Inventory… how much is too much?

Have you ever talked to a materials manager who was content with their inventory holdings? I didn’t think so. Have you ever met one who can tell you why they’re not content? They can probably tell you that they have too much inventory (and still the occasional stock-out) but when you ask them how much is too much, they’re sometimes getting a little fuzzy. 

In my personal opinion there are too many (confusing) inventory KPIs around. For years I’ve been searching for the one KPI which tells the whole story, but that is an ambitious effort which didn’t get me anywhere. After many frustrating attempts to make sense out of turn-overs, averages, days of supply, dead stock and many other measures, I decided to re-think my approach and challenged my mental model about inventory analysis.

Traditionally, inventory is measured by a set of KPIs, which do not all make sense by themselves. Take ‘dead stock’ for example. If you find out that your purchased parts have a dead stock value of US$ 300,000.- over the past 6 months, will you be happy? What if your inventory management system provides a report that says you have an average of 53 days of supply on the 567 finished products you hold in your warehouse? 75% of those are high runners which you should produce to a forecast and the rest is made to a customer order. So what of those 53 days of coverage is right and which part is not? Then you see that you held an average of US$ 1,350,000 on your raw materials. Was that enough to buffer variability? Did the stock-out occur on materials that had low inventory throughout, or did you experience bi-modal inventory swings and had materials that went from too little to too much and around again?

It’s very difficult to derive improvement actions from those KPIs. Some managers then develop strategies out of frustration. In one case, a planner decided that the only way to avoid stock-outs is with excess inventory at all times. What in the beginning was opposed with little skepticism, established itself in the long run. The whole company, including its executives, settled on the mantra that too much inventory is a good thing – it avoids stock-outs – and if anything goes wrong it’s the fault of the supplier. They went as far as – unconsciously – propping up inventory by using static safety stocks. You know, when you use a static safety stock, that quantity is taken out of the plan and becomes invisible. It raises the zero line to the level of the safety stock. It just worked for what their thinking was: more inventory is better.

So here you are,  ending up with inventory you don’t need and still experiencing stock-outs. And the inventory KPIs dead stock, average inventory, turns, days of supply etc. do nothing to help you to know what to do.

How about looking at some action KPIs? But before we do that, we’ll have to lay down some rules. In my mind, the biggest fallacy in planning, is that rules aren’t defined. I have been writing about chance-based and rule-based planning systems before. It still is a mystery to me why people accept that there are rules in traffic, in sports and in every aspect of social life, but when it comes to planning, we slack off and excel in rogue behavior being defined anew every time we have a suboptimal situation.

The rules I am talking about here must certainly not be the ones you are going by. But they are rules that work for me and I use them every time until I find a better way to achieve better results. But until then, those rules stand for me. Specifically, some of these are:

- Out of the sellable products portfolio, those products that exhibit regular sales pattern from period to period and are high movers are made to stock by a forecast and buffer variability to a certain extend with a dynamic safety stock

- Out of the sellable products portfolio, those products that exhibit irregular, unpredictable sales are only made when we have a customer order and we do not hold inventory of those.

- However, some of the ladder is worthwhile stocking a bit (especially when they have a long replenishment lead time), whilst others (expensive with short lead times) we don’t stock at all.

After these rules are defined, I can now measure whether I carry the right amount of inventory. I do so looking at the products from the first rule separately from the products adhering to the second rule. Measuring becomes relatively easy. For product that we make to order, we should not carry inventory. If there is, it’s either because I need to produce to a lot size and have a little left over, or that I falsely maintained a safety stock or have a consumption-based planning method on some products – in other words… I broke the rule and must fix it.

But according to rule three there are some parts that I do hold in stock because they are hard to replenish and are not very expensive. Those should be measured according to the Days of Supply. If I have adequate inventory to just not run out during the lead time, I’m good. I don’t need more than that, so use a matrix that shows which ones of those items have more or less days of supply than their specific replenishment lead time.

For the high movers I compare the total current or average inventory that I am holding to the total average, periodic (weekly or monthly) consumption (Sales). Is my inventory holding more than 3 times as high as its consumption, I know I have more inventory than I need and must fix the policy by which I replenish. To compare the actual inventory you are holding (of your high runners) to an average periodic consumption is a very precise indication of whether you carry too much or too little. Think about it… you don’t want to hold less than what you’re selling, but you also don’t need much more than what you’re selling. The excess over your actual sales is the buffer. So the buffer size is driven by the amount of variability you think you will encounter.

This type of measuring and monitoring makes you think about how you should plan for the future. Most planners are driven by forecast accuracy and therefore hellbent on bringing exactly in what they think how much they need (forecast) and exactly when they need it (forecast). I think that is a fruitless and frustrating behavior. If you measure the buffer you are holding you are driven to think how much buffer you need in the future to absorb variability. So how do you come up with the right buffer size? Instead of predicting the forecast to the tee, you anticipate variability and try to predict how much will come at you. Then you have an inventory target that might be a little high because you are careful not to miss any sales.

But a buffer that ends up being 15% higher than what you predicted as variable is a world better than ending up with 10 times as much inventory as you need. 

The point I’m trying to make here, is that before we can make an educated guess about the right amount of inventory that is held in the warehouse, we must lay down some rules. Simply running some inventory KPIs through your portfolios doesn’t do the trick. I am sure this isn’t a new revelation for most of you, but I do see a lot of inventory systems and I haven’t come across a fully rule-based system yet. Why is that? I believe that it has to do with long held beliefs, mental models, stubbornly holding on to what was always valid. And if the whole company beliefs that the only way to avoid stock-outs is to accumulate huge amounts of inventory, why would anybody dare to plan otherwise.

Time to change the way we think about inventory management.

Rule-based Planning for the Exception-minded Business

It's a new day... let's fix our inventory

How do you go about inventory optimization on a daily basis? I hope it's nothing like the following...

Unfortunately, for lack of a rule-based system, this kind of planning and behavior can be observed more often than not. Of course, it is not quite so bad as described in above flow chart, but there are many close variations to it, in many plants and DCs around the SAP (or other) ecosystem.

implementing rules to your inventory monitoring and optimization system is an essential part of effectively managing inventories and providing high fill rates, but even more important - at least I believe so - is that you manage by exception and not randomly. Managing randomly means that you pick your candidates every day and see what's up. Much like in the flow chart here. Managing by exception means that you let the system decide what you're looking at, according to the rule that you gave the system (e.g. alert me when a fast moving, consistently consuming part that is expensive and has a long replenishment lead time exceeds 20 days of supply).

in my workshops or blog posts, I often talk about working on the system instead of in the system. What happens in above flow chart, is that the planner works in the system - expediting and firefighting randomly and almost the entire work day. That planner works for his/her inventory management system. Alternatively (and much more effectively) one could work on the system - making sure that the basic data, or policy, can enable the system to work for you.


Maybe, you can think more along the lines of the following...(as you can see, I'm not taking away from you the ability to still surf the internet)

Rule-based Planning and why SAP often doesn't deliver the results we expect

Most organizations consider the planning of their sellable products and materials an important part of their business strategy, but the way it's being executed makes one feel that the outcome is rather coincidental or random.

If you, as a planner, have to resort to massive expediting, fire-fighting and constant responding to rush requests from sales and / or production, then chances are you're operating within such a chaotic, lawless, rogue system. Should you use SAP software to manage inventory and replenishment, you typically work with Excel spreadsheets, your most used transaction - by far - is MD04, almost all your finished products and raw materials are setup with MRP type PD and your entire day is filled with correcting orders, chasing POs and taking in angry emails from people who want stuff.
Most planners, buyers, MRP controllers I work with, believe that this is the way it has to be... one has accepted their fate and does their best to keep the situation at barely the minimum it needs to run, so as to not completely break down.

Oddly enough, management usually doesn't do much about it. This situation is considered normal and people think there's not much they can do. "We bought SAP to automate planning, IT implemented it, so what else can we do?" I hear a lot. Yes, SAP has been implemented. so much is true. But nothing else has happened. And by now, so many years into implementing SAP, we should know that implementing the software is only part of the endeavor. What's by far more important is that we're in this to improve processes and operations... better inventory levels, higher service or fill rates, more automation, less noise. However, and please tell me if I am wrong, those things are often forgotten and after the implementation we're operating the same way as before... only with SAP now.

So what can be done? Well, the best way to get out of a random system is to proactively laying down some rules which generate predictable outcomes. Like any administration is driven by policies and rules, your planning department should also be guided by principles, policies and rules. For example, a football coach publishes a playbook by which everybody knows what to do in a given situation so that the outcome is more predictable and less random. Much in the same way it should be clear that when a product has a long replenishment lead time, sells in high volumes and very predictably, one should hold some inventory so that the customer does not have to wait when they place an order.

Building this kind of rule based material and product planning into SAP can be done using the SAP Add-On Tool „MRP Monitor“. The tool is developed in the SAP namespace by SAP and supported by SAP. It’s an extension of ECC 6.0 and also runs in S/4 HANA. 

The MRP Monitor provides a number of functions: it can analyze and organize all of a plant‘s materials (I ran it for an excess of 100,000 materials at a time). While it does that, it can also perform a segmentation into up to 9 segments (ABC, XYZ, EFG, PQR etc.). The classes each material is assigned to, is then temporarily saved in a new material master screen that comes with the monitor. 

Then there is the rule (or policy) table (also included in the package). In it you save the rules, the master record setups to support the rule and the logic from the decision tree.

Now the system takes over. You’ve done the part the human must do (until AI comes around) defining the rules and publishing it to the system. From then on the system will keep the data par to the rules you defined. This happens automatically (or step by step if you feel like you have to watch it initially) and regularly. 

You see? All of a sudden your system transformed to become rule based. Green means go... red means stop. No questions asked. And everyone throughout the organization goes when the light is green and stops when the light is red. 

Gone are the days when every planner had to decide on their own how to set the basic data, how or if to accumulate inventory and when to order how much for the replenishment. 
No one knows what exactly will happen in the future, but organizing yourself into rule-based planning will give you a much better chance to predict and control desired outcomes. 

Why digitalization can't fix your supply chain problems

There's a pretty good chance that when you asked for a solution to your supply chain problems, someone brushed you off saying "don't worry, we're digitalizing soon". Just look at all the software vendor's marketing pitches, browse discussion groups and networks on the internet, listen to analysts and consultants... more often than not digitalization is perceived to be the holy grail. While writing this post I called up LinkedIn and the second post had the following text:

"Delighted to host the <name left out> workshop with more than 30 top customers in <location left out>. Focus on <software vendor left out> Digital Supply Chain Product Strategy and tangible business use-cases for Intelligent Technologies like IoT, Machine Learning and Blockchain. Thank you for your participation and insightful discussions. hashtag#digitalsupplychain "

The 3rd and 5th article were similar but I simply want to point out that the talk about digital supply chains is over proportional compared to the necessary talk about human factors influencing the outcome of planning. Undoubtedly, digitalization is coming and it certainly is necessary, however, my point here is that by simply digitalizing your supply chain or shop floor or company or whatever, you're not brushing away the problems inherent to supply chain dynamics.

In my opinion digitalization or, as it was previously called, software implementations will get you two primary benefits:
- process automation and standardization to free a planner's time away from doing busy work
- improved quality of information which allows the planner to make decisions that the machine (that digital thing) is not good at making

Now many of you will say "but the machine is now intelligent... " Really? Are we there yet? Then our manufacturing and distribution companies can be solely run by IT departments (they are already anyway) and we don't need planners anymore? The VUCA world (Variability, Uncertainty, Complexity, Ambiguity) is real and unfortunately (or thankfully) we're still dependent on the excellent functioning, very creative and immensely intelligent human brain. Humans are still making decisions and are still running the show. Machines are still stupendous data crunchers but they're very good at that.

Let's remain flat footed and not exaggerate what digitalization can do for us. Except, of course, if you're making a living selling digitalization. But for the rest of us... those that struggle to keep the right inventory at the right place in the right quantity at the right time, let's use the machines (and software and all things digitalized) for what the are good at...

- automating so we have more time to work and think analytically and make good decisions
- increase the quality of data we use to make decisions so that we make better decisions

...and further our knowledge and experience with the dynamics of a supply chain, so we can effectively use our brains to fight the challenges we're faced with by the VUCA world.

Intelligent, experienced and effective planners are still rocking the supply chain world! Let's work on raising good, effective human planners too... spend some of the digitalization budget on the human factor... it pays.

...and then I wonder why my plan doesn't work out!

Taking the noise out of the planning process improves delivery reliability and therefore fill rates to customers and production lines. I don't believe that many people would disagree with me on this. But why? Because when you send your suppliers (internal or external) an even demand, chances are that they deliver regularly and more reliably as well. Therefore, when we engage in a supply chain transformation, the first order of business is to stabilize and dampen inventory swings and generate leveled demand to the production lines and outside vendors. We do so using buffers and shock absorbers.

Now the big question is how and where to set the buffers and how big these ought to be. In my quest to optimize buffer levels I like to apply various mental models so I can analyze the problem from various viewpoints (if you follow discussions around the subject on the internet you will find out quickly that the topic is quite complex and supply chain dynamics are not necessarily easy to understand or intuitive). First of all I have come to the conclusion that chasing forecast accuracy is not very benefiting. Even If you’re lucky enough to work out the ideal plan (with very high forecast accuracy), what is it good for if your suppliers can’t deliver to it? It does seem nonsensical to shift priorities from trying to increase forecast accuracy to worrying about your suppliers, but don’t you think that when your supply comes in regular and reliable that you have a lot more control over your inventories and fill rates?

So if the intention is to level the demand to our production schedulers and/or outside suppliers then we must absorb as much noise as we can. Some suggest to de-couple parts from demand using buffers. That works in some cases but when you need visibility into future changes, this can fatally mess with your plan. I personally believe in absorbers, cushions, whatever you want to call them. In a cushion noise is absorbed to a degree and if there's a big change coming at you, you'll be notified by your planning alerts. Depending on the situation (high or slow mover, consistency in consumption, value of part etc.) you need to decide on the size of your absorber.

Other than most believe, absorbers can be implemented not only on the supply side but also on the demand side as the following graphic shows:

The absorber on the supply side is a dynamic safety stock that goes up and down with varying demand and has a minimum, a target and a maximum level. If the minimum is breached, noise transmits and alerts. The same happens if the maximum is exceeded. On the demand side we use the forecast as a buffer. To make it effective we increase the demand forecast and level it so it wraps around - and absorbs - actual demand. Once, through carefully defined consumption logic, the actual demand exceeds the forecast envelope, we use the supply absorber until the minimum is breached.

This all means that I am sending a very level demand to my suppliers and it stays that way with all the little changes until a big change alerts me to take action and expedite. My suppliers will thank me for that and after I get deliveries as expected and reliably, I really don't care that much anymore whether I had a forecast accuracy of 96 or 97 per cent.

People often wonder why their plan doesn't work out, but is it really so difficult to figure out that when you disable your suppliers from delivering on time, that it's impossible to fulfill a plan?

What's wrong with this picture?

Just this week I came back from an analysis on how a very large, global company is planning their replenishment of purchased raw materials and manufactured goods. We've looked into many functional areas and interviewed most of the users in that plant. Then there was one thing that really stuck out to me. You can see it in the following graphic:

The graphic shows one of their highest mover's consumption and receipts pattern as posted into SAP. when the red line goes up the receipts outweigh consumption and if the line goes down the opposite is true. The resulting level represents the inventory holding of that day. Whilst it is not difficult to discern that there is an upward trend of some sort going on over time, the real question is why does it consistently go up.
The easy answer is that there are simply more receipts than issues. Yes, but why do they keep on bringing more in than they consume? Wouldn't it be prudent to adjust the receipts to the issues so that the inventory level stays at the same low level as it was in June 2016 (which was plenty)?
To make my point of what's happening here, I also called up the Receipts/Issue diagram in SAP. It displays cumulative receipts and issues and if you take a close look you can see that the gap between those ever widens - which means receipts consistently outweigh issues or consumption.

Back to the question why and the 'not so easy' answer... if you look at the red line (inventory) you can see that consumption goes down very regularly (it's always the same angle). But receipts are pretty regular too. Only do they go up steeper than the issues, which go down flat. There are a number of dynamics going on here. For one this material is planned deterministic by placing replenishment orders with a long lead time to an anticipated demand. That demand is stubbornly overstated and there is no check in place when inventory keeps rising. Also, the planner is much more afraid of stock-outs than they are punished for holding too much inventory. Therefore, if one can't look at every part every day then keeping it coming is not a bad solution for them.
In my relentless efforts to try to convince organizations that placing buffers to absorb variability is better than to try to bring in... 'exactly what I need in exactly the quantity that I need it at the exact time that I need it', I often am faced with resistance to do so (calculating and placing buffers after analyzing historic consumption by the system) because planners do not want to hand over their calculations to SAP. They'd rather do it themselves to stay in control...

look again at above graphics! How did that work out for you?

Info Days - SAP, Alkyone and bigbyte in New Orleans

Join us in New Orleans to discuss Productivity, SAP Add-On Tools and the Theory of Constraints on SAP

The incredible Power of a Material Forecast

What is a material forecast? This is not to confuse with sales forecasting or a master plan where finished good's demands are forecasted through product groups. A material forecast relates to the anticipation of future consumption of purchased parts. In SAP ECC, for example, you can assign a material forecast as a policy. In that case you would use the MRP type VV together with a lot size procedure and a buffering strategy (I suggest a dynamic safety stock through a Range of Coverage profile).

This would result in a de-coupling of the part from any dependent requirements coming through the Bill of Material and the only demand that triggers replenishment, is the material forecast itself. Let me be a little more descriptive… When using such a policy you are - for planning purposes - ignoring any demand coming from a master plan and simply fill up stock at the beginning of each period… irrespective of what that a finish goods or production planner thinks you need to put up, based on what they think they will need.

To not have visibility into the future scares the living daylight out of most buyers and materials planners! This is so, because most people are told that they must bring in exactly what we need, exactly when we need it (who the heck came up with that mantra?). The problem with this kind of thinking is, that you will never exactly need what you think you need when exactly you think you need it. But because you act this way (and order this way) your supplier is chasing your lead… and that "lead" pulls in and pushes out and pulls in and pushes out and orders less and orders more and…

Because your supplier never knows what you want and when you want it, they get frustrated and won't make stuff to stock anymore. They say "if you want 25 pieces on November 20 then place an order and I start the process the first week of July. You can then have it delivered on 11/20 because it takes me 3 months to get my raw materials, 2 months to manufacture the parts and 3 weeks for transportation to your facility." So you place the Purchase Order and after 2 weeks the master plan has changed and you need 22 --> order an additional 2! One week after that it turns out that we need the parts only in December ---> exception: push out the order. Then a rush order for the finished product comes in and we need some of these parts in September ---> exception: pull in.

Now, this game can be repeated (and will happen) over and over and over and you end up in exception message galore… and you'll experience a constant back and forth between stock-outs and excess inventory… and the supplier goes crazy!

Here is an idea! Ignore all this stuff because it is not going to happen anyway, and - if you have some sort of a consistent consumption pattern - just fill up your inventory at the beginning of the period, so that you can consume what you need without running out and with no excess stock. How do you do that? You forecast an approximate future consumption (which is easy if you have somewhat consistent consumption) and put an additional buffer on top (but it must be a buffer, not a static safety stock) and tell your supplier to deliver the same quantity at the beginning of every period (so you end up ordering the same quantity regularly). Provide the supplier with that forecast and give them a guarantee that you'll pick up that quantity at that time for at least the next [fill in blank here] months. You will be surprised how the supplier all of the sudden makes the parts to stock before you ask for them, how the lead time shrinks to the transportation time only and how you get your stuff on time and in full like clockwork…

I know, I know what you say… "I can't do this. What if I have an unusual demand? What if I don't have any demand anymore? What if Florida freezes over?" Let's compare what you do today and what a material forecast does.

1. Today your suppliers experience an incredible amount of noise in your ordering. They insist to start the process ONLY when they know what you order. Tomorrow they would experience a leveled demand from you and make this stuff to stock and deliver regularly to fill your inventory at the beginning of every period.
2. Today you receive your parts after a long lead time and sometimes you'll get what you ordered. The problem is that what you ordered a long time ago is not what you need anymore. Tomorrow you just consume what you have in stock and the supplier fills it back up. Should you need more than what you forecasted, you'll run out… BUT!... The next receipt from the supplier is near. (You will not run out at the beginning of the period and if you run out at the end your next, scheduled receipt is close)
3. Today you are fire-fighting the hell out of your ordering process (exception messages are plentiful)… AND… nobody is able to help you. The suppliers can't keep up with your ordering patterns and will give up on you. Tomorrow, the supplier receives a leveled and consistent stream of orders which they are able to plan for on their side. Once the relationship has improved, engage with the supplier to have him take on part of the safety buffer your maintaining ion your side

The graphic shows the effects when you switch from a deterministic replenishment policy to a material forecast (we call the policy "Dynamic Buffer"). In this example the average inventory holding drops from 200 parts to 40 parts. The supplier is given a forecast to deliver 62 parts at the end of every months. This will ensure that there are 62 pieces plus 8 pieces buffer (5 days in the Range of Coverage profile) in inventory at the beginning of every month. With an average daily consumption in the past of 3 pieces per day, a stock-out - if it ever happens - can only occur towards the very end of the months and therefore, the worst that could happen is that a production order would have to wait for a few days until the next receipt comes in.

I strongly suggest that you explain this new situation to the supplier and give him a guarantee that you will pick up these exact quantities at exactly that time for at least the next 3 months. This should motivate them to make the parts into their own stock ahead of time so that they only need to pick the parts from their inventory and ship it on the 28th of every months. Can you see how now the lead time (Planned Delivery Time in MRP2) drops dramatically? In the above example the lead time was cut from a whopping 212 days down to 2 days transportation.

Let me be clear, this is not for every part… it has to have some sort of consistent consumption pattern and there must be some movement. But I am sure there are plenty of parts in your business that match that description… so why not improving your life as a planner at least to some extend?

Per my experience it is very difficult to get planners to not only dare to move to a "dynamic buffer" policy but to also leave it there. They feel an incredible amount of pressure coming at them when their managers, partners or colleagues do not agree with what they see now in MD04. The key to getting the change done is to communicate properly with all parties involved. You'll have to explain your intent and show the benefits this will bring along.

The switch is very hard to get done - not because it's not working - but it's hard to imagine that all of a sudden the system works for you, instead of you working for the system.

What's the Difference between a Buffer and a Shock Absorber?

Lately, in industry publications and social networks, you can read a lot about shock absorbers and how to apply them in supply chain planning to reduce variability or absorb it. Apparently, many thought leaders have been replacing and complementing buffers with these shock absorbers… at least in theory. Not wanting to get into anybody’s conversations but I do have my own view on the topic. In my opinion a buffer and a shock absorber are not the same thing and therefore I do not use them interchangeably.

Let me explain my thinking. A buffer is a medium (inventory, capacity, time) that blocks and swallows up a signal... like a firewall prevents heat getting through to the other side. A shock absorber takes the signal in and absorbs it to a certain degree. When the signal is big enough and the absorber‘s buffer is exhausted, there is no holding back anymore.

To use an analogy, think of  driving your car into a pool of mud at 50 miles an hour and you know how a buffer acts. Drive that same car through a pothole 10 inches deep and you get an idea what shock absorbers do… they let you feel what a big change in variability there may be, while a buffer simply stops you right in your tracks.

The problem with buffers is that a part equipped with a buffer doesn’t ‘see’ when a big change in demand is on the horizon. The buffer simply blocks all that’s coming at it. The shock absorber, however, swallows up the little changes but carries through the big ones. That can be very helpful in some situations but annoying and inefficient in others. This is why both buffers and shock absorbers are awesome tools to take the noise out of your supply chain. You just have to use them in the right situation and not mix them up because that can lead to chaos and bad planning.

In the same way one certainly doesn't want to drive a brand new BMW into the mud to slow down when there are a few bumps in the road. But coming down from a mountain pass in a 14 wheeler with failing brakes, you’d be happy if there’s a buffer coming up absorbing all that energy.