One of my co-workers and I got into a discussion this week about something called the Theory of Constraints Replenishment Model. Actually one of the questions I get asked a lot is how to avoid stock-outs of parts. Not just high-end, expensive parts, but simple, inexpensive things like bench stock. Bench stock includes simple things like washers, o-rings, screws, etc. And although these parts don’t cost very much, relatively speaking, if they’re not available when needed, they can be just as damaging as a high dollar part not available when needed. Today’s blog is all about parts replenishment. By the way, you will see a distinct change in font size and I've tried everything I know to make it constant, without success. You'll also see a part late in the posting where the writing suddenly went bold. Again, I have tried without success to correct this as well.
Many companies still use a supply chain/inventory system referred as the Minimum/Maximum system. In fact, the entire Department of Defense use this type of system and every place I have consulted at have had the same shortcomings and symptoms which are high inventory value with stock-outs occurring frequently. You have to wonder why anyone would continue using a system that constantly displays the same shortcomings?
In a min-max system, part’s needs are evaluated based usage and some type of maximum and minimum quantities are established for each part. The min-max operating rules are usually quite simple:
· Rule 1 – Determine the maximum and minimum stock levels for each individual part.
· Rule 2 – When you re-order, never go above the maximum level.
· Rule 3 – Don’t re-order until you reach or go below the minimum level.
The supposition behind these rules are Cost Accounting (CA) based, which I’ve written about many times in this blog, and are based upon the premise that in order to save money, you must reduce the amount of money you spend for these items. That is, if you want to save money, you can never buy more than the maximum stock level and you can’t spend money until you absolutely must (i.e. reach or go below the min level).
Although these assumptions might seem legitimate, they do not in most cases provide adequate protection from stock-outs. In fact, there always seems to be an excess of some parts and stock-outs for others. It’s funny because when the min-max system was devised so many years ago, it was supposed to prevent these kinds of occurrences from happening. So if the min-max system isn’t producing the kind of results we want, then how can we fix it? Could it be that the rules of the min-max system are wrong?
As I said before, the min-max system was created years ago and the theory behind this system was that parts should be stored and distributed at the lowest possible level of the user chain. It was in essence a push system that simply orders, receives and pushes parts through the system down to the lowest possible level. When you think about it, it kind of makes sense since parts must be available at the point-of-use. In the min-max system, the parts are used until the minimum level is met or exceeded and then an order is placed for more parts from the point-of-use. The parts order must then go back up the supply chain from the point-of-use to some kind of central order location. Sometimes the orders are placed directly from the point-of-use directly to the vendor. And when the orders are received, usually in a central supply location, the entire order is pushed back down the chain to the point-of-use where they are stored. Sounds simple enough doesn’t it? If it’s so simple, then why do we have such a problem with stock-outs?
In the min-max system we see that one problem is the reactive nature of this system, rather than being proactive. That is, when minimum stock levels are used to trigger the re-order of parts there is a high probability that stock-outs will occur. Stock-outs occur because the lead-time to replenish the part exceeds the minimum available stock remaining in the storage bin. Figure 1 below is a graphical depiction of why stock-outs occur. The curved line demonstrates the parts usage as a function of time until the inevitable stock-out occurs. And if you add in variability in the usage rate of the part, the length of time the stock-out remains could be a long time.
When the part is re-ordered, the re-order amount is the maximum level and the problem disappears until it repeats itself. You might think that you could solve this problem by simply raising the minimum level and it could provide some short term relief, but at the end of the day your inventory level would be much higher than it needs to be. The fact is this cycle of stock-outs repeats itself over and over. Figure 2 below visually depicts this cycle.
So if the min-max system isn’t the best way, then what is the solution? What if there was a system that could virtually guarantee no stock-outs with much less inventory being held? The Theory of Constraints offers such a solution referred to as the TOC Distribution and Replenishment Model. Let’s take a look at it using a very simple and commonplace example.
The simplest way to explain the TOC Distribution and Replenishment Model is by looking at what happens every day with a soda vending machine. When the soda vendor opens the door on a vending machine it is very easy to see exactly what has been purchased since his last delivery. Let’s say the people using the vending machine consumed 20 cans of coke, 8 cans of Dr. Pepper, 4 cans of Mountain Dew and 10 bottles of water. The vendor knows just by looking inside the machine which inventory has to be replaced and how much of each has to be replaced. The vendor is holding his inventory at the next highest level……the soda truck, which makes it easy to distribute his product to the point-of-use (POU). The vendor could have just left cases of soda at the POU even though only 42 containers have been consumed, but he didn’t. He didn’t do that because if he had, when he gets to the next vending machine he might find that he’s out of what’s needed because he made distribution too early at the last stop.
So after completing his rounds for the day at each vending machine, the truck driver returns to the warehouse and replenishes his soda truck for the next day. And when the warehouse people supply the overall inventory is held to the minimum value, thus tying up much less cash. In fact, it has been my experience that as much as 40-50% less inventory is required to assure no stock-outs. There are primarily two simple rules for this system:
1. Don’t hold all of your inventory at the point-of-use.
2. On a frequent basis, replenish what’s been used.
By comparison, Figure 3 is a visual depiction of whet the TOC Distribution and Replenishment Model looks like as a function of time. Compare this to Figure 2 and I think you’ll agree that this replenishment model is far superior to the min-max system. So if you work in the DoD, think of the potential money you’re tying up in inventory. And just exactly how much is that stock-out costing you in missed delivery dates? I’ll bet it’s more than you think it is.