Reference no: EM131870958

Problem: Even back when the first set of stone wheels were sold in the emerging caveman economy, it was difficult to predict demand. Otto the rock cutter just didn't have good data, so he took his best guess. Flash forward a few millennia: According to AMR Research, 40 percent of companies still forecast in monthly buckets. Then, on a monthly basis, forecasters readjust plans based on what really happened.

Although manufacturers and retailers are collaborating more and more, getting additional partners involved with the forecast doesn't necessarily make it any better. The result often sounds less like a symphony and more like the dull thud of another full pallet being dropped into a stacked warehouse. Or, worse yet, out-of-stocks divert consumers to the competition.

Fortunately, there are some big changes occurring in how retailers look at inventory, and that intelligence is rippling back through the supply chain to manufacturers and raw materials providers. If you haven't taken a hard look at demand sensing, now is the time.

Demand sensing considers individual transactions occurring across all retail stores over the course of a day. It is the near-real-time transmission of demand data coupled with who's buying a product and the circumstances under which it was purchased. For example, a 19-year-old, loyal customer purchases the Xbox 360 when a store runs a promotion that offers three games free with each purchase of a console.

Retailers usually implement this approach via a single execution-management software platform that integrates with the point-of-sale (POS) systems at store locations. The execution-management software analyzes and identifies trends by stock-keeping unit. The retailer configures the solution to provide automatic alerts to managers or take actions based on set business rules. The goal is to become more tuned into consumer behavior and manage store inventory and promotions more effectively for better profitability.

Beyond just real-time data to help update the aggregate forecast, demand sensing can do some great things at the store level. It can account for geographic blips, such as an annual parade that wipes out local beer inventory, and can identify accelerating sales on new products before an arbitrary reorder level is reached. In short, demand sensing is a pure signal of real pull with an ability to roll up to an aggregate total demand while still recognizing that individual conditions need special treatment at individual stores.

Demand sensing also drives decisions in other critical cost areas of the supply chain, including workforce management, transportation, and execution management at the store level. All the laborers-drivers, loading dock workers, clerks, forklift operators-can be driven by a signal coming from the store. This helps distribution center managers track product velocity and maintain efficient slotting. At the warehouse, demand signals are used in slotting to increase picker productivity and ensure item availability. Similarly, retailers can use demand sensing to fine-tune the forecast, plan product movement, orchestrate suppliers, optimize pricing, and have just the right amount of product available to meet demand. For the manufacturer, demand signals better equip managers to smooth production schedules. After all, they're less likely to send a massive, disruptive order to the production line if they can stay on top of actual demand. Finally, for the raw material supplier, the ability to use demand signals enables shrewd buying and fewer unexpected sourcing emergencies.

Real-World Retail

Demand sensing is not just a tool to be leveraged by hard goods retailers or general merchandise retailers. In fact, such signals can add tremendous value to the supply chain of a food service or specialty retail operation. One coffee retailer known for its small-batch, Just-in-Time roasting has used demand-sensing technology to manage store inventory levels and distribute production demand to roasting operations. As a result, customers find the freshest roasted coffee beans on the shelf, and the business creates less waste in order to meet these customer expectations.

Similarly, a convenience retailer uses demand sending to manage the inventory of fresh ingredients for its signature menu of made-to-order sandwiches, salads, and freshly prepared snacks. Near-real-time POS data, combined with demand-smoothing algorithms and efficient distribution operations, make sure stores always have the best ingredients available, while minimizing excessive inventory. Reducing waste also helps this retailer retain and recruit customers by delivering fresh food, fast.

The retail industry's approach to demand sensing is driving significant changes for the supply chain. The key is to get started, consider systems to support demand-signaling synchronization, and ask business partners if they are looking at these concepts. Another millennium need not pass. We can get it right today.

Questions: What is the point-of-sale system? How it works in a retail business environment? What have you learned from reading this article?