Every company, small or large, has to develop forecasts to estimate its future performance. These forecasts are used to set business targets, resource plans, investor expectations, and compensation plans. Forecasting is an attempt to quantify the future so a company can better prepare for expected future events. Depending on the type of business forecasts may be done at different time intervals. In general quarterly and annual forecasts are common across all industries and businesses. Despite all the technological improvements the quarterly or annual ritual of business forecasts is still an archaic process. Most organizations end up spending weeks developing these forecasts for next fiscal years.
Right before the end of fiscal year top management sets the directive for managers across company to provide their business forecasts. The finance teams propose next year's targets. The finance estimates are usually based on what has already been set as investor expectations or feels right for investor satisfaction. Each manager then develops his or her own forecast, which then is ‘massaged’ and ‘manipulated’ to match the finance targets. The whole process of forecasting turns into an interesting sociopolitical negotiation with no common methodology. Every year and quarter is different but consistently a big resource drain of time and money.
Here are five common challenges in this process:
1. Non-repeatable and non-comparable methods
Due to lack of any common forecasting tools or methodologies each manager has a very different way of forecasting. Every manager creates a ground up template for the forecast that is constantly changed every year to meet the last minute deadlines and make the numbers sound right. None of the templates utilize common set of assumptions or forecasting models. As a result business units across company create multiple different forecasts, none of which are comparable or repeatable. Each forecast is customized to a manager’s “gut feeling” largely unrepeatable. Any tweaks, or adjustments require managers to almost redo the entire forecast. Further these forecasts are then rolled into a bigger corporate forecast which compounds and amplifies errors and approximations in the final estimates.
2. Lack of quantitative analysis
Despite of many great statistical software products in market today, most managers do not utilize any quantitative analysis for their forecasts. Most of them prefer to follow a simplistic approach of linear extrapolation, either because they don't have access to these tools or do not have the quantitative know how to use them. The simplistic approach may work some times, but does not many times. The lack of quantitative baseline is one of the key reasons that most forecasts are significantly off from real performance. A forecast based on sound quantitative analysis provides a solid baseline, which can then be tweaked to account for business variations.
3. No simple way to include bottom up inputs from sales
One of the biggest challenges with any forecast is estimating changes to potential future business (wins, losses or leads). As a result, most top down revenue estimates do not account for new sales opportunities. Few diligent managers manually approximate incremental revenue from key new products, while assume all else equal. This approach is better than not including any new revenue. But it still largely does not account for any bottom up information from field about new wins, losses or potential leads that could be converted to opportunities. It also does not account for any changes in competitive landscape or price degradation.
4. Lack of tools to analyze historical trends
In any organization, sales teams are usually closest to the customer and have maximum visibility into potential business awards, losses and leads. Unfortunately very rarely is this data from sales accurately maintained. Even if it is maintained it is hardly quantified into expected net revenue by quarter and integrated in company’s forecasting process. The sales pipeline (forward looking) and business forecasting tools (with historical data, if any) are disconnected. The sales pipeline tools are not connected with the forecasting templates used by business managers. As a result, to managers either spend days just trying to collect the right information or just can't use the right info to develop a realistic forecast.
5. No easy way to capture forecast assumptions of all managers
It takes weeks for managers across large companies to compile their overall business forecasts. Once everything is all said, done and compiled and the big presentation is rolled up, the biggest challenge is explaining this forecast. Since every manager does forecast differently, makes different assumptions and maintains his or her logs differently, the final forecast lacks a common set of assumptions. The overall forecast is one comprehensive, but misses the underlying assumptions of market conditions. As a result, explaining the overall forecast becomes a challenge. The way organizations try to cope up with this by conducting many meetings to understand each others market view. This issue could be easily solved if managers used a common forecasting methodology, tools and maintained their market assumptions using common templates.
In summary, forecasting is a complex task. Managers face several challenges to develop these forecasts and loose a lot of precious time in the process. It becomes even more arduous due to lack of common tools, inconsistent approaches and no common set of assumptions. As technology advances, and newer tools that integrate the quantitative and qualitative aspects of a forecast.
What do you think? Do forecasting challenges does your organization face and how do you cope up with those? Feel free to share your thoughts in comments below.
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