In Pursuit of Perfection
Semiconductor manufacturers in Silicon Valley were among the first to use the term "accurate order" in the early 1980s, according to Hau Lee, the Thoma professor of operations, information and technology at Stanford University's Graduate School of Business. By the 1990s, this focus on measuring order delivery rates had spread to other industries, including food service, which was losing money because food distributors (the companies that deliver food to restaurants and other outlets) would withhold payment for what they considered imperfect orders. Lee says that while manufacturers understand the importance of aiming for accurate orders, many have underestimated the cost consequences of imperfect orders. At Seven-Eleven Japan, says Lee, the company noticed that highly paid truck drivers were often idle because of an imperfect order. As a result, the company started measuring perfect order rates and noticed that when an order is perfect, the driver can leave right away.
Companies trying to boost their rate of perfect orders need to first identify what makes an order imperfect. According to AMR's Hofman, orders can be imperfect for any of the following reasons: out of stocks, manufacturing and transit delays, late and inaccurate shipments, poor quality of finished goods or damage to finished goods in transit. Companies striving for perfect orders can end up increasing their supply chain costs, Hofman says, especially if they are trying to deliver goods more quickly. Pierre Mitchell, supply chain analyst at The Hackett Group, says that companies should benchmark their supply chain costs against others in their industry and balance that against how important perfect orders are for their customers. Companies that manufacture parts for automobiles, for example, may have a very short window of time for delivery of their product. "If you're not on time, the vehicle assembly line may shut down," Mitchell says. If a manufacturer is not serving a customer well in this type of scenario, it could face steep financial penalties. However, if a company is making a commodity item, such as packaging material that can be stored at little cost, achieving perfect order is less important.
For those companies that decide perfect order fulfilment is worth pursuing, the process starts with demand forecasting, a famously unscientific approach that some have compared to gazing into a crystal ball. Most experts agree that demand-forecasting software alone can't guarantee an accurate forecast. As a number of well-publicized mishaps at companies such as Nike have shown, ensuring the accuracy of the data going into the forecasting algorithms is key to avoiding expensive miscalculations.
So companies are changing their supply chain processes to get a better view. At Procter & Gamble, for example, the company started to revamp its supply chain four years ago to increase efficiencies and focus on getting a clearer picture of demand from actual consumers to supplement the traditional use of historical sales data. The idea is to provide information to suppliers on what is sold today through aggregate point-of-sale (POS) data. P&G, of course, has been exchanging POS data with some of its top retail customers, such as Wal-Mart, for the past 20 years through its automated replenishment system. When a cashier at Wal-Mart sells a box of Tide, that data flows back to a P&G distribution centre. Once a certain number of boxes has been sold, a trigger goes off to send another shipment of Tide to the appropriate Wal-Mart distribution centre so that it can be shipped to the store. But today, P&G is working to provide its suppliers (the companies that make ingredients for P&G products) better access to production data. The company is doing this by collecting POS data from its customers and then transmitting production requirements to suppliers on its supplier portal. "This allows [the suppliers] to better plan their production, and deliver raw and packing materials on a just-in-time basis," says Patrick Arlequeeuw, vice president of the global supply network at P&G.
In the past, when a retail customer saw that a product was missing from the shelf, the retailer would check his back-office inventory and the distribution centre. If necessary, he would then place an order with P&G, where someone would look at inventory levels to see how quickly she could get a shipment of Tide to the retailer's distribution centre. Then, based on the historical sales data, P&G would contact suppliers for needed ingredients and packaging materials to avoid a repeat out-of-stock experience.
Now, for an increasing number of products it sells, P&G aggregates the POS information from the store and provides its suppliers with this information through a supplier portal linked to P&G's proprietary SAP system and a customer connect portal. "Everyone in the network works from the same data," says Arlequeeuw. The result is that P&G's average out-of-stock rates have fallen from 20 percent of brand categories with a 10 percent out-of-stock rate, to just 7 percent of categories experiencing that rate. Over the same period, says Arlequeeuw, the percentage of categories that are achieving an out-of-stock rate of less than 5 percent has increased from 43 percent to 60 percent.
The problem with P&G's old supply chain model was that replenishment of empty shelves could take several weeks, or even months at times. "Now, because we provide information to our suppliers on a daily basis, they understand what is happening and can replenish shelves right away," Arlequeeuw says.
P&G's demand forecast, while still not 100 percent perfect, comes closer to delivering accurate orders because it contains information about what is happening on store shelves on a daily basis - information that is ultimately transferred to suppliers. The goal, says Arlequeeuw, is to have enough flexibility in the supply chain so that plants can produce for tomorrow what was sold the week before.
This approach should give P&G and other companies a better chance at nailing accurate customer demand. And companies that have better demand forecast accuracy will have less inventory, stronger order fulfilment and higher profit margins in the end. Hofman says P&G is moving toward having its entire supply chain capability driven by demand. P&G is aggregating the POS data and sending it to their production plants. "This is not yet widely done," she adds.
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