Types of Demand Forecasting Methods

1/27/21 12:00 AM

Demand forecasting is the process of predicting what the demand for certain products will be in the future. It identifies what both current and future customers will want to buy and tells manufacturing facilities what they should actually produce.

Ideally, manufacturing companies want to be able to accurately predict customer demands so that they can produce the right amount of products. Producing too little items leads to stock shortages and can negatively impact customer relationships. On the other hand, having too much inventory is costly and can lead to having excess stock if the items become obsolete.


Along with knowing the quantities manufacturing companies should produce, demand forecasting can help set the price for those items and determine which markets would be best suited for the company.

Methods of Demand Forecasting

Demand forecasting allows manufacturing companies to gain insight into what their consumer needs through a variety of forecasting methods. These methods include: predictive analysis, conjoint analysis, client intent surveys, and the Delphi Method of forecasting.

Predictive Analytics

Predictive analysis goes further than traditional demand forecasting by evaluating the reason why people buy. The process uses mathematical principles to predict consumer behavior by using current and historic data.

Like traditional forecasting, predictive analysis will determine what the future demand will be but will also identify the reason for this. The overall method depends on research on the company’s products and how consumers have interacted with it in the past. This analysis is then used as a framework to identify the drivers to consumer purchases and provide insights into why these individuals buy.

While this method can be used beyond demand forecasting, it remains limited as it is based on past data and does not account for unforeseen changes/external factors. 

Advanced planning and scheduling software (APS) systems may have simulation or predictive analytics capabilities. These robust demand planning and demand forecasting components can predict with a considerable certainty to allow schedules, production plans, inventory and staffing to all be secured and allocated for production. 

Conjoint Analysis

Conjoint analysis uses surveys to obtain consumer input about the most favorable attributes of their products. These surveys ask consumers how they would use and respond to certain product attributes.

When selling a product, it is important to recognize the most important attributes that consumers are considering when buying. Trade-offs happen with all goods, so it is important for companies to identify why consumers are choosing certain products over others and which features they value most.

Conjoint analysis can help the company beyond demand forecasting by identifying the products that are most attractive to consumers. This is done by having consumers rank their preferences for features which is then translated by an analysis into a report that shows what customers prefer. The technique provides a forecast of the market preferences to explore market potential for new products or features.


We’re able to make strategic decisions that improve operations. We can proactively prepare for anticipated increases or slowdowns in demand.



Client Intent Surveys

With a buyer’s intentions survey, it asks what the consumer is planning on purchasing in the future. This technique is used to understand what motivates the customer to actually buy a product they are interested in.

These surveys are usually included before entering a company’s website or accessing certain content such as a video. The survey may include questions asking consumers on a scale of 0 to 10 whether or not they are contemplating purchasing a trampoline. 

If the consumers are answering with a high probability, then this can give the company the analysis it needs to possibly go forward on a product that the company is considering. It is important to note that client intent surveys can help predict the likelihood of purchasing but that it does not always reflect actual purchasing behavior. 

However, research shows that purchase intent is a better predictor of actual purchase for existing vs. new products, for durable products, and for short-term rather than long-term forecasting horizons. This technique remains a useful component of demand forecasting that considers inputs from those who will actually buy the product - the customers.

Delphi Method

The Delphi method was developed with the assumption that forecasts from a group are generally more accurate than forecasts from individuals. As such, this method uses a panel of experts that provide their forecasts and justifications anonymously.

These forecasts are then summarized and shared with the rest of the group to allow each individual expert to adjust their forecasts. This process is repeated multiple times until a consensus is achieved. Consensus is determined by non-significant modifications to their answers.

When executed properly, the Delphi method can provide an accurate forecast that may not have been achieved by any individual person on the team. The downside of this method is that it can be very time-consuming and depends on the facilitator’s expertise to identify the important information of each forecast.


Advanced Planning and Scheduling (APS) Software

Advanced Planning and Scheduling Softwares have become a must for modern-day manufacturing operations as customer demand for increased product assortment, fast delivery, and downward cost pressures become prevalent. These systems help planners save time while providing greater agility in updating ever-changing priorities, production schedules, and inventory plans. APS Systems can be quickly integrated with an ERP/MRP software to fill the gaps where these systems lack planning and scheduling flexibility, accuracy, and efficiency.


With PlanetTogether APS you can:

  • Create optimized schedules that balance production efficiency and delivery performance
  • Maximize throughput on bottleneck resources to increase revenue
  • Synchronize supply with demand to reduce inventories
  • Provide company-wide visibility to resource capacity
  • Enable scenario data-driven decision making

The implementation of an Advanced Planning and Scheduling (APS) Software will take your manufacturing operations to the next level of production efficiency by taking advantage of the operational data you already possess in your ERP system. APS is a step in the right direction of efficiency and lean manufacturing production enhancement. Try out a free trial or demo!

Related Demand Forecasting Video 

 APS Resources

Topics: Factory Scheduling, Advanced Planning and Scheduling, Material, capacity planning, production planning, finite capacity, project management, supply chain, Forecasting, opportunity, scheduling, JIT, Demand Forecasting


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