The End (of Analysis) Is the Beginning Is the End

Been back in the woodshed for a bit.  I just completed my latest post for AITS.org, which should be published sometime in mid-July.  In the meantime, I’ve been looking at issues of data visualization, process improvement, and performance management–and their interdependencies.  The APQC blog has some interesting things to say about project management challenges which, to be quite honest, sound a lot like “mom, apple pie, and Chevrolet.”

But there are nuggets of gold in there which I will save for another post, while focusing on another article by Holly Lyke-Ho-Gland on the top challenges in organizational performance management.  There are essentially three challenges.  The first is “establishing a performance culture.”  Given that APQC’s mission is broader than what I would view as traditional complex project management, this first statement is more than gratuitous.  The second is “identifying the right benchmarks and their source.”  At first blush this gets a big “duh”, but in every profession and discipline this is an area with a pretty consistent failing, especially on the back end of that statement.  For example, if one transitions from processed, human-readable reporting to just accessing the source data should not the results be the same?  I have been told otherwise in both meetings and during private conversations at project management conferences, which should be a counterfactual and raise some eyebrows.  The third and last is “defining and using process measures (leading, in-process, and lagging) in the business.”

While somewhat conceptual and non-specific, I would view all three of these challenges as elements necessary to an successful performance management system.  Furthermore, what is interesting here is that Ms. Lyke-Ho-Gland illustrates the connection between process and performance management.  The source of the data–and its credibility–is as important as collecting data.  Furthermore, I would posit that the job doesn’t stop at finding anomalies in the data or variances in performance.  This is just the beginning of the process in determining root causes of the issues and appropriate corrective action.  Thus, information analysis isn’t the end of the process, but the beginning of the process that will lead us to the ends.

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