12 Golden rules of Rolling Forecast

Rolling Forecast

A rolling forecast is a process in which key business drivers are forecast on a continual basis. Its objective is to foresee the risks and opportunities presented by a dynamic business environment revisit strategy in the light of changing business scenarios and align resources/activities for competitive advantage at periodic frequencies. Rolling forecasts are not simply periodic updates against the annual budget and are not associated with a specific financial year.

Rolling forecast enables to anticipate short to midterm outcomes and therefore influence them whereas budgets are developed for specific period on set of assumptions. Rolling forecast provides with a moving window of the future that helps them to make strategic and tactical decisions, manage cash flows, and set shareholder expectations.

Following 12 golden rules make rolling forecast more effective and enables pro-active strategic decisions to influence outcomes:

 1. Focus most on top line forecast: First step must be forecast of sales or income line. Most other variables are dependent and related to sales or top line. A well prepared sales forecast should take account of marketing and promotion and new product launches. It should consider market share, production capacity, and competitive actions. And it should examine customer behavior patterns and pipeline.

 2. Rolling forecasts periods must be above twelve months: The purpose of forecasts is to provide a more useful framework for decision making. So they should be done regularly and cover a period that enables leaders to effectively steer the business. It is inevitable to cut across rolling forecasts go past the next fiscal year-end, thus providing leaders with more visibility.

3. Make rolling forecast a very easy and simple process: Base forecasts on a few key drivers, not masses of detail. Compiling forecasts from hundreds of lines of detail is the wrong approach. In most businesses, few numbers change much from period to period. It therefore makes more sense to focus on the key drivers of sales and costs. Given that each forecast is prone to error, the more forecasts you combine, the greater will be the error, as one mistaken assumption affects another. The essential point is that they can see the holistic view backed with factual data points.

4.  Choose the right forecasting horizon: The forecasting intervals and time taken should reflect the needs of the business. For example, with no physical supply chain and inventories to manage, forecasts can be done in few days. Whereas in a capital intensive business, which uses forecasts to make key decisions about production capacity requirements often involving significant capital sums, forecasts can take longer. There is no straight answer to the question of the length of the forecasting horizon. It depends on how long a company takes to make key decisions about operations, capacity, and capital spending. In other words, if the company takes two years to bring new facilities on stream, this might be a reasonable guide. In a fast moving retail business, forecasting should reflect lead times. If the business takes three months to change supply contracts or adjust marketing programs, there is no point in preparing forecasts for less than this period. The horizon also depends on the speed of change. For an airline or ocean transporters, changes are happening at lightning speed, and revising forecasts each rolling forecasts month would be advisable.

5.  Unified logic and rules: Create clear methods of standardizing inputs to the rolling forecasting process. If all contributors adhere to the same rules in classifying opportunities, the forecast model is at least based on similar data standards each. Standardizing requires implementing rules for classifying opportunities or costs. Then, define the type of progress required in workflow process. Finally, assign probabilities of closure based on standard rules. Inputs must be based on facts rather than opinions.

6.  Consistent and aligned rolling forecasting models: Planning tools are offered by companies like Anaplan, Oracle and IBM which have pre-built sophisticated features to enable large organizations to prepare rolling forecasts quickly and consolidate reports. Teams can build business rules and structures, then modify the model as their business evolves, easily accommodating changes such as added locations, new or discontinued product lines, or restructured cost centers. These tools have powerful modeling capabilities that enable teams to flexibly define, compare, and assess multiple business scenarios. Such systems allow teams to build models in few days. They can import data definitions from other sources like ERP and General Ledger systems. They also enable teams to build cross-functional modules.

7.  Shorter lead times: Forecasting what will happen tomorrow is much easier than what will happen in three or six months. Shorter the lead time to introduce new products or strategies, the more performance measurement accurate and useful the forecasting process will be. Fast response is the real aim. The only reason you forecast is because you cannot react or respond fast enough and if given a choice of improving your speed of reaction or improving your capacity to forecast, you should always choose speed of reaction. Rolling forecast with shorter cycle time enables to predict and adopt quickly.

8.  Match rolling forecast model to business requirements: A model is a simplified representation of the world to use to form a prediction. There are three types of models. (1) Statistical models extrapolate from history to generate a prediction, based on the assumption that “the future will be a continuation of the past.” This model is often used to forecast revenue lines, including consumer spending and product sales. (2) Mathematical models attempt to understand and model the relationship between various elements of the business to produce a prediction. Many cost forecasts, of course, vary with revenues. (3) Judgmental models are in the head of the person producing the forecast. Although forecasting based on judgment seems simplistic, human beings are capable of modeling in very sophisticated ways. The aim is to use the most appropriate model for each part of the rolling forecast.

9.  Periodic validation and comparison of rolling forecasts: Managers should learn from their forecasting experience. The purpose of validation is not to attribute blame but to learn if forecast accuracy is improving and how to improve it further. Forecasting inaccuracy can be seen in the same light as process variability. Teams therefore need to better understand the causes of that variability and work to reduce them by comparison of multiple forecast versions and process improvement.

10. Sales team must own top line rolling forecast: Purpose of rolling forecast to ascertain probable performance and not targeting setting process. More accurate and realistic rolling forecast is only possible with bottom up forecast from frontline teams.

11. Rolling forecasts must not drive revision of targets or rewards: Most unbiased forecasts are not the ones leaders want to see. If you ask managers to forecast within a budget or target based system, don’t be surprised when their forecasts magically meet the agreed on budget or target. Managers know that their leaders don’t want to be told bad news. Precisely for this reason rolling forecasting must be detached from target setting, measurement, and rewards.

12. Forecasts to be changed only with consensus: While corporate team can challenge the assumptions on which a forecast is based, and therefore its outcomes, it cannot unanimously change the forecast numbers. Otherwise all credibility in the bottom up rolling forecast process will be lost. Revision can still happen with consultation and consensus by validating forecasting drivers.

Advantages of Effective Rolling Forecast:

1. Improves strategic and tactical decision making process: A well prepared rolling forecast provides an excellent decision making framework for management (e.g. make or buy, marking down and running addition shift).
2. Enhances performance by identifying future gaps: Rolling forecasts enable managers to focus on the medium term outlook and encourage managers to take actions that close gaps against peers/competitors or benchmarks rather only their own target.
3. Enables to manage performance and avoid shock profit warnings: With limited future visibility, leaders are always vulnerable to the shock profit warning is nightmare for any corporation board. With rolling forecasts that are quickly consolidated throughout the group, leaders can anticipate sharp changes in performance. They should be in a better position to manage expectations and take control of events rather than driven by them.

Conclusion

Many corporations are implementing rolling forecasts in an effort to anticipate change, but most fail to optimize the benefits because the forecasts accuracy is impacted with supervisors influence to see their expected performance in forecast. If senior executives use forecasts to micromanage or demand immediate action, trust and confidence will rapidly vanish. The forecast numbers can be validated and challenged by reviewing data points and drivers if forecasts show a significant change and managers have not explained the change beforehand. Managers should be responsible for dealing with problems and reflecting any corrective actions they have taken in their revised forecasts.

Effective rolling forecasting only works in a culture of transparency and trust. A well implemented rolling forecast performs a number of useful roles. They help senior executives to manage shareholder expectations of value creation; they enable office of CFO to consolidate and manage cash requirements; and they help operational managers to make decisions. Rolling Forecasts enables fast strategic actions to take advantage of market opportunities or counter threats in ever changing global dynamics.