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Writing in The Measurement Nightmare, Debra Smith* says:


Having the least amount of inventory in the system [read: enterprise or supply chain] is the natural outcome of the following interdependent and necessary conditions:

        1. Producing [only] to order [read: actual demand signals, as opposed to forecasts]**Indecision_metaphor.png
        2. Releasing material at the rate of the constraint or critical process
        3. Reasonably buffering the constraint to ensure it is not starved
        4. Maximizing the uptime of the constraint
        5. Purchasing to ensure a buffer of raw materials so the beginning process can start in time to maintain the constraint’s buffer
        6. Ensuring the reliability of all processes to support reasonable buffer levels in front of the critical processes


Smith goes on to re-emphasize the use of interdependent and necessary in the paragraph above by adding the following:


Be careful here! None of these actions can stand by themselves. All or necessary conditions. The key here is to understand the interdependencies among the above conditions. The conflict [and failure to deliver “good results”] arises when one or two of the conditions becomes the focus for driving improvement methodology. The condition is translated into a “key performance indicator” and becomes the end objective of the improvement process.


How it happens


In working with our clients, it is not unusual for us to hear comments like, “We tried being ‘lean,’ but it just didn’t work for us.” By this, they typically mean, they tried cutting inventories.


What Smith wisely tells us in The Measurement Nightmare is that “having the least amount of inventory in [your] system” is a result of other factors. Starting out with a metric that leads to mindlessly slashing away at inventories is almost inevitably going to lead to more problems, higher expediting costs, and increased fire-fighting requirements.


This is especially true if you are still building to forecasts—because forecasts are always wrong. Only the size of the error varies with forecasts. So, if you are making to forecasts, chances are you are wasting precious (capacity-constrained resources) resources building things that the customers do not want and are not going to buy. Meanwhile, you are suffering shortages on the things that customers actually do want and are ready to buy.


Taking All the Steps


Demand-driven supply chains have demonstrated proven success when firmly grounded in a program where none of the steps are omitted. The five steps to achieving demand-driven excellence in performance are these:

DDMRP 5-Steps to Success.png

      1. Strategic Inventory Positioning – identifying where in your supply chain strategic buffers will deliver the highest return on investment
      2. Setting Buffer Profiles and Levels – classifying your inventories according the supply-side and demand-side variability, lead-times, and replenishment requirements
      3. Instituting Dynamic Buffer Adjustments – assuring that inertia does not overtake your system, by instituting dynamic buffer adjustments (generally done with some level of automation)
      4. Creating a Process for Demand-Driven Planning – demand-driven planning involves using forecasts to manage capacities and to scale buffers according to foreseeable events, among other things
      5. Building a High-Visibility and Collaborative Execution Process – recognizing that supply chain management must involve all of the functions (e.g., sales, operations, key trading partners) in a collaborative process that seeks to identify changes in the market before the changes become “problems”



With these five steps in mind, we can only reiterate Debra Smith’s sage advice:


“Be careful here! None of these actions can stand by themselves. All or necessary conditions” if you want to achieve the highest return on assets for your investments in inventory and capacities.


If you want the best results, don’t try to take actions without seeing the effect on the whole system—the whole enterprise, or the whole supply chain.


We can help.


Leave your comments below. We would be delighted to hear from you.



* Smith, Debra. The Measurement Nightmare - How the Theory of Constraints Can Resolve Conflicting Strategies, Policies, and Measures. Boca Raton, FL: St. Lucie Press, 2000.

** Producing to actual demand signals does not necessarily mean—and frequently does not result in—“make to order.”



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We previously published a letter to client, because the letter included some good advice with broad application to supply chain managers. Here is another you might find interesting.



Dear [Client]:


We frequently have the illusion of control when we have access to lots of data. However, the real user experience is that the more data there is to be consumed, the more attention is diffused—rather than being focused.


Consider the complexity of the discussion you and your team held around this screen (as an example):


[Identifying product information redacted]


In real life, after a protracted discussion over all of the detail that is available in such a system, it will not be unusual (I would guess) for five persons involved in the discussion to come away with two or three different conclusions as to the best action to take—for that one SKU! Now, multiply that by having to look at a dozen or more items that may be considered “critical” at any one meeting.


Think about this: Nothing on the screen above provides a single, clear, unambiguous metric that tells your team whether action on this SKU should be prioritized higher or lower than action on some other SKU needing attention.


Compare that to the methodology and simplicity found in demand-driven approaches:

DDMRP Priority Signals.jpg

While the above figure references the priority for a given purchase or make orders, the same exact principle applies across the entire gamut of decision-making in the demand-driven approach. There are two unambiguous signals:

  1. Color – Red, yellow and green; where RED is always prioritize over YELLOW, and YELLOW is always prioritize over GREEN. This color designation is determined by BUFFER PENETRATION (whether that buffer is a stock, time or capacity buffer).
  2. Buffer % - Percent of buffer remaining (the inverse of BUFFER PENETRATION—that is, a 97 percent buffer penetration is a 3 percent remaining buffer value); where the lower the BUFFER %, the higher the priority for action.


Remember also, that this simple, yet elegant, signal is really virtual buffer status, already taking into account factors such as

  • Replenishment supply on the way (e.g., open PO lines, open Transfer lines)
  • Demand spikes within the replenishment horizon
  • Other factors (where applicable)


After looking at a short list of items in the RED ZONE, or low in the YELLOW ZONE, any cross-functional team of five or six will almost always depart company having a single and collaborative view of priorities and actions.


When considering a demand-driven POOGI (process of on-going improvement), think also of the relative simplicity of the following types of metrics:

  • Unacceptable Service Level Performance
    • Cumulative days in Critical Red Zone of the last 180 days
    • Cumulative days in stock-out (Black Zone) of the last 180 days
    • Cumulative days in stock-out (Black Zone) with demand (SOWD) of the last 180 days

  • Unacceptable Flow Performance
    • Cumulative days in Green Zone of the last 180 days (> 15 days)
    • Cumulative days Over Top of Green (OTOG) of the last 180 days (<= 15 days)
    • Cumulative days OTOG of the last 180 days (> 15 days)


A monthly cross-functional POOGI meeting that analyzes the (hopefully) few items that appear on lists based on these kinds of metrics can readily Pareto the determined causes and innovate to reduce occurrences in the future using the 80/20 principle.


I think, perhaps, you can see why Einstein wisely observed, “Everything should be made as simple as possible, but not simpler.” Effectiveness is found in simplicity, because it also allows managers to use their limited time to FOCUS on the truly important matters that need attention for improvement tomorrow.


This is by no means an intent to cast aspersions on [product name redacted] as a solution. Almost all of the solutions on the market today are too complex. Sage 500’s Inventory Replenishment and MRP (materials requirements planning) are too complex. Both processes provide calculations on what should be done for replenishment, but they do not supply unambiguous signals for prioritizing action nor focus management attention. SAP’s traditional methods are too complex. All of the traditional methods provide complexity because of the false assumption that more data means better management.


Also, developers get paid for creating complexity; and—for better or for worse—complexity demonstrates well as “bells and whistles.” People are impressed when they see lots of data and lots of complexity. Here again, this is largely due to the fact that people actually believe that more data leads to better management.


It is simply a false assumption. If more data led to better management, then virtually every firm in the U.S. would be managed hundreds of time more effectively today than it was being managed in 1980. But, we all know that isn’t true. The data has changed, and access to data has changed, but management methods are largely the same; management thinking is largely the same; and the attention of management is diffused while trying to digest the volume of data now available to them. They are generally unable to distinguish the relevant information from the plethora of irrelevant information.


Just some thoughts for you and your team to consider triggered by today’s conversation. I hope you find them worthwhile.




Questions? Ask us, or leave your comments below. We would surely like to hear from you.


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Letter to a Client

Posted by RDCushing Oct 7, 2016

We thought you might be interested to know what kinds of correspondence we might have with a real client that is seeking solutions to the current supply chain and inventory management challenges. Here is a real-life example.




Dear [Client]:


Thank you for the opportunity to participate in today’s discussions regarding your firm’s current challenges and opportunities.


We want to be very clear as to what I have been calling strategic inventory positioning. In order to reap maximum return on investment from inventories in a multi-echelon environment (such as manufacturing, or in a multi-level distribution network), there are five crucial steps.

DDMRP 5-Steps to Success.png

The first step simply cannot be overlooked or missed. It is truly foundational.


Most organizations with which we work believe—and, even, know—that their inventory is a strategic investment. Chances are, it is also one of their larger balance sheet assets. Nevertheless, beyond recognizing that it is “strategic”—in the sense that it is a relatively fixed investment and that their business would fail without it—most of inventory managers and supply chain executives are unable to tell you HOW and WHY (in dollar terms) the investment of dollars in a specific SKU-Location is the right one, and how it is optimizing their ROI.


There are, we believe, critical factors in determining strategic inventory positions and investments:


  1. Customer Tolerance Time – The time the typical customer is willing to wait for a given SKU before seeking an alternative source of supply. APICS has a roughly equivalent term in “Demand Lead Time,” which it defines as “The amount of time potential customers are willing to wait for delivery of a good or a service. Syn: customer tolerance time.”

  2. Market Potential Lead Time – This is the lead time that will allow an increase in price or the capture of additional business from either existing customers or new customer channels. This lead time should be developed through the active involvement of sales and customer service teams.

  3. Sales Order Visibility Horizon – The sales order visibility horizon is the time frame in which you typically become awareDDMRP InventoryProfile_Typical.jpg of sales orders or other actual demand (e.g., transfer orders).

  4. External Variability – Includes the following:
    1. Variable Rate of Demand – Categorized simply has high, medium or low, this term references the potential for swings and spikes in demand that could overwhelm resources (e.g., capacity, stock, cash)
    2. Variable Rate of Supply – Also categorized as simply high, medium or low, this refers to potential for and severity of disruptions in sources of supply for a SKU-Location.


Because these vital factors are frequently under-appreciated, and methods to implement effective change are missing, most organizations that handle inventory use traditional methods and struggle with a bi-modal inventory distribution. That is to say, when looking across their spectrum of SKU-Locations (SKULs), they are quick to admit that the largest number of their SKULs fall into one of two categories:

  • We have too much of this…
  • We have too little of that…


Only a small slice of their inventory is, at any given moment, at what could be described as “optimal” levels.DDMRP WhereRealInventoryValueLies.jpg


Given the fact that maximum return on investment is garnered only by inventory that is strategically positioned, sized and maintained at or near its optimal average inventory value (on a SKU by SKU basis, not just a mythical dollar-value), it is no wonder that companies are constantly sacrificing ROI to lost opportunities, firefighting and expedites on the one end of the spectrum, and to high carrying costs, obsolescence and other factors on the other.


Our hope is that [your proposed solution] can, and will, provide you and your team with the data it needs to strategically position your inventory and size your stock buffers to achieve the highest levels of ROI. We will certainly do all that is in our power to help move your project in that direction.


A recently released book—perhaps the finest written to date on the subject—might be valuable to you and your team as you move forward. The book is entitled DDMRP – Demand Driven Requirements Planning: An Intuitive Proven Planning and Execution Method for Today’s Complex and Volatile Supply Chains, and you might find it worthwhile to buy a copy and share with some in your organization.


While you should read from the beginning of the book—to get the complete picture and a comprehensive understanding of why the methods are so effective—I would call your attention to chapter 7 on “Strategic Buffers.” This chapter shows you how the ROI of every SKUL can be effectively calculated and compared to alternative stocking options. (NOTE: The book was written with a focus on manufacturing environments, but the principles equally to any multi-echelon inventory environment. This is highlighted in the latter portion of chapter 6, where the writes address “Distribution Positioning Consideration.”)

We look forward to helping you and your team achieve significant gains in ROI from your inventory investment over the coming months.


Let us know if you have further questions or concerns on these matters. We look forward to hearing from you soon.


Very truly yours….




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