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Take Five: Quick Takeaways from the Gartner EMEA Supply Chain Executive Conference

By Jennifer Randall26 Jun 2019

Back home today after a fantastic trip to Spain including the Gartner EMEA Supply Chain Executive Conference. I think with all the delicious fish I consumed in Barcelona I should have enough omega-3 fatty acids to power my brain function for weeks to come…Besides a shared love of food it’s clear that global businesses converging last week found common ground on the challenges of merging the digital and physical supply chain. It feels like a tipping point is near, and it’s an exciting time to be in supply chain. Here are a few key takeaways.


1. Serious change management is required for digital transformation. On it’s own this is not surprising, however, the degree of aversion to change is significant, and often underestimated. ToolsGroup has a research project in progress to gauge progress in digital transformation of supply chain planning and early findings show that two of the biggest obstacles to transformation are fear of change and skills deficit. And no wonder: Gartner shared that this skills gap is huge. Planners and other supply chain practitioners in the new digital world need skills in communication and decision making and change management on top of the standard technical skills. It’s no surprise this talent is hard to find. According to Gartner over 50% of CSCOs say no roadmap is the biggest roadblock supply chain digitalization. To me it says that fear of change is one thing, but when compounded with an uncertain path to get there it’s an even greater obstacle. The takeaway is that businesses need to get started now with a phased digital vision and roadmap that takes into consideration culture, talent, and customer desires as well as technology enablers.


2. AI isn’t just a buzzword: Automation is a critical capability. Closely tied to change management is the automation angle. Gartner predicts that, “by 2020, 95% of SCP vendors will be utilizing supervised and unsupervised machine learning somewhere in their SCP solutions.[1]” Not surprisingly, the top three use cases where machine learning are being applied are demand forecasting, supply planning and demand sensing and shaping. Several sessions spoke of the criticality of learning to let machines make decisions in order to make better decisions, faster. Trusting the system takes time but the payoffs are sizeable. Today the more successful companies are ‘outsourcing’ tasks to technology through AI-powered automation. Although it appears likely that automation will replace some tasks and roles, the ones that remain will be far more desirable. According to a report by the Gartner community SCM World called Anticipating the Future of Supply Chain Work, “High value-adding tasks requiring creativity and problem-solving will replace those that are low value, routine and mundane.”


3. Cost or service: You don’t have to choose just one. Gartner analyst Paul Lord emphasized that you don’t always have to choose between cost and service if you take an aligned, systemic approach to inventory planning. As is often the case, with inventory strategy it’s critical to take a holistic view beyond individual sites and functions for real cost optimization. While inventory acts as a great “risk buffer,” we find many companies, especially those with intermittent demand, have supply plans or safety stocks based on wrong assumptions about demand uncertainty, and as a result targets go unmet and supply chains go into firefighting mode. When planners stop trusting forecasts they usually err on the side of holding too much safety stock. This leads to excessive costs, waste and obsolescence. It’s better to hedge your bet through probability forecasting, which helps you find your “sweet spot” of cost and service. Read more about inventory optimization for the digital age.


4. Winners are making supply chain complexity work to their advantage. Our customer MANN+HUMMEL, a leading air filtration products company, had a tough mandate to maintain a high parts fill rate while reducing inventory levels. Sergio Bellacicco, Vice President Global Logistics, Automotive Aftermarket shared his company’s journey to satisfy both sales and finance amid the complexity of multi-echelon spare parts logistics. ToolsGroup MEIO helped MANN+HUMMEL deal structurally with its slow moving items and reduce complexity. Instead of planners having to pick the best algorithm for a given situation, one adaptive algorithm automatically generates a reliable baseline forecast for every SKU – even in MANN+HUMMEL’s highly complex multi-echelon supply chain. The result was inventory levels slashed by 12 percent in less than four months and end-to-end network visibility for a more efficient operation.


Sergio mentioned in his Gartner talk that automation is a critical ingredient for success, and that he makes sure his team understands their roles are changing and that it’s critical for planners to lean on the machines for better outcomes and greater productivity.


5. Changing fulfillment strategies make understanding your customer even more critical. Is fulfillment speed a “race to the bottom”? Gartner analyst Tom Enright had a particularly interesting session revealing that service means different things depending on your customer, and it’s more critical than ever to understand what they really want. Not everyone wants super quick delivery. Now consumers want more options and ways to reduce packaging and emissions. As a result, fulfillment is changing, including direct to consumer, dark stores, and city hubs. In-store fulfillment isn’t just grocery anymore. The key, explains Tom, is having the analytical capability to position inventory across the network to fulfill changing demand. You need a richer, more credible demand signal to make it happen. It all comes back to understanding your customer demand, and delighting them by providing the items they want when they want them.


[1] Gartner: Current Use Cases for Machine Learning in Supply Chain Planning Solutions. Analyst: Tim Payne. 19 May 2018



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