[From iSource Business, April/May 2002] Life for corporate America has been anything but quiet and predictable over the past several years. There was the economic boom of 1999 followed by the drastic downturn of last year and, in between, a host of unexpected events, ranging from the September 11 terrorist attacks to the UPS strike a few years ago to California's power crisis. As if that were not enough, companies have also had to contend with ever-changing customer tastes, technology innovations, globalization and new product introductions.
To forecast demand, plan production and capacity, as well as replenish inventory, we must apply methodologies and solutions that can handle the magnitude of the complexity and uncertainty we now face. We can no longer afford to settle for decision-support systems that cannot handle massive amounts of data and complex supply chain structures, or support systems that cannot capture the impact of uncertainty and then proactively plan responses.
Time and Space Dimensions
When looking for new tools for this new age, supply chain executives should always ask the question: Can this solution handle the complexity of my supply chain? This complexity has three dimensions: the product space, the geographic space and the time space. Hence, we must ask if a solution can address, in a timely manner, the number of stock-keeping units (SKUs) a company has (product space); the scope of the network structure, such as the number of retail outlets and the distribution structure (geographic space); and the seasonalities and life cycles of the products (time space).
In addition, new solutions must address the uncertainty space, which has two facets. The first facet is demand uncertainty, which could simply be a result of customers' changing preferences and buying habits, unexpected events, competitors' actions, the introduction of new products or the obsolescence of existing products. The second facet is uncertainty in the form of supply, which could be the result of suppliers' capacity, their delivery reliability or, again, unexpected events. Some more direct questions to answer might be whether or not the solution can help make the right hedging decisions in light of uncertainties; whether or not the solution can determine if products can be lean in terms of inventory because the level of uncertainty is low; or whether or not the solution can be proactive, but also apply the most cost-effective way to guide replenishment and inventory decisions.
Finally, our solutions must have the capacity to learn. An unreliable supplier could improve over time, while a stable product could become unpredictable tomorrow. Solutions must self-adjust by capturing the latest data, analyzing the patterns and possible noises, and then fine-tuning the supply chain in response to external changes. Demand-chain optimization software, for example, can analyze patterns and predict demand over time, providing balance in the supply chain even in uncertain times.
The complexity and the uncertainty of supply chains will always be there. But by implementing the right solutions, we will be able to focus on the major problem areas related to products or suppliers since technologies will handle routine issues without requiring much management attention. Technology can also help identify existing fats in the system, such as excess inventory, that must be trimmed.
Moreover, solutions will allow us to be proactive rather than reactive, mitigating the impact of uncertainty and complexity. For example, in the pharmaceutical industry, the timing of the outbreak of the flu season has been perennially difficult to forecast. Some retailers have handled it by overstocking, while others have been caught completely by surprise and were therefore left with huge stockouts. In fact, the right solution could help characterize the timing of flu season by using statistics. Then, by applying scientific methods, one could produce a progressive scheme of safety stocks to protect against stockouts in the event of an outbreak. The key message here is that intelligence, in the form of deeper knowledge and understanding, can be created through the use of scientific and statistical methods to help address so-called unexpected events.
Lastly, new technologies can help companies to coordinate entire supply chains rather than just site-specific internal systems. By coordinating multiple sites within a company, as well as the company's suppliers, the suppliers' suppliers, the company's customers and the customers' customers, not only will the new solutions produce a more efficient company, they will also result in an efficient supply chain or a complete supply network.
Dr. Hau Lee is professor of operations, information and technology in the Graduate School of Business at Stanford University, as well as founder and director of the Stanford Global Supply Chain Management Forum. Dr. Lee is also founding scientist of NONSTOP solutions.