Supply chain management is a frequently encountered phrase these days, as managers strive to improve factory performance. The trouble is that all too often the real meaning is lost. Instead, a casual observer might interpret the activities at the factory as evidence of an intensive effort to improve supplier management.
Good supplier management, while praiseworthy, does not constitute good supply chain management without a concurrent effort to manage the rest of the aspects of delivering products to customers. In this article, I will present a complete supply chain management methodology. This approach, developed at Hewlett-Packard, will enable a manufacturing operation to better manage its supply chain, ultimately improving customer satisfaction levels while reducing overall costs.
Hewlett-Packard has successfully used this methodology and is making efforts to implement the practice of good supply chain management at all its divisions. HP identified the need to improve its process for manufacturing and delivering products to customers as profit margins suffered pressure from increasing competition. Other factors have contributed to a renewed focus, namely:
- More instances of multisite manufacturing, where several independent entities are involved in the production and delivery process;
- Increasingly cut-throat marketing channels, such as independent computer dealers;
- The maturation of the world economy, with heightening demand for “local” products;
- Competitive pressures to provide exceptional customer service, including quick, reliable delivery.
HP’s methodology has led to major changes in the way it does business. In the process, though, we have also discovered some appealing side effects. The proper execution of this methodology leads to improved team-work and cooperation among employees, especially those normally separated by either business function or geography. We’ve also discovered that this methodology leads to greatly improved customer focus, in addition to better relationships with suppliers.
In the following pages, I will introduce HP’s methodology. First, I will identify the problems inherent in supply chain management. Then, I will describe some key insights and briefly describe an analytical tool that we have developed to support a rational analysis of real supply chains. Finally, I will close with representative case studies describing HP successes with “real” supply chain management.
Responding to Uncertainty
Large manufacturing companies are “hostage to complexity,” according to Lew Platt, HP’s president and CEO. The nature of the complexity is evident in a review of material flows for a complicated product. Multiple suppliers ship to manufacturing sites with varying regularity. There, subassemblies and final products are made by complicated and somewhat uncertain processes.
1. Even JIT fanatics carry inventory of finished goods close to the customer and with suppliers. These stockpiles are small, though, because the manufacturing process has been tuned (1) to reduce uncertainty in the first place and (2) to recover quickly when something does happen. Paul Zipkin describes this as “pragmatic JIT.” See:
P. Zipkin, “Does Manufacturing Need a JIT Revolution?” Harvard Business Review, January–February 1991, pp. 40–50.
2. Lee and Billington describe a number of ways in which a firm’s supply chain can break down. This example corresponds to their Pitfall 11: Organizational Barriers. See:
H.L. Lee and C. Billington, “Managing Supply Chain Inventory: Pitfalls and Opportunities,” Sloan Management Review, Spring 1992, pp. 65–73.
3. IBM reduced its U.S. spare parts inventory investment by half a billion dollars — a 20 to 25 percent reduction — by introducing an analytical tool to set stocking levels. See:
M. Cohen et al., “Optimizer: IBM’s Multi-Echelon Inventory System for Managing Service Logistics,” Interfaces 20 (1990): 65–82.
4. I depict uncertainty in the system with the familiar “bell” curve of the normal distribution. Raw data, shown in the underlying histogram for the suppliers in Figure 2, can be readily summarized in statistical form as the mean and standard deviation. These quantities determine the shape of the curve. While I’ve shown each distribution in the example to be the same shape, in practice some will be wider (more variation, or a higher standard deviation), and some will be narrower.
5. The vulnerability of upstream suppliers to variability in customer orders is wonderfully captured in the “beer game.” This game casts players in the various roles of a beer distribution supply chain: retailer, distributor, wholesaler, and factory. The game is used at MIT to sensitize students to the importance of systems thinking. An ability to focus on system problems is critical to improving supply chain performance. See:
P. Senge, The Fifth Discipline (New York: Doubleday/Currency, 1990).
6. Makridakis and Wheelwright provide a good introduction to the field of forecasting. See:
S. Makridis and S. Wheelwright, “Forecasting: Framework and Overview,” TIMS Studies in the Management Sciences, ed. S. Makridakis and S. Wheelwright (Amsterdam: North Holland, 1979), pp. 1–15.
7. There should be more to negotiations with suppliers than price. While important, there are other measures of supplier performance that can have a greater impact on overall profitability than just a few pennies on the unit price. Hewlett-Packard’s Corporate Procurement team posts, in public areas, the names of the company’s best and worst suppliers as measured by delivery performance. Poor performers try to remove their names from that public record, while the top suppliers strive to maintain — or improve — their place on the list. For such a simple idea, this has had a remarkable impact.
8. Myriad examples of tactical planning tools appear in the literature. For example, see:
S. Graves, “A Tactical Planning Model for a Job Shop,” Operations Research, July–August 1986, pp. 522–533.
9. Silver and Peterson describe the basics of modern inventory theory. See:
E. Silver and R. Peterson, Decision Systems for Inventory Management and Production Planning (New York: John Wiley, 1979).
Nahmias provides another useful text. See:
S. Nahmias, Production and Operations Analysis (Homewood, Illinois: Richard D. Irwin, 1989).
Magee’s timeless piece is a good introduction to the field. See:
J. Magee, “Guides to Inventory Policy,” Harvard Business Review, January–February 1956, pp. 49–60.
10. The extension of the manufacturing process into the distribution center initially challenged managers accustomed to centralized control. They looked at the new approach with caution out of concern for issues like process control, quality, and operational efficiency. Because of different reporting lines for the factory and the distribution center, high-level intervention was required to execute the change, which was widely acknowledged to benefit the company on the whole. Organizational obstacles such as this represent one of the major pitfalls of supply chain change management. Modeling, which facilitates data-driven decision making, is one of the tools that can be used to overcome these barriers.