During the early nineties there were few supply chain software products on the market. Yet it was the time of innovation. New ideas were bubbling up. Better computer hardware allowed for massive number crunching. Universities that taught operations research (MIT, Boston University, Stanford, Wharton) were graduating a new generation of entrepreneurial whiz kids who didn’t want to work in big companies writing math. Instead they started or joined software companies.1
And supply chain managers from Toyota to Dell to Walmart were learning and sharing some key lessons. MRP was not working for them. The Oliver Wight approach was giving way to Andre Martin’s Distribution Resource Planning (DRP), JIT/Lean,2 and Constraint-based Planning with Eli Goldratt. Business people were gobbling up books like The Goal, Flowcasting,and Edwards Deming’s Out of the Crisis.
Forecasters were bantering around terms like Fourier Series, Lewandowski method,3 and were beginning to grapple with seasonality, variability and volatility.
All these and so much more added to the body of supply chain knowledge. And we have continued to learn and have improved a great deal. One significant point is that the founders of these ideas were not static thinkers. As the world changed, their thinking matured and their ideas evolved. Flowcasting is one of those ideas that has evolved. Maybe it’s an idea for now. (You can read Making the Change, about adopting Flowcasting).
Time for a Change
One basic approach that could change the world of forecasting would be to tackle the problem head on. And now is the best time to do it. Head on means get the data at the source. This has been talked about for decades, ever since Jay Forrester applied the concept of wave oscillations to business/demand signals (later renamed the bull whip effect). He pointed out that the farther we get from the source, the more oscillation — or error — is introduced into the forecast. Organizations that do min/max planning, believing that they are helping to avoid risks in the plan, may actually increase the peaks and troughs in these waves (amplification), thus increasing forecast inaccuracy. The net affect: inventory shortages and overages, working capital tied in up in inventory, or additional expenses in logistics.
This is why ideas like Flowcasting are so powerful. Flowcasting advocates continuous collaboration, that is, a constant refresh of the data from the source. Kevin Smith of DePaul University, previously one of the leaders of Kraft’s Flowcasting initiative, pointed out that much of the source of volatility does not actually emanate from customer demand at all. Rather, it stems from introduced errors or changes that amplify through the chain. Therefore, Flowcasting, which integrates the supply chain, can address volatility to a great degree.
I talk to suppliers all the time who tell me they would love to get clean data from their retailers. It just makes so much sense — all players in the chain could perform better. Retailers would reduce out of stocks, suppliers could build and ship on time with less inventory. Both parties could increase sales at a reduced cost.
Share, Like — and Learn
We are mobile, we are social, and we are in the cloud. We share and like, which should make this a perfect time for Flowcasting. This is an era of collaboration and we have the technologies to make it happen. With that as a theme, I am honored to mention the workshop on Flowcasting, hosted at DePaul University, which will be conducted by Andre Martin;4 Kevin Smith, and Dr. Nezih Altay of DePaul; myself; and others. Director-level professionals from CPG or retail companies are invited and can sign up here. You can also see the invitation in the brief below.
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1 Sean Williams of Optiant, now at Logility; David and Edith Simchi-Levi at LogicTools, now part of IBM. — Return to article text above
2 Lean Six Sigma (Wikipedia)— Return to article text above
3 Acquired by Manugistics, now part of JDA Software. — Return to article text above
4 Mr. Martin is now at JDA.