that make it possible for everyone in your organisation to tap into the information they need to make informed decisions across all departments, locations, functions, and roles.

Creating an interconnected organisation

As you extract meaningful information from the mountains of data you collect, it’s vital to make sure the various stakeholders in all departments in your retail organisation understand how to take action on that data — and how those actions impact other parts of the organisation. Business Analytics software enables you to tailor the information to each individual’s role for security purposes and to avoid information overload.

Performance Management

Performance Management (PM) gives the business the flexibility to build best-case and worst-case scenarios; for example, modeling outcomes of changes in demand, then pushing those scenarios through to merchandising and operations to get a full picture of the impact, and finally driving those decisions through to finance to understand the implications to the bottom line for the organisation. PM creates the opportunity to link financial and operational plans through driver-based modeling and rolling forecasts, and gives users visibility and access to the right information at the right time to build confidence in the data and results. This modeling environment also ensures consistency between corporate strategy and field execution, creates a culture of continuous planning, and keeps the entire organisation aligned around the strategic objectives of the organisation. An additional string to the PM bow is risk management, which helps the organisation understand and act in accordance with various risk areas, including market, credit, and liquidity risk to optimize decisions and satisfy external and internal governance requirements.

Visit the Our Expertise in Retail page to find out more.

No Surprises: Making Life More Predictable for the CFO

Posted by James Salmon at 17/7/2015 4:49:46 PM

Imagine, if you will, the following scene taking place during a regular board meeting: the Chief Financial Officer (CFO) is ready to present his numbers, prepared in collaboration with his team. It’s taken three weeks of uninterrupted work to get the true picture of the company’s financial health. He delivers balance sheets, consolidated sales reports, major product line analysis; in short, all the traditional tools you can think of.

When it’s finished the CFO sits back and asks: “Any questions?”

“Yes,” exclaims one of board members. “What is the evolution of sales in Stratford-upon-Avon?”

“Stratford-upon-Avon?” asks the CFO? That small Shakespearean town in South Warwickshire, she thinks, but why Stratford-upon-Avon?

Well, as it turns out, this board member was born there. He appreciates the 800 years of history in the town and regularly goes the theatre there.

As you may imagine, this is not good for our CFO who, unfortunately, is unable to answer the question. “I’ll have to get back to you on that one,” she says.

As you can see, it is a fairly innocuous question, but one which has completely derailed our CFO, certainly taking some of the shine off her presentation. And should it have? After all, the relevant data on the Town of Stratford is certainly inside the organisation’s IT system, it is simply very difficult to extract and process into operable insight from within the different silos.

An Unpleasant Surprise

Our CFO has been is the victim of outdated technology – namely the spreadsheet. And although this technology is well-adapted to provide a macro view of the business, it doesn’t facilitate an ad-hoc drill-down to a more microscopic level of detail. However, in a competitive and unpredictable world, we need a magnifying lens to make the right decisions and adapt to a changing environment at all levels of the business.

Today’s CFO needs speed, flexibility, and the ability to process large amounts of data. She should not be powerless to react to surprise questions, no matter how odd or arbitrary, because this indicates a lack of control. Let’s not forget that the CFO’s job has changed dramatically over the last fifteen years, they are no longer isolated in an ivory tower counting coins but expected to bring experience and vision to every division of the company. They must master other skills like navigating through the intricacies of global taxation, or mastering mergers and acquisitions strategy.

In this new financial landscape, basic profit and loss indicators are no longer sufficient. Each business stakeholder needs relevant indicators with fine granularity and these indicators need to be updated weekly, daily or even in real-time; to review finances annually or quarterly is simply too little too late.

The CFO Revolution

With these new requirements, we have grounds for a revolution. The tools at the CFO’s disposal are often not sufficient to handle this change. Too many financial controllers rely on cumbersome, error-prone processes involving static spreadsheets to obtain the data they need. Their Business Intelligence tools, which require the expertise of an IT specialist, may be able to offer an accurate reflection of the past but are totally unsuitable for planning.

Organisations should consider a modern collaborative solution that allows finance and business to work and plan together, a solution that provides a broad vision, but can also provide visibility on the deep details. With this type of tool, our CFO would have been able to give, on the fly, the sales status in the town of Stratford. No surprise questions will tarnish her reputation and her fellow board members will be confident in the numbers. 

The impact on Finance Departments of Big Data

Posted by Paul Bavington at 30/1/2015 4:35:30 PM

The concepts behind Big Data have been around for a while now, moving from niche marketing to almost mainstream over the past few years.  Whilst the term Big Data means many things to many people it is now much more than a set of interesting new technologies.  It has become for some organisations a business imperative, providing solutions to changing customer demands sometimes transforming business processes, organisations and entire industries.  And whilst there is still an awful lot of hype around the term, the impacts from being to analyse these vast, disparate, often unstructured data sources and make decisions are changing long standing business models.

The hype around Big Data

How though do you get beneath the marketing gloss and determine how to make sense of this explosion in data points.  Data in itself is not information nor does it make decisions.  Neither is Big Data the preserve of big enterprises with big budgets.  As with all new technologies there is an adoption cycle starting with innovators, moving from early adopters through the early majority, late majority and followed by the laggards.  Gartner have identified a hype cycle for emerging technologies, not all of which make it, that moves from the initial expectation of the technology to an inflated expectation, falling into the trough of disillusionment, finding a slope of enlightenment and ending on a plateau of productivity.  Gartner sees Big Data now at the top of the hype cycle, often the point at which the early adopters get going.  In practical terms we see a split emerging between the technologists promoting a raft of open source tools and business users trying to get something usable out of this vast bucket of data.

So is there an impact on Finance and if so what is it?

If we look at Finance departments most teams are still  undertaking an annual budget process with differing approaches to forecasting in place across the year, some monthly, some quarterly and  some on a rolling basis.  Quite often it is focused along the lines of ensuring the chart of accounts adds up to the right level of profit.  How far from the world of big data can this be?

If we get under the skin of the classic approach to budgeting and forecasting though, many Finance teams take a keen interest in the detail behind the sales forecast - how robust are those numbers, what evidence is there to support them etc?  Equally questions such as what are the resourcing requirements to deliver on those objectives, whether it be people or productive capacity need answering.

The four V’s

Whilst the details vary enormously across industries, most sectors are impacted by the move to a digitised society - the foundation of big data - in some way or another by what have become to be known as the four V's of Volume, Variety, Velocity and Veracity.  Social sentiment on Twitter and Facebook can impact the sales of consumer goods; telemetrics in cars enable insurance policies to be written on a variable basis based on driver behaviour.  Without taking into account these new or emerging impacts on business models, the drivers of revenue and costs will not be properly accounted for or included in the forecasting process.  New entrants to once impenetrable markets such as banking can quickly erode revenue streams- crowd funding and alternative payment mechanisms such as Paypal and Bitcoin.

Traditional accounting and forecasting to clickstream data

The recently formed body, CGMA - a combination of the UK's CIMA and the US's AICPA, has written a paper on just this topic, on how to ready businesses for the big data revolution.  They observe how some early adopters in the use of big data and advanced analytics have already enhanced both their operational performance and their competitive position.  Not all Finance teams may yet be using the technologies of big data but the digitisation beneath it is disrupting traditional business models.  Finance teams need to take note of these changes to analyse the impacts and ensure they are incorporated into the planning and reporting processes of their organisation.  One of our customers in the media publishing sector found that almost overnight the sale of physical products from their website moved to pay per click on various download sites.  The change in business model was quick as was the move from traditional accounting and forecasting to analysing clickstream data from multiple sources to understand revenue, royalties and margins - a great example of the four V's at work.

So to answer the question, there is an impact on Finance teams from Big Data and it is closely aligned to the ways in which they plan, report and analyse the data driving an organisations performance.

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