Optimizing Production Schedules with Safety Stock Requirements

Optimizing Production Schedules with Safety Stock Requirements

Looking to reduce inventories? Production Scheduling Optimization may have bigger impact than improving forecast accuracy. One consumer goods manufacturer finds optimizing Production Schedules with Safety Stock Requirements has largest impact according to Filippo Focacci, a product manager at IBM ILOG.

According to a recent article in Supply Chain Digest, many companies look to improving their forecast accuracy as a key driver of inventory reduction, from the common sense view that better predicting what customers are going to buy will enable companies to better match planned inventories with actual demand.

But that might not always represent the lowest hanging inventory fruit for many manufacturers, according to Filippo Focacci, a product manager at IBM ILOG.

According to Focacci, there are three main areas in the supply chain that can have a significant impact on overall inventory levels:

  • Forecast accuracy
  • Where and at what levels inventory is positioned within a multi-echelon supply chain network
  • Production planning and scheduling decisions

Speaking on a recent Videocast on the Supply Chain Television Channel, Focacci said that many companies think about factory planning and scheduling in terms of production costs, but often do not fully understand the significant impact manufacturing optimization can have on inventory levels as well – often a delivering greater reductions in inventory that might come from improving forecast accuracy can.

IBM recently worked with one consumer manufacturer to analyze this specific question. The analysis considered two main variables: (1) improving forecast accuracy, measured in terms of reducing variability of forecast demand to actual demand; and (2) improving optimization of production planning and scheduling, including better optimization of safety stock levels in conjunction with the production schedule.

In this analysis substantially reducing forecast error variability from .7 to .2 would lead to a 10% reduction in total inventory levels.

However, if the company “takes a holistic view across production and inventory planning, we would reduce the inventory by 25%,” Focacci said. “If we do a better job of [factory] planning, we can achieve a better reduction in inventory costs, rather than what we can get through improving the forecast, which is typically what everyone has in mind when talking about reduction in inventory.”

If the improved planning capability is first adopted, the reduction in forecast error would actually generate a 17% further improvement in inventory reduction, versus the 10% from improving the forecast alone.

“The key is doing production planning and inventory optimization together,” Focacci said. “You need less safety stock because you are doing better production planning” versus a given forecast and customer order due dates.

The challenge, of course, is how to quantify the likely impact of any or all of the three inventory drivers (forecast accuracy, inventory positioning, improved factory planning). It is not obvious at first to many companies that forecast error may not actually be the best target for inventory reduction.

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