Whether you’re deciding how much of a given product you should order for the upcoming season or which products should feature in your next marketing campaign, understanding the current and future demand for your products makes your decisions that much easier. Rather than stabbing in the dark and risking reduced profits or stock-outs, Demand Forecasting enables you to reduce the uncertainty and risks commonly associated with decision-making.
We’ve written about Demand Forecasting before (it’s a topic that we’re pretty passionate about), but let’s break it down even further, let’s get conceptual.
For those who are unfamiliar with the term, Demand Forecasting describes a suite of analytical tools that aim to predict the demand for products and services for a certain period of time. If you need a deeper dive into the topic before continuing, head here (then come back). Or, if you feel you’re abreast of the subject, read on to find out about the components that make up Demand Forecasting, the kinds of data that you’ll need, and who Demand Forecasting is best-suited for.
Why do we need to forecast demand?
In the same way you use a weather forecast to decide whether (forgive the word play) you’ll plan a weekend beach-trip or grab an extra jacket on your way out the door, businesses use demand forecasts to make all kinds of decisions in both the long and short term. These forecasts rely on data from a range of sources, from expert opinions and historical sales data, to weather patterns, to upcoming events and holidays, and can be chosen and customised based on the needs and goals of your business.
Namely, the best type of forecasting to use depends on:
The time period you want to forecast for
The variables you want to consider in your forecast
The products you’re forecasting for
These factors are crucial in creating a forecast with the greatest accuracy and make up the core components of a Demand Forecasting method. Since they are vital for choosing the optimal forecasting method, let’s look at them in greater detail.
Length of Forecasts
The length of a forecast refers to how far in advance the forecast will be predicting demand for. Typically, the forecast is split into three categories: short, medium, and long-term. While the specific time period for each category isn’t well-defined, in a retail and manufacturing context, short- term forecasting anywhere between 0-3 months, medium term is 3-6 months, and longer term is 6+.
The length of forecasting you opt to use is crucial, and it’s not a case of one-size-fits-all. Different term lengths are better suited for different methods of demand forecasting and for achieving your specific goals and purposes.
Starting small, short-term forecasting can be used to make tactical and operational decisions. Short-term forecasts are often broken down further into weekly or daily forecasts, depending on the operational cadence within your business. In traditional businesses, quarterly forecasts are used to budget and plan sales, while monthly and weekly forecasts can be used for short-term capacity and inventory planning. On the daily and hourly level, these kinds of forecasts are often used for inventory deployment and planning of transportation and production.
Medium and long-term forecasts, on the other hand, are used for broader strategic decisions. These forecasts assist planning of sales, marketing, and capacity, or investment strategies - think machine replacement schedules and decisions involving production capacity.
The scope of your forecast refers to the types of variables that it takes into account, and is generally divided into internal and external Demand Forecasting. Internal forecasting, as you might guess, solely considers current business practices and takes into account variables such as:
Conversely, external (or macro) Demand Forecasting considers market conditions and external environmental factors when predicting demand for a company’s product or service. This level of forecasting is often used to drive internal business decisions, such as those relating to expansion and development of customer segments, and evaluating product portfolios.
While it might be surprising to some, the types of products you want to predict demand for can be a pretty important determiner of successful forecasting. Generally, your products will fall into one (or more) categories:
Capital goods - machinery, tools, raw materials, and even factories themselves.
Durable consumer goods - these products generally have ‘low-velocity’ demand, can be used more than once, and include everything from cars and furniture to electronics and clothing.
Non-durable (perishable) consumer goods - from food to medicine, this category includes anything that is consumed once.
The demand for capital goods is derived, meaning that it depends on the demand for the consumer goods they are used to produce, as well as the rate of industry growth, market size, and the level of capacity utilisation.
On the other hand, consumer goods - both durable and perishable - have direct demand since these products are meant for consumption by end-users. For durable goods, demand is influenced by their obsolescence rate and maintenance costs, as well as socioeconomic variables, whereas the demand for non-durable