The Top Methods to Forecast Demand
Demand forecasting is a crucial component of the demand planning and sales forecasting processes that helps businesses with planning sales and customer demand expected in the future. There are a variety of demand forecasting methods to consider, whether a business is releasing a new product or attempting to predict future consequences of business expansion.
There are both quantitative methods and qualitative methods of demand forecasting available for business professionals to use. While quantitative methods heavily rely on data available for analysis, qualitative methods are largely based on opinion.
While some businesses chose a single forecasting method for their demand planning and sales forecasting processes, others choose a combination of methods. Using a combination of different forecasting methods can increase the probability of businesses to accurately predict future demand. Top methods of demand forecasting include-
The market research demand forecasting technique uses customer surveys and questionnaires in order to predict future demand. This forecasting technique is ideal for businesses that do not have historical sales data available such as when a new product is released.
Data supplied from market research initiatives can assist to identify economic indicators and customer's personal information. This data is invaluable in planning sales or marketing campaigns that target a specific demographic of customers.
Preliminary market research can also be used before new products are created en masse to identify potential issues the product development team overlooked. The ability to take corrective action or optimize a new product before it is released can save a business massive sums of money.
The trend projection forecasting method is great for businesses with big data available for analysis. Historical sales data should span at least 1.5-2 years prior to when the trend projection forecasting method is undertaken.
Historical data is used to generate a time series that projects future demand and future sales based on past sales. The time series is used when a least square or graphical plotting method is performed.
The econometric forecasting technique uses a moving average alongside other variables to better understand the relationships between the factors that influence demand and the demand itself. Due to the mathematical complexity of the econometric forecasting technique, it may not be an ideal option for inexperienced forecasters.
However, econometric forecasting techniques use big data and economic indicators advantageously and can be very accurate if used properly.
The sales force opinion forecasting technique has a heavy human bias. This technique requests feedback directly from sales representatives, asking them to estimate future sales and predict future demand.
Managerial judgement is an important component of efficient sales force opinion forecasting. The combination of sales representative feedback and managerial judgment creates the finished demand forecast.
Alike the sales force opinion forecasting technique, the Delphi technique has a strong human bias. The Delphi technique primarily relies on expert opinion and eventually a unified expert consensus.
At the beginning of the Delphi technique, experts are assigned specific segments to create a forecast for. As the experts disclose their forecast results to one another, they work together until they reach a final conclusion.
One advantage of the Delphi technique is the anonymity it provides, ideally decreasing bias. However, anonymity can also be burdensome as it limits collaborative potential between businesses and experts.
The barometric technique analyzes economic indicators and statistical indicators in order to predict future events. The leading series, lagging series, and concurrent series are commonly used when creating the demand forecast.
While not ideal for long term forecasting, the barometric method is great to consider for short term forecasting initiatives.
The regression analysis demand forecasting method attempts to establish the relationship between dependent and independent variables. Regression analysis helps to make sure that assumptions are proven and not accepted blindly or due to human bias.
Regression analysis is a great tool for demand planning and financial planning processes, providing businesses with a more concrete basis from which to make important decisions.
- Demand forecasts are commonly used during sales forecasting and demand planning processes.
- Forecasting demand accurately helps businesses to be as successful and profitable as possible.
- Forecasting model examples range from the sales force opinion technique to the trend projection method.