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The Key to Accurate Sales Forecasting By Bob McGarrah, Sales Performance International Moving from opinion-based forecasting to fact-based forecasting

Forecasting sales is never easy. There as many reasons why forecasts are missed as there are customers—the economy, misunderstood sales pipeline, customer budget cuts, competition, market shifts, product inadequacies, supply shortages, etc. Anyone who ever carried a quota can create an explanation of how things did not turn out according to how they were “supposed to”. Overachieving the forecast is almost as undesirable as underachieving. Wall Street frowns on management teams that are not in full control of the business, as demonstrated by missing a forecast by significant amounts—positive or negative. Forecasts drive manufacturing line production, which in turn drive inventory, supply, costs, and ultimately revenues. Most supply problems result from poor forecasting. The accuracy of sales forecasting needs new thinking.

B. Sales revenue forecasting. Sales revenue is an estimate of the value of the opportunities when they are closed. For example, a customer may sign a contract on June 25 for $50,000, which would be sales revenue. However the actual money paid by the customer may not flow until the hardware is delivered, the customer invoiced, and the check arrives. There may be significant time differences between the Sales revenue and the actual revenue.

2. Rigorous use of a sales process: the critical ingredient for accurate forecasts

• Precise measurements of the current condition of the environment, both near and far
  
• Historical information about what weather a particular set of current conditions produces
• Historical information about when the forecasted weather will happen under those conditions
• The more certain these three factors are, the more accurate the weather forecast will be.
  

• Precise determination of the status of every opportunity in the pipeline
• Historical information about the odds of winning an opportunity under a particular set of conditions
• Historical information about when the close happened under those conditions. Similarly, the more certain these three factors are, the more accurate the sales forecast. Let’s look at how to make these three factors practically precise.

1. at which step is the opportunity is in the sales process (status)
2. where the customer is in their buying process (status)
3. the quality of execution of the sales process up to now (status)
4. what are the historical chances of an opportunity ultimately closing at each step of the process

Over time, the accuracy of forecasts improve as the sales organization gains experience, becomes more and more rigorous in using the sales process, measures the third criterion over time, and applies it to the forecasting activity.

The second method of forecasting covers the non-key opportunities. We call these opportunities the “bulk” opportunities because they usually represent the majority of opportunities in the pipeline, smaller ones. But they may not represent the majority of the sales revenue. This forecast method examines the pipeline with the key opportunities removed to size the bulk forecast. The total forecast is then the sum of the two parts: the key opportunity forecast plus the bulk opportunity forecast.

Some sales organizations may have only key opportunities. Their pipeline has only a few large opportunities. Since there are such a small number, every one is a key opportunity can be individually forecasted by name.

Other sales organizations have a large number of small opportunities, too many to look at each one individually. The method for forecasting these would be based on the historical chances of closing, giving a forecast based on both the historical data and the progress through the process of all the opportunities in the pipeline. I’ll describe this method in more detail later.

Most of our clients have a mix of key and non-key opportunities. They use both key and bulk forecasting methods and add the two forecasts to provide the total sales forecast. Even when all the opportunities are small, some of them may be individually analyzed to the point where they can be treated as key opportunities.

4. Perform forecast post-mortems

All business processes must continually look at what worked and what did not in order to improve their effectiveness. Forecasting is especially subject to this inspection, of forecasts that were not met, and of those that were—of forecasts that were over-achieved, and of those over-achieved. Wall Street looks on a company that continually over-achieves its forecast as skeptically as one that under-achieves. A bellwether of well-managed companies is the consistent accuracy of forecasts. The forecasting process should be continually examined to improve it.

1. Compare the actual sales revenue achieved against the sales forecast.
2. Determine whether the assumptions were accurate.
3. If the forecast was significantly missed (positive or negative) determine why.
4.Modify the forecasting process or assumptions to avoid these reasons for the miss.
5. Involve customers in the forecasting process

Sales forecasting is, after all, a prediction of what customers will do. Why not involve customers in the forecasting process, especially existing customers? If there is a strong relationship with your customers and you are bringing real value to the relationship, don’t hesitate to have a discussion about the future. You might not be comfortable asking the direct question, “How much do you expect to spend?” But there are some non-committing questions that will help you increase the confidence level of your forecast:

•  “When will you satisfy all your decision criteria and be able to make the decision?”
•  “At this point in time, what do you see as my company’s chances of winning?”
• “Are there any new factors that would delay your decision?”
•  “Have there been any recent personnel changes or reorganizations that will impact your decision?”
•  “How do you view my company as compared with our competition?”
• “Is the current economic environment causing changes in your plans to buy?”

The focus of these questions is to validate the assumptions behind your forecast and determine whether any new factors are coming into play that you do not know.

5. Precisely define the pipeline and accurately grade the opportunities

A pipeline is a collection of opportunities being worked on. It is two-dimensional—the dollar amount of opportunities vs. how far along the opportunities are on the way to closing.

As opportunities are identified and enter the pipeline they are Milestone ‘A’ opportunities. As the sell cycle progresses, the opportunities move through the milestones—A to B, B to C, C to D, etc. The dollar amount represents the expected amount of revenue for opportunities that are currently at the particular milestone.

In order to draw any conclusions about what the pipeline will produce based on history, there must first be a precise qualitative and quantitative definition of what each milestone means. If the definitions are based on opinions, the result will be imprecise. If they are based on facts, they will be precise because a certain set of facts (the environment) produces consistent results. The easiest way to set these definitions is to use a well-defined sales process, in which the milestones are defined by the facts of what has been accomplished in the sales process and opportunities are religiously graded accordingly. The definitions are unambiguous and consistent from seller to seller, and from opportunity to opportunity. Just as weather forecasters depend on precise terminology and accurate meteorology on which to base their forecast, so do sales managers.

6. Forecast sales volumes based on history

A sales revenue forecast has two elements: 1. sales revenue volume and 2. sales revenue timing. For sales revenue volume forecasting, ‘history’ means “What has been the percent of opportunities that actually closed once they have made it to a particular milestone?” Think of this as the win odds. Tracking the experience of a particular sales process over time will give the answer. Many sales processes have a ‘starter’ percentage that is useful until more experience has been gained. This is a simple parameter to measure if the sales organization has good Sales Force Automation (SFA). When a well managed sales process has been implemented, these percentages can be derived with several months’ experience.

7. Forecast sales timing based on history

When the revenue will happen, i.e., when the opportunity will close, is again based on history. Specifically, “When will the ‘typical’ opportunity at milestone A close?” At B?, etc.

Conclusion

• the sales history of the company
  
• what activities have successfully been completed with the customer for each opportunity (milestones)
• confirmation of our assumptions with our customers,
• what we have learned about our sales process and past forecasts to improve our forecast process.