Sales Forecasting Management

A Demand Management Approach

John T. Mentzer, Mark A. Moon

• Publisher: SAGE Publications, Inc
• Year: 2004
• ISBN:
  9781452238395
• Edition: 2
• Topic: Commerce
• Subtopic: Marketing
• Index: Marketing

Incorporating 25 years of sales forecasting management research with more than 400 companies, Sales Forecasting Management, Second Edition is the first text to truly integrate the theory and practice of sales forecasting management. This research includes the personal experiences of John T. Mentzer and Mark A. Moon in advising companies how to improve their sales forecasting management practices. Their program of research includes two major surveys of companies' sales forecasting practices, a two-year, in-depth study of sales forecasting management practices of 20 major companies, and an ongoing study of how to apply the findings from the two-year study to conducting sales forecasting audits of additional companies. The book provides comprehensive coverage of the techniques and applications of sales forecasting analysis, combined with a managerial focus to give managers and users of the sales forecasting function a clear understanding of the forecasting needs of all business functions.

1

Managing the Sales Forecasting Process

A company thought it had a forecasting problem. Many of its products were “slow movers, with spikes.” This is that daunting forecasting problem where 4 units sell one week, 3 the next, 5 the next, 10,000 the next, 3 the next, 6 the next, 20,000 the next, 1 the next, and so on. The spikes seem to be impossible to forecast (come in different-size spikes, at irregular times, not related to promotional events) and cause huge supply chain disruptions (expedited production and overtime or excessive inventory to meet the order; disruption to supplier operations resulting in higher procurement costs; or outsourcing the large orders resulting in lost margins).

This company manufactures numerous lighting products, but one of its slow movers with spikes is called a ballast. A ballast is a little transformer that takes electrical energy and converts it into an energy beam that passes through a fluorescent bulb. Without the ballast, a fluorescent bulb does not work.

One source of independent demand (defined later in this chapter) is the individual “do-it-yourselfer,” who replaces ballasts when they wear out at home. We now have a slow mover that sells one at a time as a replacement for ballasts already in use as they wear out. As this independent demand impacts the ordering policies of the various home supply stores in this company's supply chain, we get the fairly smooth, slow-moving component of derived demand (also defined later in this chapter) that the company experiences.

However, there is another source of independent demand for ballasts. The owners of a large office building decide to retrofit all the ballasts in their building. This is a return on investment (ROI) decision, because old ballasts use more electricity to light the fluorescent bulb than new ballasts do; that is, at some point, the cost of replacing the ballasts can be justified on the basis of the savings in electric bills. The office building in question has 10,000 ballasts that need to be replaced. When the building owner decides to retrofit the ballasts in the building (generally in connection with some other renovations), an electrical contractor is chosen to do the job, who then works with the other contractors involved in the renovation to decide when to start the ballast retrofitting part of the overall project, usually weeks or months in the future.

Unfortunately, the electrical contractor does not tell the company about the independent demand for 10,000 ballasts until the week before they are needed. Because it typically takes this company 3 weeks to fill an order of this size, the company incurs higher supply chain costs (expedited production costs, costs of higher inventory levels, spot market procurement costs, outsourcing production to higher cost alternatives) associated with expediting a large order, and the company makes far less (if any) money on this large order.

By recognizing that the demand impacting this company was derived demand (derived from the contractor's ordering policies), not independent demand, the company shifted its emphasis from forecasting the spikes in independent demand to demand planning for the derived demand. The result was a new demand planning policy in this supply chain; the company now offers contractors a 3% price discount on any orders in excess of 10,000 that are placed with the company five or more weeks before they are needed. This is a considerable savings for the contractors (3% off an order of 10,000 units, each of which typically costs more than $20!) and results in increased sales for the company.

More importantly, however, this company turned the unplanned large spikes hitting their operations systems into demand that could be planned weeks before needed. Under the new demand planning system, the company knows about spikes (that take 3 weeks to fill) 5 weeks in advance. This means that instead of expedited production, overtime, higher procurement costs, and unwanted, expensive outsourcing of production, the company can actually produce the products to fill the order anytime during the 5 week window, usually in slack production times. This “smoothing out” of the production scheduling system saves this company millions of dollars every year—all with increased market share among the contractors. This would not have been possible without the realization that the demand the company was trying to forecast was actually derived demand that could be planned.

INTRODUCTION

Much like the example just given, this book is about much more than just techniques. In fact, it is about more than just sales forecasting. It is about three management activities in any supply chain: demand management, demand planning, and sales forecasting management.

A DEMAND MANAGEMENT APPROACH TO SALES FORECASTING

The role of sales forecasting changes depending upon the position in the supply chain that a company occupies. Any supply chain has only one point of independent demand: the amount of product demanded (by time and location) by the end-use customer of the supply chain. Whether this end-use customer is a consumer shopping in a retail establishment or online (B2C), or a business buying products for consumption in the process of conducting its business operations (B2B), these end-use customers determine the true demand for the product that will flow through the supply chain.

The company in the supply chain that directly serves this end-use customer directly experiences this independent demand. All subsequent companies in the supply chain experience a demand that is tempered by the order fulfillment and purchasing policies of other companies in the supply chain. This second type of supply chain demand is called derived demand, because it is not the independent demand of the end-use customer, but rather a demand that is derived from what other companies in the supply chain do to meet their demand from their immediate customer (i.e., the company that orders from them).

The derived demand for one company is often the dependent demand of their customers. Dependent demand is the demand for the component parts that go into a product. Often called bill of materials (BOM) forecasting, this is usually demand that is dependent upon the demand for the product in which it is a component. The exception is when different amounts of a component part go into different versions of the product and is, thus, a special kind of forecasting called statistical BOM forecasting. For example, the manufacturer of a large telecommunications switch may have 50 different component parts that can go in each switch, with the number of each component included varying from 0 to 5, depending upon the customer order. Thus, the independent demand of customers for the switch, and the independent demand of customers for various switch configurations (and their resulting BOM), must be forecast to determine the dependent demand for each component part.

It is important to note that only one company in any given supply chain is directly impacted by independent demand. The rest of the companies in the supply chain are impacted by derived and/or dependent demand. Equally important, the techniques, systems, and processes necessary to deal with derived and dependent demand are quite different from those of independent demand.

Recognizing the differences between independent, dependent, and derived demand, recognizing which type of demand impacts a particular company, and developing techniques, systems, and processes to deal with that company's particular type of demand can have a profound impact on supply chain costs and customer service levels. We first explore the implications of independent and derived demand, followed by a model of the demand management function in supply chain management. We will then move on to the topic of sales forecasting management.

Derived Versus Independent Demand

Figure 1.1 depicts a traditional supply chain, with a retailer serving the end-use customer, a wholesaler supplying the retailer, a manufacturer supplying the wholesaler, and a supplier providing raw materials to the manufacturer. The source of independent demand for this supply chain is 1,000 units for the planning period. However, the retailer (as is typically the case) does not know this with certainty. In fact, the retailer has a reasonably good forecasting process and forecasts end-use customer demand to be 1,000 units for the planning period. Because the forecast has typically experienced +/−10% error in the past, the retailer places an order to its supplier (the wholesaler) for 1,100 units (i.e., 1,000 units for expected demand and 100 units for safety stock to meet expected forecasting error). It is critical to notice in this simple example of a typical, unmanaged supply chain that the demand the wholesaler experiences is 1,100 units, not 1,000.

The wholesaler, in turn, has a reasonable forecasting system (note that the wholesaler is not forecasting end-use customer independent demand, but is inadvertently forecasting retailer-derived demand), and forecasts the demand impacting the wholesaler at 1,100 units. Again, the wholesaler believes the forecasting error to be approximately +/− 10%, so the wholesaler orders 1,100 plus 10% (or 1,210 units) from the manufacturer. If the manufacturer and the supplier both assume the same +/− 10% forecasting error, then each adds 10% to its orders to their suppliers. Note that we are assuming here, for simplicity's sake, that there is no BOM. If there were, the logic would still hold, but the illustration would become unnecessarily complicated.

Figure 1.1 Demand Error in a Traditional Supply Chain

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As Figure 1.1 illustrates, simple failure to recognize the difference between independent demand (which needs to be forecast) and derived demand (which can be derived and planned)—even in a supply chain where forecasting error is only +/−10%—adds greatly to the safety stock carried in the supply chain. In fact, because each member of the supply chain only needed 1,000 units to meet the actual demand, plus 100 units for the potential forecasting error, this particular supply chain is carrying 705 too much inventory ((210–100) + (331–100) + (464–100) = 705), or a 16.0% supply chain wide inventory overstock ((705/4,400) = 16.0%) for the actual end-use customer demand. Inventory carried for Total Demand Error (Safety Stock) in this supply chain is 1,105 (100+210+331+464), or 110.5% of actual end-use customer demand!

This example allows us to introduce the supply chain concept of demand planning, which is the coordinated flow of derived and dependent demand through companies in the supply chain. Demand planning is illustrated in the Figure 1.2 supply chain. End-use customer demand is the same as in Figure 1.1, and the retailer's faith in its forecast (+/− 10%) is unchanged. What has changed, however, is that the other companies in the supply chain are no longer even attempting to forecast the demand of their customers. Rather, each member of the supply chain receives point-of-sale (POS) demand information from the retailer, and the retailer's planned ordering based upon this demand. Combined with knowledge of the time-related order flows through this supply chain, each company can plan its processes (including orders to its suppliers). The result is that each member of the supply chain carries 1,100 units in inventory—a system-wide reduction in inventory of 13.81% from 5,105 (i.e., 1,100 for the retailer, 1,210 for the wholesaler, 1,331 for the manufacturer, and 1,464 for the supplier) to 4,400 (i.e., 1,100 each for the retailer, wholesaler, manufacturer, and supplier). More importantly, the inventory carried for forecasting error (safety stock) drops from 1,105 to 400 (from total demand error of 110.5% to 40.0%)—for a reduction of total demand error inventory (safety stock) of 63.8% ((1,105–400)/1,105).

Figure 1.2 Demand Error in a Demand Planning Supply Chain

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Notice, however, that the inventory reductions are not uniform across the supply chain. Whereas the supplier has a reduction in safety stock of 78.4% (from 464 to 100), the retailer experiences no reduction. In fact, the further up the supply chain, the greater the safety stock reduction. This illustrates a paradox of demand planning in any supply chain—the very companies that are most needed to implement supply chain demand planning (i.e., implementation of systems to share with suppliers real-time POS information held by retailers) have the least economic motivation (i.e., inventory reduction) to cooperate. This leads us to the concept of demand management.

Demand management is the creation across the supply chain and its markets of a coordinated flow of demand. Much is implied in this seemingly simple definition. First, the traditional function of marketing creates demand for various products, but often does not share these demand creating plans (such as promotional programs) with other functions within the company (forecasting, in particular), much less with other companies in the supply chain.

Second, the role of demand management is often to decrease demand. This may sound counter-intuitive, but demand often exists for company products at a level management cannot realistically (or profitably) fulfill. Demand management implies an assessment of the profit contribution of various products and customers (all with capacity constraints in mind—including the capacity of all components in the BOM), emphasizing demand for the profitable ones, and decreasing demand (by lessening marketing efforts) for the unprofitable ones.

Finally, as we mentioned earlier, considerable supply chain savings can result from demand planning, but the rewards are not always consistent with the need to obtain collaboration from all companies in the supply ch...