Demand management and forecasting

All major problems in inventory management arise from failures in demand management and forecasting. One of the most serious problems in inventory management is the bullwhip effect: a small variation in customer demand causes a huge trouble in the upper echelons of the supply chain (distributors, wholesalers, producers).

Therefore, good demand management and forecasting is key to ensure a continuous and smooth logistics flow. In addition, a good demand forecasting will positively affect the long-term strategic management (choice of production sites, capacities, layout of the plants) and the medium-term tactical management (choice of suppliers, inventory and transport management, and distribution).

Demand management

The purpose of demand management is to determine the future demand, and to be able to provide that information appropriately to the people who can make timely decisions. A good demand management is an activity that adds value because it helps reduce lead times!

If demand management is done correctly, it helps meeting the customer needs more efficiently; it can influence the pattern of arrival of new order and reduce their variability; it can even propose appropriate lead times or suggest alternatives!

How to influence demand?

There are five known tactics for good demand management:

1. Promotions and discounts: when demand falls, we make promotions to attract new customers
2. Delivery lead times: if we do not have the product today, we guarantee a deadline to satisfy the customer
3. Alternate products: if the customer cannot wait, he can at least choose a similar product
4. Information: advertising and marketing, publicizing information to increase demand
5. Reservations: when demand is greater than supply, an alternative is to satisfy it based on reservation – as in hotels and restaurants, but also with electronics.

Passive demand management – demand forecasting

What we have seen so far in this post are ways of influencing and modifying demand – by actively managing it. Based on historical data and other factors, it is possible to passively manage demand, only predicting what will happen, without trying to influence what can occur. This is called demand forecasting.

If the forecasts are greater than the actual demand, we experience several costs. Products will be in stock and will not be sold. Production capacity and transportation were used to produce products that no one will buy. And employees were paid to produce items that nobody needed.

If forecasts are lower than the demand, we incur other types of costs. Customers came to buy our product but we were unable to satisfy them. We had a low level of service with small offer. The quality of service offered to consumers was low. Many of these costs are impossible to estimate.

There are several forecasting techniques, and the most advanced ones are based on applied mathematics, which can be very tricky. But that’s a subject for another post!

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