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2016

Most of the managers and executives we meet on a day to day basis are stuck in a paradigm of thinking about their companies, their industries, and their supply chains with a Newtonian world view.ComplexAdaptiveSystems SupplyChain.jpg

 

Newtonian systems are linear systems and generally share the following characteristics:

  • The whole system, and its performance, can be understood by studying the systems individual parts and functions. In this sense, Newtonian systems operate as “the sum of their parts.”
  • The system state is relatively stable and quite predictable.
  • The outputs of a linear system is proportional to the system’s inputs
  • The Newtonian (linear) system’s performance can generally be pretty well modeled using a normal distribution curve. The tails of the distribution in such curves constitute anomalies in the performance of the system as a whole.
  • Newtonian systems can be optimized

 

Your Supply Chain Is Not “Normal”

While you and your management team may still be under the misconception that your company’s, or your industry’s, or your supply chain’s performance is Newtonian in nature and may be model on a “normal distribution,” I believe that your experience will reveal the error in this thinking about these matters.

 

Simply ask yourself, and answer, these questions (taken from the bullet-points above):

  1. Is your company or your supply chain “relatively stable and quite predictable”?
  2. Is the output of your company or your supply chain directly “proportional to the system’s inputs”?
  3. Is there anything approaching a “normal distribution” in the events that make up your day to day activities in managing your operations or your supply chain? Do you spend most of your time on “normal” activities and only a tiny fraction of your time and energy on firefighting the “tail” events, or is it just the other way around?
  4. Have you successfully optimized your system and everything is under control now?

 

Your Supply Chain Is a CASComplex Adaptive System

Complex adaptive systems (CAS) are not linear. Instead, they are characterized by the following:

  • Complex nonlinear systems can only be comprehended by mapping and coming to understand the dependencies and interconnections of the parts and functions.
  • Complex nonlinear systems are highly dynamic and no predictions are valid for long
  • Complex nonlinear systems tend to have fuzzy boundaries (it is hard to tell what is influencing what, especially at the edges of the system)
  • Complex nonlinear systems are embedded with other systems and co-evolve (look and the diagram above and realize that each other system—your customers, your vendors, your distribution channel, and so forth—are all systems of their own that are “embedded” in your system and coexist and co-evolve with your company)
  • The outputs of complex nonlinear systems are governed by a few critical points of interaction and are not directly proportional to inputs
  • Complex nonlinear systems tend present with a Paretian statistical model where the tail events provide the relevant information for management and improvement
  • Complex nonlinear systems cannot be optimized, but can be continually improved

 

The accompanying illustration shows only a tiny portion of the interactions that might occur in the complex adaptive system we call a “supply chain.” Actions of customers are not linear and predictable. Instead, the actions of customers are adaptive and based on internalized rules and thought processes influenced by the actions taken by other players—such as the distribution channel or even economic or political climate in which they operate. There are, quite literally, millions of immeasurable, untraceable interactions that affect the decision-making and actions of each player in the CAS.

 

Such unpredictability cannot be the rational subject of mathematical forecasting with any hope of accuracy that could be used to drive day-to-day actions. Predictability within a range is possible and can be used for scaling and long-range to mid-range capacity planning only.

 

Your “Levers” Don’t Work as Designed

You, doubtless, have experienced repeated the fact that simple “levers” devised based on Newtonian assumptions do not work in the management of a CAS.

 

For example, reducing costs does not necessarily—in fact, seldom does—result in increasing profits. This, despite the fact that in the boardroom or in the C-suite the executives are still correlating “reducing costs” with “improving profits.”

 

Something has got to change!

 

Take another look at the first bullet-point under the characteristics of a CAS:

 

Complex nonlinear systems can only be comprehended by mapping and coming to understand the dependencies and interconnections of the parts and functions.

 

The primary approach we take in working with new clients seeking internal or supply chain improvement involves building a logical map of the dependencies and interconnections involved in their CAS.

 

Of course, we realize there is no way to comprehend or map all of the millions of complex interactions. Instead, we try to help them narrow their focus to the ten or so key interactions that are clearly preventing them from making more money tomorrow than they are making today. That tend to be enough to help them get started down a path of ongoing improvement that leads to broad, system-wide, low-investment, profit-improving results.

 

It tends to rapidly change frustration and anger to smiles in a matter of a few short days or weeks.

 

You should give it a try.

 

Please leave your comments and questions below. What do you think? Is your company or supply chain a linear Newtonian system, or a CAS?

 

Contact us and we will send you a whitepaper from Demand Driven Institute entitled The Demand Driven Adaptive System.

 

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The true asset value of your inventory depends upon a large array of factors.DDMRP Inventory AssetValueCurve.png

 

However, as Smith and Smith properly assessed in their excellent book Demand Driven Performance, the factors that make inventory valuable can be summed up in general way using the accompanying Inventory Asset / Liability Curve (figure).

 

The Cost of Too Much Inventory

When you have too much inventory, return on investment (ROI) begins to decline for any of several reasons including:

  • Write-offs due to obsolescence tend to increase
  • Increased discounts may be offered to “move” the product and, as a result, profit margins are reduced
  • Liquidations may be required to unload inventory that is nearing obsolescence
  • Liquidations of current models tend to cannibalize future sales, also reducing profits in the future
  • The longer inventory is held, the more likely it is to suffer damage, or become shop-worn and require additional discounting or even be written-off
  • Carrying costs increase
  • Larger inventories may require additional capital investment in the form of more warehouse space, racking or shelving, and handling equipment

 

Unfortunately, the value of the inventory (an accounting asset) is very visible and may even be deemed positive in some respects. The costs, however, tend to be diffused and harder to recognize. These costs are no less real merely because they are diffused instead of concentrated and easily seen.

 

The Cost of Too Little Inventory

When you have too little inventory revenues can fall and operating expenses increase dramatically:

  • Expediting expenses may increase dramatically as overtime and additional personnel resources are diverted to firefighting
  • Excess freight costs—the extra you pay for expedited shipping—my explode higher
  • Backorders mean you are more likely to have to make second and third shipments at your expense
  • Stock-out may lead to lost sales
  • More stock-outs may lead to lost customers
  • Lost sales lead to increased sales and marketing expenses to make up for sales and customers lost

Both Tails Mean Reduced R.O.I.

Just as the accompanying figure clearly shows, both ends of the curve—both tails—mean falling ROI for your company or your supply chain.

 

Becoming truly demand-driven (this is not the same as make-to-order) in both planning and execution has clearly demonstrated its effectiveness at squeezing your inventory effectively into its most profitable range.

 

It Cannot Be Done by Finance

Reshaping your inventory cannot be done at the gross level. The only way to do this effectively is to determine where your red zone, yellow zone and green zone is for each SKU in each location. As Lora Cecere cogently observed in her article Seven Misconceptions on Managing Inventory in a Market-Driven World, “A frequent mistake made in the management of inventory in the extended supply chain is a blanket reduction—a corporate mandate to reduce inventory—without rationalizing the requirements for inventory in the value chain. Inventory should never be managed to a financial target.”

 

We have the tools to help companies and supply chain managers move steadily toward maximizing the ROI they get from every dollar invested in their inventories.

Executives and managers just need to begin giving up on their misconceptions in order to take advantage of these new, proven-effective demand-driven approaches to improvement. Contact us for more information.

 

 

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“Of course, no one in pro sports ever admits to quitting. But it [is] perfectly possible to abandon all hope of winning and at the same time show up every day for work to collect a paycheck. Professional sports [has] a word for this: ‘rebuilding.’”Graph failing.jpg

 

Such was Michael Lewis’s observation of management and team members’ conduct in his 2003 much-discussed classic, Moneyball – The Art of Winning an Unfair Game.

 

Sadly, I have witnessed very much the same conduct amongst executives, managers and “team players” in many small to mid-sized business enterprises. These folks will not, of course, admit to “quitting,” but it is clear that they have given up on “winning.” Instead, they have capitulated to mediocrity.

 

I have been looking at trying to put into words some of the underlying thinking that causes executives and managers to capitulate in this way.

 

It’s out of our hands

When we are involved in discussions about stirring up new concepts for starting down the road toward “winning” again (read: a process of ongoing improvement), we frequently are met with a barrage of reasons that all of have one thing in common. Each of the objections to making a fresh effort at “winning” seem aimed at one thought: it’s out of our hands.

 

You surely have heard these excuses before. Perhaps, you have even repeated these mantras yourself—in your head, if not out loud.

  • Our suppliers don’t always deliver on time
  • Our customers seem to change their minds at the last minute, or order too late
  • Our workers don’t understand (or can’t understand, or don’t care enough to understand) what needs to be done
  • “Corporate” (or senior management) forces things on us

 

If this thought is allowed to take root and grow, we find that such companies will remain little changed from year to year. They may continue to try over and over the same tired things they have been recycling as “improvement” efforts for the last decade or so, but they are unable to break out of their rut until they begin to see something different.

 

What you’re suggesting won’t do what you’re promising

There are two sides to this problem. One the one side, some of those making this argument are simply declaring that they are tired of trying again and again and seeing little or no positive results from their efforts.

 

It may also mean that they are jaundiced, having heard too many claims and promises from consultants and software peddlers.

 

On the other side, this may be partly our fault. It may mean that we have not created a clear connection between the actions we are suggesting and the outcomes to be expected. If that is the case: we need to do a better job of making that connection in the minds of the hearers.

 

Yes, but…

In many cases, rebuttals to suggested actions for improvement that begin with “Yes, but…” are statements about how “unique” their company, their customers, their suppliers, or their situation is.

 

On the face of it, this sound valid.

 

But, when you consider the fact that, in reality, every company is unique from every other company, you begin to realize that compelling differences do not necessarily mean that all of these different companies are not facing fundamentally very similar problems in their supply chains, or elsewhere. And, if that is true—that there are fundamentally similar challenges underlying the uniqueness on the surface—then solutions that have been proven to work effectively in many companies probably may be readily adapted and adopted for improvement in other companies.

 

Don’t give up on winning

Giving up on “winning” only assures your place in mediocrity—or worse, failure.

 

But, your executive and management team needs to also realize that you are not going to improve significantly by applying again and again all of the things you have already been trying for that five, ten or fifteen years.

 

A fresh start on “winning” will come from a fresh approach to “winning.” Look for new concepts and think about how you might learn to apply these new concepts.

 

Overcoming the “given up on winning” syndrome is not easy

Our experience shows us that, under ideal circumstances, three elements are essential to help a company turnaround from “giving up”:

  1. A willingness by executives and managers to at least listen to and seriously consider new ideas—even if the ideas seem radical, at first
  2. About five days in a guided discussion with the whole executive and management team gather together
  3. A quality guide or mentor with the proper tools to help the team of executives and managers begin to unlock all their “tribal knowledge” and get them thinking in fresh, new ways about the possibilities they have before them

 

Don’t give up on “winning.” We can virtually assure that there is hidden potential in your enterprise that is presently invisible to you.

 

We can help.

 

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RDCushing

On Forecast Accuracy

Posted by RDCushing Jun 17, 2016

The steady back-and-forth, back-and-forth motion of my wipers swooshing away the “thirty percent chance of rain” from my windshield carried me back to thoughts of forecasts and forecasting accuracy.

 

WeatherForecastGrid.jpg

On the “How” of Forecasting

My thoughts wandered past a description I had heard once of what a “percent chance of rain” really meant. It went like this:

 

A 30 percent chance of rain means:

  • There is a 30 percent chance that 100 percent of us will get wet, or
  • There is a 100 percent chance that 30 percent of us will get wet, or
  • There is a 70 percent chance that the weatherman is 100 percent wrong!

 

I recalled that, when I first heard it, I thought it was cute, but not necessarily accurate. Only later did I learn how that “X percent chance of rain” was actually calculated by forecasters.

 

To calculate the percent probability of precipitation, as I understand it, they take a 10-mile by 10-mile square grid and center it over the forecast target area. (See the accompanying figure.) Then, by taking into consideration factors like the size of the weather cell and other factors they believe will affect its path, they compute the likelihood of precipitation across the 100 square-mile grid.

 

So, in fact, they are saying precisely what the quip above states:

  • There is, perhaps, an X percent chance that 100 percent of the 10X10 grid will receive precipitation, or
  • There is, perhaps, a 100 percent chance that 30 percent of the 10X10 grid area will receive precipitation, or
  • There is, in the alternative, a (100 – X) percent chance that their forecast is off the mark entirely.

 

On the Use of Technology to Improve Forecasting

As my mind continued wandering to the steady rhythm of the windshield wipers, I also recalled a statement from the meteorologists from the National Weather Service. The statement, as I recall it, originated in the early days of computer-assisted forecasting, but just as computing power was becoming cheaper and more widely available. The statement went something like this:

 

Give us enough computing power, and we will be able to provide you with forecasts that are always 100 percent accurate.

 

Of course, after supercomputers were made available to them, all they really discovered about creating accurate forecasts is that the more they knew, the more they realized that they did not even know all of the factors that influence the weather. In fact, amongst the hundreds of factors that they now know have an influence, there is no universal agreement as to how they should be weighted and applied in various forecasting circumstances.

 

Assuredly, more computing power has had some effect on improving weather forecasts, but—more than anything else—it has exposed what is not known in the field of forecasting and meteorology.

 

On the Use of Big Data

Today, advocates for the use of “big data” and “unstructured data” in business forecasting schemes are discovering the same thing. The more computing power becomes available to crunch the data, the more the folks doing the analysis recognize their shortcomings in being able to recognize all of the factors, or in knowing how to weight and apply the various factors, that might affect the forecasts.

 

Great for Selling Computer Systems and Forecasting Software

Today, many on the selling side of computer systems and forecasting software firmly hold to the more than 40-year-old prophecy from the National Weather Service. They, too, believe that, if we just had enough computing power, we could create flawless forecasts to drive supply chains and other business results.

 

On the buying side of the equation, there are also many managers and executives who have bought into this concept. The result is, more and more money is being spent on computer hardware, software and consulting services and, all too frequently, with relatively meager return on investment (ROI).

 

Where Are the Gains?

In the end, the computer systems’ sellers prosper and the buyers stumble on with forecasts that can now tell them, with a small degree of improved accuracy, something like this:

“There is a 70 percent chance that you will sell N quantity of products in the Y product line in the coming quarter, and the product mix might look like this.”

 

This kind of forecast accuracy is suitable for managing order of magnitude decisions—like deciding on capacities and means.

 

However, it is not suitable for driving manufacturing and distribution execution decisions. And, relying upon such inaccurate forecasting to drive execution results in business-as-usual with overstocks, shortages, high expediting costs, firefighting, and less than adequate customer service levels.

 

Only by becoming truly demand-driven (by which, I do not mean, make-to-order), can a company or supply chain overcome the weaknesses that will always be inherent in forecasts—regardless of computing power and software prowess.

 

Those who have undertaken a truly demand-driven journey have received handsome rewards in terms of increasing profits and dramatic improvements in ROI. Why would you not want to become one of them? Big technology and big data, not required.

 

Contact us by leaving a comment below. We are happy to help.

 

 

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Today, our reliance on computers is pervasive. As your company, your supply chain, and even your home, are increasingly reliant upon computers to control everything from the flow of electricity to the flow of products and services, you need to be informed about matters of cybersecurity.evaluate.JPG

 

Here are some helpful videos to get you started:

  1. Hackers: The Internet's Immune System
  2. Fighting Viruses, Defending the Net
  3. Hire the Hackers
  4. All Your Devices Can be Hacked
  5. How Cyberattacks Threaten Real World Peace (French with English subtitles)
  6. Governments Don't Understand Cyber Warfare; We Need Hackers
  7. What's Wrong with Your Pa$$w0rd?
  8. The 1s and 0s Behind Cyber Warfare
  9. A Vision of Crimes in the Future

 

How are you dealing with cybersecurity risks to your business and supply chain? Please, leave your comments below. We would like to know more.

 

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Have you ever thought about it? What is the single most crucial KPI for your enterprise, or your supply chain? What is the biggest single factor limiting your ability to achieve more of your goal? What single metric stands between you and making more money tomorrow than you are making today?Baseball_outfielder.jpg

 

For 15 years (1983 through 1997), Sandy Alderson was general manager of the Oakland Athletics, a Major League Baseball team. After coming across some other writings by Eric Walker, a former aerospace engineer-turned-sports writer, Alderson started thinking about that very matter for his team.

 

In fact, Alderson commissioned Walker to write a pamphlet on baseball strategies and tactics that touched on the matter of crucial KPIs (even though the term was not used in the pamphlet). Here is what Walker said:

Analyzing baseball yields many numbers of interest and value. Yet far and away--far, far and away—the most critical number in all of baseball is 3: the three outs that define an inning. Until the third out, anything is possible; after it, nothing is. Anything that increases the offense's chances of making an out is bad; anything that decreases it is good. And what is on-base percentage? Simply yet exactly put, it is the probability that the batter will not make an out. When we state it that way, it becomes, or should become, crystal clear that the most important isolated (one-dimensional) offensive statistic is the on-base percentage. It measures the probability that the batter will not be another step toward the end of the inning. [1]

Unlike the sports of football or basketball, there is no time clock governing baseball. Time, in baseball, is measured only in “outs.” In every inning, each team gets three outs. And, as Walker keenly observed: until the thirds out, anything is possible; but after it, nothing is possible.

 

On-Time Performance

There are only two (2) system-level (enterprise-level) KPIs that matter—in the long run:

  1. On-time performance, and
  2. Return on investment

 

Interestingly, these two KPIs are inextricably linked. Almost without exception (in fact, I cannot think of any exceptions in the long-run), companies and supply chains that suffer from poor on-time performance, ultimately suffer from low return on investment, as well.

 

Time is the Crucial Factor

Return on investment (ROI) is, of course, measured over time. While the investment part of the equation may remain relatively static, the “return” part—the profit—is garnered over time.

 

Even more to the point, on-time performance is directly related to the clock on the wall and the calendar that hangs beside it.

 

On-time performance affects ROI both directly and indirectly.

 

Poor on-time performance may affect profits (and, hence, ROI) directly through lost orders. But it can have lasting effects on ROI in other ways, as well. Lost orders may lead to lost customers. Lost orders and lost customers lead to increasing sales and marketing expense in attempts to make up for the revenues lost and customers disaffected. Greater discounts, required to recapture lost sales and lost customers may cut into margins. All of these lead to long-term reductions in ROI—over time.

 

If we take this baseball analogy a little further, we can draw a rough equivalence between on-base percentage and on-time performance.

 

Every day your company and its supply chain have a certain number of opportunities to “get on base” (deliver on-time) or “get an out” (fail to deliver on-time). While there is still time in the day, some things may still be possible. Once the clock expires, nothing is possible—you can no longer deliver “on-time.”

 

Increasing Your On-base Percentage

If time is your crucial limiting factor to “winning” or “losing,” then two simultaneous objectives should be the concern of supply chain managers:

  • Effecting strategies and tactics that improve the odds of on-time performance while, at the same time…
  • Holding investments (e.g., inventories, technologies) to a minimum

 

These two, working together, satisfy the demands of two system-wide KPIs: on-time performance and return on investment.

 

You Might Need a Partner

Many of the firms with which we come into contact in our consulting business have realized that time is there real constraint. Their executives and managers are so occupied—day-in and day-out—with the activities of normal routines and ongoing firefighting that they do have neither the time nor the energy to effectively work toward ongoing improvement.

 

In such cases, working with a consulting partner capable of rapidly bringing focused attention to those few changes that will improve your odds of “winning” through on-time performance and increasing ROI can pay-off handsomely. Many times the changes required for early and rapid improvements have nothing to do with technologies, at all. Instead, seeing things in a new light and taking the proper steps toward changes in policies, procedures, and tactical execution can bring about dramatic improvements with little or no additional investment.

 

Time and management attention are crucial limiting factors for your success. Rapidly uncovering ways to improve your odds of success can lead to huge gains. Start today!

 

 

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Call me cynical. Call me a pragmatist. Call me whatever you want. But, in this Internet-of-Things (IoT) age, where nearly everything that gets written and published is also hyped and promoted on key-words and catch-phrases, I’m having trouble with this one: “the bimodal supply chain.”FIG Incr Revenues vs Reduce Costs.jpg

 

Maybe it is not even the phrase itself. Maybe it is just Gartner’s Research VP Mike Burkett’s description of becoming “bimodal” that I am having trouble swallowing.

 

In an article by Jane Barrett posted here, Mr. Burkett describes “bimodal” this way:

In mode one Supply Chain must continue to focus on efficiency and operational excellence – the traditional operational caretaker. In mode two, in parallel, you must be able to experiment, fail (fast), innovate and embrace new crazy ideas. This needs different people, incentives and culture. You must hire data scientists and sociologists, experiment with drones and other smart machines, harness unstructured data and design e2e connected processes like never before. Analytics must become embedded and mainstream.

 

How does this work?

We come to work as consultants for companies on a regular basis where the companies, despite their best efforts, find themselves divided. Call it “bimodal,” if you want. But, it is really a form of double-mindedness—schizophrenia—that results in wasted time, energy and money as management oscillates from one pole to the other.

 

Here are some examples of the oscillations—double-mindedness—we commonly encounter:

  • Should we run larger batches to reduce costs? Or, should we run smaller batches to improve flow?
  • Should we service our equipment only when required to keep efficiencies up and costs down? Or, should we invest in preventive maintenance so that we don’t have unanticipated disruptions to flow?
  • Should we buy in volume to achieve the lowest costs? Or, should we buy in the quantities required to achieve flow and conserve cash?
  • Should we hold prices to achieve greater margins? Or, should we reduce prices to increase sales and total revenues?
  • Should we build to stock? Or, should we build to order?
  • Should we produce only on the optimal resources to keep production costs down? Or, should we produce on any available resource to maintain flow?
  • Should we ship complete orders only to save on shipping costs? Or, should we ship partial orders to maintain flow?
  • Should we allow overtime to maintain flow? Or, should we severely restrict overtime to keep costs down?

 

From Burkett’s description of “bimodal,” it seems to me you are asking “the system” (read: the company, or the supply chain) to hold in their minds two distinct goals.

 

On the one hand, Burkett wants the “mode one” folks to focus on costs and efficiencies—“saving” the company as much money as possible. Meanwhile, in the other wing of the building, or in an office somewhere else, there is a “mode two” team burning hundred-dollar bills in “fast failure” and “experimentation” that have no assurance of benefiting the company (or supply chain).

 

How long can this go on before jealousies and rivalries break out into the open—or worse, remain covert but equally damaging—between the “mode one” folks and the “mode two” folks? The “mode one” folks angry that they are constantly pressured to scrimp and save while the “mode two” folks contribute what may seem to be little or nothing for months, or even years, at a time. Meanwhile, the “mode two” folks become perturbed at the “mode one” team when they fail to produce the profits necessary to keep the “mode two” team functioning in the lifestyle to which they have become accustomed.

 

One goal and a unified approach to innovation and problem-solving

When we work with our clients and their supply chains, we work hard to help bring them a clear and unified view of their “system”—that is, their company and their supply chains.

 

Out of this unified view, we employ the Thinking Processes to help them choose and prioritize strategies and tactics that coordinate breakthrough innovation efforts and throughput increasing approaches that virtually assure improvements in ROI. We help them break the back of damaging management oscillation (read: double-mindedness) and set them on a path of ongoing improvement.

 

We don’t believe your supply chain needs to be “bimodal”—at least not as Burkett describes it—in order to have the best of both worlds: both flow and innovation.

 

(My apologies to Mr. Burkett and Gartner Group.)

 

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