How do you forecast sales?

Calculating sales forecasts is essential to boosting your company's growth! You've got all your figures at your fingertips, your brain in calculator mode, but you're lacking methods? Don't worry! To help you, we've listed the most effective tools for successful calculations.

The result is improved sales execution performance and a better understanding of your transaction reports (or pipeline analyses).

Not afraid of maths? Then let's get started!

What is a sales forecast?

As the name implies, a sales forecast enables you to estimate your sales volume over an upcoming period.

This sales forecast calculation will be very useful for :

• Estimate your future sales
• Review your budget and resource allocation
• Facilitate the work of your teams (software or training needs)
• Identify opportunities and anticipate future problems

Okay, but how do you go about it?

To achieve this, you'll need to collect both internal statistics and external data (technical advances, changes in purchasing behavior, etc.).

With this information in hand, all you have to do is choose from the following methods to calculate your sales forecasts.

Sales forecasting methods

Simple quantitative methods

Simple quantitative methods are based on historical, objective and quantified data. In short, you use only the statistics of your past sales to predict your future performance.

When you draw up your sales forecasts, you can choose whether or not to include seasonal variations.

Beware, these methods have their limits, as they assume that your sales will be repeated in a linear fashion, from one year to the next.

More complex quantitative methods

For a more precise calculation of your sales forecasts, you can integrate additional variables.

For example, you can add external factors such as changing customer intentions, macroeconomic trends or the influence of competitors.

While these quantitative methods are more complex, they are also much more reliable!

Use of simple quantitative methods

Basic principle

With a simple quantitative analysis, you only use statistics derived from your past sales. This assumes that your company's activity is regular, and that this regularity continues.

You'll need to represent your data in the form of graphs (also known as scatter diagrams). These representations often include two pieces of information: sales by year, month or quarter, and sales volumes.

All you have to do is choose from the 3 methods below.

Extreme point method

You can use the extreme points method if you find that your first variable, such as sales volume or sales revenue, rises or falls steadily with your other variable (years, for example). Your scatter plot is therefore logically not very dispersed.

This is the simplest method of sales planning.

In concrete terms, you will create a graph and place :

• Numbering of month, year or quarter (x) on x-axis
• Sales volume or turnover (y) on the ordinate

All that remains is to calculate the equation of the linear fit line of type y = ax + b. It passes through the first point (a) and the last point (b).

To determine your sales forecast or next sales volume (y), replace x with the relevant year in the equation. The result determines your sales target.

Average point method

The mean-point method, or Mayer's method, is also fairly straightforward. Use it only if your point cloud is close enough to a straight line.

To begin, divide your data into two subgroups, then calculate an average value for x and y in each. Then calculate the equation of the adjustment line that passes through these two points.

This method is more precise than the previous one. Why is it so? Simply because it corrects for variations between closely spaced measurements.

Least squares method

The least-squares method is already a little more complex (but also more accurate). Use it if your point cloud is more dispersed.

Here, you need to find the equation of the fitting line that passes as close as possible to the set of points.

Calculating forecasts using other quantitative methods

Regression and correlation methods

With the linear regression method, you'll establish a relationship between two variables x and y.

In simple terms, the variable x is said to be independent or explanatory, as it does not change with the other parameters. When calculating sales forecasts, x designates time (year, quarter or month).

The variable y, on the other hand, is dependent (sales volume or turnover) because its value evolves as a function of x.

You then determine the correlation coefficient (r) between these two variables, i.e. the strength of their relationship.

A little hint: the coefficient r must always be between -1 and 1. It will be positive if your two variables increase together. It will be negative if the values of one variable increase while those of the other decrease.

Exponential smoothing

With exponential smoothing, you also use your past data, but place greater emphasis on your most recent statistics.

How do you do it? Simply assign an increasing weighting coefficient to the oldest data.

When calculating your sales forecasts, remember to choose a smoothing constant between 0.1 and 1. The higher the value, the greater the weight given to recent data.

Moving averages

In the case of moving averages, sales forecasts are based on average sales over a given period.

In concrete terms, you'll need to divide a period (year, quarter or month) into several sub-periods, then calculate the average for each of them.

This technique is best suited to companies whose customer demand is relatively stable over a given period.

Don't forget to integrate these indicators for accurate forecasts

You've made your choice and can't wait to get started? So much the better! Before you start, don't forget that your sales forecast should also include :

• Your sales force, i.e. all the people, resources and techniques involved in your sales performance.
• The nature of your sales channels (physical or online store, marketplace, etc.).
• Seasonality, i.e. the fluctuation of customer demand and sales at different times of the year.
• A forecast of your future objectives and strategies (launch or discontinuation of an offer)
• Your acquisition channels (advertising, search engine optimization, social networks, etc.) and your conversion rates at each stage of the sales tunnel.

As you can see, calculating sales forecasts is THE key to setting clear objectives and adjusting your strategy. By choosing the right methods and tools, you put all the chances on your side to boost your company's growth.

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