What do the results of companies depend on? Results depend on decisions: macro decisions set a north, micro decisions are the execution.
If you work in a company that manufactures or markets something, I am sure you agree with me on a macro decision: maintaining a high level of customer service is the highest priority.
That's a high-level, macro decision. An alternative would be: "Our company's highest priority is to reduce costs, even if it means serving some customers poorly." I assume that you already have enough experience to know that this decision has higher costs in the medium and long term, so I will stay with the first macro decision: fulfilling the promise to customers is the first priority.
Now let's look at the potential promises that a large proportion of companies make. They are basically two possible promises:
- They promise immediate delivery.
- They promise a delivery time.
Promise 1 is made by companies that produce standardized products, where customers have no tolerance to wait for the delivery time (production and / or transport) because there are other suppliers that have immediate delivery. And to fulfill that promise of immediate delivery, you need to maintain inventory.
Anytime a customer places an order and you have no inventory, this is a lost sale. We call that stock out or inventory shortage or missing. Suppose you maintain a portfolio of 150 items, and 35 of them are out of stock. That gives 23% of stock outs. How many lost sales are you going to have because of this? To answer that question, which is the relevant one, we must understand that not all items are sold in the same volume. Pareto described this phenomenon as an 80/20 asymmetry; 80% of sales are made with 20% of the items. We know that 80/20 is just an indication of skewness. Sometimes it is 70/30 and other times it is 90/10.
The important thing is that if within our 23% there are several high-turnover items, the lost sales are more than 23%, sometimes much more. I knew a case years ago, where a company with about 250 SKUs (items) had a 5% of stock outs. Each week they were different items, but the missing items remained at 5%. They decided something really daring: they decided to eliminate the stock outs by having excess inventory. And they succeeded. After eight months of holding that stock, sales increased 40%. This is an experiment that I do not recommend, but it does demonstrate what I am saying. Usually the mistake was to underestimate the sale of items that are out of stock, so their turnover is higher than originally estimated.
The story of that company does not end well. The first year they increased sales by 40%, but the excess inventory caused problems from the second year:
- It ran out of storage space and it became very expensive to keep growing inventory, especially if you need to pay for additional space. Note that the problem is that the items that were produced and not sold, accumulate. And you keep producing faster than you take up space.
- The money to keep growing in inventory is also limited, and afterwards they could not keep the stock outs at zero either.
- Many of the excess products were perishable and suffered a large loss from waste.
In this case we see that the macro decision is the same that I would have made: top priority to fulfill the promise of immediate delivery.
And each day, what micro decisions did that company make to align with the macro decision? In this case it was manufacturing in excess, what matters is not losing sales. It is with this decision that I do not agree.
The results observed in stock outs and inventory are the product of micro decisions, of those decisions every day. Specifically, for each item it is necessary to decide each day whether or not it is produced, and in what quantity. The same applies to deciding whether to dispatch to other nodes in the supply chain.
It is commonplace to say that it doesn't matter how good a strategy is if it fails to execute. That is, macro decisions are usually very good. It is the micro decisions that lead to a different result than expected. Many people think that it is not possible to achieve a fill rate of more than 94% permanently, because the cost makes it unfeasible, and they settle for an "acceptable" level of stock outs.
I learned directly from Dr. Goldratt not to settle for a compromise result. And in this matter, the Theory of Constraints solution has managed to reduce inventories and costs while availability approaches 100% in thousands of companies, of all sizes and from the most diverse industries, throughout decades.
Why do the micro decisions of most companies produce such suboptimal results? It is because they are based on wrong assumptions. It all comes from the fact that the time between replenishments (production orders, purchase orders, or dispatch orders) is variable and is longer than necessary. That time is the main factor in the amount of inventory required to have availability, resulting in a larger quantity than companies can afford, due to their space and / or capital limitations.
Why is the time between replenishments long and variable? Because it results from calculating EOQ (economic order quantity) and using MIN / MAX techniques or reorder point. Both concepts considered the basis of optimal inventory management. And they are based on the wrong assumption that operating costs are absorbed uniformly by each unit of product when it is produced, purchased, or shipped.
If one sets a fixed frequency and makes that time makes shorter, the amount of inventory to guarantee availability is less, to the extent that neither space nor capital are active constraints, therefore the double objective of reducing inventory and raising fill rate up to close to 100% is achieved.
The next time you are told that it is impossible to achieve a fill rate of more than 94-96%, think again and more deeply about the causal relationships in your system.
Promise 2 will be examined in the following article.