Getting FP&A back in the game – scenario planning or dynamic forecasting?

As various industries and markets start to emerge from the immediate shutdown of COVID-19, the very different world they’re faced with might make traditional FP&A challenges feel like a walk in the park.

That’s not to say that those concerns have gone away – forecast accuracy, understanding the business and its key drivers, and gathering the numbers together for analysis are still crucial – but the current environment serves to magnify these issues and as a result, creates much bigger uncertainties.

The old ways of working to a static forecast and a rigid 12-month planning cycle are no longer fit for purpose so new, more agile methods need to be adopted.

Looking at the approaches of our clients, two terms come up time and again: rolling / dynamic forecasting and scenario planning. We’ve talked about both before, but to recap:

Dynamic forecasting works in short-term cycles on a foundation of longer-term plans. Rather than trying to use historical precedent to predict long-term futures, recent and current information informs decisions about the near-future. This evolving bigger picture is then incorporated into plans for the year, with active analysis of the planning efforts and results from the previous period impacting on direction taken.

A dynamic forecast also serves as the closest possible example of a single version of the truth – a shared point of reference across the organisation to ensure all business elements are working off the same plan.

Scenario planning is a thinking method that identifies a specific set of uncertainties and considers the alternative future realities they could bring about. This method of considering ‘what-if’ situations creates new insights and is forward-focused – dealing with assumptions of what could happen – rather than based on what has previously occurred.

Either / or?

Looking at these approaches – is one preferable to the other? Perhaps a combination is more effective? The key thing is there is no right or wrong answer here. The choice may come down to availability of data that produces answers to two essentially different questions.

One of our clients has made a full commitment to dynamic forecasting and has moved away from scenario planning entirely for now. For their operation, the power lies in having a single version of the truth to drive decision making – they are using their rolling forecast as a day-to-day operational tool.

But for others, the volatility of their markets makes scenario planning vital at the moment. They are dealing with too many unknowns and need to make plans based on a huge range of uncertainties: how might the crisis affect their suppliers? Or key customer segments? Will it be a different case across geographic regions?

It’s crucial that considering these scenarios and their differing outcomes is not a one-time activity but a continuous approach. The situation is fluid and there will be different scenarios to analyse as developments emerge; what is important is that the scenarios considered pose relevant questions to drive planning. Our advice for FP&A teams taking this approach and modelling scenarios is clear – keep it simple. Limit the number of factors being considered to ensure that they deliver useful insight and avoid chaos.

What are the numbers telling you?

On the surface, it’s easy to see the attraction of rolling forecasts – they enable a more proactive response from businesses. With a focus on delivery in the here and now, this method of planning engages teams in reviewing the situation and results more regularly, enabling agile decision making to have an immediate impact within a changing environment.

However, forecast inefficiencies can be masked if the time isn’t taken to review the effectiveness of outcomes. Forecasts are never 100% accurate but dismissing variance without drilling down into it can lead to problems down the line. What is causing the discrepancies? Is it performance across the business or have the drivers behind the forecast fundamentally shifted?

In most instances, 20% of the drivers account for 80% of the variance – regularly reviewing inaccuracies in forecasts can reveal much about the true impact of key variables. Taking the time to analyse this data will likely generate new insights about ways in which the business, and the environment in which it’s operating, are changing.

Ultimately, there is a time and a place for both of these planning approaches – the agility they provide is the fundamental aim. By monitoring on a rolling basis, it is possible to more accurately forecast and therefore plan for multiple scenarios. The ‘what-if’ approach helps lay the groundwork for responses to changing situations through modelling ahead of time.

With these frameworks in place you’ll get early warning signals that you wouldn’t see with more static methodology. If you’d like to find out more about how you can use Planning Analytics to enhance your planning agility, get in touch with us today.