The Fundamentals of Revenue Forecasting

By Kevin Hinton, Diane Chen

It is nearly impossible to predict annual revenues precisely, particularly for new products or businesses, but it is critically important for companies to create high-quality revenue budgets. To maximize the odds of being in the right ballpark relative to actual results, stick to a few key fundamentals.

 

Rate

Summary: It is nearly impossible to predict annual revenues precisely, particularly for new products or businesses, but it is critically important for companies to create high-quality revenue budgets. To maximize the odds of being in the right ballpark relative to actual results, stick to a few key fundamentals.

Executives, managers and financial analysts throughout the country will soon turn their attention to the critical but extremely challenging process to develop revenue budgets for the 2006 fiscal year. Managers with revenue responsibility will spend weeks (and in some cases months) assessing market conditions, conducting analyses and negotiating with peers and superiors to set revenue expectations for next year. Executives will push their managers to set aggressive targets; managers will lobby executives for more achievable targets and greater resources; and sales teams will advocate targets that offer the best opportunity for maximum compensation.

We have learned from our years of experience developing and managing revenue budgets that it is almost impossible to predict revenues precisely. This is due to the fact that the dynamics of the economy, the marketplace and company decision making can never be captured fully beforehand. It is doubly difficult to predict revenues when new products or emerging markets are involved, due partly to the absence of historical data to which managers and analysts can point to substantiate expectations. Large corporations cope with these realities partly by installing quarterly forecast cycles that capture new information as each fiscal year progresses. This approach improves the accuracy of forecasts but is cost prohibitive for small or medium size companies to employ.

Getting revenue projections right—or, more specifically, being in the right ballpark relative to actual results—is vitally important for both small and large companies. Stock prices plunge after public companies miss their own revenue predictions. Managerial reputations rise and fall based on the ability to forecast and hit revenue targets effectively. Sales teams flounder under the weight of unrealistic expectations. These kinds of outcomes occur not only in public companies, in which executive firings are triggered by disappointing quarterly results, but in private and closely held companies that do not receive constant external scrutiny.

Our goal in writing this article is to help managers boost the odds that revenue projections for their businesses will be in the right ballpark relative to actual results. To this end, we have identified three fundamental practices that enhance the quality of projections significantly. We offer guidance primarily with businesses selling to other businesses in mind, but much of what we will discuss can also be applied within businesses selling to consumers. Specifically, we recommend that managers and analysts responsible for developing revenue budgets adhere to the following basics:

  • Understand thoroughly how sales channels work and how prospects become customers.
  • Ground revenue projections in market facts.
  • Be extremely disciplined in applying and evaluating key revenue assumptions.

Rigorous adherence to these basics will make the difference between budgets that give everyone the best chance to succeed and budgets that reflect little beyond wishful thinking masquerading as sound planning. Please note that this article only addresses the development of “top line” expectations. The development of expense budgets is a topic worthy of an article unto itself.

The Fundamentals of Revenue Forecasting

Understand thoroughly how sales channels work and how prospects become customers. On a high level, many companies develop sales forecasts by applying an expected or desired market growth rate to current year revenues. These forecasts are then substantiated using a bottom-up forecasting approach that takes into account inputs such as projected product units sold, price, sales productivity and seasonality, to name a few. Most of the time, the second approach ends up using assumptions designed to meet the end result of the first method.

We recommend a more rigorous approach, relying more heavily on analysis of sales channel productivity and customer purchasing behavior. Here’s why: from an execution standpoint, the effectiveness of sales channels and the purchasing behavior of customers are the two most important drivers of revenue growth. This is a critical point to note for managers of businesses relying on sales teams. Managers must understand how much typical inside or outside sales reps can be expected to accomplish, and what they will actually spend time doing, to develop realistic revenue targets. Even the best sales reps have limits to what they can accomplish over a given time period, and all sales reps spend some percentage of their time on non-selling activities. It is even more important to understand how customers make purchase decisions and to determine the amount of time and effort needed to convert prospects to buyers based on the customer decision-making process.

With these things in mind, we recommend that projections take into account the following:

  • The total number of potential customers with which a company can realistically do business, described sometimes as the “addressable market.”
  • Sales team productivity variables: the number of productive sales reps in the market, the number of calls each can make, the number of calls and average length of time expected to close a sale, average close rate(s) per rep and per product and any ramp-up time required for new products or reps.
  • The incentive structure of the sales team and its potential impact on product sales. For example, if sales reps are rewarded based on gross monthly sales, then one should not be surprised if they spend their time selling products with the highest price tags.
  • Online sales channel productivity variables: the number of products that customers will be comfortable purchasing online, the speed and effectiveness of the fulfillment process, the type of marketing investment required to drive the level of transaction activity sought.
  • Any seasonality associated with buyer behavior.

The value of this work extends beyond the budgeting process. Once a company masters the drivers of sales productivity, it can then track these drivers over time and use this information to assess when corrective action needs to be taken.

Ground revenue projections in market facts. This might seem obvious, but our experience has shown that this is easier said than done. Budget discussions often involve significant negotiation, and someone once wrote that business negotiations are driven as much by emotion as by economics. This often proves to be the case with revenue budgets. The numbers that receive final executive approval often differ materially from the numbers generated by knowledgeable revenue budget owners and financial analysts. This happens for many reasons, some of which have little to do with the level of analytical rigor applied to initial forecasts.

Page 1 / 2

About the Authors

  • Kevin Hinton is a business development and product management professional based in Washington, DC. Kevin possess over 15 years of combined experience developing growth strategies, building revenue budgets and managing products. Kevin can be reached at knhinton@yahoo.com

  • Diane Chen is a senior financial analyst with Starbucks Corporation in Seattle, Washington. Diane possess over 15 years of experience developing growth strategies, building revenue budgets and managing products. Diane can be reached at dianech@gmail.com.


Categories:  Product Management Leadership


Post a Comment

Comment

Allowed HTML: <b>, <i>, <u>

0 Comments