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2017

Some years ago I was involved in promoting an ERP integration with vertical solutions for the ready-mix concrete and aggregate industry at the World of Concrete exhibition and trade show in Las Vegas, Nevada. (It has one of the few convention centers large enough to host all of the heavy equipment displayed at this event.)World of Concrete Exhibit Hall Floor Map

 

As one gentleman was making his way by our booth, I stepped up an inquired if his company might be interested in a new ERP system that offered distinct advantages for his specific industry.

 

His reply intrigued me.

 

It’s got to work

He said to me, “No, sir! We are just wrapping up an implementation of SAP now.”

 

My reply was a little sarcastic—I confess: “Well, I’d like to shake your hand! I haven’t met folks from many companies that have actually ‘wrapped up’ an SAP implementation.”

 

He smiled knowingly, clearly recognizing the significance of what I had just said, then replied with, “Well, some things still aren’t working the way we’d like.”

But, it was his next line that really stuck with me.

 

He continued, “But, we’ve spent so much money now that it’s got to work.”

 

Here the implication is clear: if a solution is big enough, complex enough, and costly enough “it’s got to work.” (Even if that means, I fear in some cases, that management will declare “it’s working,” although the rank-and-file users may not actually view it the same way.)

 

Juxtaposition

I’d like to juxtapose that in your minds with another incident out of my past.

 

Working in the ERP systems and systems integration marketplace for nearly three decades has been interesting. We have, not infrequently, found ourselves head-to-head in competition with the so-called tier-one ERP systems like SAP, J.D. Edwards, and Oracle.

 

And, while I am confident that this sense went unspoken on several occasions, I recall one “selection committee” member at a prospect once articulating this amazing statement:

 

“Your software only costs $X ?!? Then it can’t possibly be capable of handling the kinds of complexity we will be throwing at it.”

 

Here, again, the implication is that, a key indicator in whether a solution will be a real and effective solution is somehow determined by whether it is big enough, complex enough, and costly enough.

 

Ignoring the full picture

What may be even more amazing is the fact that these statements were being made at a time when the mainstream news outlets, plus accounting and information technology literature, were chock-full of stories of hugely expensive and untimely failures in ERP implementations being done with tier-one software such as SAP and others.

 

Today, despite the valiant and effective efforts of the Demand Driven Institute (DDI), there are still far too many supply chain executives and managers that, I fear, still fall into this trap. They, too, turn a blind eye toward excellent and effective solutions merely because they are offered by companies without tier-one status, and the solutions, at first glance, seem to be “too simple” to handle the perceived complexity of the challenges.

 

Of course, these perceptions are wrong.

 

Tier-one software companies have provided the management world with ample examples of big, complex and costly failures. We don’t really need more of those.

 

The concept of inherent simplicity tells us that the more complex a challenge appears to be, the simpler the effective solution must be. The principles within the demand-driven operating model (DDOM), and the hundreds of successes achieved by companies that have conscientiously applied these principles, have proved this to be true.

 

Don’t ignore the real picture. Don’t confuse costly or complex with effective.

 

Reader response

What are you doing? It is costly and complex, or simple and effective?

 

What is working for you, and what is not?

 

We would be delighted to hear from you. Please leave your comments below, or feel free to contact us directly.

 

 

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Typical Forecast Accuracy by Percent of SKUs

 

The figure above represents the reality of forecast errors faced by typical supply chains. Here’s a summary of what the figure is expressing:

  • Forecast errors less than or equal to 20 percent – Items that have high levels of consistent demand are pretty easy to forecast with relative accuracy. The SKUs’ coefficients of variability (COV) will be low, so almost all the forecasts represent relevant information. Unfortunately, in many organizations, the percent of SKUs in this category is very small—not infrequently as few as six percent.
  • Forecast errors between 20 and 50 percent – The next group of SKUs will have forecast errors ranging between 20 percent and 50 percent. These probably are items that move fairly steadily and also probably have either shorter average lead times or more frequent replenishment than other the remaining SKUs in the portfolio.
  • Forecast errors greater than 50 percent – Typically up to 50 percent of SKUs are lower velocity items which, in turn, also tend to have higher—much higher—coefficients of variability. This makes forecasting accurately almost impossible, regardless of the strength of the underlying forecasting algorithms.

    [The numbers of SKUs in the figure is based on an example total of 10,000 SKUs.]

 

Too much and too little

Of course, this little diagram helps us also see readily why the typical supply chain ends up with bimodal inventory. Bimodal inventories are characterized by the all too typical complaint: “We’ve got too little of the right stuff, and too much of the wrong stuff.”

 

Relevant information versus irrelevant information

It’s time to face the reality!

 

Look at the figure above one more time, and consider this:

  • For the six percent of SKUs, those with 20 percent or less in forecast error rates, we can easily see that 80 percent or more of the forecasts match actual demand. That means that 80 percent or more of the forecast is relevant. A relatively small portion--only 20 percent or less of the forecast--represents irrelevant information.
  • For the middle 44 percent of SKUs, those with 20 to 50 percent forecast error rates, we can readily understand that the forecasts are constituted of 50 to 80 percent relevant information.
  • For the remaining 50 percent of SKUs, 50 percent or more of the forecasts are constituted of irrelevant information—the error portion of the forecast.

 

Simply put, the portion of the forecast demand that matches the actual demand is relevant information. However, that also means that the portion of the forecast demand that does not match actual demand is, in reality, irrelevant information.

 

As supply chain managers and executives, we see our supply chains relying on large volumes of irrelevant information day after day, month after month. We also see that our supply chain performance, generally speaking, is not improving day-to-day, or month-to-month.

 

Why do we do this?

 

Confessing the reality

My observation is that we frequently persist in such folly simply because we won’t change our language. We call data “data,” and we never distinguish between what is relevant in our information flow, and what is irrelevant.

 

We also fail to connect the fact that, in our supply chains, when we act upon irrelevant information, we end up doing the following:

  • Producing irrelevant products—products not required our customers—thus consuming capacities that might otherwise be used to produce relevant products
  • Shipping irrelevant products—thus consuming our logistics resources that might otherwise be used for the transportation of relevant materials
  • Buying irrelevant products—thus consuming our working capital that might better be invested in flow of relevant materials
  • Storing irrelevant products—thus consuming our storage resources that would be much more profitable if they were storing relevant materials

 

When we start seeing and confessing the reality of our situation, chances are we will start looking in a fresh, new direction for answers.

 

Just think about this:

 

How much of your supply chain is clogged with the flow of irrelevant information and irrelevant materials?

 

 

If you’d like to talk about this, we would like to hear from you. Please feel free to leave your comments below, or contact us directly, if you would prefer.

 

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Daniel Burrus says, “Disrupted or disrupter: you do have a choice.”

Disrupted or Disrupter: It's Your Choice

The world is moving very fast.

 

You may have noticed.

 

Supply chains have to move fast to keep up. Supply chain executives and managers must be able to make fast, effective, and accurate decisions—and they typically must be able to hundreds of such decisions every business day.

 

But, when SKU-level forecast errors exceed 50 percent of forecast volume on half or more of the items in your portfolio, how can you be expected to make accurate or effective decisions about product movement and replenishment?

 

It seems to be an impossible task.

 

You will never change the way you work until you change the way you think

Most supply chain executives and managers today are finding themselves under tremendous financial pressure. The financial reports are clearly indicating that their enterprises have too much working capital tied up in inventory, and operating expenses are impossible to control.

 

Worse! Much of the money tied up in inventories is tied up in inventories they don’t need! They’ve got too much of the wrong stuff!

 

At the same time, they are finding they must over-staff their supply chain with people who are pretty much dedicated to firefighting and expediting. Plus, they frequently have to pay for overtime in various operations just to keep their heads above water.

 

So far, the C-suite and supply chain leaders in the firms have done the safe thing. They’re doing the same things everyone else is doing.

 

They’re trying to tweak their MRP, MRP II and APS systems.

 

They’re investing the big bucks in “big data” and software that’s supposed to improve forecast accuracy.

 

They’re even considering upgrading their ERP systems, or adding new specialty supply chain management solutions promising improvements.

 

But, they are beginning to see that five, ten, even 20 years of investments in such “improvements” haven’t really moved the needle in terms of producing ROI (return on investment), or long-term competitive advantages.

 

They are certainly seeing that all this spending hasn’t made them a disrupter. And, more and more, they may be finding themselves disrupted by unexpected changes in their industry or markets.

 

It’s beginning, perhaps, to dawn on them that doing the same things is never going to produce different results!

 

It’s time to install new thoughtware*

It’s time to face the reality that only a new way of thinking will ever move your company and your supply chain from the disrupted quadrant into the disrupters quadrant of your industry. Anything else just leaves you as an “also-ran.”

 

The Demand Driven Institute (DDI) has been on the forefront of making new thoughtware available for supply chain executives and managers. Their promulgation of demand-driven methodologies, their educational resources, their certification of compliant solutions, their case studies, and their other efforts have dramatically increased awareness of power and effectiveness of becoming demand-driven.

 

NOTE: Becoming demand-driven doesn’t mean you’ll never use a forecast again. But, it does mean that you will de-risk your operational execution from forecast error. (It is beyond the scope of this article to explain how. Go to the DDI website to learn more.)

 

Isn’t it time for you to install new thoughtware in your supply chain? Become a disrupter. It’s your choice. We can help.

 

We would be delighted to hear from you. Please leave your comments below, or feel free to contact us directly, if that is your preference.

 

 

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* New thoughtware is a concept and term first promoted by The Thoughtware People.

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In all of the debate over the origin and meaning of “demand driven” with reference to supply chains, let’s be clear about one thing:

Every supply chain—every company that has a supply chain—is demand driven.

 

Actually, the question isn’t whether—in reality—a company or supply chain is, or is not, “demand driven.” They all are. We can say this without hesitation because, when the demand ceases, ultimately, there is no more supply chain and no more use for the companies that used to supply them.

 

The real question

The real question is what the demand drives the companies and supply chain managers to do.

 

In the vast majority of companies, the demand drives supply chain managers to:

  • Costly and vain attempts to improve forecasting – In a world where “80 per cent forecast mix accuracy is considered ‘world class,’” we find that this level of accuracy still conceals “the fact that most SKUs… will be achieving less than 60 per cent (i.e., greater than 40 per cent error!) because their demand volumes are medium to low and their statistical variability is medium to high.”* Despite huge investments in new forecasting technologies, the needle has barely moved toward effective improvement.
  • Inventories characterized (still!) by too much of the wrong stuff and too little of the right stuff
  • High-cost expediting practices
  • A multiplicity of schedule disruptions
  • Excessive and highly-variable lead times
  • Tens of thousands of dollars spent regularly on various firefighting efforts

In a minority of companies—companies where the supply chain managers have discovered new ways to think about how their inventories should be viewed and managed, and how to synchronize the flow of relevant information and relevant materials—the supply chain managers are now driven in by an entirely new set of metrics that lead to:

  • Achievement of planned service levels, while
  • Reducing average on-hand inventories by up to 50 percent, and
  • Exposing capacities in their supply chains allowing them to reach out to new and expanded markets, by offering
  • Dramatic lead-time reductions, all
  • Without costly expediting and firefighting, and without big expenditures on new forecasting technologies

 

So, yes!

 

Every supply chain and supply chain manager is “demand driven.” The difference—the huge difference—is found in what the demand is driving you to do.

 

What is your demand driving you to do? Is your supply chain really improving, or are you just getting better at expensive, on-going bad habits like "firefighting" and expediting?

 

Leave your comments here, and let us know. Or, feel free to contact us directly.

 

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DDMRP 5 Basic Steps

If you are a regular reader of my articles on supply chain management matters, you will know already that I am a big fan of “easy” versus “hard.” You might also recall that I am a firm believer in the principles of “inherent simplicity”—the concept that the more complex a problem appears to be, the simpler the effective solution must be.

 

Five Steps Forward

Recently I came across an article written by a highly respected leader in the world of supply chain management. In the article, the author acknowledged—as many others have—the utter poverty of technologies that came out of the 1990s and earlier when it comes to solving today’s supply chain problems, writing: “The… technologies of Advanced Planning (APS) along with Distribution Requirements Planning (DRP) and Material Requirements Planning (MRP) amplify the bullwhip effect within the supply chain resulting in the loss of agility and an inflexible response for the long tail.” [Note: I’m not trying to start or contribute to an argument here, so I will not mention the author by name.]

 

In the article, this writer lays out five steps for “moving forward.”

 

I would like to compare the five steps articulated in the article I read with the five steps articulated by the Demand Driven Institute (DDI), because both the author in question and the DDI believe that the answer for supply chain executives and managers must be found in becoming “demand driven.”

 

Here we go:

 

Proposed Step

Comments

DDI Step

Comments

Step 1: Define the [supply chain] process from the customer back, mapping all the demand signals (social sentiment, weather, ratings and reviews, channel inventories, and point of sale) and define how to use new forms of demand data. Measure and understand the impact on demand latency.

Sounds intimidating just reading it. I suppose if you happen to be a Fortune 500 enterprise willing to spend (perhaps) millions on such a venture, this might be in the realm of possibility. But how long will it take? What evidence is there that you will actually see a positive return on investment?

Step 1: Strategically position your supply chain buffers

In the typical implementation, this can be fully accomplished in a matter of days or weeks, and at a relatively low cost. (The cost for this phase will certainly be in the thousands of dollars, not the hundreds of thousands or millions that might be required by the alternate Step 1.)

Step 2: Build an outside-in demand planning model to use channel data. Experiment with attribute-based planning and probabilistic forecasting to better predict the long tail.

“Building” and “experimenting” sound like potentially long and drawn-out processes. And, what if the experimentation results in little or no real gains in your supply chain’s performance?

Step 2: Set buffer profiles and levels

Buffer profiles and levels are already taking advantage of actual demand feedback from your “channel,” and designed “probabilistically” cover your supply chain needs—long tail, or not.

Step 3: Use the probability of demand (not fixed numbers) to drive the flows and buffer strategies for inventory and material planning. Focus on managing form and function of inventory.

Here we find considerable agreement! Views of the DDMRP buffer status are truly a reflection of the “probability” that the buffer will meet demand expectations.

Step 3: Institute dynamic buffer adjustments

DDMRP employs the concept of buffer status to drive execution. The buffer status—a simple combination of a color and a value—tells everyone in the supply chain the likelihood of the buffer being able to protect supply chain flows.

Step 4: Implement demand sensing technologies to improve the short-term demand signal to improve replenishment and supply chain execution…. However, realize that most… [such] projects are [still] evolving.

Again, this just sounds expensive. It also sounds unproven, since the writer tells us that these kinds of projects are still “evolving.” If you’ve got time and money to spend (or, maybe, waste) on such things, take this step.

Step 4: Create a process for demand-driven planning

This is a “creative” step, all right, but the Demand Driven Institute has clearly laid out the rather simple steps for creating such a process. This is not rocket science and it doesn’t require vast investments in technologies.

Step 5: Experiment with new technologies to drive improvements in traditional approaches (including machine learning, cognitive computing, streaming data architectures, and more)

More experimentation with bleeding-edge technologies. This sounds to me, again, like very expensive with little assurance of positive return on investment. Got money to burn? Go for it!

Step 5: Build a high-visibility, collaborative execution process

As I have written elsewhere, since the data-set require is simple (not complex) building a high-visibility environment that encourages broad and effective collaboration across your supply chain becomes a low-cost, relatively easy-to-implement option.

 

When I compare these two sets of five steps, I cannot help but observe that the five steps proposed in the article I read are absolutely out of reach for 99 percent of the companies with which we work day-in and day-out. The have neither the time nor the money to spend on such programs—especially when the pay-off (if any) is likely to be in the far distant future, and may not come at all.

 

The concepts articulated by the Demand Driven Institute, on the other hand, are proven effective and can be readily implemented in almost any business enterprise in a matter of a few months. Read the case studies here.

 

To me, the choice is clear.

 

What do you think? Leave your feedback here. Or, if you prefer, feel free contact us directly instead.

 

 

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Nearly 20 years ago, someone wisely observed:

The most powerful computer system is the one that gets used.

 

This comes to mind today in light of the current debate in the supply chain management world between the different schools of thought—much of the debate seeming focused on deriding the demand driven operating model (DDOM) or DDMRP (Demand Driven Material Requirements Planning).

 

Some involved in the debate have stated more or less explicitly that the DDOM is too simplistic. They suggest that the DDOM simply  doesn’t have the sophistication required to effectively manage today’s complex markets and supply chains. Instead, they advocate for seemingly ever-increasing levels of complexity in the tools, including “probabilistic forecast driven multi-echelon inventory optimization.”

 

However, my more than three decades of working with supply chain matters and computer systems has shown me that, when the people using a system don’t fully understand the system, they are also likely to:

  1. Distrust the system outputs
  2. Ignore the system outputs (explicitly or implicitly), and
  3. Work around the system outputs to get to results they do trust

 

I, and many others, have found that system users will do this even if their home-brewed results are not leading them toward ongoing improvement.

 

Why? Because they clearly don’t think that the outputs from their complex computing systems are leading them toward ongoing improvement either.

 

The crucial factor is trust

People tend to trust what they understand and distrust what they don’t understand. (And, by the way, I have found that amongst our clients—small to midsized enterprises—there are very few supply chain managers and staff who are highly trained in statistical methods.)

 

They trust their own calculations because they understand the derivations of them—the underlying logic. They generally distrust “black box” outputs that cannot readily be reconciled in their minds to underlying data that they believe are relevant.

 

They may distrust the complex systems from the outset, or they may give these new systems a try and discover for themselves that, despite the sophistication, the results generally are not significantly different from previous methods in terms of improving customer services levels, reducing out-of-stocks on fast-moving items, or limiting the volume of excess stocks at the other end of the spectrum.

 

What I am saying is this: one of the reasons DDMRP, the DDOM and DDAE (Demand Driven Adaptive Enterprise) methods have proven to be so very effective at producing positive results is that everyone involved understands how the system works and, as a result, trusts the system’s outputs.

 

Finally, focus and agreement

Thus, they are not distracted from their goals by efforts to construct workarounds in order to find numbers that they do trust. Instead, they are focused on improvement. (And, if the enterprise wants to employ some “probabilistic forecast” as a factor in their buffer-sizing, they are certainly welcome to do so. Nobody’s stopping them.)

 

But, equally as important is the fact that the DDMRP and DDAE models keep everyone’s focus on “the surprise” in the data stream (the “tails of curve”)—which is where the real information lies. It also unifies everyone’s thinking around the proper responses and priorities.

 

Complexity tends to create a lack of focus—with too many factors to consider—and confusion over priorities. Pouring over huge volumes of data to see if the S&OP team is going to come to a consensus (forgetting even the possibility of unanimity) is not generally time or money well-spent.

 

In the midst of this debate, then, about which supply chain management system is the most powerful, I have come to this conclusion:

 

The answer lies, not in the sophistication of the underlying algorithms, nor in the complexity of ‘big data’ the system is able to process. Rather, powerful and effective supply chain management is found in the system that is able to be understood and trusted, and which, as a result, creates focus and a unified response to critical factors affecting FLOW.

 

My experience teaches me that, focus and flow will beat complexity and sophistication almost every day. (And, on the days when complexity and sophistication appear to “win,” it’s more by chance than any other factor.)

 

If you would like to learn more about DDMRP, the DDOM and DDAE, you may do so by visiting the Demand Driven Institute website, and we can help you get started with this proven and powerful approach to effective supply chain management.

 

We would like to hear your comments. Please leave them below, or feel free to contact us directly, if you prefer.

 

 

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