Integrated Demand Signals Update

EXECUTIVE SUMMARY | In 1992, Wal-Mart deployed Retail Link® to provide its vendors with information on the sales trends and inventory levels of their products. Since that time, the industry has been bullish on the opportunities that exist for leveraging POS and other downstream demand signals to improve upstream supply chain operations and planning. A recent MIT symposium on Integrated Demand Signals (IDS) delved into what companies are planning to do about IDS. The bottom line is that managers are in a quandary. Extensive piloting has shown that huge benefits are possible; however, to garner them will involve two daunting types of implementations: Massive enterprise-wide business processes and a Demand Signal Repository (DSR) database. In 1992, Wal-Mart deployed a computer system called Retail Link® to provide its vendors with information on the sales trends and inventory levels of their products sold at the retailer's stores. In 1996, Wal-Mart's Retail Link® was available via Internet, making it the application platform. Since then the system has been continuously enhanced over time, according to WalMart's website (http://walmartstores. com/Suppliers/248.aspx): BULLISH ON DEMAND SIGNALS The initial deployment of Retail Link® marked one watershed event in the Efficient Consumer Response (ECR) movement that was also starting around that time. ECR was a concept whereby manufacturers and retailers might drastically reduce inventories, costs, and waste in grocery goods supply chains by sharing information. At the 1994 annual meeting of the Council of Logistics Management (now called the Council of Supply Chain Management Professionals), I spoke about forecasting in the Consumer Products industry and one of the charts I showed was an early version of that depicted in Figure 1. I said that companies were thinking about and starting to establish relationships with downstream trading partners to better understand supply chain dynamics, and using the knowledge to start engaging in multi-tier forecasting and planning to improve forecast accuracy and better integrate supply chains. I had just finished working on a consulting project in which we had installed a forecasting system for a consumer-products manufacturer that used knowledge of a distributor's inventory to help forecast the future sales to that distributor. Since the manufacturer did a great deal of end-ofquarter promotions-during which distributors stock up heavily on its products to take advantage of price breaks-sales to distributors were depressed at the beginning of the next quarter, as distributors invariably drew down on their excess product inventories. Since then I've been bullish on leveraging all types of downstream demand signals. I have conducted research, written, and spoken about the potential opportunities that exist to leverage POS (Point-Of-Sale) data and other downstream demand signals to improve forecasting and integrate supply chains to make them more efficient. For example, I wrote a column in the Fall 2008 Journal of Business Forecasting (JBF) titled, Use to Improve Forecasting. It was a follow-up to my Winter 2001-2002 JBF column titled, VMI Can Be Good for Your Forecasting Health, which argued the potential usefulness of this type of demand signal. In the follow-up article, I was able to provide some proof of my claims by reporting on the research findings of a project during which I advised an MIT graduate student and was the topic of his Master's thesis. He worked with a major consumer-packaged goods (CPG) company to investigate whether the inventory replenishment plans for VMI-program customers were more accurate (as forecasts) than the forecasts generated by its operational forecasting department. The department was not incorporating demand signals into its forecasting process. The student found that (for weekly forecasts up to four weeks into the future) the signals were much more accurate than the operational forecasts. …