6 Types of Demand Forecasting
Demand forecasting is the process used to predict future customer demand based on historical sales data. Forecast accuracy influences a wide variety of business operations ranging from inventory management to supply chain management.
Depending on a business's needs and objectives, a single demand forecasting model or a combination of multiple forecasting methods may be used. Common types of demand forecasting include-
1. Passive Demand Forecasting
Generally considered the simplest demand forecasting type, passive demand forecasting uses historical data to predict future customer demand. Passive demand forecasting is a great fit for businesses with excellent sales data and a focus on maintaining stability rather than pursuing growth.
2. Active Demand Forecasting
Active demand forecasting utilizes market research and other external factors in order to predict future customer demand. As sales data is not focal for this forecasting type, active demand forecasting is ideal for newly established businesses or companies that are currently in a growth phase.
3. Short Term Projections
Short term demand forecasting only estimates customer demand for the upcoming three months to one year. Short term demand forecasting applies real time sales data to adjust customer demand projections that may otherwise be outdated if a long term projection was previously used.
4. Long Term Projections
Long term demand forecasting predicts the next one year to four years of customer demand. Long term forecasting is primarily based on market research and sales data.
Experts advise that this forecasting type should be viewed as more of a general roadmap because projections are likely to change over such a long period of time.
5. Internal Business Forecasting
Internal business forecasting helps businesses understand if their capacity planning is appropriate for anticipated customer demand. Providing a more comprehensive review of business operations, internal business forecasting assists with identifying improvement areas in order to optimize available resources.
6. External Macro Forecasting
External macro forecasting is an excellent supply chain management tool. Focusing on external factors that influence business operations, external macro forecasting identifies potential trends and how those trends may influence company objectives.
Demand Forecasting Models
Demand forecasting models are generally categorized as either quantitative methods and qualitative methods. Qualitative methods are useful when big data is lacking, for instance when new products are developed and sales data is nonexistent.
Quantitative methods focus on big data utilizing tools like machine learning to predict future customer demand. Qualitative and quantitative methods of demand forecasting models include-
1. Trend projection
Generally considered the simplest and most streamlined forecasting model available, trend projection applies past sales data to future sales predictions. To maintain forecasting accuracy long term, business professionals should update their trend projections in real time when unexpected and influential changes occur.
An unexpected change that would necessitate a trend projection update could include a shoutout by a prominent social media influencer or a supply chain management mishap.
2. Sales Force Composite
Forecasting demand based on sales team feedback, sales force composite provides unique insight on customer desires and competitors. The sales force composite forecasting process necessitates extensive departmental collaboration including managers and supervisors.
Business professionals must factor in that the sales force composite method contains a substantial human bias. The sales force composite forecasting method is often used concurrently with quantitative methods for this reason.
3. Delphi Method
The Delphi technique uses external feedback to estimate future demand through surveys and questionnaires. The end objective of the Delphi forecasting model is a unified and informed consensus of experts.
4. Market Research
Market research forecasting is ideal for newly established companies that need to understand customer demand patterns without prior sales data available for analysis. Through the administration of customer feedback surveys, demand patterns are identified and future marketing initiatives can be customized to target specific demographics.
Market research may occur during a concentrated time period or be integrated as a consistent business process.
Big data intensive, econometrics depends on a complex analysis of external factors. Machine learning tools are especially helpful for econometrics due to the massive volume of data that needs to be processed.
The ultimate objective of econometrics is to identify relationships between external economic factors. For example, customers with an increase in their incomes may correlate with increased home renovations.
- The demand forecasting process helps businesses to predict future customer demand. The availability of accurate demand data influences many business operations.
- Passive demand forecasting uses historical data in order to predict future customer demand. Active demand forecasting uses external factors including market research techniques in order to predict future customer demand.
- Short term projections estimate only the imminent three months to one year of customer demand by using real-time sales data. Long term projections estimate the upcoming one year to four years of customer demand by using market research and historical sales data.