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Understanding Demand Forecasting: Decoded

Data Analytics has led to scientific means to obtain solutions to all pertinent questions an organization has. In that, demand forecasting is an exciting field of study. It helps organizations plan for future demand based on past and current data. This impacts various spheres of an organization – Inventory planning, Manufacturing planning, Manpower planning, etc. In today’s day and age, organizations that base their decisions on data wins. Demand forecasting is an important tool that can help organizations be effective and efficient.

Organizations can use the following steps to set up a process for demand forecasting.

  • The first step is to set a clear purpose as to why the exercise is being done. It should have details of costing & pricing. And factors that affect the cost include inventory levels, Quality of finish, etc.
  • Understanding the market for the product. Each product has its business cycle. For example, capital goods have a longer business cycle, whereas FMCG products have a smaller business cycle.
  • Having a short-term and a long-term vision is the next step. Short-term is usually between 3-6 months, and long-term is between 2-4 years. Long-term exercise is complicated and involves brainstorming at a broader level and industry trends. This exercise is critical.
  • Choosing the method to evaluate demand is the next step. There are various qualitative and quantitative methods to evaluate demand. Organizations can choose the method that best suits their business.
  • Setting the process for collecting and cleaning data is the next step. The research data is of two types – Primary & Secondary. Primary data are the ones that organizations collect by themselves. Secondary data are the ones that are available in any public forum. For example, a simple google search and collecting data is secondary data.
  • The last step is analyzing and fetching actionable insights. All the calculations and evaluations must lead to actionable insights, which is extremely important. Data with no insights are of no use.

This exercise is an ongoing process. The organization must compare the forecasted demand and actual sales at specific intervals. It helps in tweaking the model and making it more efficient.

There are various methods to do demand forecasting. But broadly, it is of two types:

  1. Qualitative method
  2. Quantitative method

Qualitative method

Some of the techniques which are followed here are:

  • Delphi
  • Salesman opinion
  • Market research

As the name suggests, this technique involves discussing with someone who has knowledge of the product and its market and forecasting based on that. 

In the Delphi technique, the forecaster can take opinions from the experts in the field. Usually, the experts are from top management with the market vision. This lets the forecaster understand the trends of the future. This could be helpful for long-term forecasting.

A Salesman has ears to the ground. He is someone who understands problems at the ground level. Talking to them and forecasting based on that could help the forecaster gauge the reality.

Market research helps the forecaster understand the customers and their preferences. This can also help the organizations develop products that might suit the market.

Quantitative method

As the name suggests, these are heavily dependent on statistical models and past data without any opinions. Some of the techniques here are:

  • Projecting trends by graphical plotting or the least square method
  • The barometric method helps forecasters know the lead indicator and lag indicator and predict demand accurately based on that
  • The econometric forecasting technique helps forecasters understand the broader economy and its impact on the demand for the product.

Over time demand forecasting can be extremely helpful for organizations to improve efficiency and cut costs. It’s always these scientific methods that aid organizations win in the market.