Demand-Driven Manufacturing

Manufacturers face numerous issues from global competition to cost pressures and customers demanding exacting on-time delivery performance. Alfred Sherk, CEO of SherTrack, explains how technologies and methodologies are emerging to address some of the top challenges.

“Complex manufacturers need predictive analytic tools to give them insight into customer demand over the current and next manufacturing cycle”
-Alfred Sherk, CEO of SherTrack

BM. Demand-driven manufacturing in complex production environments is a tough management challenge. What technologies and methodologies are emerging to address some of the issues?
Alfred Sherk. Every process has a capability limit. A demand or pull based fulfillment process is inherently more efficient than a forecast driven process. In facilities that produce many products on the same lines, the complete set of firm customer orders required are not available. Our research has shown that predictive analytics can be successfully applied to actually predict near term orders with defined confidence levels. When variation is properly bounded, probabilistic inventory algorithms that are synchronized with finite scheduling are very effective in determining the optimal production system response.

This breakthrough enables customer orders rather than demand forecasts to drive the production response in complex plants. Eliminating the reliance on forecasts offers vastly improved performance but it comes with a change management challenge.

BM. Why is this especially important in the current economic climate?
AS. Since the credit crisis spread to Main Street in September 2008, all industries have seen dramatic volatility in their demand, which had not been anticipated by most sales forecasts. Many companies did not adjust their production levels until weeks after their order books weakened.

Companies with significant hydrocarbon or energy costs saw their raw material costs and product prices drop precipitously. Those companies with sluggish supply chains had large financial losses on the value of their inventories.

Demand-driven manufacturing operations can sense demand shifts and are inherently more responsive to shifts in demand. As the economy recovers, they will be able to provide better service and more agile responses to their customers and have the opportunity to gain market share, permanently.

BM. What challenges are there in applying continuous improvement initiatives to complex plant operations?
AS. Complex plants are characterized by multivariate and non-linear process relationships that are nearly impossible to analyze with standard tools such as spreadsheets and off the shelf simulation products. For example, how will on-time-delivery be affected by providing shorter lead times? Would more frequent production changeovers be required? The inability to quantify these performance impacts is the roadblock that occurs in the analyze phase of the Six Sigma DMAIC process.

Predictive modeling, based on a detailed and accurate digital representation of the facility, opens up sophisticated design of experiment approaches to determine an operation’s true physical capabilities. Operational strategies and tactics can be assessed without experimenting on your plants or your customers.

BM. We have implemented the supply chain modules from our ERP vendor and we have set up sales and operations planning (S&OP) teams. Can we use these tools to become demand drivers?
AS. For assembly operations, the answer is yes. These tools can be used in a Lean process but the way they are used may need to be modified. However, complex manufacturers’ need predictive analytic tools to give them insight into customer demand over the current and next manufacturing cycle. Forecast systems are incapable of providing order level information. Probabilistic inventory and scheduling are also required to ensure the proper response by operations.

In demand-driven operations, the S&OP teams provide tactical guidance only. It is too slow and unwieldy a process to be used for execution decisions when customer orders drive operations.