- The Demand-Driven Institute has created the DDMRP concept which began with a perversion of Orlicky’s 3rd edition MRP Book.
- DDMRP is very simply a repackaged of JIT and Lean.
Introduction: The Real Story into DDMRP
In this article, we will analyze proposals made about something called DDMRP.
DDMRP is an adjustment to MRP that is proposed to improve MRP systems outcomes greatly. I will begin by analyzing a book which helped kick off the DDMRP craze.
Ridiculous Orlicky’s 3rd edition MRP Book
Joseph Orlicky was one of the originators of MRP. Orlicky wrote the first book on MRP in 1975 when MRP was beginning to be known. Orlicky died in 1986. In 1994 the 2nd edition of Orlickly’s MRP was written/adjusted by George Plossl. I am not a big fan of the 2nd edition of books being written by authors other than the original author. This is apparently an attempt by the publisher to extend a popular book to a new group of buyers. However, George Plossl is probably my favorite inventory management authors. George worked with Orlicky, so the second edition was quite consistent with the first edition.
Curiously, the 3rd edition of Orlicky’s Material Requirements Planning book was published in 2011. That is right; we are now releasing new editions of books 25 years after the author has passed away.
This book was written by anyone who worked with Orlicky, but instead by Carol Ptak and Chad Smith, who also wrote the book DDMRP.
When I read 3rd edition of Orlicky’s MRP book back in 2012 (according to my Amazon account), I noticed that it did not appear to have much correspondence to the 1st or 2nd editions. Furthermore, I don’t even think that Orlicky would have agreed with much of the material presented in the third edition of “his” book.
Therefore, the 3rd edition is only “Orlicky” in name only. It is neither written by him nor inspired by him.
The Most Accurate Way to View The 3rd Edition of Orlicky’s MRP
In my view, Orlicky’s MRP 3rd edition is merely a way for JIT/Lean proponents to worm their way into MRP and to try to get companies to change their MRP systems into order to conform with JIT and Lean principles.
To explain why this is so problematic, we need to revisit the history of JIT and Lean briefly.
The History of JIT and Lean
JIT was first introduced outside of Japan in the 1980’s. JIT was a highly inaccurate presentation of parts of the Toyota Production System. At the time Toyota (as well as other Japanese manufacturers) were attaining quality levels that no other automobile manufacturers from other countries could match (and continue to maintain). The TPS developed during the postwar period and is based upon very low levels of waste. However it was brought over to countries outside of Japan by consultants, and consultants grossly oversimplified the TPS and JIT. Important things that the TPS/JIT consultants left out included the following:
- Unionization and Empowerment of Factory Workers: Toyota plants were highly unionized. This means empowered workers that could stop the line to keep quality levels high. Consultants knew that US executives detested unions, so this feature of the TPS was entirely left out of the books on the TPS at the time.
- Supplier Inventory Location: Much was made of keeping low inventories in the factory. However, JIT consultants left out the fact that Toyota suppliers were closely located to Toyota factories. Therefore, the inventory was normally “right around the corner” although not on Toyota’s books. When the math did not add up, companies that moved to such low inventories based upon faith in JIT consultants experienced reduced production capabilities.
- Stable Production Schedule: Quite the opposite of “Flexible Manufacturing” Toyota, in the 1970’s and 1980s at least, had a stable production schedule for one month out. This meant low material variability and a strong ability to coordinate deliveries with suppliers. Knowing that this would infuriate US executives who like a very unpredictable production schedule (outside of manufacturing) the consultants “left that little part out.”
JIT Definition or JIT Meaning
The JIT meaning or JIT definition is the reduction of inventory so that the new inventory that replenishes the stocking level right before it is to be depleted. There is some debate as to technically this is when this happens. That is after safety stock has been partially depleted, but there are many different JIT practitioners, and they have differing opinions.
The JIT definition of JIT meaning has several sub-areas. These JIT definition or JIT meaning includes just in time inventory and just in time manufacturing, JIT manufacturing or JIT production, which we will discuss further in the article.
While many people do not know the specifics of the JIT definition or JIT meaning, most do know that JIT results in lower inventory. But what is not at all well known is the method by which JIT proponents arrive at their proposal of stocking level is philosophical and based on the anecdotes of experience in inventory management from Japanese manufacturers.
Just in Time Inventory or JIT Inventory
Just in time inventory or JIT inventory is the minimization of inventory based on the concept that a smaller stocking level can be maintained and an increase in delivery frequency performed. Quantification of the extra costs of the JIT inventory system is not part of the JIT method. The just in time inventory system or JIT inventory system is based upon philosophy, not based upon developing a body of evidence to support the move away from traditional inventory management.
JIT Delivery and Higher Ordering Costs, Delivery Costs, Receiving Costs and Put Away Costs and Delivery Frequency
Extra costs of the JIF inventory system include higher ordering costs, higher delivery costs, higher receiving costs and
- Higher Ordering Costs
- Higher Delivery Costs
- Higher Receiving Costs
- Higher Put Away Costs
Put away is the process of moving and stocking the inventory at its stocking place. Put away follows goods receipt.
One of the primary reasons why JIT proponents don’t calculate the ordering costs, delivery costs, receiving costs or put away costs is that if this were done, the overall costs would necessarily look higher. The reason for this is that the inventory carrying cost is far lower than all of the transactions that make up the stocking level.
Delivering in small quantities with high delivery frequency is called JIT delivery. Many shipping companies specialize in JIT delivery frequency to meet the market demand. JIT delivery can be driven my JIT or Lean thinking, or it can apply to factories in congested areas that lack sufficient stock space.
The EOQ formula produces an order quantity based on a trade-off between inventory holding cost and inventory ordering cost. In such a formula, the ordering cost costs, delivery costs, receiving costs and put away costs could all be placed into the ordering cost category. JIT inventory management does not support the concepts of such mathematical determinations.
Just in Time Manufacturing, JIT Manufacturing or JIT Production
JIT primarily came from Japanese manufacturers, through US consultants and to global companies. Although the greatest JIT craze was probably in the US. Just in time manufacturing, JIT manufacturing or JIT production means JIT applied to manufacturing. Therefore, JIT is a manufacturing inventory concept that came from factories and was then applied to the overall supply chain.
Just in Time Supply Chain
Just in time supply chain is simply applying just in time manufacturing, JIT manufacturing or JIT production principles to supply chain, which means to inventory management outside of the factory. Just in time supply chain supports seeing the overall supply chain as if every stocking position and every stocking level is a short lead time product location that is no different than a manufacturing facility that is lucky enough to be able to be continuously replenished under the Toyota, inventory model.
JIT Inventory System
A JIT inventory system is simply a method that applies JIT. Any supply planning or MRP/ERP system can be made to operate under JIT principles. This typically results in the system being set to work on consumption-based planning using methods like reorder points. JIT is opposed to forecasting philosophically, considering it too unreliable. The problem is that while this may apply to a stocking level or stocking position, it is not possible to apply consumption based planning in all circumstances. And the longer the lead time.
Misinformation on Inventory Conceptually Because of Lean or JIT
Lean is just rebranded JIT. Since at least the 1980’s a philosophy of keeping low inventories has gone by various names. At one time it was JIT, and then it became Lean. JIT was based upon low inventories that the Japanese were able to keep. But without understanding, that Japanese companies work more collaboratively than US companies. Second that many industrial areas in Japan have suppliers located close to their customers. The US does not have the same supplier network setup that Japanese companies do. Also, if simply a supplier is maintaining your inventories, then the overall system inventories are not lower. This distinction was left out of most of the explanations provided to US companies by JIT/Lean consultants.
Lean is primarily a philosophy which is based on taking a concept from production planning that works in specific circumstances. Lean does make sense when it uses an analytical approach to segment the product location database and converts some of the unforecastable product locations to reorder point planning.
JIT as Esoteric
With JIT consulting the name of the game was sounding leading edge and esoteric — not communicating the true nature of TPS and JIT as practiced in Japan.
JIT eventually developed such a bad reputation that JIT consultants and consultancies knew they had to make a change. Drunk on their own Kool-Aid, the answer was not going to be to include more accuracy in their consulting. That is to make it representative. Instead, they opted for a name change.
JIT became Lean — and the unsupported claims resumed. It resumed to this day.
Today you can receive all manner of certificates on Lean, most of which merely consists of imposing unrealistic proposals on manufacturing and inventory management. I have never seen any of these certificates, any Six Sigma plaque, Lean plague, or other merit badges to have any relationship with better outcomes for inventory management in companies. In operations, having them often makes the difference in getting jobs or not getting jobs.
How JIT and Lean are Incorporated into Systems
JIT and Lean consultants like using Japanese words. They like saying Sensei and Kopai. They like to talk about Toyota….as often as humanly possible. Lean has its rituals and in this way is quite similar to the Crossfit cult.
However, what JIT and Lean proponents don’t like to address is that JIT and Lean capabilities have resided in software since supply and production software was first introduced, and before that in inventory formulations. I propose using some of these approaches as well. They are outlined in my books Lean and Reorder Point Planning and Multi-Method Supply Planning in SAP APO (where “Lean” methods and forecast based planning are mixed by product location in SAP, as well as multiple forecast based procedures are mixed in).
I cover how to assign product location combinations to reorder points, min-max, etc.. based on a concept called forecastability. I have a forecastable/non-forecastable formula at the following this How to Understand Forecastable Unforecastable Formula.
The matter is rather simple.
- Some items can be reliably forecasted — and for those, it makes sense to use a forecast based supply planning method. MRP is one of these available in the software.
- For items that cannot be reliably forecasted, it makes sense to use consumption-based methods.
All of this can be set up in supply planning systems. It does not require donning a kimono or learning Japanese. It does not require an APICS certification. And it requires no colored belts of any kind. It is the application of basic inventory management knowledge.
DDMRP proposes using MRP as a non-forecast based planning approach — which makes little sense.
To explore why I have included quotations from several articles on DDMRP.
Articles on DDMRP
The article Demand Driven Material Requirements Planning (DDMRP) on Linkedin, makes the following points.
“DDMRP is a revolutionary planning method that is designed to meet the needs of the modern day market. Compared to MRP, DDMRP generates orders based on actual sales orders, rather than forecast.”
That does not make any sense. This is because MRP is a forecast based planning method. One can, of course, decide to only feed an MRP system sales orders — but as covered in the book Replenishment Triggers: Setting Systems for Make to Stock, Make to Order & Assemble to Order, the vast majority of companies cannot move to make to order environments. The lead times just don’t work out. Therefore, right off the bat this explanation of DDMRP essentially pitches fools gold to executives.
“This allows for much higher customer service levels, lower costs in expedite, and the right levels of inventory.”
Why is any of that true? Why does basing MRP on sales orders allow for higher customer service levels? If, as in most cases, the environment cannot be made make to order, service levels will decline. In fact, the company will experience stock-outs and lost sales.
Basing MRP on Sales Orders
Secondly, how does basing MRP on sales order reduce the cost of expediting? It would be the opposite. Also, it does not lead to the “right levels of inventory.” This will only be the case if the environment is, in fact, make to order.
“MRP hasn’t changed since its inception and this is where DDMRP was designed to tackle all the critical issues in order to maintain a healthy production environment.”
Well, the math may not have changed, but modern MRP systems are a lot better than the MRP systems that were first introduced. When MRP was first introduced, it was run off of computer tape. That is, MRP pre-dated disk storage.
“Today, there are more complex and planning scenarios than before. The past is no longer a predictor of the future.”
This all sounds quite sexy. But the reason for this has more to do with companies increasing their SKU count (with supermarkets in the US having roughly 40,000 to 50,000 SKUs. This lowers forecast accuracy. But even though products are becoming less forecastable, it does not mean that DDMRP is the answer. The problem is that again; it is not feasible to run planning off of sales orders.
- “Achievement of 98% customer service levels
- Revenue maximization
- Inventory reduction by 40%
- Expense minimization
- Cash flow”
This is where the author is moving into exaggeration (Hasso Plattner style exaggeration in fact – which is a higher level of an exaggeration than Larry Ellison or Steve Jobs).
No Inventory Method is Designed for 98%
No inventory method or technique on planet Earth is designed for the “achievement of 98% customer service levels.” The service level achieved depends on the input and the situation.
Does DDMRP maximize revenue? Hard to see how that would turn out to be true. Companies that only base MRP on sales orders will be in for a world of customer disappointment.
Why is inventory reduced by 40% exactly? Why not 35% or 45%? This seems to be directed towards hooking executives by telling them what they want to hear.
“DDMRP is also a new way of planning and control, which shifts from a forecast driven model to a sales order driven model. In MRP, requirements are calculated based on the forecast, which eventually becomes irrelevant as time moves on.”
This is a highly uninformed statement. Forecasts will in almost all circumstances have an error.
- Low errors are good.
- High errors are bad.
However, this does not mean that forecasting is invalid.
Actual Percentage of Make to Order Products?
And once again, as customers demand products more quickly than they can be produced, make to stock environments are the most common environment to be found. Only a very small percentage of business is true make to order.
Make to order means that no procurement orders are created, until the sales orders are received. It does not mean that stock is maintained until an order is received and then manufacturing begins from that point. That is called assemble to order, and is a different thing altogether.
Probably less than 5% of businesses can work this way. Defense contractors being a perfect example of this. Construction projects are another.
The Article “Why DDMRP”
The article Why DDMRP Is A Necessary Condition For Industry 4.0 To Deliver On The Promise makes more bizarre contentions about DDMRP.
“This vital element is the use of the Demand Driven Operating Model and the related planning methodology Demand Driven MRP (DDMRP). This is currently the only approach that allows to effectively synchronize supply and demand across complex and volatile supply networks.”
Let’s not hyperventilate too heavily DDMRP proponents! I know that there are projects to be sold, but let us keep it within the realm of sanity.
So according to this quotation, only DDMRP can synchronize supply and demand over volatile supply networks. This is quite interesting because MRP is not the most sophisticated method of matching supply and demand. Inventory optimization and multi-echelon as a planning method is far more advanced than MRP.
MRP Versus More Advanced Supply Planning Methods
Unlike MRP it has the math to compare stocking locations across the network and can set stocking positions while cognizant of the stocking locations around the stocking location. Overall, it is entirely inaccurate to say that DDMRP is “the only way” to connect supply and demand.
“For instance, one of our clients recently reported to us that from the moment they have changed their distribution planning using DDMRP they completely eliminated shipments between distribution centers. This used to be a major supply chain expense before, due to inventory being in the wrong place. During the same period inventories went down by 20% and service levels improved. Meanwhile, order stability achieved perfection: not a single supply order has been changed once placed to the sourcing plant.”
This anecdote could only be true if this company is a make to order environment.
However, if this company is a make to order company, why was it performing redeployment in the first place?
Why is Inventory Carried…..Again?
The authors in DDMRP seem continually confused as to why inventory is carried in the first place. No one wants to carry inventory. But that is what the lead times that companies face are required to do.
This misunderstanding extends to comments made in the article.
“Thanks Patrick for This excellent article. … 85% of forecast accuracy means that at least 15% of mistakes are propagated throught all the supply chain ! Is it good enough to reach more than 98% of service rate ? … probably no.”
Once again, unless you can hit 99% to 100% service levels, forecasting is a waste of time because of “propagation” according to nascent DDMRP experts!
In another article titled When SAP will include a DDMRP solution in the existing supply chain solution? The proposal is that SAP must offer DDMRP. This is an attempt to move MRP into software before it is proven as an approach.
How To Understand Trendiness in Supply Chain Management
With terms like JIT, TQM, Lean, B2B marketplaces, Kanban, optimization, supply chain management is filled with trendy concepts that influence decision makers (a strangely high percentage of which are Japanese in origin for some reason).
In fact, for an area of study that is supposed to be more of a science than an art, supply chain management has been remarkably trendy.
I have previously described the fact that approaches applied to supply chain software very frequently do not have to pass any logical test. As I stated in response to a comment on demand sensing being a method to primarily fake forecast accuracy:
“One consultant I was working with stated that company XYZ was reported to have success with the approach. I had just come from that exact company, and my experience with them was they neither their executives nor their IT group knew anything about forecasting, and this multi-billion dollar company could not do the most elementary forecasting functions. Actually, very few companies can be used as models for forecasting excellence. Most companies do a horrible job of taking advantage of systems to improve their forecast.
However, if a big consulting company does something, or a big client does something, that seems to be sufficient evidence that other people should do it as well. I think the first question needs to be “does it make sense?” and secondly, “have we tested it?” The fact that a consulting company or a client did this or that really means nothing. Very few executives call in journalists into their office to report that they completely bombed on their IT implementation because they were ripped off by Accenture who lied to them about what software could do for them and this caused them to miss their quarter. This is called reporting bias, and obviously must be adjusted for.”
Illogical Supply Chain Management Trends
Observing the illogical nature of many supply chain management trends was noticed and written about decades ago by George Plossl. George Plossl was very focused on practical and often mathematical approaches managing the supply chain, and therefore many of the trends in a supply chain, most of which have failed to pay dividends must have struck him is strange as they strike me.
“Probably the greatest misconception is that the job of effective planning and control is primarily technical. The literature of the technical societies and the words of a few consultants have led many managers to believe that all they need for control are the right techniques in a system. Overselling sound and necessary techniques like MRP has certainly been a great disservice to hard-pressed managers. Interest in new techniques flares up like fads in clothing and sports. Too many managers seem to believe that they can buy their way out of trouble quickly by adopting the Japanese “Kanban” technique or the Israeli super mathematical “Optimal Production Technology.” Over-simplified solutions to complex problems, like jogging for better health and fad diets, continue to beguile many people unwilling to adopt the necessary changes in life-style so needed for achieving their real goals. Sound planning, effective execution of the plan and adequate control requires more than techniques and computer programs however elegant and expensive these may be.” – George Plossl
In this quote, George Plossl does a good job of explaining the penchant for trends that he saw in his consulting work.
The false statements regarding DDMRP come hot and heavy from DDMRP proponents.
- Misleading Book: Orlicky’s 3rd edition has very little to do with Orlicky, and in my view, Orlicky would disagree with much of it. If the authors wanted to promote DDMRP, they could have done this through their book which has that title. Why infiltrate a pre-existing book that does not have much to do with what you are promoting?
- Accuracy Issues: Statements made by DDMRP proponents are highly inaccurate in the articles that I have analyzed — many of the statements presenting a lack of knowledge about how supply planning systems function.
- Plain Old MRP Was not Demand Driven?: The term DDMRP or demand driven MRP used to differentiate it from plain old MRP is nonsensical. MRP is a forecast based supply and production planning method. As such it is already demand driven. The opposite of demand-driven would be supply driven. This is where the supply side is the focus of production and distribution. There are many environments that not only should be supply driven but have to be supply driven. This is covered in the article The Forgotten Supply Driven Supply Chains. However, plain old MRP is not “supply driven.” It can’t be as MRP not a constrained method of planning. MRP always runs as if supply is unconstrained (something which is addressed in a later planning run called capacity leveling). MRP can only incorporate supply limitations through the use of min lot sizing. Therefore it is illogical to try to cast “plain old MRP” as something which is supply side. This is what “demand-driven” MRP seems to be doing. A more accurate name would have been sales order based MRP.
- But Wait, The Ginsu Knife Also Comes With…: DDMRP has a bunch of other areas to it, including sizing inventory buffers. Upon review, it is difficult to see how this adds value to the traditional methods of stock level setting. It is different, and therefore more difficult to validate, but is it better? Overall DDMRP has nothing that strikes me as having contributed to inventory management — so why would this area be anything but more unrealized promises?
- Following the JIT/Lean Playbook of Exaggerated Claims: Much of the exaggerated claims, as well as the idea that forecasts cannot be trusted, is right out of the JIT/Lean playbook. However, after some decades now, JIT/Lean has produced very little in the way of improvement in inventory management. The reason is simple. JIT/Lean proponents are more concerned with making an impression and a “splash” than in presenting what is true. DDMRP will end up being simply more of the same.
This is a response to a question asked by Sanjeev Gupta on LinkedIn. I could not fit the response into the LinkedIn comment box without breaking in into too many comments. I think Sanjeev’s questions is very important, so I am profiling it here.
“Potentially useful back and forth between Shaun and Carol/Chad!
I don’t think it matters whether DDMRP repackaging of JIT and Lean or not (sometimes truth is eternal, sometimes old truths are new fallacies), whether Orlicky would have agreed with DDMRP or not (he wasn’t God and even God can be wrong), and whether MRP is Pull or Push (that is just semantics).
My limited experience is that many supply chains struggle with high inventories and unavailability as well as firefighting, and I believe all that matters is, “Does DDMRP result in higher availability with lower inventories and less management effort?”
Carol/Chad: Is it possible to provide a mathematical proof of this, something that is not just qualitative cause-and-effect? Conversely, Shaun, can you provide a mathematical proof that DDMRP does not yield better results than old MRP?” – Sanjeev Gupta
Sanjeev is asking several questions. For clarity, I have created a topic heading for each answer topic. These topics are as follows:
- Does a Mathematical Proof Answer the Question of DDMRP?
- Admitting When Things Do Not Work
- A Mathematical Test for DDMRP Versus MRP?
- The Problem with Investment Prioritization
Does a Mathematical Proof Answer the Question of DDMRP?
You are proposing that there is a single way to determine whether DDMRP is an improvement over MRP. And that the way is a mathematical proof. I can provide several reasons why that is not true. (I am not trying to pivot away from your primary question as I have researched this topic and I will refer you to a study that does what you describe.)
- Example 1: It is often the case that a new and complex forecasting method/mathematics is introduced, that it can outperform less complex forecasting methods in a laboratory environment. However, in actual practice, the more complicated forecasting method which is “mathematically superior” will often lose against more simple straightforward methods. Forecast papers often test small data sets and are willing to put a lot of effort into improving forecast accuracy. But real supply chain departments do not work like that. This is because in real-world environments there is a very limited amount of effort that can go into maintenance of the forecasting system. I covered this topic in detail in the following article Complex Versus Simple Forecasting Methods. This is a concept promoted by strong evidence by Armstrong in his excellent book Principles of Forecasting 2001.
- Example 2: Inventory Optimization and Multi-echelon (MEIO) is more mathematically sophisticated than MRP. In fact, there is nothing in MRP beyond arithmetic (the procedure itself, not the parameters). MEIO can build inventory to match a service level (the inventory optimization mathematics), and it is aware of the stocking position of locations around it (the multi-echelon mathematics). Therefore MEIO is better right? Well, it depends. MEIO is too complicated for the level of investment that most companies are prepared to make into their supply planning systems.
Is the Criticism of DDMRP Being Repackaged JIT and Lean Relevant to its Probably Improvement Over MRP?
JIT and Lean proponents have a decades-long established history at this point of exaggerated claims. Of using hyperbole such as “forecasts are wrong” and Toyota “did this or that” and they have rebranded themselves once before, that is when they moved from JIT to a new name (with a new bunch of books called Lean). Do these proponents need me to trot out simple-minded books like “Zero Inventory” or the books that misrepresent what Toyota did, and to go over the terrible exaggerations and mistakes made by following JIT and Lean consultants? Is this some mystery at this point? It is indisputable that JIT/Lean has been littered with exaggerations as I cover in How the Toyota Production System Was Misrepresented to US Audiences. Deloitte JIT/Lean consultants told one of my accounts to break up their inventory into multiple stocking locations in the factory — which surprise lead to a major increase in inventory. They told them Toyota did this and that it was a “Supermarket.”
It is strange that I would be making this argument because I am a major proponent of turning off forecasting for product/locations that are deemed as non-forecasted — as the following article Forecastable Non-Forecastable Formula.
The majority of companies I have consulted with are forecasting items and putting effort into improving the forecast for items with no discernable pattern. (that is they are assigned to a Level forecast by a best-fit algorithm). Turning off forecasting for products that cannot be forecasted efficiently is an important strategy in both improving stocking positions, but also in allocating the scare time available in overburdened forecasting departments.
But JIT/Lean proponents move far beyond the judicious use of consumption based techniques, and into diminishing all supply planning procedures, and sell companies on the idea of moving to make to order environments that can’t I refer to this as The Make to Order Illusion.
It has been proposed to by many JIT/Lean consultants to many soft target executives with predictable results. JIT/Lean proponents should be held to account for these inaccuracies. But they will have none of it, they are interested in hiding these failures, and going to make more projections. It would certainly be the ultimate dream of every JIT/Lean proponent to undermine procedure based planning. And DDMRP gives them a cover to do this. So we should be suspicious of their intentions.
If people misrepresent their history of success and then rename their methods into something that is the opposite of this type of planning, then this is quite germane to the discussion of the validity of what they propose. And this gets to the topic of honest in recognizing the failures or shortcomings of your approach.
Admitting When Things Do Not Work
I come from a background of advanced planning. I was very excited in my mid to late 20s in working in advanced planning, and I drank some (although not all) of the Kool-Aid served by my employer, i2 Technologies. However, I observed from working on projects that the optimization projects I worked on did not match the sales that we presented to customers. The media gave i2 Technologies the typical unquestioning coverage, and for several years everyone wanted to “do optimization.” How i2 Technologies was able to “corner the market” on optimization is another story, because optimization had been kicking around in academics for years and no one “owned” anything all that proprietary when it came to optimization.
With my background, I am one of the only, and probably most well-published critics of how badly cost optimization failed to add value to companies.
While i2 Technologies eventually fell, major companies are still trying to get a flawed optimization approach to work in SAP that will never work, which you can read about in detail in the article The Problem with SNP Optimizer Flow Control.
I say this as a longtime consultant in SAP, but the SAP is ripping off accounts and lying to them about the benefits they can obtain from a system I have extensively tested, and essentially does not work. SAP charges somewhere around $450 per hour to a group of Ph.D.s in Waldorf that must be seriously laughing at these customers who can’t put 2 and two together that the applications need to be deactivated.
And these are big name brand companies using this solution you would recognize. If you like you can hire SAP consultants to “improve your SAP optimization,” and you will not hear a peep from these consultants about the history of cost optimization.
Many SAP consultants have reached out to me in private not speak and write about these things. They have asked that I air my issues in private, that to do so in public creates “bad feelings” and reduces the optimism about cost optimization. And you should have optimism about something if a major entity proposes that it is true, and if you can bill hours for selling the illusion and hiding the truth.
So my point being, I have a track record of being honest when things that I have worked in don’t work. But I can’t see where I have seen JIT/Lean proponents do that. They shy away from telling the truth of what happens on projects. There are certificates to be attained, various colored belts to receive and various trendy items to placed on resumes, but little time to determine if things actually work.
So hopefully that explains why I do think the issues I have brought up are relevant to whether or not DDMRP will produce real benefit. I have used the same techniques of skepticism to make previous predictions on SAP, and have so far batted 1000 on my SAP predictions. Of course, one’s accuracy improves if you don’t get paid by the entity for which you make projections.
Now, let us switch gears.
A Mathematical Test for DDMRP Versus MRP?
There is a single published study I was able to find which tests DDMRP. It is titled MRP vs. Demand Driven MRP: Towards and Objective Comparison and published by the Institute of Electrical and Electronic Engineers in 2015.
I don’t want to give away everything in the study, as the researchers deserve compensation for their work. And furthermore, the conclusion is a bit of a mixed bag, so one has to read it for oneself. In conclusion, the authors stated that DDMRP performed a little better in one area and a little worse in another. And the study points out that if the demand had been made more variable, the results might have been better for DDMRP.
So the results would seem inconclusive. However, I found something that the study did not highlight. And that is that DDMRP requires a lot of investment and a lot of change regarding working in the DDMRP paradigm. New inventory buffers must be calculated and maintained; there are new seasonal factors, planning adjustment factors to be incorporated, and so on.
In reading the study, which did an excellent job of explaining what had to be done, I began to wonder where the funding for all of this effort is going to come from. The MRP systems that I have seen at companies are held together with glue and tape. Multinationals with billions in revenues tend to want to invest as little as possible in their MRP systems. The planners tend to be poorly paid. Many of the directors of supply chain don’t even understand how MRP works (I have also seen people come over from sales to head supply chain departments — how can that end well?). Many speak in platitudes about high service levels and come up ideas like “how about we move to daily forecasting!” At one company where there was virtually no budget for MRP improvement, I was shown the stock sales of company insiders which ranged from $2 million to up to $36 million. So let’s face it, MRP investment is a distant second to exercising stock options apparently.
The Problem with Investment Prioritization
I came up with an inexpensive way to optimize supply planning/MRP parameters. I am often told there is no budget and is there something their planners can do to get the same benefit, like maybe reading some of the books or reading some articles or going to APICS, all while some analytics project that often has little output ends up with plenty of funding. People have frequently told me “it’s too complex.” Read it for yourself at 3s – Safety Stock and Parameter Setter.
Well if parameter optimization — which does not change the MRP process in any way — is too complicated and too time-consuming — where is the funding and motivation for a large effort like DDMRP going to come from? I recently worked as a sub-contractor for a consulting company that had won a contract in my area but had no reason to have received the contact for this work. I realized they had received the work because they exaggerated and “sold” the account.
It makes me wonder if this is where we are with DDMRP? Does one have to oversell, to propose amazing outcomes to get investment for MRP improvement? Is this why money is flowing to DDMRP projects?
So to answer your question, I only know of one study on DDMRP and please read the study for yourself, but the study appears inconclusive. Chad Smith has been very vigorously promoting the case studies that show DDMRP success. And I am not trying to be difficult or contrary, which seems to be the view of a few commenters, but the indisputable fact is that companies don’t publish their failures. If the customer provided published information was reliable, then we would have to accept that every single case study published on every vendor and every consulting website is true. Secondly, it is very rare for companies to have good metrics on their supply chain. Companies routinely overestimate their forecast accuracy.
This is because most do not know that the only relevant forecast error measurement has to be at the product location (and not at a higher level of aggregation). Research shows that they think they deliver a seven percentage point service level than they do, and there is virtually no funding for such measurement. The business is normally just trying to keep up with their normal planning work. If I could personally measure these benefits, it would mean something. But self-reported benefits from companies that aren’t very good at measuring and don’t follow a scientific approach does not mean much to me.
The problem with DDMRP is it put forward an illusory magic solution for supply planning. DDMRP requires a great deal of adjustments on the part of companies that implement DDMRP, extensive new training, etc..
One of the primary claims of DDMRP is that standard MRP does not work. However, the bigger or more central issue is that MRP systems are poorly maintained. Whenever we extract parameters from an MRP or other supply planning system we find a wide variety of irregularities. Since the 1990s, multiple vendors have proposed that MRP was no longer relevant and that companies needed to move to cost optimization, allocation, heuristics or inventory optimization.
The net result?
The vast majority of products planned in the US and Europe are planned by the MRP procedure. DDMRP is in our view just another in a list of supposedly better methods of supply planning that reduces the incentive to focus on the key areas that are necessary for improving MRP.
The Problem: Maintaining Inventory Parameters
A major part of replenishment is inventory parameters. These parameters include values like safety stock or days of supply, rounding value, reorder point, lot size/economic order quantity and minimum order quantity. Whatever the planning procedure that is used, these parameters control what the supply planning system does.
Testing of the extracted parameters of ERP and external supply planning systems clearly shows that these values are poorly maintained. The result is far worse planning results than could be obtained otherwise.
Being Part of the Solution: Our Evolution of Thinking on Maintaining Reorder Points in ECC or APO
Maintaining inventory parameters like rounding values and lot size in systems comes with a number of negatives that tend to not be discussed. One issue is that when using ERP systems, inventory parameters are typically managed on a “one by one” basis. This leads to individual planners entering values without any consideration for how inventory parameters are set across the supply network. After years we have given up managing safety stock or other inventory parameters in we now calculate inventory parameters in our application, the Brightwork Explorer, and then simply upload the data into the ERP system. See our link below. We have developed a SaaS application that sets the inventory parameters that allow for simulations to be created very quickly. These parameters can then be easily exported and it allows for far more control over the parameters. In our testing, the approach, which is within the Brightwork Explorer is one of the most effective methods for managing planning in any system. This approach is laid out in the book How to Repair Your MRP System.
In our testing, the approach, which is within the Brightwork Explorer is one of the most effective methods for managing planning in SAP applications.
One of the questions we have considered is whether DD-MRP is logical, which is a high maintenance change to MRP, or if instead MRP and supply planning software can be tuned with an external application.
“Production and Inventory Control: Applications,” George Plossl, George Plossl Education Services, 1983
Orlickly’s Material Requirements Planning, 3rd Edition, Carol Ptak and Chad Smith.
DDMRP: Demand Driven MRP, Carol Ptak and Chad Smith.
Lean and Reorder Point Planning Book
A Lost Art of Reorder Point Setting?
Setting reorder points is a bit of a lost art as company after company over-rely upon advanced supply planning methods to create the supply plan. Proponents of Lean are often in companies trying to get a movement to Lean. However, how does one implement Lean in software?
Implementing Lean in Software
All supply planning applications have “Lean” controls built within them. And there are in fact some situations where reorder points will provide a superior output. With supply planning, even within a single company, it is not one size fits all. The trick is understanding when to deploy each of the approaches available in software that companies already own.
Are Reorder Points Too Simple?
Reorder points are often considered to be simplistic, but under the exact circumstances, they work quite well.
There are simply a great number of misunderstandings regarding reorder points – misunderstandings that this book helps clear up.
Rather than “picking a side,” this book shows the advantages and disadvantages of each.
- Understand the Lean Versus the MRP debate.
- How Lean relates to reordering points.
- Understand when to use reorder points.
- When to use reorder points versus MRP.
- The relationship between forecastability and reorder points.
- How to mix Lean/re-order points and MRP to more efficiently perform supply planning.
- Chapter 1: Introduction
- Chapter 2: The Lean versus MRP Debate.
- Chapter 3: Where Supply Planning Fits Within The Supply Plan
- Chapter 4: Reorder Point Planning
- Chapter 5: Lean Planning.
- Chapter 6: Where Lean and Reorder Points are Applicable
- Chapter 7: Determining When to use Lean Versus MRP
- Chapter 8: Mixing Lean and Reorder Points with MRP-Type Planning