Manufacturers have depended on demand forecasts to determine their production schedules for a long time. As the retail world moves more fully into the fast-paced internet age, it is becoming increasingly difficult to accurately predict demand. New insights into market uncertainty and response have shown that previous methods of demand prediction have been overlooking critical data for a long time, as well. The current problem of faulty forecasting is becoming crippling to manufacturers. Faulty forecasting can fill the storage with the wrong product, wasting time and resources and crippling a manufacturer’s ability to respond to actual demand without incurring even more losses to make room for the correct match between supply and demand (Fisher et al. 84). Any manufacturer that refuses to keep up with the rapidly changing interests of the modern market is doomed to fall behind those that become more flexible and responsive.
The biggest difference between the new Accurate Response (AR) system and older methods is the acknowledgment of uncertainty and of certain kinds of data that were previously ignored. AR is revolutionary in that it “measures the costs per unit of stock-outs and markdowns, and factors them into the planning process. Most companies do not even utilize activity-based costing to measure how many sales they have lost, let alone consider these costs when they commit to production” (Fisher et al. 84). While previous concerns had been with avoiding the wasted product, AR makes just as much effort to ensure there is enough product available to satisfy the full demand of the customers. AR also determines which products are more or less predictable (Fisher 84). This feature allows manufacturers to prioritize their manufacturing, producing what they are more confident will be in demand ahead of time and keeping their facilities open when the less predictable demands come in.
Efficiency is the key fiscal advantage of AR. AR helps companies “use the power of flexible manufacturing and shorter cycle times more effectively. And the capability to do a better job of matching supply and demand produces savings that drop straight to the bottom line” (Fisher et al. 84). By hitting the mark more closely, fewer markdowns and fewer stockouts mean more pure revenue for the time spent manufacturing. Because this is its primary advantage, AR is best suited to products that have a high turnover and a short life-cycle (Fisher et al. 86-87). Since a lot of marketing and retail is moving to the internet with companies like Amazon, more and more products are taking on these characteristics.
In addition to the business where AR was developed, a few other businesses have adopted the principles of uncertainty and flexibility that are at the heart of AR. Sport Obermeyer, Ltd. is the home of AR and it employs it to great effect, reportedly cutting their costs lost to supply and demand mismatch in half. The Timberland Company incorporates sales tracking with real-time forecast updates and L.L. Bean is putting stock out data to good use thanks to its role as both manufacturer and retailer (Fisher et al. 85). These companies are making dramatic improvements to their own revenue by acknowledging the changing world of manufacturing and retail and will likely leave behind any competition that refuses to adapt.
Fisher, Marshall L., et al. "Making Supply Meet Demand in an Uncertain World." Harvard Business Review, 1994, pp. 83-93.