The Criteria for Good Demand Forecasting

the criteria for good demand forecasting

Top Criteria for Effective Demand Forecasting

Demand forecasting is the process used to predict future customer demand based on historical sales data. An accurate forecast can make the difference between a business thriving or potentially not surviving the fiscal year.

The results of demand forecasting are used for a wide variety of business processes ranging from capacity planning to market research initiatives. The criteria for good demand forecasting include-

1. Accuracy

A demand forecast that is not accurate is detrimental to a business's short term and long term success. A common cause of inaccurate forecasting occurs when the data available and used for demand forecasting is inaccurate or incomplete.

Regardless of which forecasting technique is utilized, an accurate forecast must generate a definitive value. Instead of a broad conclusion predicting that sales will increase, a specific percentage should be agreed upon and reported.

2. Replicability

Significant benefits of using a good forecasting method are the replicability and adaptability potential they offer. The likelihood of generating an accurate forecast is greatly improved when the same forecasting model is used long term.

Business professionals can learn from any mistakes that occurred during a previous demand forecast in order to increase the accuracy of upcoming forecasts. When business professionals need to constantly acclimate to different forecasting methods a lot of time, money, and energy are used.

Identifying and continually using a good forecasting method or combination of forecasting methods that work effectively is both easier and more economical.

3. Flexibility

In the ever changing global market, good forecasting must be flexible and revisable. Both short term and long term rigidity can deter businesses from important decision making and necessary corrective actions.

For example, a supply chain issue could result in an unpredicted delay in shipments of raw materials. Or, a competitor could release a new product that completely skews the accuracy of a previous demand forecast.

One great technique to combat inflexibility is making sure to always factor in risk management to all forecasting methods used. Thankfully, good forecasting techniques generally contain at least some level of risk assessment inherently.

However, it is never a bad idea to incorporate additional risk management efforts. Predicting future potential obstacles help businesses to not only avoid devastating unforeseen problems but also correct them more swiftly should they occur.

4. Economical

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Demand forecasting is a time consuming and labor intensive process. Labor costs can quickly add up, especially when heavier statistical methods that require intensive data analysis are used.

Keep a resource optimization mindset when deciding which forecasting method or methods to use. The benefits that demand forecasting will provide should always outweigh the initial investment that a business incurs.

Although it is preferable to use the same forecasting technique or combination of forecasting techniques long term to increase familiarity and expertise if a forecasting model is consistently unsuccessful business professionals should research alternative forecasting methods available.

5. Accessibility

Complex statistical methods of demand forecasting may be intimidating to interpret. However, for a forecasting technique to be sustainable long term it must be accessible to a business's staff members.

Although it is not necessary for every employee to understand the intricacies of a forecasting method on an expert level, the concluding data available should be easily digestible. Make sure to provide employees with a summary of the information obtained during the demand forecast using accessible language whenever possible.

Additionally, clearly communicate to team members that any information that is unclear can be explained by a designated employee who is knowledgeable about the demand forecasting process at your business. When everyone working towards business objectives is on the same page the entire company benefits.

Key Takeaways

  • Demand forecasting uses historical data to help businesses predict both future demand and anticipated sales. Demand forecasts provide data that can be used for a wide range of business processes including the launching of new products and production planning initiatives.
  • Replicability allows business professionals to continually hone their forecasting capability over a long term time period and become comfortable using a specific forecasting technique repeatedly.
  • Rigidity is a significant problem for demand forecasting, forecasting techniques should be flexible and adaptable to unforeseen changes. Additionally, the benefit of demand forecasting should outweigh the investment of time and money a business incurs while performing it.
  • Data produced by demand forecasts should be accessible to employees. If an employee does not understand crucial forecasting conclusions, a staff member should be available to assist them.