Multi-echelon Inventory Optimization and Lean/Six Sigma

The Emerging Role of Optimization in Business Decisions

For many, there was a point in the past when the idea of “optimization” used to summon images of Greek letters juxtaposed in odd arrangements kept in black boxes that spewed out inscrutable results.  Optimization was sometimes considered a subject best left to impractical theorists, sequestered in small cubicles deep in the bowels of the building to which few paths led and from which there were no paths out.  From that perspective, optimization was something that had to be reserved for special cases of complex decisions that had little relevance for day-to-day operations.

That perception was never reality, and today, growing numbers of business managers now understand the role of optimization.  Those leaders who leverage it intelligently, are not just valuable assets, but absolutely essential to achieving and sustaining a more valuable enterprise.  Global competition mandates that executives never “settle” in their decisions, but that they constantly make higher quality decisions in less time.  Optimization helps decision-makers do just that.  The exponential increases in computing power along with advances in software have enabled the use of optimization in an ever-widening array of business decisions.

 

How Lean Thinking Helps

Lean principles are applied to drive out waste.  One of the most predominant lean tools used for identifying waste is Value Stream Mapping which helps identify eight wastes, including overproduction, waiting, over-processing, unnecessary inventory, handling and transportation, defects, and underutilized talent.  In inventory management, this often happens through a reduction of lead times and lot sizes.

The reduction of lead times and lot sizes through lean in manufacturing has focused on reducing setup time to eliminate waiting and work-in-process inventory, as well as the frequent use of physical and visible signals for replenishment of consumption.  One of the challenges is that consumption or “true demand” at the end of the value network is never uniform for each time period, despite efforts to level demand upstream.

Acting and deciding are closely related and need to be carefully coordinated so that the end result does not favor faster execution over optimizing complex, interdependent tradeoffs.

 

The Importance of Six Sigma

Six sigma pursues reduced variability in processes.  In manufacturing, this relates most directly to controlling a production process so that defective lots or batches do not result.  It has been encapsulated with the acronym of DMAIC:  design, measure, analyze, improve, control.

There has been a natural interest in the convergence of lean and six sigma in manufacturing and inventory management so that fixed constraints like lead time and lot size can be continuously attacked while, at the same time, identifying the root causes of variability and reducing or eliminating them.

There are obvious limitations to both efforts, of course.  Physics and economics of reducing lot size and lead time place limitations on lean efforts and six sigma is limited by physics and market realities (the marketplace is never static).

Until it is possible to economically produce a lot size of one with a lead time of zero and infinite capacity, manufacturers will need to optimize crucial tradeoffs. 

 

Crucial Tradeoffs for Manufacturers

In a manufacturing organization, 60% to 70% of all cash flow is often spent on the cost of goods sold – purchasing raw materials, shipping and storing inventory, transforming materials or components into finished goods, and distributing the final product to customers.  So, deciding just how much to spend on which inventory in what location and when to do it is crucial to success in a competitive global economy.  Uncertain future demand and variations in supply chain processes mandate continuous lean efforts to reduce lead times and lot/batch sizes as well as six sigma efforts to reduce and control variability.

As long as we operate in a dynamic environment, manufacturing executives will continue to face decisions regarding where (across facilities and down the bill of material) to make-to-order vs. make-to-stock and how much buffer inventory to position between operations to adequately compensate for uncertainty while minimizing waste.

Taken in complete isolation, the determination of a buffer for a make-to-stock finished good at the point of fulfillment for independent demand measured by service level (not fill rate) is not trivial, but it is tractable.  But, for almost every manufacturer, the combination of processes that link levels in the BOM and geographically dispersed suppliers, facilities and customers, means that many potential buffer points must be considered.  Suddenly, the decision seems almost impossible, but advances in inventory theory and multi-echelon inventory optimization have been developed and proven effective in addressing these tradeoffs, improving working capital position and growing cash flow.

 

So What?

In many cases, the key levers for eliminating waste and variability in any process are the decision points.  When decisions are made that consider all the constraints, multiple objectives, and dependencies with other decisions, significant amounts of wasted time and effort are eliminated, thereby reducing the variability inherent in a process where the tradeoffs among conflicting goals and limitations are not optimized.

Intuition or incomplete, inadequate analysis will only result in decisions that are permeated with additional cost, time and risk.  Optimization not only delivers a better starting point, it gives decision-makers insight about the inputs that are most critical to a given decision.  Put another way, a planner or decision-maker needs to know the inputs (e.g. resource constraints, demand, cost, etc.) in which a small change will change the plan and the inputs for which a change will have little impact.

Multi-echelon inventory optimization perfectly complements lean and six sigma programs to eliminate waste by optimizing the push/pull boundary (between make-to-stock and make-to-order) and inventory buffers as lean/six sigma programs drive down structural supply chain barriers (e.g. lead time and lot/batch size) and reduce variability (in lead times, internal processes and demand).

Given constant uncertainty in end-user demand and the economics of manufacturing in an extremely competitive global economy, business leaders cannot afford not to make the most of all the tools at their disposal, including lean, six sigma, and optimization.