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.

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Pricing, Promotion, Analytics and SCRM

First, I’d like to take this Veterans Day (it is this Sunday) as an occasion to express my appreciation to those who have sworn to uphold and defend our Constitution with their very life.  From one vet to another, “Happy Veterans Day”.  For those of us who have served or do serve as Marines, a “Happy 236th Birthday“.  May all of us remain faithful to the courage, honor and commitment required of Marines in all areas of our lives – Semper Fidelis!

Second, I’ve put together a few thoughtful questions and some questioning thoughts that I hope will stimulate your mind on three important topics – pricing and promotion of consumer goods, making the most of analytical decision support, and supply chain risk management.

On pricing and promotion in consumer goods

If you are a consumer goods manufacturer, you likely purchase syndicated data to evaluate product trends and share by category, market and channel.  If you are more advanced, you have figured out how to leverage this data in your demand planning process so that your SKU forecasts are more accurate.  But, many firms have not yet incorporated it for the purpose of analyzing and optimizing pricing and promotion decisions.  If you haven’t, why haven’t you?

On making the most of analytical decision support

I have argued in previous posts that the process of analytical decision-making is not just math and data, but it is an interactive process through which the analyst must use his or her experience and skill to artfully find information despite defects in the data and deficiencies in the data model.  One case-in-point would be multi-stage, stochastic, inventory optimization (MESIO – for more, see “Who Is Spending Your Cash?”, the 30 September post from Supply Chain Action).  Consider the possible objectives of an effort to improve inventory (a portion of working capital) efficiency.  Here are a number of possible goals:

1. Achieve a stated average time between stockouts
2. Minimize the total value short
3. Minimize the total stockout occasions
4. Minimize the cost per unit short
5. Minimize the cost per unit short per period
6. Minimize the combined costs of shortage, overage and replenishment (think about shipping an individual unit versus a more economical pack size)
7. Achieving a target likelihood of no stockouts in a period
8. Achieving a target likelihood of demand satisfied directly from the shelf (think fill rate)
9. Using idle capacity to build stock that will sell in a specified period of time

Most off-the-shelf applications will only give you one or two of these objectives and necessarily prohibit interaction of the modeler with the model because the software company needs to protect its intellectual property.

This does not mean that an off-the-shelf application will not work for your business.  It may, indeed, be the best answer and provide an enterprise-scale solution that is fully integrated with your other planning operations.  The point is that you have to do some careful thinking and testing in order to validate that it will work and that you will have whatever ability to interact with the model that your analysts will require.

On supply chain risk management

How do you evaluate the resiliency of your value network?  Do you have the capability to electronically represent your value network from one end to the other?  Have you determined how to represent the value (in terms of materiel, currency and data) that pulses along the paths in the value network?  Have you quantified the consequences of a disruption (from whatever cause) that would impact that flow?  If so, do you have a plan for dealing with such an interruption?  What have you done to make sure key people know the plan and can execute it?

Thanks again for dropping by Supply Chain Action.

Until next week, remember this thought from an anonymous source, “Make sure what you do today is important because you are exchanging a day of your life for it.”

Have a wonderful weekend!

Who Is Spending Your Cash?

“Cash is king,” we hear.  I have seen this in the core values of major, multi-national corporations.  If you travel for your company, you likely face restrictions on the amount and/or cost of travel which you can book without very senior level approval.  I know of one company with revenues of about $15 billion in which the CFO has mandated approval of any air fare over $500, even for employees who routinely must book and re-book travel on short notice due to the nature of their duties.  I do not debate the wisdom of such policies.  I only use them to illustrate how carefully the expenditure of cash is scrutinized in many cases.  Capital expenditures require even greater examination and multiple approvals, perhaps even from the board of directors.  Despite these procedures, I pose this question:  “Do you really know who his spending your cash are how they are doing it?”

Consider where most of the cash is spent and who spends it.  In most manufacturing firms, the largest single expenditure of cash is for the acquisition of raw materials and their transformation and distribution, namely, the cost of goods sold.  What is not sold remains on the balance sheet as inventory.  A manufacturer with 40% gross margin is doing very well in most industries, although there are notable exceptions in pharmaceuticals and a few other manufacturing industries.

A 40% gross margin would mean that 60% of the cash inflow from sales is spent on inventory – inventory that is either sold or stored.  In fact, manufactured product (or at least the raw materials, components or intermediates/work-in-process) in every manufacturing operation is stored at some point before it is shipped to a customer.  That is why inventory turns or days in inventory (both relating inventory to sales through the cost of goods sold) are the most appropriate kinds of metrics for inventory rather than the absolute amount.

So, given the relative proportion of cash flow in the majority of manufacturing firms that is spent on inventory of one kind or another compared to, say the proportion of cash flow spent on travel, one might assume that the level of scrutiny and approval required for spending on inventory would be extraordinary and performed at the most senior level of the firm.  Is that true in your company?  Of course not.  Manufacturing and distribution operations would be paralyzed and servicing customers effectively would be precluded by such a bureaucratic approach.

Many firms, today, have a position called buyer/planner.  These are people who must determine how much should be procured, when, and where.  Purchasing or sourcing professionals whose mission is to make sure that the purchase price is minimized support the planning function, but purchase orders are issued by buyer/planners.

Even if “buying” is separate from “planning”, it is the planner who decides how much is needed when and where.

Planners do not rank among the highest paid employees, yet they are pulling the lever to spend the majority of the company’s cash flow.

Most planners today have access to advanced planning and scheduling (APS) tools which embed material requirements planning (MRP – I know this should be “little mrp”, as opposed to “big MRP” for manufacturing requirements planning, but allow me this convention here for visual ease) and distribution requirements planning (DRP) calculations to aid them in determining how much to purchase.  These tools are very helpful.  They are particularly helpful if the forecast is exactly right, if forecast error is always normally distributed, if stated transit lead times are always reality, if yields are constant, if service from one internal manufacturing or distribution point to another is always constant and known.  However, almost none of these conditions are ever true, and they are never true all at the same time.

So, not only do planners have to ultimately determine what to move, make and buy for every item in the bill of material (or formula/recipe) at every location in every future time period in the planning horizon, they must do so in an environment with many unknown inputs.

(At this point, I will include a plug for recruiting, training and retaining the very best planners – not vp’s of planning or directors of planning, but planners themselves since they are likely spending most of your cash!)

This problem is called multi-echelon, inventory optimization (MEIO).   MEIO is fast becoming a best practice requirement.  MEIO optimizes the answer to the very challenging problem of how much extra inventory a planner should plan to have at each location, for every item, at every level, given the many other unknown factors as well.  Put differently, “What is the inventory safety stock level that should be targeted for every item at every location, such that the cost of holding inventory for achieving a given service level is minimized.”  This question must be answered across all nodes while considering all of the unknown factors mentioned above.

When solved, the result is a lower required buffer inventory than could be planned with just MRP or APS in order to achieve an optimal service level.  That means more available cash and more revenue and profits.

Solving the MEIO problem remains a massive challenge for which many planners still do not have sufficient tools at their disposal.  However, algorithms have been developed and can be implemented through commercially viable software.  It’s also increasingly possible to build your own on and advanced analytics platform.  As MEIO continues to be adopted, more planners can go about their normal planning process of determining what to move, make and buy, but with a much better starting point, namely the amount of inventory buffer required at each item, location.  This buffer, or safety stock, already a standard row in a supply planner’s gross-to-net calculation in his or her advanced planning system, allows planners to perform their work without disruption while achieving significantly better results for the cash management of their firm – when populated through MEIO.

Questions:

1)      How do your planners account for the unknown factors in determining how much cash to spend on which inventory in which locations and when?

2)      Are you thinking about evaluating MEIO?  If not, why not?

3)      Can you afford not to pay more attention to where the majority of your cash flow is going?

Careful, Comprehensive Inventory Management (Part 3)

As a memory aid, I use A⁵6σ to represent such a careful, comprehensive, and corporate approach to inventory management.  Each component of A⁵6σ is essential for achieving sustainable, continuous improvement in inventory efficiency.  There are five concepts which I will alliterate with the letter “A” and the tools of six sigma.  Below, is the third “A”.  Please see my previous posts for earlier points.

Accurately – calculate safety stock

We cannot know for certain what demand will be tomorrow.  Even organizations dedicated to consumption-based replenishment of “true demand” cannot know exactly how much will be required of which products, at which locations at which times.

Make-to-order businesses have an easier time of this, but, even then, orders can change and often do.

This is not only true of the demand, but also the lead time to meet the demand which is affected by variation in the ability of manufacturing to respond in a timely and accurate fashion (driven by batch sizes and setup times, by variation in the conversion process, and by other factors), and variation in the transportation operation (caused by traffic volume or accidents, road construction, weather, illness, and any number of other factors), not to mention the capability of warehousing to know what is exactly where and pick, pack and ship it in a timely way.

For these reasons, you must have more inventory than you will actually be needed if everything goes perfectly.

Any other approach implies the intentional loss of revenue.  Done poorly, this can put you out of business.

Fortunately, there are techniques for doing a good job of this through optimization.  Do a bit of research to identify the technique that fits the structure of your operations (single-tier distribution or multi-tier manufacturing, for instance) and get the analytical and software support (if necessary) to embed that technique into the normal planning process.  This can often yield a step-function improvement in both reducing the necessary investment of working capital in inventory as well as in improving customer service.

Combined with the set of decisions around supply chain flexibility with which inventory decisions are interdependent, decisions around inventory are essential to increasing the value of your enterprise.

You can find more on this in my published article, “Don’t Manage a Supply Chain, Lead a Value Network”, just published by the Journal of Enterprise Resource Management (http://www.apics.org.au/Default.asp?page=363).