Friday, October 13, 2017

Absorption Based Planning 

There is – and actually has been for a long time – a lot of talk about buffers, safety stocks and de-coupling points in supply chain planning. Let me add another term to this: shock absorbers. “Oh my”… you might cry out “Not another buzz term or theory!” I’m with you… too much confusion and buzz around this subject. But please allow me to take a shot on simplification and order in this area.
From experience we know that supply chains are exposed to variability in supply, demand, in process and sometimes we even inflict it ourselves. We also know that when variability is present things do not work out as planned. We might end up with stock-outs, too much inventory, late deliveries, backlogs, exception message galore or general chaos. That is why we should plan with variability in mind.
None of this is new or of any revelatory kind. We all know this. The question is what we can do about it. And there are many schools of thought and also some schools of not-so—much-thought-through thought. My approach is one of segmentation with subsequent policy setting. That is also not new but just recently I had a little bit of an epiphany (far from earth shattering) with what I call absorbers. Allow me to elaborate:
Most planning systems I come across are set up with rigid connections. I call these deterministic. In it network nodes and Bills of Materials are strictly dependent on each other and any changes in demand or supply will cause a “rattling” of the entire structure. There is immense noise and nervousness in such a system and it often produces superfluous inventory, vast amounts of stock-outs and exception messages with no end to it.

Planners are usually very aware of this nervousness and being forced to work “in” the system (as opposed to be allowed to work “on” the system) trying to facilitate the issues with expediting and fire-fighting. When the situation starts to look like an unsurmountable mountain of orders, materials and requests, the static safety stock looks like a plausible solution. That is when things completely fall apart and for some reason no one can explain why inventories grow further and stock-outs happen more frequently (delays, my friends, delays is the problem).
So what can be done? I am not claiming that I know the all encompassing solution to the problem but let me make a couple of suggestions:
First, assess your network and bills of Materials and look for spots where you can de-couple the rigid structure. What I mean by that is that you free up the deterministic planning process of dependent requirements and dependent supply. De-coupling, however, is not limited to only inventory buffers (and that is my little epiphany here), it may also act like a shock absorber.
The problem with an inventory buffer is that you can only use it if your past consumption is somewhat consistent, that part is not too expensive and the replenishment lead time is relatively short. Some of those thought schools might not agree but how do you calculate a reasonable buffer that doesn’t become real expensive when you don’t know anything about the future demand, one part costs $1,000 and it takes 3 months to replenish?
Don’t get me wrong… I love replenishment buffers to de-couple rigid supply chains but sometimes they just don’t work. I have used these buffers extensively in our optimizations but often the planner rightfully asks “what if I get unusual demand? Where is my signal? How do I make sure I don’t miss it?”. My belief is that you must ignore the little signals but still see and react to the big signals. And that can be achieved by way of a shock absorber.
So what is a shock absorber? It is NOT inventory! Let’s think about safety stock in a planning environment (static or dynamic. Counter to most beliefs it is not inventory as long as it is in the future plan and it is acting as a buffer (there is a minimum and a target level of your safety stock). If you have such a buffer, then a replenishment element is only generated when the buffer is exceeded with demand. Any demand changes that are within the buffer between a minimum and a target level are simply absorbed.
Let’s further explore how this can work when your planning operations run on SAP software. The absorber I am talking about may be set up with a Range of Coverage profile (dynamic safety stock). SAP‘s RoC has a minimum and a target range of coverage. If, let’s say, you have a minimum of 1 day and a target of 5 days and your average future daily requirement comes out to 10 pieces, then you absorb incoming variability of 40 pieces. Note that this is not actual inventory you hold in your warehouse. It is a quantity you are holding in a plan. Any changes (in forecast or customer orders) not exceeding 40 pieces are simply absorbed in the profile and do not cause noise. However, if there‘s a BIG change the signal transmits right through to the next level (use MRP type PD together with a RoC).
And this is the desired outcome for materials that can’t be replenished with a consumption based method.
Sounds too trivial and simple? Good! Because that’s what we need in this overly complicated supply chain world (sometimes it seems to me that it is made complicated on - some calculated - purpose).
In summary here is my suggestion:
1. visualize your supply chain dynamics (a value stream map)
2. run a segmentation (ABC, XYC, EFG, UVW)
3. find places where you can decouple with inventory buffers (MRP type VV or V2 with a coverage profile)
4. find places where you need to decouple with absorbers (MRP type PD with a coverage profile)
5. replenish (accordingly), rinse and repeat (periodically)
You will find yourself working „on“ the system now and the system starts working for you (instead of you working for the system).
In the end it does not take a new revolutionary approach, theory, culture or methodology. Common sense is good too. Use it.

Monday, June 19, 2017

Working ON the system instead of IN the system

As we're optimizing inventories, implement new production scheduling methods or improve our forecasting, we're working in or on a system... a system where individual parts make up a whole and feedback loops and certain dynamics take place. What defines a system? First, they have purpose. An automobile has the purpose to move people. However, its purpose is a property of the system as a whole and not just of a part. An automobile takes people from one place to another. That is its purpose as an automobile as a whole and not just of its wheels.

Also, all parts must be present for a system to carry out its purpose. If you can take pieces away from the system without affecting its functioning then you have a collection of parts, not a system. Take a wrench out of the toolbox (which is not a system but a collection) and you still have not changed the nature of what’s in the box. Likewise add something to a collection and its still a collection. But when you change a system you’ll see a difference (take off those wheels from the automobile and you will see). Thirdly, in a system the arrangement and order matter. The order in which the parts are arranged affects the performance of a system. As an example, in a traffic system there are clear rules defined and the way these rules are set greatly influences the way the system works. And finally, systems attempt to maintain stability through feedback. Through feedback a system can derive information about its position relative to a desired state. The most important feature of feedback is that provides information to the system relative to a desired state. Your body's desired temperature for instance, is regulated by the body's response (sweating, shivering) to a feedback of the actual temperature




When working on or in a system, there are different levels at which we can work on to optimize, improve, create, design or simply fix problems. Below is a list of these levels in order of leverage or effectiveness.

Events are the occurrences we face on a day to day basis. We catch a cold, a fire breaks out or we have a defective part on the assembly line… or there is a missing part that's needed for a production order

Patterns are accumulated memories of events. They can reveal recurring trends like: we’re catching a cold more often when we’re tired… fires break out more frequently in certain neighborhoods… and defects happen more often during shift changes… or missing parts are happening a lot when we use a deterministic replenishment policy without safety buffer

System Structures are the ways in which the parts in a system are organized. These structures actually generate patterns and events that we observe. In our example, fire houses, and therefore fire trucks, are located at points where they can deploy rapidly to specific areas of the city or... the way the shifts are scheduled might not allow an overlap between outgoing and incoming workers and therefore allow for a higher defect rate… or there is a value stream map that identifies de-coupling points, what buffers are located where and what the specific setups are for master records

Mental Models are the beliefs and assumptions we hold about how the world works. We can see these mental models as generators of systemic structures because they provide the blueprints for those structures. When you have defective parts, the shift crews might think they are only responsible for what happens on their shift – what they produce during their shift – not what happens after. This might have led the company to schedule shift changes without overlap. Or, similarly, a planner might think that a part's demand can not be covered with buffer stock but will have to be expedited when the demand occurs. In that case the planner will always use deterministic replenishment policies. It’s the stuff that we learned from the past (use PD - use static safety stock), accumulated experiences, that wants us to hold on to what we think we know about how the world works. Letting go of those beliefs is what makes change sustainable or even possible.

Vision is our picture of what we want from our future. It’s the guiding force that determines the mental models we hold as important as we pursue our goals. Maybe the people on the various shifts on the assembly line hold a vision of competition – of trying to produce better products than the other shift crews. This vision drives the mental model that says each shift is responsible for what they produce. Or the vision stems from a false (and dangerous) ‘lean’ philosophy of “zero inventory”. It would generate the mental model of avoiding buffer stock at all cost and favor deterministic replenishment policies (without considering delays).

It now should become clear that working on a deeper level of a system makes our work, and the associated outcome, far more valuable and effective. Instead of firefighting a stock-out every time it occurs, we may fix the pattern of how we plan that part (change the replenishment policy), go to the systemic structure of our system of materials planning and perform a segmentation so each part gets an appropriate policy (PFEP), or break down the mental model of our perception how the static safety stock works and implement replenishment buffers instead. we might even elevate the optimization efforts to our executives, convincing them that a vision of 'zero inventories' does not only harm the flow but eventually implements many barriers to success and results in total failure.

As you're moving your efforts down the iceberg, you will inadvertently work more on the system rather than in the system. This means that your impact gets bigger too. Who do you think has the most impact on safety and comfort on a flight from New York to Miami? ...the pilot? ...the flight attendant? ...or the engineer? The pilot and flight attendant work in the system and have a limited influence on what's happening. Most all they can do is react to events and fight fires. the engineer, however, works on the system and it is evident how that can make all the difference.

I truly believe that if you want to make sustainable change, you must work on the system. Remember that next time you want to lose weight... or when you want to reduce your inventory levels while at the same time avoiding stock-outs.

Thursday, May 25, 2017

Capacity Planning with SAP

Working for more than 20 years with companies from many different industries, I took a stab at writing down my thoughts on how SAP's functionality might help to make more sense out of production scheduling.

Capacity planning, sequencing, leveling and scheduling of orders is a topic that often is neglected and carried out in Excel spreadsheets and third party tools. With this writing I attempted to explain in simple terms some possibilities in the SAP-ERP offering and express my views on the subject and how it is often used (or not) in companies running on SAP.

The book is available on amazon or espressotutorials.com



Thursday, April 27, 2017

Why do you sacrifice yourself to save the safety stock?


Here is something I never understood: why do so many people plan without the safety stock? and why is the safety stock taken out of the planning situation (at least in the standard configuration in SAP-ERP) I know... everybody claims to use it when its needed but until then you have introduced a kazillion rescheduling messages, new order proposals and canceled purchase orders.

I know the above comic strip (if you can call it that - I apologize for the amateur-ish illustration) is not one hundred percent correct; it is meant to make a point, the point being that in planning we ignore that portion of the inventory that is safety stock - as if it weren't there. In actuality, the safety stock is used at the very time when you need it, but only exactly then. If an increase in demand comes in exactly at the same time you fulfill the demand, then you would use the safety stock and issue it. However, if an increase in demand comes in at any date before the date it is supposed to be fulfilled, one ignores that portion of the inventory that is safety stock and your MRP generates a new order proposal.

In my illustration above the consumption of the water should happen at the same time the demand stands and therefore Jenny would certainly take a sip, however, if Jenny would have applied the same planning principles as in the Acme company, and she would spend a certain amount of days in the Sahara Desert, she'd run into a few problems. Let's say she plans to be there for 5 days and calculates with a bottle per day. Using a reserve of 1 bottle she'd planned for 6 bottles for the trip. Also assume that she can order more bottles (minimum a six pack) from a kiosk in Aoulef, Algeria. But it would take three days until the water arrives.

Now, on the first day in the desert, the trip gets extended by one day because they missed a dune. Ignoring the safety stock, Jenny would place an order for six bottles and end up with 8 bottles on day 4 with 2 to go.

On the other hand, if the trip gets extended (again by one day) on day 4 (from 5 days to 6 days), she'd again place an order but this time the six pack would arrive too late and is not necessary either.

This illustrates the two problems of introducing unnecessary noise (the second situation) and surplus inventory (the first situation) that we will get when the safety stock does not act like a buffer. In fact, you'll end up with an unmanageable amount of exceptions and a lot of dead stock (unused, surplus inventory).

Monday, March 6, 2017

Deterministic planning and safety stock

Last week I visited three manufacturing companies. One from the medical device industry, the other one producing fresh and frozen foods and the third in the business of musical instruments and electronic components. they are of very different size, one being a huge, global manufacturer, present almost everywhere in the world, the other one still in the billion dollar revenue range. the third is a mid-size corporation that is privately owned.

Even though they seem so different, the one thing they all have in common is that they're planning deterministically. I am not sure, but I seriously doubt that they a) are fully aware that they plan the demand only and b) that they comprehend all the unintended consequences of their actions and behavior in supply and demand planning.



First, let's discuss what it means to plan deterministically. My definition is, that you plan for the demand that you know (this could be an actual demand or a forecast that you desperately try to get right) and react to every change that comes along until fulfillment of the actual customer order. That is a heavily noise-laden planning process, especially if you propagate the changes throughout the Bill of Material or to feeder plants and distribution centers in a manufacturing and distribution network. As we all know, the 'bullwhip effect' does its damage on top of it and increases not only variability but also noise throughout the supply chain.

I strongly advice against practices like this and almost always recommend to switch to buffering practices where the supply chain is de-coupled and through use of the three buffers inventory, capacity and time, the process absorbs variability and takes the noise out of the planning procedures. There is an entire methodology behind the design and implementation of a buffering planning process to replace the deterministic process, but any more detail would exhaust the purpose of this post. (I simply want to raise awareness about what's potentially happening in your environment too)

Now most planners would argue that they use safety stocks to buffer variability. But - at least in the case of the three customers I worked with last week - the safety stock that was used was static and did not help at all. If you are using SAP software to run your supply chain and you are using the field safety stock in the MRP2 screen you are doomed by the static behavior of such a static safety stock which does absolutely NOT behave like a buffer.

Assume, as an example, that you are holding a safety stock of 100 pieces and you have a demand of 200 pieces due in 2 months from now. The MRP run will generate a purchase requisition of 200 pieces to add to the 100 pieces in safety stock, so that just before the due date you have 300 pieces in inventory (after delivery of 200 you would still have the safety stock of 100). After you converted the requisition into a PO and sent it to your supplier, the customer increases the order from 200 to 250 pieces. As safety stock (at least in SAP) is taken out of the net requirements calculation, the MRP run will generate a new requisition for 50 additional pieces. This way you'll end up with an inventory of 350 pieces even though you need only 250. The safety stock would have covered the additional demand and that is what it is actually meant to do: to buffer variability... but it didn't and your safety stock ends up in unused dead stock. this situation gets only worse if you have minimu lot sizes that you need to order.

You might say: "there is the possibility to customized the safety stock so a portion of it is used as a buffer". Correct, I say, but who does that? the three companies from last week didn't... why? because they were not aware what actually is happening.

Take a look in your own organization. I can tell you it will be worth your while if you use a coverage profile with a dynamic safety stock instead (make sure the minimum safety target is always set to 1 day). This is what we call "picking up low hanging fruit"

Saturday, January 21, 2017

Systems Thinking for the supply chain

Thinking in Systems is a concept that has beenaround for many years. Names like Jay Forrester, Donella Meadows, John Sterman and Daniel H. Kim are coming to mind when you're thinking in systems.  If you want to know more about this very interesting approach to problem solving in your every day life or the supply chain in particular, google those names or read their books. You'll find a wealth of information and maybe a new obsession to effectively solve problems... not only in your supply chain.

In fact we are dealing with systems all the time, whether you're aware of it or not. Your family is a system, the toaster in your kitchen, a football team or ... Anything that has interaction going on and can be described by interrelated and interdependent components (which by itself might represent yet its own system) is a system. And a system differentiates itself from a collection by these relationships and interactions. A database of parts and product information is a collection but as soon as you start buying these parts to consume them or put them into inventory you are operating within a system.

If we are now starting to think in systems we look not only at the parts in a collection but at its 'whole' and its relationships and dynamics. Traditionally, most of us take an analytic, reductionist view on our problems. We take things apart to investigate sources and outcomes. In systems thinking you put things together, look at behavior over time and, maybe most importantly, consider delays and their effects (which we mostly disregard in the analytical view).


Delays is what confuses us when we try to do the best we can but don't understand what's going on or why it's going on. As perfectly described by the beer game (which teaches students what happens if you have demand variations in a supply chain), if you ignore delays you will end up with inexplicable outcomes that are counter to your intentions. The beer game's major insight is that when customers start purchasing a little more or a little less than before, the delay that occurs between ordering from the supplier until they deliver the goods will then causes wide swings in inventory holdings. You first end up with too much and then too little and then too much again. What is even worse is that if you have an interconnected system of 'consumer - retailer - distributor - manufacturer' over multiple levels, the demand swings are exponentially propagated throughout the chain and looks like a bullwhip as the swings get bigger and bigger towards the manufacturer who ends up with total chaos.

As you probably know this is the Forrester Effect, or otherwise known as the Bullwhip Effect.

An analytical, reductionist approach to solving this problem makes it very hard to see what went wrong. If you look separately at the retailer, distributor, manufacturer you won't see the dynamics between them. What ends up happening is the blame game when, in fact, it is no ones fault that the distributor sits on large inventories at one time and has back orders at other times. The problem lies in the dynamic of the system structure with its delay between orders and deliveries. But this cannot be understood if you look at just one part of the system and forget its interactions with other parts. In many cases one doesn't even look at the distributor as a whole but only at its parts (sales department, purchasing department, materials planning).

When you start thinking in systems you may use tools like causal loop diagrams, stocks and flows and value chain mapping to visualize structures, dynamics and eventually get to the core of the problem. Systems Thinking also provides you with archetypes - templates of repeating structures and behaviors - that you might use in supply chain management. 'Shifting The Burden" is one such archetype. In this type of a situation the problem symptom is not addressed by the long term solution but with a quick fix. The quick fix solves the problem for now but has negative consequences in the long run.

In our example we have part shortages in front of the assembly line. The problem is solved with 'heroic' expediting efforts described by balancing loop B1.

The shortage goes away - for now. In the long term though, the problem is not solved. A sustainable solution would be to improve the effectiveness of materials planning through the use of standard and proven replenishment policies after portfolio segmentation. Because the burden is shifted to expediting, there is an unintended side effect: our heroes feel good and get a pad on the shoulder every time they 'quick fix' the problem. This does not fix the problem at hand but increases the need to expediting further. Additionally, because delivery delays to the customers occur more frequently, the customers compete with each other to grab demanded product not sufficiently available and induce even more crisis on the production lines.

Thinking in systems allows you to see the dynamics resulting from quick fixes,  from not using the effective fix, delays and subconscious actions committed by players who aren't aware that they cause problems. There is a wide variety of archetypes which were developed over the years. If you're in the business of optimizing supply chain dynamics and producing better results it may make sense to dive a little deeper into the world of Systems Thinking.