ERP and Supply Chain: Metrics

What are your supply chain’s key performance measurements? Are they likely to change or be perceived differently as a result of an ERP implementation? One would think that a measurement is a measurement, and performance in one system would be the same as performance in another system. However, there can be odd math differences, and it is best to be out in front of any changes, especially if any compensation is tied to performance metrics. Things to examine thoroughly include:

1. Inventory turns or days of inventory – There are a couple of things to look for here that could alter the measurement without anything actually changing in the physical world. The first is if there has been any change in accounting methodology such that the nominal dollar value of the inventory has changed. The second is that – in general – there is a tendency to put more things into an ERP inventory that were expensed out in legacy – like samples or merchandising materials, perhaps. Both of these tend to be smallish effects, and over time, the cost of goods sold will change correspondingly.

2. On-time delivery, or fill rate – This metric can get confusing in that many legacy systems measured either (a) what was easy, or (2) what was considered important. ERP, at least at the start, can only handle the math of comparing a due date to an actual date, and from that comes a binary decision about on time or late. Typically, if numerical performance deteriorates significantly, it will generate a lot of non value-add discussions, as people explain that the customer didn’t really need the order, that sales over sold manufacturing capacity, and so on. Using fill rate can help avoid some of these arguments, but fill rate isn’t always applicable from a common sense basis. A tire manufacturer who delivers only three of four tires to an automobile maker may have a fill rate of 75%, but the auto maker is not 75% satisfied.

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3. Manufacturing lead times – Possibly no other supply chain conversation more closely resembles the biblical phenomena of talking in tongues as trying to have a group define what a manufacturing lead time is. This is true in both process manufacturing and discrete manufacturing. Manufacturing lead times can be a function of capacity, existing sales orders, the factory schedule, the labor complement, and numerous hedge factors, but rarely does it have any correlation to actual machine processing time. ERP contributes further complications by providing additional numeric fields (like lab testing time, or post production processing time) to calculate internal date logic. Coupled with the fact that manufacturing firmly believes that the way to improve on time delivery is to maximize lead times, this metric will take a while to sort out after ERP go-live.

The key to mastering these metrics is thinking. We do what is inspected, not what is expected, so the way we define our metrics will define the way we behave. Profitable definitions will drive profitable behavior.