Make-to-Order vs Make-to-Stock: Additional Decision Factors

For all your products, you have to decide between make-to-order and make-to-stock. A similar decision is needed for components or raw materials that you produce or purchase. As described in my precious posts, the key criteria is the quantity and the fluctuation. In this last post in this small series I will look at where to make the cut, and what other factory play a secondary role for your production system.

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Make-to-Order vs Make-to-Stock: The ABC XYZ Analysis

In my last post I started to look at when to produce make-to-stock and when to produce make-to-order. There are quite a few factors that influence this decision (more on this in my next post), but the most important ones are the total sales or production volume as well as the fluctuations thereof. To understand these, you could use a Pareto analysis, an ABC analysis, or an ABC-XYZ analysis. I do like to include not only quantity but also fluctuations, but usually I need to divide this into only two groups, and the three groups of ABC or nine groups of ABC-XYZ is, in my view, a bit of an overkill. Anyway, let’s have a look:

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When to Produce Make-to-Order, When Make-to-Stock?

One of the questions for any production system is if the product is produced on stock before the customer order (make-to-stock, MTS), or only on demand after the customer order (make-to-order, MTO). In many cases this is an easy decision. Custom-made items are always make-to-order, since you cannot start before you know what the product will be. Everything else does have exceptions. Let me dig deeper into the decision tree on deciding which items to produce on order, and which ones for stock. This is a short series of blog posts, and the first one looks at the key aspect (but not the only one) in deciding between make-to-order and make-to-stock.

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Can You Plan Around Your Fluctuations?

Abstract Wave MoleculeBalancing the need of high material availability with low inventory is tricky. Pull systems are a very good way to achieve this. But sometimes people argue with me that planning can be better if you use all the available information to create a production plan which then outperforms a pull system. In theory, this could work, but in practice it rarely does. After all, that is what conventional push systems are trying to achieve, usually with mediocre results. Let’s have a look.

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About Just in Time and Fluctuations (Like… a Pandemic…)

Global logistics networkJust in Time (JIT) is a powerful tool in lean. However, it is not an easy tool. Using it without understanding the requirements can quickly make things worse. I have written about related topics before, but during the COVID-19 pandemic, Just in Time was often blamed for a lack of material, usually by people who do not understand how just in time works.

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Reducing Fluctuations Downstream

This last post of my series looks at fluctuations that originate downstream from your location. In other words, how to reduce fluctuations originating from your customer. Granted, this often is the most difficult one, as you usually have not so much influence over your customers (unless you have a monopoly). Let’s have a look.

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Reducing Fluctuations Upstream

This post will list a number of tools that can help to reduce fluctuations. They can reduce fluctuations in the material flow, including its inventories and the durations and lead times. Since reducing fluctuations (mura) is an underlying important idea throughout lean manufacturing, a lot of tools can help. And, depending on how you interpret tools, this list is not even complete.

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