Forecasting: A Forgotten Requirement

aliaxis-logoA few months ago, I attended the ToolsGroup Supply Chain Transformation conference in Boston. I am always interested in case study presentations, as I find that I learn a lot about how companies are applying their technology and business processes to solve a problem. These case studies are also an opportunity to give other practitioners a different way to look at a problem they may be experiencing as well. One of the case study presentations that I caught was by Brian McLaren, of Aliaxis. Brian was the first person to state the obvious – no one here has ever heard of Aliaxis. However, it turns out that everyone knew what the company does

Aliaxis, headquartered in Belgium, is a global leader in fluid handling solutions. That is, they manufacture plastic pipes, for industrial use, professional services, and for the do-it-yourself segment. The company has 89 manufacturing sites in 40+ countries, and over €3 billion in revenues. None of the pipes actually say Aliaxis on them, however. Aliaxis has built a federation of companies through acquisition, and each of these companies continues to operate as their own entity.

Brian McLaren discussed a shift in focus for the company in 2013. Up until that point, Aliaxis had simply been a financial holding company. But in 2013, they wanted to streamline operations and become an industrial holding company. For Brian’s team, they were tasked with driving supply chain excellence (and revenue from supply chain efficiencies) for the company.

The major problem at Aliaxis was that the company did not forecast. The focus was on financial forecasting with little or no volume forecasting. This lead to a disconnect between customers demand and manufacturing plans, as well as disconnected business metrics. There was a high level of obsolete and slow-moving inventory on the shelves, which took up valuable warehouse space that could be dedicated to profitable products. With little collaboration between business units, the problems were not going to get better.

A second set of problems emerged when trying to decipher what the top supply chain initiative of the team should be. Every stakeholder gave a different answer, ranging from establishing forecasting and sales operations plans to implementing a warehouse management system. Brian’s team knew that getting a better handle on demand could have a positive impact on customer service levels as well as inventory holding costs.

The solution was to get a plan in place. Specifically, the company implemented sales and operations planning (S&OP), which is an integrated business management process that determines the optimum level of manufacturing output. Considering the incredible disconnect at Aliaxis, the company was looking for a baseline level of S&OP. Aliaxis decided to pilot a program in North America first, with three critical steps in the process. First, they focused on four key performance indicators (KPIs) to measure success: perfect orders, demand forecast accuracy, cash-to-cash cycle time, and supply chain management costs. Second, they selected a system to support S&OP. And third, they measured the benefits to business of the pilot.

After the pilot, Aliaxis noticed significant results. They reported a 19% improvement in demand accuracy, as well as a 10% improvement in short-term item-level forecast accuracy. The company improved forecast accuracy at both the 1+ and 6+ month horizon, and reduced safety stock costs by $1.5 CND. Based on the results, the company ran a second pilot in Europe including inventory optimization this time. The results were similar, and the company went live with its plan across every company across the globe. They have since put basic demand management processes in place, and are achieving their highest level of on-shelf availability.

The company learned that its “forecasting” processes were not really forecasting. They would simply take last year’s numbers and add 5%. The result of this process was a high level of obsolete and slow-moving inventory on the shelves. The company was solely focused on hitting €3 billion in revenues, so low margins and perfect orders were not a priority. Since rolling out their S&OP initiative, the company is achieving significant improvements in demand accuracy, forecasting accuracy, and safety stock savings. It was a difficult learning process for Aliaxis, but in a short period of time, it was able to move from a system where they did no forecasting, to achieving over 95% fill rates across its product lines. For a company that would simply tack on 5% year-over-year to its “forecast,” the results are even more impressive.

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