Challenge

What happens in your organization when something goes wrong? 

Typically, fingers are pointed, conclusions are jumped to, and symptoms are treated, right?

My next question is how are projects selected in your company?

My experience has been that there is a huge bias towards the “sexy” initiatives.
Are you constantly hearing about overhyped tools, such as AI, control towers, multi-echelon inventory optimization etc.? Have you been involved in developing a business case to show the tremendous ROI for a given tool? This approach makes sense, right? Sorry!

You can have the sexiest software in the world, but if there is no process to support it, then your project is doomed. Even if the process is in place, how do you know that project will have an impact on your ACTUAL problems?

A business case tends to start with the solution and explains why its ROI makes it worthwhile. But that doesn’t mean it is the project that will have the biggest bang for your buck. Throughout my career, I have learned that the projects which will most impact your bottom-line are unlikely to be technology projects, at least at earlier levels of maturity.

Solution

Root Cause Analysis In summary, we react badly when things go wrong, and our project efforts are not focused on actual problems. There must be a better way, and there absolutely is! We call it root cause analysis, but in supply chain we only need to use a small subset from the vast array of root cause analysis.

The overall philosophy is completely contradictory to standard approaches to management. Under this approach “every defect is a treasure”, and we only make improvements when specific data supports the initiative. One reason that this approach is so much more effective, is that if you take the time to look at the data, you’ll often find that what you THOUGHT was causing the problem, was NOT the cause at all.

Very often there are one or two gaps in the process, which are causing most of the issues. How do you find these gaps? It’s straightforward really! First gather “defect data”, just like you would if you were analyzing the quality errors in a manufacturing process. In this case though, the defects are being created by the broken supply chain business process.

For example, if your strategic objective was to improve customer service by better on- time delivery, what “defect data” would you analyze? Correct, you should look at your late shipments over a period and ask the team to discuss and determine what caused each delay. You only need to do this for about 30 late shipments, and patterns will emerge, and you will soon be on your way to understanding your chronic issues. Then, and only then should you select and prioritize projects.

As you can see from the table below, the beauty of this approach is that it can be applied to almost any supply chain issue. 

Results

Improved on-time delivery from below 80% to 95% in less than 4 months. We have achieved great results using this approach for most of these objectives. For example, for the customer service objective, we improved on-time delivery from below 80% to 95% in less than 4 months, just by monitoring late orders for a few weeks on a daily basis in a cross-functional team. It is amazing how much alignment is possible in this environment, as opposed to each department pointing the finger at each other, when shipments are late.

I have also used it for improving inventory turns. In this case, “defect data” would be any item with excess inventory. In one case, we were quickly able to identify that the key reason for excess inventory was speculative forecasts for custom orders, that never actually happened, causing customized products to sit in the warehouse gathering dust. We quickly implemented a more rigorous approval process to reduce future excess inventory by 80%.

If you wish to learn more about this approach, contact me for an assessment session.

I’d love to help solve your life science supply chain issues.