I talked in an earlier post about the need to collect supply chain metrics and record your activities on a very detailed level. Reason being that you will need it in order to support you in turning performance indication into preventive actions. Now to part two and the importance of measuring what doesn’t happen!

We certainly need to capture reasons for exceptions – it can be error codes for when we get apples instead of pears from a vendor, when we have a shortage in picking, or when the delivery is rejected by a customer due to damages. All of these are tangible and identifiable events that can and should be measured. They will also trigger actions.

The next level is to detect, alert and log the things that did not occur. NOW WHAT? How do we record an activity that never started? Well the point is that events that are expected to take place but fails to do so are really good indicators that something is not running as it should. We talk about things that cause a lot of extra work and confusion as well as the chained effects that cost both performance and money. You might recognize things like:

• An ASN that is not transmitted or received in time – so the receiving floor gets congested while the staff chase for information.
• An inbound shipment that is late without notification – so cross-docking gets messed up, orders are picked incomplete, and customer service KPIs drop.

A major stumbling block here is that you will usually not know until it is too late. So when designing your decision support system it is a good exercise to think more in terms of “What will the impact be if this runs late?”  Properly designed applications can deal with some of this, but when we need to look across different applications and processes we need more flexibility to configure our operational decision support. An event management solution can help you define critical events and detect situations also where time passes the expected deadline. You can implement a mechanism where you:

• Escalate the awareness and take preventive action quickly
• Automatically log when things run late so you can measure also things that did not occur
• Systematically work with eliminating similar situations in the future

This can effectively close the loop in the traditional business intelligence approach of measure-analyze-correct. So get your toolset and go ahead to turn indication into action – in this case before it happens!

Agree or disagree? What challenges do you see in identifying and measuring ‘non-events’?
Post your comments and I will explore further in a coming blog post (look for Part Two).

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