Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

5.2.1 Demand Management: Bid and Customer Blanket Order Processing and Demand Forecasting

Intended learning outcomes: Describe demand management, customer bid, order success probability and customer blanket order. Present some aspects of demand forecasting.

Demand management is, according to [ASCM22], the function of recognizing all demands for goods and services to support the marketplace.

According to Figure, this task comprises — among others — the following part task and processes of long, middle, and short-term planning (see Section 5.1):

  • Bid and blanket order processing
  • Demand planning and forecasting
  • Order entry and order configuration

A customer order is a deterministic independent demand. Quantity, due date, and other facts are completely known. (Customer) order service, according to [ASCM22], encompasses order receiving, entry[note 509], configuration, and confirmation of orders from customers, distribution centers, and interplant operations[note 510].

Order service is responsible for responding to customer inquiries during delivery lead time as well as for interacting with master scheduling regarding the availability of products. One important factor when scheduling customer demand is the organization’s distribution network structure. See Section 4.1.4.

What precedes the status of order confirmation of a customer order are — in the case of investment goods — various bid statuses.

A customer bid is a quotation, a statement of price, terms of sale, and description of goods or services given to a customer in response to a customer request for quotations.

The bid statuses are of differing duration, during which requirements are defined more and more precisely. In this case, the requirements are not absolutely definitive, but they will guide the planning of production and procurement. For customer order produc­tion (often single-item produc­tion), there is a certain probability that a bid will lead to an order as it is already defined at this point. The simplest technique of including bids in planning is to multiply the requirements by the probability of their success.

Order success probability devalues the demand defined by the customer bid. Only demand reduced in this way will be planned as independent demand for resource requirements planning.

Continuous adaptation of order success probability to real conditions, e.g., by continuous measuring of the order success rate, with decreasing temporal range of planning, is crucial to this simple technique. In addition, bids must be confirmed, or removed, early enough that definitive orders can be scheduled even if bottlenecks occur in procurement. For this, an expiration date must be assigned to the order, from which time onward the confirmed delivery date may be postponed or the order termed inactive. This function can be automated in an IT-supported system.

If bottlenecks occur in procurement or production, it is difficult to set a reliable delivery date for a bid that is to be planned. If many other bids have been planned, a completion date that has been calculated by placing the new bid in this limited resource situation is only a probable completion date. This date needs to be complemented by a latest (maximum) completion date, calculated on the assumption that all bids, or at least the majority of them, will be realized. To do this, the portion of demand not reserved for each bid on the basis of order success probability is totaled up and used in the resource requirements management of capacity. The lead time for required but not available components yields the “maximum” completion date for the new bid. While this method, described here only in its rudiments, involves a great deal of complex calculating in detailed planning, it is often an appropriate technique for rough-cut planning with acceptable levels of calculation.

A customer bid often concerns and results in a customer blanket order. Here, the delivery quantity is often set by a long-term minimum and maximum blanket order quantity for a particular period of time.

If the minimum blanket order quantity is zero, it is merely a forecast.

  • Uncertain quantities in a blanket order can be handled in a way similar to bids, that is, through continuous precision-tuning of their success probability with decreasing temporal range. In short-term planning, a certain quantity is ordered through a short-range blanket order for a defined period of time, but exactly when and in what breakdown the blanket releases will be made is left open.
  • For uncertain dates, some additional information is usually available. This informa­tion will express, for example, the quantities that will be called for in the future, together with an estimate of the deviation factor in percent. These values allow partial demand to be distributed along the time axis. Here again it is important to continue to adapt the break­down of the demand to reality or at least to the customer’s increasingly precise requests. For more on blanket orders, see Section 5.2.4.

Demand forecasting is, according to Section 1.1.2, the process that estimates the future demand.

Demand forecasting is a necessary process as soon as items upstream from the (customer) order penetration point (OPP) must be procured or produced (see Section 4.4.3).

Demand forecasting is a necessary process as soon as items upstream from the (customer) order penetration point (OPP) must be procured or produced (see Section 4.4.3). The need for forecasting varies throughout the course of time and depending on the industry, market, and product. Examples of buyers’ markets with a great need for forecasting include trade in consumer goods or the provision of components needed for a service or for investment goods. Before a customer places a definitive order, for example, single parts of a machine or “frameworks” containing data descriptions and programs for a software product must have already been produced or procured.

There are simple techniques of forecasting, including those based on judgment and intuition, but there are also some very complicated techniques. Chapter 10 presents many of them.

Course section 5.2: Subsections and their intended learning outcomes