Supply Chain Frontiers issue #21. Read all articles in this issue
Each time a customer attempts to place an order is a defining moment for your company. It is at this point where all the supply planning and process execution come together to test your ability to deliver on the promises you have made to the buyer.
The key is to match supply and demand in an optimal way – which means performing the balancing act so that you meet corporate goals, such as sustained profitability, and satisfy customer demand. That requires you to set realistic customer expectations and accurate supply-demand planning. Optimized order promising requires the integration and coordination of supply-demand planning, customer service policies, business priorities, and segmentation strategies.
As industries move from make-to-stock manufacturing to build-to-order environments, order promising becomes harder yet more crucial. In a make-to-stock environment, a customer service rep determines whether a warehouse has the stock to fill the order and provides a quote based on the time it takes to pick, pack, and ship the goods. When the goods are out of stock, backorder management takes over, and reps try to assess when stock will be replenished, often quoting standard lead times on an ad hoc basis.
However, in a build-to-order environment, order promising is more complex. To fill an order, raw materials, components, and work-in-process inventories, as well as other supply resources, need to be brought together to produce finished products before they are packed and shipped. Assessing the time it takes to complete this process and give the customer a firm delivery date requires more careful and detailed planning of exactly how an order will be filled. Basically the planning needs to match up the order with the current and future supply resources needed to fill it.
Companies often use standard information to formulate delivery promises. For example some enterprises promise an order delivery time when an order is taken; others quote from a standard lead time list provided by the manufacturing organization. This type of manufacturing lead time quoting is misleading at best. The lead times are not based on real or even planned supply but are drawn from estimated guidelines that often reflect history, not today’s reality. The result: empty order promises based on inaccurate information.
Accurate order promising requires precise planning as well as the allocation or “pegging” of the resources needed for the order. This involves matching up available and future supply resources with demand to ensure that the resources are there when needed, thus reducing the need for expediting services and avoiding unmet delivery times.
However, even if very accurate promising is achieved, that does not necessarily translate into optimized supply and demand matching. Accurate order promising focuses only on meeting the customer’s delivery date; optimized order promising balances what the customer wants against the business goals of the company.
To achieve this balance certain customers and orders must receive preferential treatment. Optimal order promising requires that resources be supplied to those customers that are prepared to pay more for them or to the most strategically important customers. Too often orders from the largest customers are less profitable since these buyers invariably demand the biggest discounts and are resource-intensive. A better option might be to assign a higher preference to mid-sized customers that are growing faster and offer greater strategic potential.
In addition to prioritizing customers and orders in this way, companies need to evaluate order promising methods that are more complex than FIFO-based (first in, first out) options.
The most effective demand management approach aligns a company’s tactical supply-demand plans with its customer segmentation strategies, policies, and priorities. When these components are in step, the company is well prepared for its moment of truth – when a customer places an order and a fulfillment promise is made.
This article is based on a longer piece written by Larry Lapide, Director, Demand Management, MIT Center for Transportation & Logistics, to be published in the August 2007 issue of Supply Chain Strategy (see the news item Publishing Change for Supply Chain Strategy). For more information on CTL’s demand management research, contact Larry Lapide. For information on Supply Chain Strategy, contact the Editor Ken Cottrill.