Operation Improvement Inc.

At the start of a new operations process development or improvement effort, I typically want to see two things firsthand.

It is important to have a personal view of the work presently being done, as well as the methods and the tools or resources available at the place of effort. It is also vital to get an early look at the process metrics and performance outcome data that the workers and their management think is actionable. These first steps allow us to start with a clearer picture of the objective (the deliverable) and begin to develop a vision and implementation plan for a better way.

What I frequently get in response to my requests is one or more reports instead of data. Where once there might have been actual data, its source and method of capture is undefined and cannot be audited. What began as  observations systematically compared to a standard has been digested into predetermined narratives with implicit and often wrong conclusions.

Data means measurements, with the method of measurement totally transparent and always open to constructive critique, caveat and refinement.

As an example, telephony systems have not always left audit trials for call center operations.(And many today do not meet the standard of measurement above.) In the systems that do have call detail databases, much time and effort is spent trying and failing to reconstruct the “state of the business” at some past date and time.

I approached this problem on an older system by taking and saving periodic real time snapshots of the PBX system state. (Calls in queues,  current wait times, etc.) These frequent “state of the business” measurements gave us actionable data and  helped us to monitor performance as we made changes and introduced new methods and tools to call center agents.

The entire chain of logic (observation, data grouping, statistical summation) and graphical reporting was presented in a form that not only provided actionable information, but also communicated the answer to this most important question, “How Do We Know?”

Of course, measurement in the service sector has the same issues of measurement variability as precision measurement in manufacturing. The solutions to this challenge are similar, but that is another topic.