Is your sales forecasting perpetuating weak practices? Potential-based sales forecasting is a powerful new way to drive revenue growth, and change.
Sales forecasting should be the centerpiece of revenue improvement in every company. Yet, all too often, managers treat forecasting merely as a necessary distraction from productive work.
The reason why sales forecasting so often fails to live up to its potential is that in most companies, it is implicitly treated as a descriptive rather than prescriptive process. This means that managers use the process to try to predict future sales based on average current performance, rather than using it to analyze, manage, and improve the revenue stream. This serves to embed current practices, both good and bad, in the forecast. In this way, managers lose the all-important opportunity to shape their future.
What's wrong with this picture? Typically, sales forecasting occurs in one of two ways. First, in companies like distributors, with identifi-able accounts, forecasters try to distill and predict the sales pipeline. Second, in companies like retailers, with masses of customers, forecasters look at the demographic and competitive landscape, and try to relate these factors to sales.
Consider Company A, a distributor of HVAC products. The company has a typical sales force: each sales rep has about 120 accounts, with 5-10 "A" or large accounts, 10-15 "B" or medium accounts, and about 100 "C" or small accounts. Each rep calls on the "A" accounts weekly, the "B" accounts bi-weekly, and the "C" accounts monthly, if that.
The sales force uses a popular sales management software package in which each rep tracks his or her progress. The software produces "funnel" reports that calculate the expected value of upcoming sales based on amount, likelihood, and timing. This becomes the core of the sales forecast.
Company B is a retail chain with about 100 stores. Here, the marketing group has developed a forecast model in which each store's sales is related to the demographic and competitive characteristics of its trade area. Based on this model, the company develops sales forecasts both for existing stores and for new "greenfield" locations.
What's wrong with this picture?
The missing element Both Companies A and B have forecast processes that are designed for financial projections, not for improving the business. They implicitly assume that the companies' current activities will be continued, and therefore can be projected into the future.
The point of management, however, is fundamentally different: it is to identify the key leverage points to improve the business, and to rapidly change the company for the better.
A well-designed sales forecasting process accelerates positive change, while a typical backward-looking process retards it. Current sales forecasting approaches all too often perpetuate weak practices while keeping them hidden. A better forecasting process discovers and builds on best practices, channels sales efforts toward the highest-potential, most productive situations, and projects accurately the resulting revenue growth. Importantly, if the company makes significant positive changes, forecasting on the basis of past performance is inaccurate and counterproductive.
Distributor forecast management Let's start with Company A, the distributor. In my research and consulting work, I have found that the key point of leverage for rapidly increasing sales is identifying and turning around high-potential, underpenetrated accounts. For example, in one project, I traveled with high, medium, and low performing sales reps. I asked each how he or she would approach turning around a major potential account that was only slightly penetrated. What would be the plan month by month? How many visits and what sales would result?
The top-performing reps all had strikingly similar account turnaround processes, and even told me at what point the inexperienced reps would give up. In fact, it turned out that these top reps all had independently discovered the most effective account turnaround process, and made it the centerpiece of their sales activities. That's why they all were President's Club winners.
The lower echelon reps, on the other hand, were either very optimistic or very pessimistic about their ability to turn around high-potential accounts. The problem was that the overly optimistic reps got discouraged quickly when they encountered sales barriers, and the overly pessimistic reps were reluctant even to try.
In this context, how can a manager structure sales forecasting to improve results? Many managers assume that sales forecasting and improved selling practices are not connected in a direct way. This view is completely wrong and counterproductive. The objective of great forecasting should be to discover the company's own best practices, and to build these improved practices into the forecast, instead of perpetuating weak practices. The key to achieving this objective is to deploy a two-step potential-based forecasting process.
First, forecast account potential, not actual sales, for all significant accounts in a territory. This may seem daunting at first, mostly because few companies do it today. However, in practice a manager can do this effectively by focusing on the company's own best practice, its most highly-penetrated accounts, and understanding what characteristics these accounts share. Based on this analysis, it is not difficult to identify the salient characteristics of the company's other accounts and to estimate the upside. In addition, several good commercial databases show rough account potential. The combined picture is quite accurate, and a few telesales calls usually can confirm account potential. Because account potential usually does not change much from year to year, the information is relatively easy to maintain once it is developed.
Several important surprises emerge at this stage. Some of the "C" accounts that received little attention in the past because they had low actual sales are really high-potential underpenetrated accounts. With a critical mass of rep attention, combined with systematic rep training in the company's own best practice account turnaround process, these accounts can produce quantum sales increases for the company.
Once a 70-80% accurate picture of account and territory potential emerges, the second step is to measure the difference between account potential and actual sales. This straightforward calculation gives a measure of unrealized potential for both individual accounts and overall territories. It also gives reps and their managers a key measure of the reps' effectiveness in converting potential sales into actual revenue dollars. It shows, for example, whether a rep is a great performer with an inherently meager territory, or a moderate performer with an inherently great territory. This perspective is critical for effective sales management.
With this picture, sales managers can direct reps to devote a portion of their time to turning around individually-targeted high-potential accounts, rather than simply deploying rep time against historical account sales. This is the key to rapidly maximizing sales force productivity.
Potential-based forecasting can be quite accurate, even in the context of changing and improving revenues. The analysis of account and territory potential enables managers and reps to target particular accounts in each territory. Because they can project the sales amounts and timing that the top reps' best practice methods would have produced in each account, they can get an upper bound on this revenue growth. Because managers can gauge the effectiveness of individual reps at growing sales in turnaround accounts, they can forecast the proportion of best practice sales growth a particular rep can achieve. Thus, potential-based forecasting can achieve a high degree of accuracy even in the context of a changing revenue stream.
Retailer forecast management In retail, the two-step potential-based sales forecasting process is again critical to revenue improvement. However, here the process works a little differently.
Let's return to the case of Company B. This retailer sells a variety of products in several related categories. In the past, the company had forecast store sales by relating broad measures such as trade area, aggregate population, average income, and competitive intensity to respective store sales. It used this process both for forecasting existing store sales and locating new stores.
In order to make its sales forecasting more accurate and useful, the company decided to deploy a two step potential-based sales forecasting process, analogous to Company A's process, described above. Because the store collected customer zip code information at its registers, the company had records of customer purchases by zip code. After careful inspection of its sales by zip code, it appeared that even within a store trade area, sales varied widely from zip code to zip code even when the zips were very similar in demographics, distance from the store, and competitive intensity.
When the management team saw this zip to zip variance, they decided that simply forecasting average store sales would not be helpful. Instead, they decided to estimate the potential sales in each zip. In order to do this, they focused on identifying and understanding the best practice (i.e. highest sales) zips in each store's trade area. Then, for each store, they related these best practice zips to relevant factors, such as zip demographics and distance from the store.
With this information, they were able to estimate the potential for each store's non-best practice zips, projecting what the store's best practice zips with similar characteristics would have produced. This was analogous to the distributor's process of estimating account potential by focusing on its most highly penetrated accounts.
In the second step, the managers subtracted each zip's actual sales from its estimated potential sales, yielding a picture of the unrealized potential, or upside, of each store's trade area, zip by zip. This gave the management team a precise roadmap of where best to deploy marketing resources in order to turn around the high-potential underpenetrated zips.
By comparing actual and potential sales measures from store to store, top managers could gauge each store's relative effectiveness in mining its trade area. When the managers ranked each store's effectiveness, they could see not only the unrealized potential of each store relative to the store's own best practice, but also they could estimate the additional potential sales that a top-selling store could have achieved in each lower-performing store's trade area.
With these measures of trade area potential and relative store effectiveness, plus an understanding of the speed of best practice market development in focused zips, the management team could forecast sales improvement with the expectation of improved sales practices built in.
In retail, zip code-based analysis is not the only useful approach. Some store chains find customer market segmentation to be a powerful forecast variable. However, it is often very difficult to get a good measure of market segment actual and potential sales, and, in any event, sales potential almost always declines very rapidly as customer distance from a store increases. This suggests that for most retailers, zip code-based analysis is a good place to start.
Converting potential into actual sales Once a company has a sound roadmap of potential, it can target its prime turnaround candidates, whether accounts or zips. Three steps are needed to convert these opportunities into actual sales.
Best practice. Identify the company's own best practice for particular types of accounts or markets, categorize it, and train the reps or store managers in the process. For a detailed explanation of how to do this, see my column, "Use Best Practice to Fire Up Your Sales Team."
Low-risk experiments. In chess, it is a classic error to try for checkmate on an early move. The same is true in business. Once a manager has identified target accounts or zips, the next step is to initiate a series of low-risk experiments in various accounts or zips, and to carefully keep track of how well each works, generally including comparison to a control group. This process allows a manager to fine-tune best practice with low risk and minimal investment.
Account/market plans. Account plans are critical for identifying opportunities and barriers, and for articulating milestones that can be tracked, making the sales process systematic, manageable, and coachable. In retail, this powerful process can be applied to zip code or market segment development. Managers also can use this process to assess and understand the results of their initiatives, and employ this understanding to make mid-course corrections and improve plans the next time. For a more detailed explanation of account planning and management, see my column, "Account Management: Art or Science?"
Potential-based sales forecasting Potential-based sales forecasting can be a prime driver of rapid revenue increases. The key to success is to recognize that forecasting should not be built on the past and embed weak approaches to selling, but instead should be based on best practice potential and embed improved practices through the two-step process. With this process, a manager can write the future, rather than projecting the past.
Jonathan Byrnes is a Senior Lecturer at MIT and President of Jonathan Byrnes & Co., a focused consulting company. He earned a doctorate from Harvard Business School in 1980 and can be reached at jlbyrnes@mit.edu. Please see his website http://mit.edu/jlbyrnes for other articles and information. If you want to receive notices of Jonathan's columns and other writings, please register on his Website, or simply send him an e-mail. 
