In the first piece in this series, I suggested that despite it being widely recognized that rolling-reforecasts help improve both the accuracy of the forecasts and corporate agility, only a third of companies actually use them today. I am now even more convinced that my estimate is in the right ballpark as it is not far from the 40% figure that Deloitte found in their most recent survey on planning and budgeting. The reason for this low level of adoption is that many organizations treat a reforecast as a re-budget. For them, moving to monthly rolling reforecasts would mean budgeting 12 times a year, which is clearly unacceptable.
To be effective, forecasting needs to be a rapid, light-touch process for both citizen planners and the finance team managing the process. It should be a quick assessment of the real trajectory of the business, reviewing any external or internal changes, and realigning resources to address issues and opportunities. Rather than episodic, it should be a fundamental part of what managers do every month. But ideally, it should not take up for more than a few hours of their time.
As a first step, the organization needs to align the outlook of its forecasts with the volatility and lead times inherent in its business model. If they operate in a volatile and fickle market, this means implementing more frequent reforecasting so that planners can quickly realign resources with fluctuating demand. However, if the company has long lead times and course-correcting actions take time to have their desired effect, then forecasts need to provide a longer-term view that extends far beyond the current year-end.
Most organizations will find this first step to be relatively straightforward; the next steps may be more contentious though. If it is impossible to deliver rolling reforecasts by treating every forecast as a re-budget, then surely a new mindset is called for. To my mind, the three points below are the essential building blocks that are imperative for successfully achieving monthly rolling reforecasts:
1. Develop a reforecasting model
Implementing rapid, light-touch reforecasting means abandoning templates and replacing them with a dynamic model that uses a handful of business drivers and standard unit costs to calculate all of the important variable line items, such as revenue, and staffing expenses. Inevitably not all line items will be “driver-based” as certain elements of expense are essentially fixed or discretionary. However, these typically require less frequent reviews.
2. Automate the detail
Reforecasting models will only gain traction if they provide the level of detail that managers in the operational areas of the business need on a daily basis. This is easy to achieve by incorporating algorithms into models so that higher-level input are automatically spread down to individual product variants and pack sizes based on recent history. At the same time, incorporating statistical forecasting functions, such as linear regression and seasonality modelling, that are available in the Anaplan App Hub, will help cut forecasting cycles even further.
3. Move to real time
It is imperative that the enterprise planning and budgeting solution supports real time “what-if” modeling. Otherwise, citizen planners contributing to a reforecast will inevitably resort to using spreadsheets, which will significantly increase their workload and lengthen reforecasting cycle times.
What to look for in a solution to support rolling reforecasting
If you are intent on implementing monthly rolling reforecasts, you will be running 12 reforecasting cycles each year. If your ambition is to implement quarterly rolling reforecasts, then you will be running four cycles each year. Either way you will be making more frequent use of your chosen planning and budgeting solution to support reforecasting than you did in support of annual budgeting. If you follow this logic through, you reach the irrevocable conclusion that when you choose a planning solution, the most important selection criteria should be its functionality to support rolling reforecasting, rather than its capabilities for budgeting and reporting. In these uncertain times, when the ability to reforecast more frequently will deliver more value than the ability to budget, I would say this is not just a subtle change of priorities; it is an imperative. Put simply, forecasting today is way more important than budgeting.
So what distinctive capabilities should you look for if you are seeking a planning tool to support rolling reforecasts? Well clearly, not a solution which has its foundations in financial budgeting. This is a point that Dean Sorensen made recently in an article where he suggests that what is needed is a new breed of software that he calls “EPM2.” Thecharacteristics that Sorensen suggests differentiate EPM2 from EPM1 address each of the three building blocks needed for rolling reforecast highlighted above, namely embedded modeling logic, the ability to process large volumes of data, and real-time processing. Sorensen points out that it is important that the chosen solution includes all of these capabilities. He also suggests that embedded planning-model logic is the critical capability, rather than in-memory computing which he says can simply get to the wrong answer faster.
Taken together, these three capabilities undoubtedly provide the essentials for making rolling forecasts a reality. If you wanted to extend the list, I would add self-management, integrated workflow, and built-in automation to minimize model maintenance by doing away with the need to edit business rules. One example of this is the functionality for rolling time periods that Anaplan delivered in the January release.
The importance of rolling forecasts is gradually changing how forward-thinking companies are evaluating and investing in performance management software. They recognize that effective rolling reforecasting can only be achieved by integrating operation planning with financial planning. This leads them to look beyond traditional planning and budgeting solutions to ones such as Anaplan that also incorporate embedded driver-based planning model logic that is essential for success.