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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.

Putting Analytics and AI in Context for Better Outcomes

User AvatarPosted by James Salmon at 18/07/2019 11:25:37
content type Industry Perspective

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 The information may or may not be relevant; it could even be out of date or misleading.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 18/07/2019 11:21:21

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.

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