With the benchmark results in hand and ready to move forward, P&G's demand planning team surveyed the company's various business units and their respective supply chains to identify a likely candidate for a pilot project. "We looked for a business that was willing and able and had some need," Kremblewski says, "an area that was looking for some improvement around safety inventory and that fit the 'sweet spot,' with a reaction time on which they based their safety stock in the zone of 10, 15, 20 days." That business unit wound up being in Western Europe, and it went live last March on a pilot project. The objective for the project was to improve short-term forecasting accuracy sufficiently to yield a 10 percent reduction in safety stock.
In moving into the pilot, the demand planners worked closely with the supply side of the business to ensure that as safety stocks came down, the reductions produced no disruptions in product availability. Over time, both demand and supply gained increased confidence in the solution's results, allowing for further reductions in safety stocks on an incremental basis. The demand planning group was able to facilitate that process by "baking" Procter & Gamble's own inventory models directly into the RTF solution. Over the course of several quarters, P&G was, in fact, able to document a decrease in its short-term forecast error of more than 30 percent within this business unit, which translated into safety stock reductions of greater than 10 percent, exceeding the goals for the pilot.
Based on the results of the pilot, Procter & Gamble has started to roll the Real-Time Forecasting solution out to other business units, initially in Western Europe and North America. The individual businesses have to pay for the solution out of their separate budgets, but P&G isn't mandating the solution for all its supply chains, simply because it is not appropriate for all of them. "If you've got a four-month supply chain from China, your forecast accuracy over the next two weeks or three weeks or six weeks is meaningless," Kremblewski says. Rather, the solution makes sense only where short-term accuracy can have a real impact, and those are the business units that Procter & Gamble is targeting.
In terms of lessons learned during the pilot, Kremblewski says that companies considering such a project should not underestimate the challenge of getting the right data feeds established to supply the Real-Time Forecasting solution with the information necessary to make the forecasts. "It's not because there's anything wrong with the RTF tool, it's because we do some very strange things in our own systems," Kremblewski says, referring to the various idiosyncratic ways that P&G, like any large company, handles its enterprise data. In addition, he recommends working closely with supply chain partners to reassure them that the changes brought about by the improved forecast accuracy will not have a negative impact. As with the company's own staff, these partners must also gain confidence in the solution's results, Kremblewski explains.
Procter & Gamble has estimated that deploying Terra Technology's solution ultimately will yield more than $100 million in increased cash flow globally for P&G, according to Clark. But the greatest benefit from adopting this type of solution may come over the long term, as Procter & Gamble is able to shift its demand planners away from the inevitable firefighting and scrambling inherent in focusing on short-term forecasts. "Our demand planners have more than enough things to do without focusing on the next one, two or three days, or the next week," Kremblewski says. "The ‘black box' takes care of all that, which allows our demand planners to focus on the longer term, on the trends, on the business intelligence regarding the marketplace, what our customers are doing, etc. And that's where their real value is added, not watching orders or watching short-term trends. If the box can do it, let the box do it."