With the advent of thinking read and production initiatives just in time, it was even thought that activities related to demand forecasting had their days numbered. However, the need to trigger an entire supply chain for raw materials is a process that normally requires considerable time and hardly fits within the expectations of an increasingly demanding market. Given this scenario, there are still spaces in the market for areas of demand forecasting and consequently inventory management, and together with them ways to increase the company's operational productivity.
Figure 1 – Example of application of forecasting techniques in a real series
Source: ILOS
Leonardo Julianelli has already commented on the different forecasting techniques available and in which cases they are best applied. But the benefits of properly applying these techniques go far beyond reducing forecasting errors. Faced with a forecast with good accuracy, the purchasing area is able to place efficient orders for raw materials, which will not generate surplus and/or obsolete stocks, or unnecessary shipments, nor will they use expendable warehouse spaces. There are cases of simulations carried out showing that for every 1% decrease in the forecast error, the company's total stock of components also decreased by 1%, not counting the gains in material obsolescence and warehouse movement.
Another important consequence of a good forecast is the level of service offered to customers in the form of fill rate, or percentage of complete orders. Large companies typically deal with a high number of SKUs and it is not uncommon to find items out of stock at the time of a customer's order. At this point, the forecast collaborates in increasing the company's overall revenue, since sales lost due to lack of stock are hardly recovered in the face of the fiercely competitive market in which most companies are located.
In this way, considering the operational productivity of companies as a ratio between their revenue and their efforts (or, in a measurable way, their costs), demand forecasting contributes to the improvement of this indicator both in the numerator, increasing revenue with less lost sales, and in the denominator, lowering inventory, warehousing, and ordering costs.
And does your company have an efficient demand forecast area? Your overall productivity may be suffering from excessive forecasting errors.
References:
<http://www.scdigest.com/experts/Logility_17-05-11.php?cid=12384>
<https://ilos.com.br/web/impacto-da-crise-economica-na-demanda-como-melhorar-a-previsao-de-vendas/>
