Author: Jim Riley Last updated: Sunday 23 September, 2012
Sales forecasting is a difficult area of management. Most managers believe
they are good at forecasting. However, forecasts made usually turn out to
be wrong! Marketers argue about whether sales forecasting is a science or
an art. The short answer is that it is a bit of both.
Reasons for undertaking sales forecasts
Businesses are forced to look well ahead in order to plan their investments,
launch new products, decide when to close or withdraw products and so on.
The sales forecasting process is a critical one for most businesses. Key decisions
that are derived from a sales forecast include:
- Employment levels required
- Promotional mix
- Investment in production capacity
Types of forecasting
There are two major types of forecasting, which can be broadly described
as macro and micro:
Macro forecasting is concerned with forecasting markets
in total. This is about determining the existing level of Market Demand and
considering what will happen to market demand in the future.
Micro forecasting is concerned with detailed unit sales
forecasts. This is about determining a product’s market share in a particular
industry and considering what will happen to that market share in the future.
The selection of which type of forecasting to use depends on several factors:
(1) The degree of accuracy required – if the decisions
that are to be made on the basis of the sales forecast have high risks attached
to them, then it stands to reason that the forecast should be prepared as
accurately as possible. However, this involves more cost
(2) The availability of data and information - in some markets
there is a wealth of available sales information (e.g. clothing retail, food
retailing, holidays); in others it is hard to find reliable, up-to-date information
(3) The time horizon that the sales forecast is intended to cover.
For example, are we forecasting next weeks’ sales, or are we trying
to forecast what will happen to the overall size of the market in the next
(4) The position of the products in its life cycle. For
example, for products at the “introductory” stage of the product
life cycle, less sales data and information may be available than for products
at the “maturity” stage when time series can be a useful forecasting
Creating the Sales Forecast for a Product
The first stage in creating the sales forecast is to estimate Market
Market Demand for a product is the total volume that would be
bought by a defined customer group, in a defined geographical area, in a defined
time period, in a given marketing environment. This is sometimes referred
to as the Market Demand Curve.
For example, consider the UK Overseas Mass Market Package Holiday Industry.
What is Market Demand?
Using the definition above, market demand can be defined as:
Defined Customer Group: Customers Who Buy an Air-Inclusive
Package Holiday Defined Geographical Area: Customers in the UK Defined Time Period: A calendar year Defined Marketing Environment: Strong consumer spending in
the UK but overseas holidays affected by concerns over international terrorism
For example, the market demand could be calculated as follows:
Number of Customers in the UK: 17.5 million per calendar
year Average Selling Price per Holiday: £450 Estimate of market demand: £7.9 billion (customers
x average price)
Stage two in the forecast is to estimate Company Demand
Company demand is the company’s share of market demand.
This can be expressed as a formula:
Company Demand = Market Demand v Company’s Market Share
For example, taking our package holiday market example; the company demand
for First Choice Holidays in this market can be calculated as follows:
First Choice Holidays Demand = £7.9 billion x 15% Market Share = £1.2
A company’s share of market demand depends on how its products, services,
prices, brands and so on are perceived relative to the competitors. All other
things being equal, the company’s market share will depend on the size
and effectiveness of its marketing spending relative to competitors.
Step Three is then to develop the Sales Forecast
The Sales Forecast is the expected level of company sales based on a chosen
marketing plan and an assumed marketing environment.
Note that the Sales Forecast is not necessarily the same as a “sales
target” or a “sales budget”.
A sales target (or goal) is set for the sales force as a
way of defining and encouraging sales effort. Sales targets are often set
some way higher than estimated sales to “stretch” the efforts
of the sales force.
A sales budget is a more conservative estimate of the expected
volume of sales. It is primarily used for making current purchasing, production
and cash-flow decisions. Sales budgets need to take into account the risks
involved in sales forecasting. They are, therefore, generally set lower than
the sales forecast.
Obtaining information on existing market demand
As a starting point for estimating market demand, a company needs to know
the actual industry sales taking place in the market. This involves identifying
its competitors and estimating their sales.
An industry trade association will often collect and publish (sometime only
to members) total industry sales, although rarely listing individual company
sales separately. By using this information, each company can evaluate its
performance against the whole market.
This is an important piece of analysis. Say, for example, that Company A
has sales that are rising at 10% per year. However, it finds out that overall
industry sales are rising by 15% per year. This must mean that Company A is
losing market share – its relative standing in the industry.
Another way to estimate sales is to buy reports from a marketing research
firm such as AC Neilsen, Mintel etc. These are usually good sources of information
for consumer markets – where retail sales can be tracked in great detail
at the point of sale. Such sources are less useful in industrial markets which
usually rely on distributors.
Estimating Future Demand
So far we have identified how a company can determine the current position:
Current Company Demand = Current Market Demand x Current Market Share
How can future market demand and company demand be forecast?
Very few products or services lend themselves to easy forecasting . These
tend to involve a product whose absolute level or trend of sales is fairly
constant and where competition is either non-existent (e.g. monopolies such
as public utilities) or stable (pure oligopolies). In most markets, total
demand and company demand are not stable – which makes good sales forecasting
a critical success factor.
A common method of preparing a sales forecast has three stages:
(1) Prepare a macroeconomic forecast – what will happen
to overall economic activity in the relevant economies in which a product
is to be sold.
(2) Prepare an industry sales forecast – what will
happen to overall sales in an industry based on the issues that influence
the macroeconomic forecast;
(3) Prepare a company sales forecast – based on what
management expect to happen to the company’s market share
Sales forecasts can be based on three types of information:
(1) What customers say about their intentions to continue
buying products in the industry
(2) What customers are actually doing in the market
(3) What customers have done in the past in the market
There are many market research businesses that undertake surveys of customer
intentions – and sell this information to businesses that need the data
for sales forecasting purposes. The value of a customer intention survey increases
when there are a relatively small number of customers, the cost of reaching
them is small, and they have clear intentions. An alternative way of measuring
customer intentions is to sample the opinions of the sales force or to consult
Time Series Analysis
Many businesses prepare their sales forecast on the basis of past sales.
Time series analysis involves breaking past sales down into four components:
(1) The trend: are sales growing, “flat-lining” or in decline?
(2) Seasonal or cyclical factors. Sales are affected by swings in general
economic activity (e.g. increases in the disposable income of consumers may
lead to increase in sales for products in a particular industry). Seasonal
and cyclical factors occur in a regular pattern;
(3) Erratic events; these include strikes, fashion fads, war scares and other
disturbances to the market which need to be isolated from past sales data
in order to be able to identify the more normal pattern of sales
(4) Responses: the results of particular measures that have been taken to
increase sales (e.g. a major new advertising campaign)
Using time series analysis to prepare an effective sales forecast requires
Smooth out the erratic factors (e.g. by using a moving average)
Adjust for seasonal variation
Identify and estimate the effect of specific marketing responses