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Predictive commerce represents the “new science of planning,” says Smith. It satisfies the desire to connect upstream demand sensing with the planning and execution of transportation. Its “secret sauce” is a model that encapsulates demand all the way through to that final function.
The practice draws on data that’s already part of transactions today, Smith says. Companies can take advantage of existing information about orders and order lines to “interrogate demand variability.’
The end-user of predictive commerce techniques can be a traditional demand or supply planner. But the discipline also crosses over into sales, marketing and trade finance. In the end, says Smith, it allows companies to make better decisions about trade promotions, expenditures and other factors in merchandising.
Smith cites the example of Costa Express, a U.K.-based chain of self-serve coffee bars. It places stand-alone kiosks in multiple locations, including shops, movie theaters and the London Underground. To scale the business, Costa had to depart from its customary spreadsheet approach, which had depended on what it thought demand was going to be. Instead, the company sought to automate the process, so that it could sense demand at every one of its thousands of locations. Information now pulses back every four minutes, giving Costa the ability to ensure that inventory is in the right place at the right time. As a result, it has been able to increase sales by more than 300 percent, while cutting logistics costs by more than 30 percent.
Additional benefits include the ability to reduce field stock by 20 percent, cut CO2 emissions by 30 percent (because of a reduced need for transportation loads), and avoid having to add headcount to manage processes in a fast-growing company.
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