Successful Build-to-Order Strategies Start With the Customer

All companies wish they could produce exactly what customers want when they want it. The ability to be that precise would not only delight customers but reduce costs. The challenges, however, are formidable, and most companies settle for manufacturing standard products in bulk, guided by long-term forecasts. Unfortunately, demand rarely coincides with forecasts, and results fall short of expectations. Companies miss out on potential sales, or they end up burdened by inventory-holding costs and must entice customers with steep discounts or other incentives. Profits erode, and customers do not get what they really want.

In an attempt to offset their losses, companies end up creating island solutions, such as lean factories, believing that this will improve the entire value chain. The automobile industry, often considered an originator of best-practices models, is well known for such solutions. Auto manufacturers have used lean production to create more-efficient factories and improve productivity, but at the expense of the all-important customer perspective. To compensate for their poor understanding of customer needs, they produce larger volumes and more product variants, relying on their forecasts. Their focus then becomes how to get rid of stock and how to offset the cost to manage it. The more they continue on that path, the harder it is to produce the exact car the customer wants within the time the customer deems acceptable. (See “Why Push Strategies Ultimately Fail.”) Indeed, a survey of prospective car buyers shows that they are willing to wait only two weeks for a custom vehicle, and few volume manufacturers are able to comply.1

Why Push Strategies Ultimately Fail »

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References

1. See “Gartner Survey Shows U.S. Customers Prefer Concept of Build-to-Order When Buying an Automobile,” Feb. 9, 2001, www.gartner.com; and “Fulfilling the Promise: What Future for Franchised Car Distribution?” The ICDP Review (2000), International Car Distribution Programme, www.icdp.net.

2. Y. Monden, “The Toyota Production System — A Practical Approach to Production Management” (Norcross, Georgia: Institute of Industrial Engineers, 1983), 2, 55–67.

3. M. Holweg and D.T. Jones, “The Build-to-Order Challenge: Can Current Vehicle Supply Systems Cope?” in “Manufacturing Operations and Supply Chain Management: The Lean Approach,” eds. D. Taylor and D. Brunt (London: Thomson International, 2001), 362–374.

4. H. Mather, “Competitive Manufacturing” (Upper Saddle River, New Jersey: Prentice Hall, 1988), 31–48.

5. For more on the bullwhip effect, see H.L. Lee, V. Padmanabhan and S. Whang, “Information Distortion in a Supply Chain: The Bullwhip Effect,” Management Science 43 (1997): 546–558; and J.W. Forrester, “Industrial Dynamics — A Major Breakthrough for Decision Makers,” Harvard Business Review 36 (July–August 1958): 37–66.

6. For more on the Collaborative Planning, Forecasting and Replenishment Committee of the Voluntary Interindustry Commerce Standards, see www.cpfr.org.

7.See www.mycereal.com.

8. E. Feitzinger and H.L. Lee, “Mass Customization at Hewlett-Packard: The Power of Postponement,” Harvard Business Review 75 (January–February 1997): 116–122; and J. Pine, “Mass Customization: The New Frontier in Business Competition” (Boston: Harvard Business School Press, 1993).

9.The data is for the 1999 models offered in the United Kingdom. For more detail, see M. Holweg and A. Greenwood, “Product Variety, Life Cycles and Rates of Innovation,” World Automotive Manufacturing (April 2001): 12–16.

10. In the auto industry, swing plants handle demand variation, and they are typically in countries that have generous policies toward subsidizing worker salaries when plants are not operational. In the textile industry, plants near the customer base (generally higher-wage locales) manage deviations from demand forecasts.

11. That is not unrealistic. A typical European short-haul flight has nine major pricing categories, which can yield more than 100 ticket prices for the same flight. Thus, two people on the same flight are very likely to pay a different price for the same service.

12. “Gartner Survey,” www.gartner.com.

Acknowledgments

The authors wish to acknowledge Max Warburton, David Simons and Simon Elias for their support, and the 3DayCar Programme at Cardiff Business School and MIT’s International Motor Vehicle Program for sponsoring the research.