What is Demand Forecasting?
Demand forecasting is the process of forecasting demand based on previous sales data and trends. Many companies rely on this technology to improve planning, efficiency and effectiveness. However, this is not a 100% forecast, but it can still help companies adjust their decisions in one direction and save a lot of unnecessary costs.
Types of Demand Forecasting
There are broadly two types of Demand Forecasting:
Short term Demand Forecasting
When the forecast demand is as long as 18 months, it is called short-term demand forecast. It is useful to extract information like costs associated in the short term and the price which may be charged. Generally, these estimates don’t go too wayward because in the short term not a lot of conditions change.
Long term Demand Forecasting
If the forecasted demand period exceeds 18 months, it is regarded as a long-term demand forecast. This is very useful for financial planning and budgeting decisions. The expected volatility of the conditions cannot be ignored. If so, the estimates may be too arbitrary. In the case of long-term demand forecasting, wrong estimates may bring a huge financial burden, because resorting to this method involves huge costs.
Example of Demand Forecasting
An automobile manufacturer of say company XYZ will always analyze past sales data and extract the necessary information out like what color has been demanded the most, how much was demanded and at what price the level of demand was maximum and so on. Now, when he continues to manufacture cars, he can predict demand based on the set color, function, cost and price. He will try to balance these elements in a combination from which he can expect maximum demand.
AI’s influence on Demand Forecasting
Traditionally, the volatility in the environment and conditions have been small so such estimates were done with ease via traditional methods of it but these days there are changes happening every other moment and if the estimate is not able to factor in these changes then the forecasts of Demand will go for a toss. AI has revolutionized it just as it has done to everything. Companies can improve upon the Demand estimates with the help of Advanced Analytics powered by AI. It helps in illustrating real-time changes that occur and provide real-time demand forecasts with adjusted changes. This makes companies take better decisions, save costs, energy, time, and increase revenue, project or product success rate.
There are a lot of examples, which highlight the need for accounting such changes. For example, in 1980-81, petroleum industry invested $500 bn on improving their infrastructure based on higher Demand forecasts but eventually lost billions when it didn’t happen and lots of companies halted their operations. On analysis, it was found that a lot of changes occurred during this time which were not taken into account while forecasting the Demand.
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