There’s an important distinction to be made between demand sensing and demand shaping, says Chase. Demand sensing draws on historical trends and product seasonality to react to buying patterns. Shaping takes that effort a step further: it allows companies to link replenishment data and shipment history with point-of-sale information. Applying analytics and metrics to that information, companies can begin to influence actual demand.
In the process, merchandisers can make more intelligent use of pricing, advertising and promotional strategies. They can determine whether a particular sales promotion is really paying off – or whether it’s simply appealing to consumers who were already loyal to the brand.
Companies have come a long way from the original Collaborative Planning, Forecast and Replenishment (CPFR) model. There’s more information available to them than ever before. At the same time, the storage and processing of that wealth of data is no longer a problem. Sophisticated algorithms can be deployed “on a grand scale,” says Chase. Suppliers can forecast by region, by market, by channel and even at the level of the individual store.
Social media provide yet another boost to the notion of demand-driven forecasting. Suppliers and retailers can draw on data about consumer sentiment from any number of internet sources. They can use the information to enhance a product over time, maximizing profitability throughout its lifecycle.
Given drastically shrinking product lifecycles, it’s vital to be able to react to buying trends as rapidly as possible. “It’s no longer difficult to forecast short-lifecycle products,” says Chase. “You can even forecast the lifecycle itself, including phase-outs.”
