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I would like us to consider for a moment how it is that the “spend” decision made when it comes to buying new or “improved” technologies?


All too frequently, the ill-considered steps go somewhat along these lines:


FIG-03 ERP Decision to Buy.jpg


I find that this is especially true if the company is…

  • Making reasonable profits and has cash flow to support the proposed spending; or
  • Not making a reasonable profit, but feels it must “spend money to make money.”


Oh, wait! That covers almost the whole gamut, doesn’t it?


Sometimes, however, there are more steps involved. Those steps might go something like this:

  1. “We believe that information is the key to better management.”
  2. “More or better information means we will be able to manage better.”
  3. “Let’s ask some software or hardware vendors or VARs about technology ‘X’ (e.g., warehouse management, logistics management, CRM, ERP, ad infinitum) to see if their technology can give us more or better information and if they think we can manage better if we use their new technology.”
  4. “All the folks we’ve talked to have repeatedly assured us that, if we buy and implement their technology, we will, in fact, be able to manage better because we will have more and better information at our disposal.”
  5. “All our managers and executives have listened to the folks we’ve asked about this matter and they, too, believe we will be able to manage better if we buy the new technologies being proposed.”
  6. “Let’s buy these new technologies.”



There’s a long and tedious history to matter, and I won’t go into it—because I’ve discussed it in other articles, but it seems that somehow it has gotten into the heads of many executives and managers that new technology is like an engine additive for your car.

Frequently, executives and managers seem to think that, if you just “pour in” some of “new and improved” technology every now and then, in some magical way your company will run faster, smoother, longer and get better mileage. No questions asked.


While the number of executives and managers who still hold to this sense is shrinking, even today there are those who remain convinced that they simply have no alterative but to “invest” in new technologies or fall behind their competitors. This despite the fact that “a substantial number of [technology] implementations are not successful and others do not deliver the expected return on investment. In particular, midsize businesses struggle with wringing the most value from their… applications.” [1]

Lack of a comprehensive business case for IT


One of the big problems is that “very few midsize companies create a thorough business case for their [technology] implementations? …They do not understand that [a new or upgraded technology] implementation provides them with an excellent opportunity to transform their businesses…. [2]


After all, if an executive believes that there is no real way to pin-down the value of IT improvements in order to calculate an ROI, then he or she will not take the time to construct a business case with measurable outcomes and specific goals for increasing Throughput, reducing inventories or other demand for new investment, or slashing or holding the line on operating expenses while supporting significant increases in Throughput.

No KPIs for IT improvement projects


Interestingly (and disappointingly), “[w]hen asked point blank if [companies] know what the ROI of their ERP application is, many companies are not sure. And why aren’t they sure? Because they haven’t estimated ROI to begin with.” [3]


In a “recent survey of 920 small and midsize companies shows that 52 percent ‘sometimes’ or ‘never’ estimate ROI to provide justification for an… implementation. An even greater number do not calculate ROI after implementation. There are midsize companies that have estimated ROI; however, many of them do not have the metrics and key performance indicators in place to track ROI sufficiently or drive business goals. Many use static reports that provide historical information, but no on-demand, real-time metrics or predictive analytics that provide better decision-making capabilities and help mitigate risks.” [4]


It would seem as though, if an executive is “not able to track the performance of [the company’s IT systems] and… never had a clear idea of what the ROI might be in the first place, it is very difficult to justify the investment or perceive that it has value.” [5]


Even though many cannot present numbers to “justify” their investment, the still “pour in” the new technologies on a routine basis and, apparently, just hope for the best.

A better way


We think there is a better way. We think there is a simple formula for calculating ROI for improvement projects and helpful tools for unlocking what needs to be known to get reasonable values and KPIs for completing the calculations.


This formula can be read as:

ROI = (the change in Throughput LESS the change in Operating Expenses) divided by the change in Investment; where “Throughput” is defined as Revenues LESS (only) Truly Variable Costs (TVCs).


We’ve discussed other details on this formula elsewhere, so I won’t go into them again here.



We would like to hear your questions and your comments. Please feel free to post your comments and questions here, or contact us directly, if you wish.


[1] Maximizing Enterprise Resource Planning ROI: A Guide for Midsize Companies. White Paper. Somers, NY: IBM Corporation, 2010. Print.

[2] Ibid

[3] Ibid

[4] Ibid

[5] Ibid

Reading Lora Cecere’s article “My Take: Let’s Admit Seven Demand Management Mistakes of the Last Decade”* reminded me of several matters of which everyone involved in supply chain management should take note.


Supply_Chain_Management metaphor.jpg


I find the following two excerpts to be refreshingly frank and very much on the mark:

“[T]he words “Demand Planning” stir emotions. Usually, it is not a mild reaction. Instead, it's a series of emotions defined by wild extremes including anger, despair, disillusionment, or hopelessness. Seldom do we find a team excited about demand planning. Supply chain leaders want to improve it, but are not optimistic that they can make improvements.” [Emphasis added.]


“Teams are also confused on the process. What drives excellence in demand planning has changed and well-intentioned consultants give bad advice.” [Emphasis added.]


To say the least, more than 30 years of “supply chain management” efforts appear to have led to some success and then into a cul-de-sac where the path forward is somewhat less than clear.


Cecere confirms this with the following blunt statement:

“Today, most supply chain professionals believe that the supply chain planning solutions have driven steady progress to reduce costs, improve inventories and speed time to market.  What we find is that we have actually moved backwards over the course of the last ten years on growth, operating margin and inventory turns.” [Emphasis added.]


I heartily concur with Cecere’s first demand management mistake: One-number forecasting is a hoax. Of course, I would carry that further. Reliance on forecasts of every kind should be absolutely minimized. Whenever and wherever possible, forecasts should be supplanted with supply chain agility, where flexibility, capacity and rapid replenishment cycles replace reliance on forecasts and large inventories.


Next, Cecere mentions the “consensus planning” approach. She properly identifies the real problem with consensus planning: all too frequently it’s not about consensus, but about company politics. Cecere tells of this episode from her experience:

“I have worked with one company that has redesigned their collaborative demand planning processes three times.  Each time it was to improve the user interface to make data collection easier by sales. Not once did they ever question the value and appropriate use of the sales input or apply discipline on the input that was driving a 40% forecast over-bias.”


I cannot tell you how many firms I have worked with over the years where the “sales department” may have been the C-suite. In fact, in many cases, many of the C-level executives had come up through the sales department, so the affinity was to be expected.


Not infrequently I have had owners or CEOs of small to mid-sized business enterprises say to me (in one way or another): “We will do whatever needs to be done. But don’t mess with the sales department’s ‘mojo.’ They’ve warned us that if we mess with their ‘mystical mojo,’ thinks will go badly for the whole company.” The intimidation of the management structure appeared to be complete.


When it comes to “consensus,” it seems that the “sales department” hold all—or, at least, most—of the cards in a great many cases.

“Wherever there is fear, you will get incorrect numbers.” – W. Edward Deming


There appears to be plenty of “fear” to go around when it comes to anything that “messes with the sales department’s mojo.”


Number three in the last decade’s mistakes in demand planning, according to Cecere, is “collaborative planning forecasting and replenishment (CPFR).” Here she mentions moving from each participant in the supply chain using their own forecasts and, rather, carefully aligning the manufacturer’s forecast with the retailers’ forecasts.


Here again, I would take her argument further. The problem is not just with forecasting “maturity.” The problem is with forecasts in the nature. They tend to be wrong—all the time.


More importantly, a retailer may be able to tell the supply chain quite accurately how many watches (for example) it will sell over the coming three months. What they cannot tell you accurately is the number of each model of watch it will sell. Yet, it is precisely the model that must be manufactured—and not some generic “watch” to fill a forecast. As a result, when working from forecasts the supply chain will do the following with certainty:

  • WASTE resources manufacturing, storing and transporting the WRONG watches
  • TIE UP resources manufacturing, storing and transporting the WRONG watches which will, in turn, PREVENT the RIGHT watches from being manufactured and shipped on-time
  • LOSE revenues due to out-of-stocks on the most popular models over the forecast period
  • LOSE revenues by being forced to liquidate watches that were manufactured, but never sold, because they were NOT the model desired by the end-user


Number four on Cecere’s list is “data model design: forecasting what to make versus forecasting channel demands,” then on to number five: “rewarding the urgent versus the important.” On this topic she rightly opines:

“Time after time, we see companies implement demand planning technologies and improve forecasting processes, but not improve the overall results of the supply chain.” [Emphasis added.]


Here I would disagree with Cecere’s conclusion as to the cause for the lack of improvement. She blames it on “lack of training on how to ‘use the better forecast signal.’” This may be partially true but, in my opinion, real and lasting improvement in supply chain performance stems from a relentless drive toward improved supply chain agility and a dramatically reduced reliance upon forecasting.


The article’s number six reason is stated as “80% is good enough,” in which Cecere correctly points out, “the devil is in the details” of the forecast. Some of the details she mentions by name are “seasonality” and “causal factors.”


Here we get to the subtle difference between “demand planning” and “demand management.” Some confound these two—believing them to be the same or interchangeable in meaning. They are not.


But one of the major bug-a-boos in the supply chain is the result of what I deem to be “demand mismanagement.” Here’s why I say that:


Forecasting mechanisms are constantly befuddled by demand variability so, it would seem, that supply chain participants would do everything within their power to reduce demand variability. But they don’t.


Many participants in the supply chain are well aware that short-term promotions, end-of-period price breaks or incentives to salespeople, and similar controllable price changes cause demand variability. In fact, they are implemented precisely to cause demand variability (but they don’t call it that when they are trying to create it).


Furthermore, most supply chain managers know that demand variability (in the absence of intimate supply chain collaboration) is a huge contributor to “the bullwhip effect,” and that the bullwhip effect is a major contributor to stock shortages in the supply chain. Yet, with all this knowledge present in the supply chain, managers and executives appear almost unwilling to change policies in ways that would contribute greatly toward the elimination of self-induced demand variability.


What’s up with that?


I concur with Cecere’s error number eight, as well: “focusing on ‘sell-into’ the channel versus ‘sell-through’. She is dead on, but it will take another whole article to address that issue.


Thank you, Lora Cecere, for taking up this topic. I hope many listen to your frank and much-needed discussion on these important matters.



We would like to hear what you have to say on these topics, as well. Feel free to leave your comments here, or contact us directly.



*Cecere, Lora. "Supply Chain Expert Community." My Take: Let's Admit Seven Demand Management Mistakes of the Last Decade. Kinaxis, 29 Jan. 2013. Web. 18 Mar. 2013.

An article by Bill Gerneglia appeared recently at myCIOview on the very topic of CFOs and return on investment (ROI) for IT investments.



One of the comments that took me by surprise was this:

“[T]he ROI projections for major IT initiatives are often wrong.”


What took me by surprise in this statement was—cynic that I am—that there were, in fact, “ROI projections for… IT initiatives” at all! For, indeed, these projections had to exist before they could be wrong. And, sadly, a great many of the IT initiatives with which I have been involved over the years never had (to my knowledge) any formal ROI projections prepared for them in advance of the project at all. Nor, apparently, did the C-suite have any real interest in preparing such formal ROI projections.

Separating Investments from Operating Expenses


So, let us consider when and why an IT initiative should be considered an “investment” versus the conditions under which an IT initiative should be properly labeled as an “operating expenses.”


The “simple rule,” I believe, should be this: any IT initiative aimed at maintenance of current operations should be labeled as an “operating expense” (OE) project and monies paid out for such a project should not be subjected to any kind of ROI analysis.


Examples of such OE projects might be:

  • Upgrading or replacing hardware due to age or obsolescence
  • Upgrading or replacing operating systems due to age, compatibility requirements or obsolescence
  • Relatively minor upgrades or updates to software due to age, compatibility requirements or obsolescence
  • Upgrading or replacing technical infrastructure components and systems due to age, compatibility requirements or obsolescence
  • The addition of new infrastructure, systems and software as the result of normal operational growth (such as the addition of new personnel) not the result of any other corporate initiative and investment aimed at stimulating such growth


So, “What’s the simple rule for seeing an IT initiative as an “investment” versus OE?” I hear you ask.


That’s pretty easy.


As soon as you hear someone or some department say something like the following, you should be getting out your ROI calculator and putting it to work:

“If we [speaker describes an IT initiative], I’ll bet we would [speaker describes how business would be sell more, save money, or reap some other benefit].”


By the way, sometimes the speaker of the above sentence is the hardware vendor, software vendor or a value-added reseller. In such a case the statement probably sounds a bit more like this:

“If YOU buy [or, more subtly, ‘invest in’] OUR [product or service], you should be able to [describes business benefit such as, ‘save Y amount of money on N operations’ or ‘ship faster’ or ‘reduce your operating expenses by X percent’] .”


NOTE: If you hear that statement coming out of the mouth of any of your IT vendors, then for sure you will want to get out your ROI calculator and pin them down to some real hard numbers to be used for post-purchase evaluation.

Pinning down the ROI numbers


Remember! In getting to an estimated ROI, it is far more important to be approximately right, because the estimate is never going to be exactly right anyway. So, spending long and agonizing hours trying to pin down a number that will be precisely wrong is a huge waste of time.


You need to estimate five variables to get to your project’s ROI. Pick a period of time for the evaluation period—say, a year, or two years. Then work out values for the following:

  1. Revenues – How much will our revenues change (increase, generally) over the evaluation period?
  2. Truly Variable Costs (TVCs) – How much will our TVCs change over the evaluation period? Sticking with easily calculated TVCs keeps your finance people from wandering off into complex algorithms about cost or expense allocations that throw a monkey-wrench into the works with every incremental change in units sold or other variable under consideration. Make sure you have narrowed this number to the REAL TVC value.
  3. ThroughputThis is an easy calculation. It is the change in Revenues less the change in TVCs.
  4. Investment – How much will our investment change as a result of this project? Investment includes what you are spending on the project itself; but it must also include any other change in investment that may result from the project’s effects. Such changes might be increases or decreases in inventory; the need to add new offices, warehouse or production space and equipment; or, on the contrary, a reduction in investment that may accrue because a new office or warehouse does not need to be purchased or built because of added efficiencies or alternative approaches are undertaken.
  5. Operating Expenses – How much will our operating expenses change as a result of this project?


Besides the estimated values—or, perhaps in the course of creating the estimates for these values—you should carefully document the ‘why’ (the rationale) behind each estimate. Write down, as precisely as you can…

  1. How and why the project under consideration will lead to increased revenues
  2. How and why the project under consideration will lead to changes in TVCs
  3. How and why the project under consideration will lead to changes in investment
  4. How and why the project under consideration will lead to changes in operating expenses

Be relentless in your drive for “hard numbers” and the underlying rationale


For each of these, be as specific as possible. This will help you keep the project on track as you move forward.


For example: if an IT initiative in business intelligence is supposed to an increase in revenues of X percent, then the “how and why” should say something long the lines of:

“Improved analytics will allow us to segment our market and dynamically identify market segments where carefully constructed targeted offers (so-called “Mafia offers”) and value-pricing are expected to add $2.2 million to revenues in the first year and $3.8 million in year two of the evaluation period.”


Make the people asking for the “investment” tell you very specifically how the investment is going to pay-off. Make them tell you, whether they are in-house people, or salespeople from a vendor or VAR (value-added reseller). Don’t let them get by with “rules of thumb” and other mumbo-jumbo.

Now, use this simple formula to calculate your projected ROI



  • delta-T = the change in Throughput
  • delta-OE = the change in Operating Expenses
  • delta-I = the change in Investment


There you have it. Just remember these simple matters…

  • Separate OE projects from business improvement projects
  • Be relentless in seeking valid estimates and document the underlying rationale for the estimates provided
  • Remember that being approximately right is the goal, not precisely wrong


We would like to hear from you. Let us know what you think by leaving a comment here, or contact us directly, if you choose.



Gerneglia, Bill. "CFOs Require Proof of IT Investment ROI." MyCIOview. MyCIOview, 18 Mar. 2013. Web. 19 Mar. 2013.

Consider the basic supply chain eco-system. It looks something like this:


FIG SupplyChain EcoSystem typical.jpg


What makes it so difficult to build a solid foundation of collaboration between the supply chain participants? And what makes it even more difficult to sustain high levels of cooperation and collaboration between and among the participants?


If you’ve had any experience with attempting this, you probably already know the answer.


“It’s simple,” I hear you saying. “Everyone in the supply chain is looking out for themselves and when push comes to shove, they’re going to do what’s best for their own company, regardless of what happens elsewhere in the supply chain.”


This, of course, is true.


I’ll go even further. Not only is it true but, because I want it to hold true for my company, I’ll be fair and say that it ought also remain true for all the companies participating in the supply chain.

What can be done?


Let’s take another look at extended collaborative supply chains—like this:


FIG SupplyChain ExtendedCollaboration.jpg


Now, let’s consider the players in just a smaller piece of this extended supply chain—something along these lines:


FIG SupplyChain ExtdCollab_Excerpt.jpg


We have the following players:

  • A manufacturer
  • A final assembly operation
  • A direct-sales firm
  • A wholesale warehouse
  • A distributor
  • A retailer


Every one of these players is looking out for his or her own interests. Each participant in the supply chain is seeking to maximize its profits—or, at least, I hope it is.


How can we possibly bring meaningful collaboration out of this mess?

Cost-world thinking leads to a zero-sum game


Whether firms who have achieved genuine, durable and agile supply chain collaboration use the terminology I am about to apply or not, I can say with better than 90 percent certainty that durable collaboration has not been erected on cost-world thinking!


If the final assembly operator is thinking that the way to make more money tomorrow than it is making today is by getting the manufacturer to reduce its prices (cut into its own margins), that thinking will only go a short distance before any hope of further collaboration dissolves. The same is true if the wholesaler or distributor are hoping to improve their profitability by getting the final assembler or the manufacture—or both—to cut costs and reduce their prices.


The assumption underlying such supply chain tactics is this:


If my company is going to make more money, then someone else upstream in my supply chain needs to find a way to make less money or cut their expenses while still offering better prices to my firm.


Essentially, the reasoning is that the supply chain is a zero-sum game (or so close to it that any differences from it are virtually indistinguishable).


Of course, those of you who have been through this already know where I’m going with this: durable and agile supply chain collaboration is, of necessity, built on the upside to be gained through collaboration.

Making the move to Throughput thinking


The cost world has its limits.


After all, it is possible to cut a firm’s cost of doing business to zero!


It’s call “going out of business.


And, if you’re a manager or executive in a small business trying to make in today’s world, you may be one who has felt the pressure of leading “big box” merchant strong-arming you to take less and less in profits while volumes increase to higher and higher levels. Now you’re making and selling more product than you ever thought possible and, yet, taking less to the bottom-line than you did before you bought into your first EDI contract!


I once had an executive in a distribution operation selling to major “big box” firms all across the U.S. tell me: “We can ship $20,000 worth of merchandise to [named company] and end up owing them $5,000 when all is said and done.”


Such experiences—and worse—are what drive many participants out of major supply chains.


However, imagine a truly durable, truly flexible, truly agile supply chain that focused its collaborative efforts on increasing Throughput (i.e., the difference between revenues and truly variable costs) for every supply chain participant? Think where that might take those who labored for its success.

This goes way beyond sharing data about who bought what quantities where!


Consider the following questions, as examples:


  1. What can the retailers—who interact on a day-to-day basis with the end-users—tell the manufacturer about what the consumer likes or doesn’t like about the products? Rapid and frequent feedback on this channel could lead to speedy improvements in product design and increased Throughput for the whole supply chain.

  2. What could the final assembly operator tell the manufacturer that might make the products more flexible and less burdensome on the supply chain at the same time? Perhaps the assembler could recommend concepts that could delay decision-making and lead to greater flexibility. This could lead to fewer out-of-stocks and fewer liquidations of overstocks at the same time.[1] The final assembly operator might also be able to suggest changes that would minimize the required variety of parts while still meeting all customer demands. This, too, would reduce supply chain inventories and liberate supply chain resources for that which is necessary to produce and ship to meet actual end-user demand.

  3. What feedback could a collaborative retailer or distributor provide to wholesalers or manufacturers about actual changes in market demand? These data could eliminate or dramatically reduce the bullwhip effect in the supply chain. This could liberate resources to manufacture or transport what customers are actually seeking to buy, rather than tying up resources manufacturing and transporting units of goods destined only to sit on pallets and, ultimately, liquidated at or near cost.

The bottom line is the bottom-line


Ultimately, the goal of such collaboration—broad, extensive and extended supply chain collaboration—is mutually beneficial to all the supply chain participants. Unlike cost-cutting efforts, everyone benefits. There is no more zero-sum game.


FIG ToC AccountingToActionLinks.jpg


The efforts described in the examples above should have the following mutually-beneficial effects:

  1. INCREASE Throughput
  2. REDUCE Inventories—along with the need for other capital investments
  3. DRIVE DOWN Operating Expenses—or, at a minimum, hold the line on operating expenses while allowing substantial growth in supply chain Throughput


The benefits, which should also spread across the entire supply chain, are

  1. INCREASES in net profits
  2. INCREASES in return-on-investment (ROI)
  3. INCREASES in cash-flow



I am convinced that truly collaborative, agile and durable supply chain collaboration is achievable when it is based on increasing Throughput and not driven by cost-world thinking.


[1] Hewlett-Packard made such a change some years ago whereby they made the power supplies for their printers modular and allowed “final assembly” to install the power supply hardware after the destination country was known. This lead to several billions of dollars in savings over a short period of time as zero products were produced where the power supplies were incompatible with the countries for which orders existed. More orders were able to fulfilled without delay and zero overstock existed for printers with “the wrong” power supply to fulfill open orders.



We would like to hear your thoughts on this topic. Please feel free to leave your comments here, or contact us directly.

All over the world, there are still millions of people employed in manufacturing and distribution companies, but as the worldwide economy shakes out—especially in these challenging economic times—we increasingly find that that the real competition is between supply chains more than products.


Logistics and Supply Chain Management.jpg


We’re all in the service economy now, baby.


It really makes little difference what your product is, the Internet-empowered consumer—whether he’s a buyer for a major distribution chain or Jane Doe making a purchase from home—is seeking “value” with, perhaps, hundreds of options from which to choose.


“Value” to these smart buyers means a combination of functionality, usability, reliability and economy with speed. While the four basic attributes certainly apply to the product itself, the empowered consumer is also seeking reliability, economy and speed in delivery of the product, as well. These latter attributes all apply to the supply chains responsible for getting the products into the consumer’s hands.




When it comes to quality in manufacturing, variability (deviations from quality standards) is an enemy and needs to be driven out of the production environment as much as possible.


Unfortunately, many supply chain managers—having “grown up” in the manufacturing environment—are still expending huge amounts of time, energy and money trying to drive variability out of their supply chains. But in today’s world, we need to face up to the fact that change is omnipresent.


Today’s empowered consumer is not voluntarily going back to less variety in available product. “The long tail” is here—and here to stay. If anything, today’s consumer is demanding more “mass customization” and increasing variety in product and service offerings.


In the supply chain, variability is not the enemy! If anything, it constitutes the basis for improving profit opportunities for those who embrace it.


Today’s supply chain managers, if they are going to improve profitability, must embrace the omnipresence of change and variability and spend their limited resources of time, energy and money on increasing supply chain agility and resilience. More money poured down the rat-hole of attempts “driving out variability” or “improving forecasts” is likely to be counted as loss.


The difference between managing your supply chain (or any other service) and managing manufacturing is that, in providing services, dynamically shifting customer expectations require an acceptance of change and variation and the building of systems that readily accommodate variation without breaking down, bogging down or failing completely.

Agility – accommodating (even planning for and expecting) change


Supply chain agility is all about expecting, planning for and accommodating change. In order to achieve agility, at least three factors come into sharp focus:


  1. Faster feedback – It is much easier to accommodate change if your supply chain participants are getting feedback every day about actual demand for the products they provide than if they are hearing about demand only through orders that flow in a few times a month. If end-user demand has been pretty steady for weeks at x-units per day, everyone from the raw materials gatherers to final assembly firms in the supply chain will be better to prepared to respond if they know that average daily demand by end-users has tripled in the last week, rather than simply getting huge new orders at the end of the month. Remember, many of those “huge new orders” will be magnified way out of proportion by the bullwhip effect.

  2. Less inventory in the supply chain – Large amounts of inventory clogging up the supply chain means that you are more likely to have too much of the things your customers are not asking for and too little of the things your customers want right now. It also means that resources—like shippers and manufacturers—are more likely to be tied up building or transporting the wrong stuff. This, in turn, means that these resources have less capacity to be building and transporting the right stuff.

  3. Smaller production and transfer batches – Whenever and wherever it is possible to do so, production and transfer batches should be driven smaller. Doing so will reduce lead times (automatically) by freeing up resources to respond more rapidly—making the right stuff at the right time. Prices can always be negotiated based on aggregate consumption over time—not the size of the transfer batch (e.g., shipment). A good place to start is to cut present batch sizes in half—just to see what happens. The results will almost always be good (except in cases where increased set-up times between batches create a new bottleneck in the system). The increased system Throughput will generally outpace any incremental costs incurred due to the reduced batch sizes, as well.


What’s your opinion? We would be delighted to hear from you. Please leave your comments here, or feel free to contact us directly.

Recently I went back to watch “Moneyball” again. The 2011 film is based on the real life story of Oakland A’s general manager Billy Beane and a statistician by the name of Paul DePodesta. These two men changed the game of baseball by changing how the game (specifically, “the team”) is viewed by managers and executives. Beane

It’s unbelievable how much you don’t know about the game you’ve been playing all your life.” – Mickey Mantle

Without retelling the entire story, allow me to summarize. Manager Billy Beane played major league baseball where his competitors (like the New York Yankees) had an unfair advantage. They had a payroll budget nearly four times as large as the Oakland A’s club, but the same number of players in the clubhouse. Naturally, they could buy the best names in baseball to play on their team.


Beane said, “It’s an unfair game.” He recognized the real state of affairs. In the film, Beane went on: “There are rich teams and there are poor teams; then there’s 50 feet of crap; and then then there’s us.”


Moneyball_1_TheIndustry.jpgBut he didn’t say this with resignation. Instead, he told his staff and managers: “We’ve got to think differently…. If we try to play like the Yankees in [the back office], then we will lose to the Yankees out there [on the playing field].”

Start by thinking differently


Billy Beane started by thinking differently—but he didn’t yet know how it ought to think. He just knew that conventional wisdom was never going to let his team have any hope of making any real gains against industry leaders and “giants.”


He refused to let his managers and executives continue “business as usual,” where they seemed to think that fighting fires and restoring normality (i.e., “how it was before”) could be a substitute for real improvement.


On a recruiting visit to another team’s offices, he stumbled upon what he believed was to be the key to unlocking a way for his team to gain an advantage against his league-leading rivals. Beane met up with Paul DePodesta (Peter Brand, in the film), a statistician doing “player analysis” for a competitor.


Here’s what Peter Brand (aka Paul DePodesta) told Beane in the film:

There is an epidemic failure within the game to understand what is really happening, and this leads people on major league baseball teams to misjudge their players and mismanage their teams….


People who run ball clubs… think in terms of buying ‘players.’ Your goal shouldn’t be about ‘players;’ your goal should be about ‘wins.’ And, in order to buy ‘wins,’ you need to buy ‘runs.’


… When I see [what other folks call ‘a star player’], I see an imperfect understanding about where runs come from….


Baseball thinking is medieval. They are asking all the wrong questions. And, if I say it to anybody, I’m ostracized….

Misapplication of both intuition and statistics


“Moneyball” provides a great and very applicable metaphor for studying the misapplication of both intuition and statistics for ongoing improvement. You’ll have to watch the movie (again, perhaps) to catch more of it. I did.


The “old way” of baseball recruiting was to use scouting “intuition” (about everything from the player’s appearance to the kind of girlfriend they had) in conjunction with some statistics about past performance in crude attempt to prognosticate about the player’s future performance. As right or wrong the decisions may have been about forecasting the future performance of the individual players, it was entirely focused on local optimization—that is, trying to select each player and improve each player. The underlying assumption was that local optimization would lead to improvement of the system as a whole.


What Beane and DePodesta brought into clear relief was that focusing on the entire “system”—buying ‘wins’, or playing ‘moneyball’—would allow better performance at lower cost.

Better performance at lower cost—isn’t that the “holy grail” of every for-profit business enterprise? What need we learn?

Lots of parallels


There are several parallels that can be drawn from the concepts proven by Billy Beane, Paul DePodesta and the Oakland A’s in their 2002 season. Here are a few:


  • Lean/Agile Development – Breakthrough thinking in the world of Lean or Agile software development has helped changed management’s understanding about how to direct the work of a group of what used to be called ‘prima donnas’. It is no longer about ‘buying players,’ but it is all about ‘buying wins’ and creating a that fosters ‘wins’—and profits—through improved productivity.
  • Lean/Agile Supply Chains – New concepts about supply chain management are chaining the view of managers and executives about the ‘key supplier’ and the premiums sometimes paid to keep them happy in the supply chain.
  • Theory of Constraints – Stop optimizing “departments” and “functions” and start optimizing the whole system. Start grooming the entire system for “wins,” and stop grooming the individual “players” for stats.

Peter Brand, the Yale-educated economist who was doing player analysis in the film, told Billy Beane: “From among the 21,000 prospects we can evaluate, I believe we can find a winning team of 25 players who are undervalued and we that we can afford.”


I believe the same is true in a supply chain, for example. I think there are dozens—even hundreds—of supply chain ‘players’ out there who are presently ‘undervalued’ by their industry and could become part of a winning, collaborative supply chain ‘team.’


What lesson can we take from this?


Even when the playing field seems utterly “unfair” and you are competing against giants in your league, if you look to system thinking instead of local optimization, your chances of winning are dramatically improved.


We would like to hear what you think. Please leave a comment here, or contact us directly.

Writing at “Spend Matters,” Joshua Nelson, Director of Strategy and Operations Practice at The Hackett Group, regarding the group’s “2012 Key Issue Study”, Nelson highlights what supply chain managers and executive have identified as the key issue for supply chains and supply chain managers. (See: Nelson, Joshua. "Evaluating Supply Chain Risks with Single vs. Multiple Vendor Sourcing Strategies." Spend Matters Evaluating Supply Chain Risks with Single vs Multiple Vendor Sourcing Strategies Comments. Spend Matters, 28 Feb. 2013. Web. 01 Mar. 2013.)




Granted, Nelson and the supply chain “2012 Key Issue Study” do not put it quite so bluntly as I do—so mine is a conclusion drawn. Nevertheless, I think you will agree with me.


The Hackett Group’s study found the following to be the top three “major” or “critical” supply chain issues as reported by the managers and executives surveyed:

  1. Improving supply chain flexibility/agility (92 percent)
  2. Improving cross-organization collaborationimproving planning(77 percent)
  3. Mitigating supply chain risks (e.g., supply disruption, severe quality) (77 percent)


My opinion—drawn from these three leading “critical” issues—is that these three all point to precisely the same core issue and essential resolution. These are all pointing to a singular, yet very real, challenge. The singular solution to this singular challenge has, in my opinion, also a singular side benefit.


What is this singular issue?

The singular, most important issue is the need for supply chain agility.


Of course, issue number one (above) clearly states that supply chain “agility” is the issue. But what about numbers two and three?


Let’s look more closely.


From what I have observed, number 2 (above), that is, seeking after improvements in cross-organization collaboration (especially collaboration between supply chain partners) generally has one end in mind—namely, increasing agility. The side-benefit is this: the drive for agility automatically drives down supply chain risk at the same time.


So, while a firm’s drive for improved collaboration might be described by management as a pursuit of “risk mitigation” or “risk management,” it almost always tends towards increasing supply chain agility as the method by which reduced risk is delivered.


“And, what about the ‘improving planning’ part of this?” I hear you ask.


Well, since forecasts are always wrong, firms frequently find themselves caught up in a virtually endless pursuit of “better planning” and better planning mechanisms. These pursuits may provide some marginal improvement. However, the inherent unreliability of forecasting and planning methods and mechanisms end up introducing just one more variation into the whole supply chain mix. “Will our forecasts be ‘more right’ or ‘more wrong’ this month?”


The difference is this: unlike “improved planning,” improved supply chain agility has the ability to deliver improved performance virtually every time it is conscientiously and effectively applied. So, while a firm may seek “improved planning,” the real answer to their pursuit is “improved supply chain agility.”


And this, of course, inevitably leads us to issue number three above: “mitigating supply chain risk.”


What is the truly most reliable way to mitigate supply chain risk?


The answer, of course, is to improve supply chain agility. Improving the supply chain’s ability to respond rapidly and effectively to the unexpected automatically, and without further action, reduces the supply chain’s exposure to risk!


So, as I said at the outset: the three top supply chain issues are not three, at all. They are, in fact, just one issue expressed three ways and finding their safest and most effective solution in one response—increased supply chain agility.



We’d be delighted to hear your opinion. Leave your comments here, or contact us directly, if you’d like.

Recently I’ve read two disturbing articles.

Graph failing.jpg


The articles focus on just ERP implementations, but my suspicion is that the symptoms presented in the report are far more widespread.

Cost Overruns


This, of course, is old news. Cost overruns for IT projects are, unfortunately, no longer “surprises.” They haven’t been for the better part of two decades—probably, even, since the inception of “information technology” as a new foray in business.


I guess we can console ourselves by noting that cost overruns are declining slightly: from 74 percent of projects in 2010 to 56 percent in 2012 and, finally, down to 53 percent in 2012.


Of course, what we don’t know is the cause of this decline. Are cost overruns being reduced because VARs, vendors and systems integrators are getting better at estimating (or, perhaps, more honest), or is the implementation process simply getting more honed and efficient? Then, again, it may be that overruns are being reduced because the customers themselves have been through implementations more times, so they have learned how to cooperate more fully and effectively during the implementation.


What the reduction in cost overruns certainly does not tell us whether the cost of the project is actually any lower for the buyers of such implementations.

Schedule Overruns


While cost overruns are diminishing slightly—for whatever reason, schedule overruns are growing. Of the 172 implementations included in the report quoted in the articles, the average project duration was 17.8 months, with nearly two-thirds (61 percent) reporting that their implementation “would take longer than planned.” This compares to only 54 percent reporting the same in 2011.

Success and Satisfaction


As I said, overruns are “old news.” In fact, they are so commonplace as to be considered—sadly—the industry “norm.” But, let’s look at some more troubling information that surfaces in the report.

Fully three out of five (60 percent) survey respondents indicated that their firms’ received half or less of the business benefits they anticipated from their IT project.


Despite this dramatic failure, in my view, more than four out of five (86 percent) of decision-makers indicated that they were “satisfied” with the results of their project and most (60 percent) labeled the project “a success.”


It is, indeed, and vast understatement, then, when Eric Kimberling, managing partner of Panorama Consulting (which conducted the survey), states:

“[T]he delta between actual… implementation results and the self-reported satisfactory levels indicate that companies are setting expectations of the business benefits they should achieve from… [their] system far too low….”


Kimberling strikes the nail on the head, I believe, when he goes on to say:

When [project] durations stretch and scope increases…, it… becomes tempting to change the definition of success to just “getting the system up and running.”

Very low expectations, indeed


This is akin to deciding to buy a new car in order to take a family trip to Disney World and then settling for just being able to get the car started.


Of course, if the executives and managers in the enterprise view IT purely as an expense, they likely have not developed any effective means to estimate and measure POOGI (process of on-going improvement) project return on investment (ROI).


If not, please name any other corporate matter in which they would invest tens or hundreds of thousands of dollars without any expectation of real, measurable ROI? I don’t think there are many.

Estimating ROI for any POOGI project


We actually use a very simple formula for estimating POOGI project ROI. It is stated here:



It reads: ROI is equal to (the change in Throughput less the change in Operating Expenses) divided by the change in Investment.


Of course, the figures used even in this formula will be estimates; but we use tools to help unlock “tribal knowledge” in a way that can aid you in getting to pretty solid numbers that will allow managers and executives to create metrics by which to actually measure post-project results against pre-project expectations.


We believe that this approach can rescue firms from the deadening effect of low expectations and money spent of IT (or other POOGI, such as supply chain) projects with little or no benefit being delivered in the end.



We would be delighted to hear your opinions on this important matter. Please leave your comments here, or contact us directly.

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