Even in a pandemic, collaboration is key to cash flow modelling

The COVID-19 pandemic is having an unprecedented impact on the world’s health, economies, and organisations. Executives everywhere now face substantial uncertainties about how to manage their operations, including strategy and financial projections. For organisations trying to avoid financial distress or even bankruptcy, financial projections in particular are critical to accurately forecast cash flows- the lifeblood of any organisation.

And though the process is usually orchestrated by finance, financial projections shouldn’t be the sole domain of finance.

If you’ve already realized the strategic advantage collaborating with your colleagues and business partners, you’re ahead of the game. Financial planning and analysis (FP&A) folks who regularly meet with line managers, employee teams, and business partners tend to gain a much deeper understanding of the numbers, have better insights into the business, and make better decisions. And budgets, plans, forecasts, and business models that are created collaboratively provide a richer, more accurate, and more revealing picture of the business.

Amid the disruption caused by COVID-19, this is more important than ever. And with modern videoconferencing technologies and cloud planning platforms, finance teams can continue to collaborate during the current crisis.

Over the years, I’ve learned that business modelling benefits from this kind of data collaboration. Models are a representation of physical realities. And by working closely with colleagues and business partners, we can achieve better, more efficient results. The power of FP&A models is they are in the language of money—a common denominator for comparing decisions for prioritising actions.

Turns out, collaborative business models share these four common characteristics:

  1. Collaborative models are more robust
    Every good business model flows from source data and converts it into information. But without data collaboration between finance and business partners, your model will fall short. After all, business modelling isn’t just about looking at the numbers. It’s also important to speak with people throughout your organisation to understand their point of view, their business concerns, and the types of data they think need to be included in the model.

For example, a videoconference with sales, HR, or accounting can provide an understanding of the business that you can’t get by reading a report. And stakeholders truly appreciate having input into the metrics and variables used to create the model. After all, if you’re using the wrong metrics and variables, the whole model will be less effective.

With the COVID-19 pandemic, new variables will be needed that did not apply when operations were “normal.” For instance, you may want to factor in unusual cash flow impacts like extended payment grace periods, or the cost of equipment allowances to employees now working from home.

  1. Integrated and automated models support better decisions
    Most model building starts in Excel, but it’s hard to get a comprehensive picture of the business when the model is sitting in different racked-and-stacked spreadsheet files spread around the business. If you’re trying to import data from different sources (CRM, ERP, HRIS) using spreadsheets, it’s hard to get everything lined up and even more difficult to extract the right data quickly.

The ability to import all of this data automatically and integrate it into the proverbial “single source of truth” is a triple win. First, you can build models faster. Second, decision-makers have real-time visibility into what’s happening with the business. And third, it’s easier to work together to develop a high-caliber model when everyone trusts the data. Also, if business partners can access self-service reports, it’s easier for them to understand the context of their decisions and much easier for FP&A staff to collaborate.

  1. Simple models enable greater buy-in
    It’s great to have business models that contain lots of data, but more isn’t always better. It’s easy to get fixated on the data—just be sure your models add focused insights that guide company strategy and the decisions that will execute the strategy. Some FP&A practitioners try to include everything in their model—formulas, scenarios, data. But having a more focused, simple model can save time and keep you (and your colleagues) focused on the vital metrics that matter and not the more trivial ones. Also, creating overly complex models can prevent business partners from accessing information, because they have to rely on finance to get them the information they need.

A proven approach is to begin with a pilot or prototype model, including approximated estimates, to accelerate the learning and buy-in from your colleagues. Then iteratively expand the model, integrating it with extracted data, to right-size the model. This prevents getting diminishing returns from extra unnecessary precision that requires extra administrative effort to collect, validate, and use the data. Always ask yourself, “Is the higher climb worth the better view?” Stop when the model is “good enough.”

So while it’s important to make sure your model can accommodate queries and questions, it’s even more important that it be simple enough for anyone to use.

  1. Models that are regularly tested and iteratively refined are more robust
    What good is a collaborative, robust, accurate model if you never test it? Obviously, testing is important—but testing isn’t just seeing how well the numbers align to your plan. It’s also imperative to make sure your colleagues and business partners agree with the assumptions in the model and then help identify any variance patterns. Once you’ve conducted a variance analysis, you’ll be able to quickly see how far off the projections are and the magnitude of their deviation from the actual metrics and results. Then go back and reconfigure the model with additional or better assumptions and information.

The result of frequent testing is that you’ll have the opportunity to continuously improve and refine your business model, make changes to assumptions, and adjust targets and recommendations as the business environment changes. Ultimately, the quality, accuracy, and robustness of your model depends on how well you’re able to partner with people throughout your business, show them how you define the assumptions, and refine things further with their feedback.

Building a collaborative, automated, simple, tested, and refined business model can help you plan, anticipate, and react to marketplace changes and revenue shocks quickly.

Collaborative models help companies prepare for an agile future
I’ve found that collaboration is also critical to helping your company achieve agility. And now more than ever, business agility is existential.

With an active, dynamic business model that is grounded in shared assumptions and sufficiently accurate information, decision-makers will be able to more quickly respond as things change in the marketplace. Make collaboration part of your planning and forecasting culture, and 0n-the-fly analysis, real-time information, rapidly gained insights, and fast decision-making will become part of your day-to-day operations.

Complex financial modelling can start simply and give you the results you’re looking for.