How do supply chains fail even when they appear to succeed?
Dan Gilmore, editor-in-chief of Supply Chain Digest, has an interesting take on this question. In an article entitled ‘Metric Strategies and Supply Chain Performance’ Gilmore suggests that many companies have KPI targets that are too low. They set targets they know they can achieve, hit them, and then conclude that their supply chain must be performing well. Even when it isn’t.
Which brings us to another question. Assuming that all the right supply chain KPIs are in place, what kind of result should you be aiming for?
In the case of a KPI like delivery performance, there’s an obvious theoretical best: 100%. If you’re hitting 90%, it’s clear that you’re 10% below what you could be achieving – at least theoretically.
Costs are a different story. For example, how can anyone be sure that a certain figure represents the lowest possible cost? Perhaps costs could go even lower. Perhaps even much lower.
While hard numbers are difficult to come by, it is possible to develop a sense of what’s possible. Take, for example, a field service company. The planning constraint with the biggest impact on costs is probably the time windows within which customers must be served. To get a feel for how much better the company could be performing, we can remove that constraint and optimize plans based on the assumption that customers don’t mind when they’re served. Of course this is a ridiculous assumption, but it does provide a starting point. If the cost turns out to be 40 million dollars, it would be unrealistic to aim for anything lower.
Next, we re-introduce constraints. For example, we might assume that the time windows are 24 hours instead of the usual one hour. What are the costs now?
The point of this exercise is to arrive at a range of what’s possible. If your current costs are 53 million dollars and the constraint-free minimum turns out to be 51 million, well then you know that your potential for improvement is rather limited. On the other hand, if you’re hitting 53 million when the constraint-free minimum is 40 million, there could be considerable room for improvement.
This raises another difficulty. It’s one thing to say that the present KPI targets are too low. It’s quite another to be able to create supply chain plans that optimize KPIs and enable significant improvements.
Telling planners which supply chain KPIs they should aim to improve is good, but isn’t enough. What’s needed is supply chain planning that’s actually driven by the relevant KPIs.
Given the complexity of their supply chain planning puzzles, planners need help. Specifically, they need to be able to see the effect their plans have on KPIs – even before making a decision. This kind of KPI-driven planning goes beyond monitoring supply chain performance. It’s about being able to generate plans that optimize supply chain KPIs and minimize violations of constraints. It’s about the ability to actively steer your organization towards your business goals.
For example, if delivery performance is a key competitive advantage, you might choose to give greater weight to that KPI. Plans could then be generated to move your company in that direction.
Or perhaps it’s important to reduce your company’s impact on the environment. If the cleaning liquids being used in your processes are damaging the environment, you could increase the cost of those liquids in your planning system. An intelligent planning system would then automatically minimize the amount of cleaning required, for example by creating longer batches or changing the sequence of orders on machines.
Putting the right supply chain KPIs in place and monitoring how well the supply chain is performing isn’t enough. To succeed, companies need the complete business control that comes with intelligent planning and optimization.
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