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Imagine, if you will, a supply chain where the repeated sequence of events is like this:

  1. Consumers buy products (day 1)
  2. At the end of the day, the retailer send the shelf take-away data to the distributor
  3. The distributor ships the quantity consumed (yesterday) to the retailer (day 2)
  4. At the end of the day, the distributor sends shelf take-away data to the wholesaler
  5. The wholesaler ships the quantity consumed (the day before) to the distributor (day 3)
  6. At the end of the day, the wholesaler sends shelf take-away data to the manufacturer
  7. The manufacturer ships the quantity consumed (the day before) to the wholesaler (day 4)

SupplyChainConcepts DemandDriven.jpg

The retailer would need to keep an inventory of an average day’s demand, plus some quantity to cover variability in daily demand (assuming zero variability in supply—just for this example’s sake). Each participant in the supply chain would also need to keep on-hand a quantity equal to an average day’s demand (at their aggregate levels), plus some quantity to cover variability in demand.


Forecasting requirements

Forecasting would be virtually eliminated. I say, “virtually,” because if artificial demand variability is introduced into the supply chain through policies and procedures—like, short-term price promotions or quarter-end sales incentives for the salespeople or channel participants, then, of course, the impact of those short-term changes in demand must be estimated (forecast) and accounted for in the ordering and replenishment process.


Lots of agreement

There is lots of agreement that this approach to supply chain management would work—in theory. There is also lots of agreement among supply chain managers as to why this approach is “impossible to achieve” in most circumstances.




Let’s agree that this idealistic supply chain may, in fact, not be achievable in most real-life circumstance.


Back to our current reality

But, let’s look at how most supply chains today actually function (or, fail to function, in too many cases).

SupplyChainConcepts As-Is.jpg
This supply chain look quite similar to the idealistic supply chain above. That is because what are not shown in this simple diagram are all of the trouble-causing delays introduced into supply chain execution.


Here is what the steps look like:

  1. Consumers buy products over days 1 to r
  2. Day r +1, the retailer places an order with the distributor
  3. The distributor accumulates actual demand over one or more days (d)
  4. On day r + d + 1, the distributor places an accumulated order with the wholesaler
  5. The wholesaler accumulated actual demand over one or more days (w)
  6. On day r + d + w + 1, the distributor places an accumulated order with the manufacturer
  7. The manufacturer may also accumulate orders over 1 or more days (m) before producing the products
  8. On day r + d + w + m + 1, the manufacturer produces the required goods


Since consumer shelf take-away data probably does not flow end-to-end across this supply chain, the manufacturer that produces the goods is separated from knowledge of actual consumer demand for its products by, at least, r + d + w + m days, plus any additional delays induced into the order process by excess inventories being held anywhere in the supply chain.


If these numbers are typical, they might look something like this:

  • At retail (r) = 1
  • At distributor (d) = 7
  • At wholesale (w) = 14
  • At manufacture (m) = 14


This, in itself, is problematic.


How do most address this situation in the supply chain?


Unfortunately, for a great many small to mid-sized companies—companies with sales, perhaps, into the hundreds of millions of dollar—the answer to this problem is sought primarily in finding ways to improve forecasts and optimize inventory quantities to cover over the days of delay and the negative effects introduced into the supply chain.


Companies appear to be willing to spend hundreds of thousands of dollars to carry more inventory and to purchase more and more advanced analytics in order to produces more and more sophisticated “guesses” about what their market will actually be like 30+, 60+, 90+ or even 120+ days into the future.


Is this really necessary?


We do not believe that this is really necessary in a great many cases.


Maybe you can’t cut your supply chain replenishment cycle from where it is today to a daily cycle. In fact, it is likely you cannot—and should not. However, it might be a very good step to produce a plan for improved supply chain collaboration to cut your current supply chain end-to-end cycle in half over the coming six months. Then, perhaps you can look at halving that cycle-time again six months or a year later.


Much of what is necessary to make such changes are low-cost, or even no-cost, solutions.


We think these options deserve more attention.


Please let us know your thoughts on this matter by leaving your comments below.


Dealing with complexity

Posted by RDCushing Nov 19, 2014

Supply chain professionals— folk who are, apparently, much smarter than I am— have told me that, in supply chains, there can be both “good” complexity and “bad” complexity.


Let me try to explain the difference:

Kind of Complexity


Good” Complexity

Complexity that functions as a barrier to keep competitors from entering the market with the same or very similar product or service


“Bad” Complexity

Complexity that does not bring with it any known competitive advantage

While this may be true, my concern is that some supply chain professionals may try to reclassify complexity that brings no competitive advantage as “good” complexity simply because it provides cover for not having to try to get rid of some particularly in-transient complexities in the supply chain systems.


What do we do with complexity?

We humans do not really like anything we cannot fully comprehend. We harbor a certain fear of what might come from the things that we do not understand. This fear is generally manifested in avoidance.

CRT_A Dealing with Complexity.jpg


This may be what is being manifested when a manager reclassifies—in his or her mind, at least—“bad” complexity into “good” complexity. That does not actually get rid of the complexity, but it does alleviate the fear of actually having to come to grips with it and deal with it.


In complex systems—like companies and supply chains—one of the ways we deal with complexity is to try to break down complex systems into subsystems. In this way, we hope to be able to more clearly comprehend what is going on within the subsystem, even if we cannot fully comprehend all of the complexities in the total system.


In a company, these subsystems generally correlate to departments and functions. In a supply chain, these subsystems break down into departments and functions internally, and into companies (e.g., vendors, distributors) and some external functions (e.g., 3PL, logistics), perhaps.


Un-Desirable Effects (UDEs)

There are undesirable effects that come from attempting to impose our means of getting to some level of simplicity on apparently complex systems.


One UDE is that we attempt to improve the overall system by managing each subsystem—each department or function—toward localized improvement.


This leads to additional UDEs, because systems tend to have more friction between subsystems—read: departments or functions—than within each department or function. The metrics used to manage warehouse inventory levels, for example, frequently have a dramatic impact on other departments and functions like sales, customer service, channel management.


Not infrequently, the metrics we employ in trying to optimize one department or function causes conflicts with the metrics we want to employ in optimizing another department or function.


Using our preceding example, the sales department gets upset when orders cannot be fulfilled because of inventory shortages. The salespeople get measured on sales, of course.


But, the inventory manager just got called on the carpet in the CFO’s office because inventory dollars are going through the roof; and the inventory manager gets measured on how “efficiently” he (or, she) manages inventory—generally, meaning higher turnover rates.


System Thinking

There is a solution to such dilemmas. We frequently help companies get a grasp on how their whole system—read: entire company, or entire supply chain—operates. We do it using tools with impeccable credentials and proven effectiveness.


You can learn more about the tools we use by reading here.

Recently I read a report entitled “Developing Supply Chain Strategy: balancing shareholder and customer value – A Management Guide”. This report was released by the Cranfield School of Management, Cranfield University (UK). Here is what the forward had to say about the publication:

The Guide has been developed through 7 [sic] years of practical engagement with over 70 firms striving to achieve supply chain excellence. We acknowledge the importance of the insights we have gained from those we have worked with, many of which form the basis for the cases and illustrations we use….


I quote the forward in order assure you that the illustrations used in this article stem from real-life situations. And, likely, not from an isolated incident or two, but from an array of firms involved in the seven year study.


Typical strategic objectives

The accompanying table is taken from the study and is for a FMCG (fast-moving consumer goods) company.




Business Unit

Operating Firm






Global growth: +10%

Global growth: +10%

Global growth: +15%

Profit (IBT)

Global: +$5bn (10%)

Global: +$1bn (12%)

+$100m (6%)

Cost Savings

Global: +$500m (20%)

Global: +$200m (20%)

+$20m (10%)


Maintain 15%

Maintain 15%

Maintain 10%

Cash Flow

Global: +$150bn

Global: +$60bn







From 40% to 50%

From 35% to 45%

From 30% to 40%


+10 new products

+8 new products

+5 new products


Hold #1 position

Grow to match #1 in market

Grow to be #2 in market






Global: 98%

Grow from 90% to 98%

Grow from 90% to 98%


Enlarge key accounts by 20%

Enlarge key accounts by 20%

Add one new key account






Global: processes and organization

Global: processes and organization

Global: processes


Global: supply chain management

Global: supply chain management

Global: supply chain management


Global: IT

Global: IT

Global: IT


These are certainly worthwhile objectives for any firm. Although, we might ask a rational question regarding the “cost savings” portion of the strategic objectives: if the firm truly believes they can squeeze half-a-billion dollars of cost out of their firm, why is this a “strategic objective”? After all, one should rationally assume that if the $500m is in the strategic plan, they must have some idea where this large some is presently being wasted; and, if they do, why wait for some strategic future to take care of it?


Waste, if it is present, should be stopped today, not at some “strategic” time in the future. This is especially true of it means adding $500m to the bottom-line.


Next, we will talk about a more troubling matter in this report: trade-offs.


So-called shareholder and customer value trade-offs

The following table indicates how management at the various levels in this FMCG company feel about what they feel are necessary “trade-offs” to be address during strategic and tactical execution.




Business Unit

Operating Firm

Shareholder value (SHV) versus customer value (CV)

Balance SHV and CV

Balance SHV and CV

Balance SHV and CV

Sales growth (SG) versus cost reduction (CR)

Balance SG and CR

Balance SG and CR

Place emphasis on SG over CR when in conflict


I emphasize that the concepts laid out in this “trade-offs” table are troubling because, I am convinced that the assumption that these so-called trade-offs even need to be made is incorrect at its core. And, I’m not alone in this belief.


Toyota, which is without doubt one of the most successful corporations in the world today by any number of measures, would never accept the rationale that these trade-offs need to be made.


Toyota, for example, holds as a core value that if the value delivered to the customer is constantly increased, so, too, is the value for the shareholder. Toyota—and companies like it—never sacrifice long-term gains in delivering both customer and, thus, shareholder value to short-term interests that might appear to increase shareholder value at the expense of the value delivered to the customer.


Similarly, no company—to my knowledge—ever became a leader in its market by cutting costs. They became market leaders by focusing on increasing Throughput. And, whether these firms would necessarily articulate it precisely as we do here, such for-profit organizations generally view Throughput as the rate at which the company is achieving more of its goal, where the goal is making more money tomorrow than they are making it today.


While costs are certainly not immaterial, and firms certainly need to be cognizant of cost incurred in producing Throughput, a consuming focus on costs (we call it “cost-world thinking”) will ultimately eat away at a company’s ability to compete and survive. Indeed, in the 1980s—the heyday of cost-cutting and right-sizing—many of the Fortune 500 firms that were self-described “cost-cutter” were no longer among those in the Fortune 500 a decade later.


We believe that companies and supply chains need to be focused on increasing Throughput and, while managing costs, not focusing on cost-cutting. Certainly, they should never “balance” sales growth opportunities with cost-cutting. After all, the math is simple:


∆P = ∆T - ∆OE

where ∆P = change in Profit, ∆T = change in Throughput, and ∆OE = change in Operating Expenses;
and T is defined at Revenues less Truly Variable Costs (TVC);
and TVC is limited to only those costs that vary directly and incrementally with changes in incremental Revenues
(no allocated expenses)

Dangerous trade-off paradigm

The danger of the paradigm that induces companies to believe they must make the kinds of trade-offs indicated in the study (i.e., shareholder value v. customer value; sales growth v. cost reduction) is that the underlying assumptions lead to management decisions that, in turn, lead to mediocre performance by most companies. After all, it is a statistical fact that most companies will be mediocre.


Our experience in working with small to mid-sized business enterprises and their supply chains tells us that we can supply the tools to help management become clear on matters that can lead to far better than mediocre performance. We will talk more about those tools and methods in future articles. Come back to find them soon.


In the meantime, we would be delighted to hear your comments regarding the thoughts presented here. Just leave your comments below. Thanks.

Are you disappointed with not being able to discover the answers to the following questions in your business or your supply chain?

  1. What needs to change so that we can make more money tomorrow than we are making today?
  2. What should the change look like?
  3. How can we effect this change?What You Want v What You Get.bmp


Lisa Anderson recently wrote in “Strategy is easy; Execution distinguishes leaders”:


“It is interesting to sit back and watch as companies spend millions of dollars on strategy formulation, just to achieve minimal results due to poor execution. Yet, the process repeats constantly – more money is dumped into strategy formulation, 3 ring binders, fancy Power Point slides, etc. On the other hand, I’ve found that strategy doesn’t fail in formulation; it fails in execution.


“So, why not focus the resources on execution? In my experience, it might be due to the fact that execution isn’t viewed as the exciting or ‘high-level manager’ activity. Give me a company that is excellent at execution with an ‘ok’ strategy anytime vs. a company with an awesome strategy with ‘ok’ execution….”


I would like to suggest that there are some other, perhaps additional, reasons so many companies spend so many of their valuable resources—time, energy, management attention, money—on strategy and still fail when it comes to achieving big—or even, consistent—success and improvement.


What holds companies and supply chains back from achieving more of their goals set by strategy?

A great many times, when we are faced with difficult—or, seemingly impossible—choices in our path toward fulfilling our strategy for success and ongoing improvement, we simply respond in self-defeating ways:

  • We lower our expectations
  • We compromise—attempting to please everyone by taking the worst of the best and the best of worse
  • We avoid taking ownership of the issues at hand—finding someone else to blame (hopefully, someone outside our company)
  • We find ourselves halting between two opinions—we oscillate between taking first this action, then that action, because both options have some negative consequences
  • We simply give up and start ignoring problems that we think we can’t do anything about


Taking any of these approaches does not lead to success or ongoing improvement.


Yet, a great many executives and managers in businesses of all sizes, in all sorts of industries, do just that. In fact, if you are honest, chances are my readers have had first-hand experience with taking one or more of these no progress responses to challenges they have faced in the past.


There is an art—even, a science—to really effective problem-solving

Eliyahu Goldratt once wrote: “We grossly underestimate our intuition. Intuitively we do know the real problems, we even know the solutions. What is unfortunately not emphasized enough, is the vast importance of verbalizing our own intuition. As long as we will not verbalize our intuition, as long as we do not learn to cast it clearly into words, not only will we be unable to convince others, we will not even be able to convince ourselves of what we already know to be right. If we don't bother to verbalize our intuition, we ourselves will do the opposite of what we believe in. We will ‘just play a lot of games with numbers and words.’” – Theory of Constraints, (Great Barrington, MA: North River Press, 1990), p.3.

CRT Example Excerpt A.jpg

The key to effective problem-solving is verbalizing our intuitive knowledge and reasoning.


Doing this in prose has little effectiveness, however. It’s too hard to digest. It’s too difficult to rewrite. It’s too difficult to visualize the cause-and-effect flow of our reasonings about the issues and challenges we face.


That is precisely why Goldratt came up with the Thinking Processes (Theory of Constraints).


Compare these two methods of expressing the same thoughts:


Method 1: Prose – If we say, “we know” because we believe that we understand how our business works and, therefore, how to make it better and what we think we know about our business is not accurate or properly understood, then sometimes we make changes in our business expecting one result but get another—sometimes negative—result instead. And, if that is true, then that would explain why we have already tried many things that have had little or no positive effect on our bottom-line. Hence, we now sometimes have doubts about what we think we know about how our business works or fails to work.


Method 2: Logic Diagram – Now, compare reading and comprehending the paragraph above to reading the accompanying diagram from the bottom to the top using IF…THEN statements.


Consider, also, which method of “verbalized intuition” would be easiest to revise—perhaps, multiple times—and be clear to the new reader with each revision.


My experience tells me that the Current Reality Tree (CRT) excerpt in the accompanying diagram gets the most votes.


Articulating and understanding our Un-Desirable Effects (UDEs)

Many organizations try to improve through “business process re-engineering” (BPR). I have been to organizations that, as Lisa Anderson stated above, spent tens of thousands of dollars and managed to accumulate several three-inch and five-inch thick three-ring binders to describe each and every process carried out within their enterprises.


Unfortunately, those kinds of flow-charts and prose generally do not capture where the real challenges to ongoing improvement lie.


Our experience tells us that the biggest hindrances to a process of ongoing improvement (POOGI) in most organizations and supply chains are not found in the processes themselves—or even the automation applied to those processes. The biggest hindrances are

  1. Policies – both written and unwritten
  2. Training – how employees are trained (are they trained “to think”, of just “to do”)
  3. Metrics – how are employees, departments, managers and executives measured


The diagram of the CRT excerpt is a “flow-chart” of sorts. But it is not a flow-chart of work. It is a flow-chart of the underlying “thinking,” assumptions, policies and the effects of training and metrics that affect outcomes all across the organization or supply chain.


This kind of approach helps uncover the real issues that are keeping a company from making more money tomorrow than they are making today.


Resolving conflicts and inventing solutions

The Thinking Processes provide logic-based tools to help organizations

  • Visualize and resolve conflicts
  • Surface and validate or invalidate underlying assumptions
  • Resolve interpersonal or interdepartmental conflicts
  • Empower participants to visualize and innovate
  • Invent real and effective solutions
  • Manage the organization upwards – toward ongoing improvement

Execution is everything

As Lisa Anderson so appropriately pointed out, the failure of organizations to actually achieve real improvement—a durable competitive advantage—is almost always rooted in execution failures, not in strategy failures. An company may fail to create a strategy. But, if they do create a strategy, I am doubtful that many corporate or supply chain strategies are focused on “being a fair-to-middling company making a minimum of profit and eeking by year after year.” Nevertheless, that is precisely where a great many companies find themselves—year after year.


Linking strategies to effective tactics

Successful execution is derived from the ability to link effective tactics directly to the strategies that have been developed. The Thinking Processes provide a step-by-step method to build effective tactics to take a firm and, perhaps, its whole supply chain, from where it is today—its current reality—to where it wants to be (as indicated by its strategies).


Don’t stop with strategizing and then feel like your vision can never be achieved because you feel trapped in your “current reality.” There is help and there are tools available.


We would be delighted to hear what you have to say on this topic. Please leave your comments here.

Recently, a client of ours was taking steps toward Lean RfS (Repetitive Flexible Supply) as we had suggested in our report to this client. (Read more about Lean RfS here and here.)

LEAN RFS Buffer Sizing example.jpg

The client was stuck trying to figure out a way to make the transition to Lean RfS when he saw high levels of demand volatility in some of the firm’s green stream SKUs. To be fair, this client has some other limiting factors in its supply chain and production:

      • Short product shelf-life (they produce refrigerated food products with relatively short times to expiration)
      • Some limitations around batch sizing not driven necessarily by policy, but physics

Nevertheless, we are finding a way to help them make the transition.

Given demand variability, which is driven in part by the mode in which this firm’s customers order, this client wanted to know how they could possibly move to the “flow” of RfS and not end up with huge overstocks on weeks when demand was well below normal.

The following is based on our response to this client’s inquiries:


We are pleased that your are, in fact, taking steps toward Lean RfS, as we suggested in our report.

With the specific issue you are asking about, however, we think you might be leaping to a weekly RfS schedule with too much haste or, perhaps, not giving due consideration to all of the factors. Allow us to elaborate.

The first question we would ask is this: When you performed your Glenday sieve analysis, how many items were in your green stream? That is, what number of SKUs account for 50 percent of your volume activity? This tells us how many SKUs should be targeted—ultimately—for the potentially weekly cycle.

Most organizations do not attempt—and we do not necessarily recommend—leaping from today’s non-RfS mode of scheduling immediately to a weekly RfS schedule. Because the ability to slash changeover or set-up times comes with repetitive practice, it generally makes some sense to begin with, say, a monthly or bi-weekly RfS schedule first. Then, after some months of practice, and a POOGI (process of ongoing improvement) focused on improvements in changeover/set-up times, it may be practical to move to a weekly RfS schedule. This new schedule may be predicated on shorter runs of each product than may be practical under today’s scenario because changeover times have been dramatically or, at least, significantly reduced.

Another factor to you should take into consideration is the “tank” or buffer size you establish for each SKU in your green stream. The buffer size should be determined by product demand variability. The greater the demand variability (as a percent of average demand), the larger the buffer required to accommodate that variability. How have you gone about determining your proper buffer size? You should be able to use Excel, for example, to do a simulation of buffer sizes and production schedules for a SKU (using the last 12 months of actual demand) to see if buffer sizes and production schedules are achieving your desired end for RfS.

Establishing an initial buffer size that is likely to cover your demand (in light of the replenishment cycle under the new regime) may come from relatively simple analytics around average weekly demand and standard deviations. In the accompanying figure, for example, establishing an initial buffer size somewhere between the average demand an one standard deviation above the average probably makes sense. After the initial buffer size has been established, however, the buffers should be dynamically managed by rules (see below).

It is important to note also that there may be demand variability that drives other decisions relative to green stream SKUs. For example, let us say that you have established a weekly RfS schedule (at some time in your future), and this particular SKU you are considering is part of the green stream. You would still monitor buffer penetration and dynamically manage the buffer size. Much of the dynamic buffer management can be automated with relative simplicity.

Rules governing dynamic buffer management are typically along these lines: if a buffer penetration is between one-third and two-thirds at each replenishment point, then no action need be taken. The buffer is properly sized to accommodate demand variability.

If, however, buffer penetration is found above two-thirds (67% or greater) at two or more consecutive RfS replenishment cycles, then you should consider increasing the buffer size by one-third. Similarly, if the buffer penetration is in the top one-third of the planned buffer (less than 33% or overstocked) on three or more consecutive RfS cycles, then we suggest that you reduce the buffer sized by one-third.

As part of dynamic buffer management, it is necessary to also institute a “cooling-off” period after each change in the buffer size. For increases in the buffer size, allow a cooling-off period of at least one full replenishment cycle. For decreases in buffer size, do not start counting buffer penetrations for further adjustment until the buffer has fallen from above (overstock position) into the top one-third of the buffer during a replenishment cycle.

Whenever dynamic buffer management rules trigger a change in the buffer size, it is wise also to determine if the cause is excess variation in demand or unexpected variation in supply. The RfS plan should be changed if there is an apparent persistent risk of service disruptions (out-of-stocks) or distressed stock (obsolescence in overstocks) from the combination of the buffer size and the present R¦S plan.

Also, if demand variation (or a disruption by Murphy) indicates a severe potential out-of-stock condition in the near future, then you should consider running the SKU on the red line, in addition to its normal R¦S scheduled run on the green line. On the other hand, if your monitoring shows that you are likely to create an overstock condition of more than one-third of the present buffer size, then you should consider canceling the next RfS-scheduled run for that SKU.

Of course, known variations in demand (that is, policy-induced demand variances) should be accommodated in your RfS schedule and dynamic buffer management. For example, if you know in advance that demand is likely to leap 30 percent over a two-week period due to promotions being carried out by your sales channel, then adjustments to the buffer size and/or RfS schedule should be made at least one replenishment cycle prior to the known change in demand. Typically, these RfS schedule changes simply mean a longer run, or supplemental runs of green stream SKUs on the red line, in addition to the normal green stream RfS routine.

If you need further assistance in working through any of these matters, please do not hesitate to let me know. RfS and dynamic buffer management take some practice and it is a culture shift. These changes should be introduced with executive-level support, of course, but also by carefully and thoroughly training those who will be affected by the program so that they fully understand why these changes will make their life better in the long-run.

We find that the three leading constraints in almost every business we touch are these:

  1. Policies – written and unwritten
  2. Training – whether people are trained to “think,” or just to “do”
  3. Metrics – how people and work are measured and, especially, when metrics for one department lead to actions that conflict with the metrics in some other part of the organization


The good news about these top issues is that these cost nothing to change. There is virtually no capital investment required to eliminate bad policies or metrics or change the way employees are trained.

Please note that R¦S should also drive improvements in changeover and set-up times. Many times we have found that holding POOGI breakthrough events to innovate around how improvements can be made is well worth the time and effort. Toyota has taken some setups and changeovers that used to take as long as a full shift and, over a period of several years, reduced these changeover times to a matter of minutes (sometimes less than ten minutes). This, too, takes more than just a top-down demand to “get this done.” It takes a change in culture, so that the workers see the work as always reinventing itself. No incremental improvement is too small to be considered.

We’re here to help, if you need us. Thanks for contacting us on this question.


We hope this information helped you, as well. If you have further questions or concerns regard this approach to production, inventory and supply chain management, please post your comments or questions below. You may also feel free to contact us directly.

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