Sales forecast methods are an integral part of business, affecting nearly every core function within an organization. It impacts your Marketing budgeting and spending; your Human Resources plan for staffing; your Production and Operations plans and procedures, and so on. Produce too much, and you’ve tied up your cash in inventory. Produce too little, and you’ve missed out on the opportunity to fully capitalize on the market, potentially leaving room for a competitor to steal market share.
The more you deviate from your predictions, the more costs you incur that take away from your bottom line. And in today’s increasingly globalized marketplace, a myriad of factors (longer lag times, shipping across borders, accounting for demand across multiple markets) add layers of complexities to those predictions. With so many factors at stake, one thing’s for certain: an accurate sales forecast method is more critical than ever. Here are some key strategies that can help.
A Critical Look at the Components
First, it’s important to address the two main approaches used for sales forecasting: the top-down approach, which starts on an industry-wide level, and the bottom-up approach, which starts with sales estimates from individual salespersons. Along with these approaches, various forms of qualitative and quantitative methodologies can be employed, some of which are well-known and widely used; and others that are more obscure. Understanding these methodologies is only half the story, of course – knowing how to apply them is what will help you maintain a healthy bottom line. And that brings us to our first tip.
Tip 1: Fine-tune your forecast using multiple sales forecast methods.
There’s no single methodology that ensures 100-percent accuracy. So try focusing on two or three different methods, both qualitative and quantitative. Let’s take a look at some key qualitative methods:
- Executive Method – This common method of forecasting is developed by an executive within the organization.
- Delphi Method – A team of experts (for example, department heads and/or consultants) develops and reviews forecasts.
- Salesforce Method – This method consolidates individual estimates from each member of the sales team, often rolled up by region or parent SKU
- Ask the Customer – An organization goes straight to its customers to gauge their intentions for buying a company’s products or services.
- Test Marketing Method – This method uses smaller, more controlled markets to determine demand for new products or services.
Sales forecast methods comes with its own pros and cons, of course. For example, the Executive Method is quick and relatively inexpensive; however, it is entirely subjective and hard to break down into sub-units. On the other hand, while the Ask the Customer method provides detailed insight from multiple sources, it can be slow and time consuming.
Now let’s look at some Quantitative Methods of forecasting, which are typically more complex and mathematical.
- Moving Averages/Weighted Moving Averages – Uses a company previous year’s sales to calculate current sales averages
- Exponential Smoothing – Sales forecast for next period = (L) (actual sales of this year) + (1-L) (this year’s sales FCST); where (L) is a smoothing constant ranging from 0<L<1
- Decomposition – Breaks down a company’s sales data from previous periods into components like trend, cycle, seasonality, other events; then recombines those components to produce a sales forecast
- Naïve / Ratio method – Sales forecast for next year = Actual Sales of this year X (Actual Sales TY/ Actual Sales LY)
- Regression Analysis – Identifies causal relationship between company sales (dependent variable, y) and independent variable (x), which influences sales. Company sales are usually influenced by multiple variables including price, population, promotional expenditure.
Again, pros and cons prevail for each method. The commonly used Moving Averages method, for instance, is quick and easy but does not account for downturns or upturns. Similarly, the Naïve method is relatively simple to calculate, but inaccurate if past sales have fluctuated. Conversely, a Regression Analysis is more accurate and can accounts for upturns and downturns, but it’s complex and usually requires specialized statistical software. It’s important to note that finding the optimal mix of methodologies takes time, and largely depends on a company’s resources and time. It also takes ongoing, active coordination between teams within an organization, which we’ll discuss next.
Tip 2: Create collaborative sales forecast methods.
Just like with methodologies, it’s a good idea to involve multiple groups within your organization to come up with a sales forecast. By having forecasts from different groups, your company is able to see the range of deviation between the forecasts. If that range is too large, those groups can get together to reevaluate methodologies and the underlying assumptions behind the forecasts. This type of collaborative teamwork, across various cross-functional teams, helps produce a much more accurate sales forecast.
For example, you may ask your Sales VPs to provide a top-down sales forecast, in addition to gathering a bottom-up forecast from their sales people (often referred to as Sales Field Forecast). Then, Marketing leaders can provide their sales forecast and, finally, Finance leaders can provide their forecasts as well. This collaborative strategy can be especially effective for the year’s initial forecast, as it drives planning efforts for the entire year. From there, a final full-year (FY) forecast is broken out by quarter by parent-level SKU and/or by top-level accounts. And once the initial FY forecasts are loaded, your organization can develop a methodology to keep a close watch on any changes. And that leads us into our next tip.
Tip 3: Establish processes that allow for continuous evaluation.
Sales forecast methods are fluid all year round, year after year. After developing your FY forecast, it’s never as simple as being able to “set it and forget it.” To get the most accurate picture, you’ll need to implement systems and processes that allow you to evaluate your data on a weekly, monthly and quarterly basis. Here are some ways to do this:
- Coordinate monthly meetings between sales and finance to summarize and evaluate your sales YTD (Year-to-Date), sales forecasts and any risk/opportunities that have arisen.
- Account for seasonality. If your organization is seasonal, for example a toy company that generates over 50% of sales revenue in Q4, you’ll want to go through a major reforecast in Q3, and have cross-functional teams come up with a revised forecast for Q4. The ultimate objective is to make sure that any risks and/or opportunities in the sales forecasts are communicated throughout the organization, so that the cross-functional teams can take the appropriate measures to successfully execute the business while maximizing the profit potential and controlling costs.
- Develop robust daily reports/scorecards that can be sent out to cross-functional teams. These types of reports would show the YTD sales (by top account or by parent-level SKU) versus YTD Forecast and LY YTD sales (by quarter and by month), along with weekly changes to the GM/VP forecast estimates for the quarter. This type of daily tracking system allows your organization to stay on top of your sales forecast, and react and adjust in a timely manner.
- Consider cross-functional systems. Companies can invest in enterprise-wide business intelligence solutions (for example, Anaplan). These sophisticated systems can capture and communicate the cross-functional impact of a change in the sales forecast in real time — which is especially significant for organizations that outsource overseas. For instance, let’s say a sales forecast drops by 10 percent. The Marketing VP will immediately see a cut to the budget — which will, in turn, impact a Production Manager in China, who can adjust the next order of raw materials accordingly. In short, the entire organization will see the real-time, direct impact of the modified forecast.
Sales forecasting is a highly involved, time-consuming effort — and the need for accuracy can place an enormous burden of responsibility on your organization. For global markets especially, the stakes are too high for significant deviation. While the strategies provided here are a good starting point, an experienced 8020 Consultant can help your organization fine-tune its forecasting methodologies and implement the best-fit tools and systems — and in doing so, help your company realize its full profit potential. For additional information on helping your sales team operate more effectively, contact us. You can also download our sales comp plan tip sheet by clicking the button below.
About the Author
8020 Consulting’s Emir Kiamilev has several years of experience in helping organizations evaluate and improve their financial forecasts. He is a strategic thinker with the ability to synthesize large complex data points to uncover efficiencies and provide expert recommendations. His action-oriented financial planning and analysis has helped a number of companies cut costs, and improve growth and profitability.
Categorized in: Financial Planning and Analysis