Supply Chain Evolution

Consumer goods companies have invested heavily in supply chain processes and technologies with mixed success. The recent focus on customer and consumer insights has provided the potential for substantial new benefits, but has also added new complexities. This month, Robert Byrne, president and CEO of Terra Technology, provides his perspective on how supply chains have evolved and what it will take to stay ahead of the curve.


Q: How do you see volatility affecting the supply chain?

BYRNE: The past few years of market volatility have put a lot of pressure on the supply chain. Changing consumer behavior and customer needs have made it increasingly hard to predict demand – to the point where what happened last year often has little bearing on what will happen tomorrow. To complicate matters, we have seen an increased reliance on promotional activities to drive volume. This makes it even harder to forecast, but also means getting promotions right is more important than ever. Meanwhile, the continued economic uncertainty has made inventory a very visible target, with companies across the board facing financial pressures to increase cash flow. Improving demand prediction and reducing inventory have shifted from being supply chain projects to business priorities.  


Q: A lot of money has been spent implementing Demand Planning tools and processes, what kind of results are people getting? With your experience in Demand Sensing, how has it changed over time?

BYRNE: In a study that encompasses roughly one third of North American consumer packaged goods volume, the average weekly forecast error during 2011 was 53 percent. This figure has increased gradually over the past two years, which comes as no surprise given all the volatility. The study also showed that a major driver of forecast error is the rapid pace of innovation in consumer products (CP), which presents a chronic challenge for Demand Planning. With half the items having less than two years history, the seasonal statistical models used by traditional Demand Planning tools can’t provide much value. Demand Sensing first addressed this issue by using current information from within Enterprise Resource Planning systems to create forecasts in tune with market realities, lowering forecast error by 40 percent. It has since evolved to a multi-enterprise solution incorporating downstream data from retailers, such as point of sale, to gain another step-change in forecast accuracy. In this time, we have also seen Demand Sensing go global, proving effective in both modern and general trade markets.  


Q: How will the consumer products supply chain use “big data” to change over the next five years?

BYRNE: Mark Twain once said about the weather that, “Everyone talks about it but no one does anything.” Integrated supply chains in CP also fall into this category. There has been plenty of discussion of “end-to-end” and “shelf-back” supply chains but not a lot of action. Big data will change this and drive cash flow, better return on capital, lower inventory, higher service and reduced waste. Currently, CP manufacturers use big data to sense demand with mathematics which dynamically adapt to changing market conditions. These systems sort through an ever-increasing pool of potential demand signals to determine what is predictive and make use of it without human review. Not just for one product, brand, location or retailer, but for all. We see this as the future of collaboration. Retailers provide their data, and in return, manufacturers provide better service with lower costs. It is simple, scalable and avoids the complexities of earlier collaboration attempts like CPFR. The next big step is to extend inventory optimization and planning models to include retailer warehouses. Perhaps we will finally have broad, automated collaboration.