Demand Forecasting refers to the process where historical sales data is used to build an estimate of an expected customer demand forecast. For all companies, demand forecasting allows you to develop an estimate of the amount of goods and services that customers will purchase in the upcoming future. Vital business pillars such as like profit margins, cash flow, turnover, capital expenditures, risk assessment, mitigation plans, and capacity planning all depend on demand forecasting.
6 Types Of Demand Forecasting
There’s a few different demand forecasting types you need to become familiar with, each differing in the amount of detail, time span considered and market scope.
Let’s take a look at the major types of demand forecasting. These include;
- Passive Demand Forecasting: Passive Demand Forecasting is carried out for stable businesses with very conservative growth plans. Simple extrapolations of historical data is carried out with minimal assumptions. This is a rare type of forecasting limited to small and local businesses.
- Active Demand Forecasting: Active Demand Forecasting is carried out for scaling and diversifying businesses with aggressive growth plans in terms of marketing activities, product portfolio expansion and consideration of competitor activities and external economic environment.
- Short-term Demand Forecasting: Short-term Demand Forecasting is carried out for a shorter term period of 3 months to 12 months. In the short term, the seasonal pattern of demand and the effect of tactical decisions on the customer demand are taken into consideration.
- Medium to long-term Demand Forecasting: Medium to long-term Demand Forecasting is typically carried out for more than 12 months to 24 months in advance (36-48 months in certain businesses). Long-term Forecasting drives the business strategy planning, sales and marketing planning, financial planning, capacity planning, capital expenditure, etc.
- External macro level Demand Forecasting: This type of Forecasting deals with the broader market movements which depend on the macroeconomic environment. External Forecasting is carried out for evaluating the strategic objectives of a business like product portfolio expansion, entering new customer segments, technological disruptions, a paradigm shift in consumer behavior and risk mitigation strategies.
- Internal business level Demand Forecasting: As the name suggests, this type of Forecasting deals with internal operations of the business such as product category, sales division, financial division, and manufacturing group. This includes annual sales forecast, estimation of COGS, net profit margin, cash flow, etc.
Demand Forecasting Examples
Let’s do a demand forecast example, we’ll say we’re suppose to sell 300, 350, 400 units of product Z in the month of October, November, and December. Now, it’s fair to say we should have demand for at least 300 units of product Z for the month of January if things remain the same.
We can also use a more detailed forecasting example. A furniture manufacturer, they want to refer to the last 12 months of actual sales for each specific furniture type, size, and color; and based on the expected growth, they can forecasts the short-term demand for the next 12 month for purchases, production and inventory planning.
Why Demand Forecasting Is So Important
Demand should always play a key role when it comes to making important decisions in your business. In competitive market conditions, there is a need to take correct decision and make planning for future events related to business like a sale, production, etc. The effectiveness of a decision taken by business managers depends upon the accuracy of the decision taken by them.
Demand is one of the most important factors to help a company achieve its goals. Many key business decisions depend on demand like production, sales, staff requirement, etc. Forecasting is not an optional strategy or tactic, but rather it’s a necessity for your company.
Demand forecasting can also help you reduce risk and proper risk management is always important. It also can help you with production, a good forecasting expert can help you plan to achieve your business goals.
While we don’t discuss it much, forecasting is pivotal for your accounting. A good forecast can help in production planning, process selection, capacity planning, facility layout planning, and inventory management.
Demand forecasting provides reasonable data for the organization’s capital investment and expansion decision. It also provides a way for the formulation of suitable pricing and advertisement strategies.
The reason demand forecasting is significance is because it can help you:
- Planning and hitting business objectives
- Preparing the company’s budget
- Making crucial business decisions
- Evaluating how your business is performing
Now, it’s important to note that forecasting is not completely full of proof and correct. Even so, it can help you evaluate various factors which affect demand and enables management staff to know about various forces relevant to the study of demand behavior.
Based on the demand forecast, strategic and long-range plans of a business like budgeting, financial planning, sales and marketing plans, capacity planning, risk assessment and mitigation plans are formulated. Even shorter based tactical plans such as pre-building, make-to-stock, make-to-order, contract manufacturing, supply planning, and network balancing are all execution based.
Demand Forecasting Methods
One of the most important steps of the Demand Forecasting process is the selection of the appropriate method for Demand Forecasting. Demand can be forecasted using (A) Qualitative methods or (B) Quantitative methods as explained below:
The Delphi Technique: This forecasting technique requires a panel of experts to be appointed to produce a demand forecast. Each expert assigned would need to build a forecast for a specific segment. Once the initial forecasting round is complete, each expert would then read out their forecast. It’s an interesting concept as each expert can be influenced by what other experts are forecasting. This consequent forecast is made by all experts and this process is repeated until everyone involved can reach a near consensus scenario.
Sales Force Opinion: The sales manager asks for inputs of expected demand from each salesperson in their team. Each salesperson evaluates their respective region and product categories and provides their individual customer demand. Eventually, the sales manager aggregates all the demands and generates the final version of demand forecast after management’s judgment.
Market Research: In market research technique, customer-specific surveys are deployed to generate potential demand. Such surveys are generally in the form of questionnaires that directly seeks personal, demographic, preference and economic information from end customers. Since this type of research is on a random sampling basis, care needs to be exercised in terms of the survey regions, locations, and demographics of the end customer. This type of method could be beneficial for products that have little to no demand history.
Trend projection method: Trend projection method can be effectively deployed for businesses with a large sales data history of typically more than 18 to 24 months. This historical data generates a “time series” which represents the past sales and projected demand for a specific product category under normal conditions by a graphical plotting method or the least square method.
Barometric technique: Barometric technique of demand forecasting is based on the principle of recording events in the present to predict the future. In the demand forecasting process, this is accomplished by analyzing the statistical and economic indicators. Generally, forecasters deploy statistical analysis like leading series, concurrent series or lagging series to generate the Demand Forecast.
Econometric forecasting technique: Econometric forecasting utilizes autoregressive integrated moving-average and complex mathematical equations, to establish relationships between demand and factors that influence the demand. An equation is derived and fine-tuned to ensure a reliable historical representation. Finally, the projected values of the influencing variables are inserted into the equation to generate a forecast.