August 2000 President's Desk Key to Success in the e-Economy By John Birge jrbirge@nwu.edu As you finish your Web search for that limited edition CD, that perfect peripheral for your new computer or even this week's groceries, you want immediate delivery. You have come to expect such service with information, so why not with all products? Someday, maybe each home will have a tiny fabricator to make anything from a storehouse of raw elements (á la the morphing terminator in T2). Until then, we will have to rely on someone to transport a bunch of whole atoms and molecules and not just electrons. OR/MS is, as we all know, the key to making that transport time as low as possible. But how can we ensure that others are equally enlightened? An expanded e-economy will clearly demand even greater OR/MS capability. Even with some recent devaluations in dot-com mania, the forecasts implied by market prices indicate tremendous growth. An order of magnitude increase in home-delivered products would appear to require an even greater increase in OR/MS involvement. How can we ensure that happens? The Quality Factor To answer these questions, we might look at the phenomenal success (in terms of visibility and corporate awareness) of the quality movement. For example, one professional organization, the American Society for Quality, dwarfs INFORMS with more than 10 times the membership. Their awards and other quality prizes, such as the Malcolm Baldrige National Quality Award, attract interest in all industries and government — up to the president of the United States. These high-profile successes accompanied the push to quality competition in the previous two decades. The world of e-business is built on responsiveness competition that calls for OR/MS abilities in addition to quality appreciation. This trend might lead naturally to successes like those in quality, but we can help ensure such acclaim if we take a lesson from the quality boom. A key to awareness on quality is the ubiquitous presence of performance measures. How many manufacturing plants, for example, do not have numerous quality charts prominently displayed? Everywhere you look within factories, warehouses and even some halls of academia, you see graphs tracking yields (successes) and defects (failures). These figures (which you also might see in logistics and transportation firms for on-time performance) relate to achieving consistency. In OR/MS, however, we generally want more. We want optimality. Optimal Success To highlight OR/MS performance then, we need performance measures that focus on achievement relative to optimum. How can we define these measures? How can we create an OR/MS equivalent of Cpk that provides an instant reference point for any industry, and a benchmark to define world-class performance? Many metrics might provide the answers. I will make a few suggestions, but I encourage you to think of others. The key to success in this arena will be widespread use and comparisons across many organizations. With luck, our constant use of such measures and emphasis on performance relative to optimum can deliver high visibility and awareness of OR/MS impact and value. As I mentioned earlier, the focus should be on performance relative to optimum. Fractions above a minimum target or below a maximum objective seem like obvious choices. The difficult part is in defining optimal performance. The OR/MS analyst must provide that definition and be explicit about the constraints and conditions used in the definition. As an example, suppose we are a dot-com direct retailer. We want to measure our total time from order placement to order fulfillment relative to the best possible. We can either define fractions of orders at minimum time (e.g., next day), or the difference between our mean times to fulfillment and the minimum possible given our particular market. Our value in showing the minimum expected time (or other appropriate target) should reflect conditions such as demand and processing time variation. We can assess uncontrollable factors such as demand variability and physical transport and processing times to determine best possible due time performance fractions or mean delivery times. Actual performance can then yield a measure of overall efficiency relative to optimum. Other measures can apply in different contexts. Our main goal should be to keep an objective in the minds of both users and managers and to continuously measure performance relative to that goal. Using such measures can highlight OR/MS achievements and provide benchmarks similar to those in the quality area. Whether we can achieve visibility at the presidential level with an OR/MS prize presentation in the Rose Garden remains to be seen, but if we focus on these measures, maybe we have a chance. E-economy success relies heavily on OR/MS expertise since competition based on responsiveness requires optimum (or close-to-optimum) performance. Highlighting our value through performance relative to optimum can help make that point to everyone. If you have other ideas for delivering our message about responsiveness and performance, I look forward to hearing them. Please send them to me at jrbirge@northwestern.edu. Table of Contents OR/MS Today Home Page OR/MS Today copyright © 2000 by the Institute for Operations Research and the Management Sciences. All rights reserved. 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