Modeling mastery performance and systematically deriving the enablers generates data in Analysis efforts – for use in downstream improvement efforts, including additional analyses and design/development efforts. It fits within a Big Picture of Enterprise Performance…
INTRODUCTION TO THE KEY DATA-SETS
The two key data-sets are Performance Models and Enabler Matrices. They respectively capture the model of mastery performance, and the enablers of that mastery.
The Performance Model and the Enabler Matrices are two, linked set of data that are produced for the current state view by current Master Performers, who have proven that high performance levels are attainable. The Performance Model and the Enabler Matrices can also be produced for a future state view.
The Performance Modeling effort documents the requirements of the performers within the scope of the intended project and creates Performance Models. The Performance Model is the device used to capture ideal performance requirements; and it documents identified gaps from that ideal performance and their probable causes.
The Performance Model has two components: 1- AoPs (Areas of Performance) which are the “segments” of overall performance; and 2 – Performance Model Charts capture the data details for each AoP segment. Performance Models may be developed for an organization, a function, a job, a task, or a process.
An example of the AoPs for a Convenience Store Manager’s job follows.
The information in a Performance Model includes a segmentation of overall performance into “Areas of Performance/AoP” segments, plus AoP details regarding the expectations for outputs and their measures and standards, the tasks per output, and the roles and responsibilities per task, for all of the performers involved. That ideal, mastery performance is documented on the left side of the Performance Model chart. It is then used to facilitate a structured and systematic gap analysis on the right side.
The entire Performance Model data-set, with the ideal and gap analysis data, is then used in the specification and analysis of both the human enablers, and the environmental enablers that are required to enable mastery performance.
The Enabler Matrices document the human and environmental asset enablers required for mastery performance.
Human Asset Requirements Enabler Analysis is where the requirements for the human assets are determined via a systematic review of the documented mastery performance outputs and tasks. Human assets categories are:
- Awareness, Knowledge, Skill
- Physical attributes
- Intellectual attributes
- Psychological attributes
- Personal Values
Environmental Asset Requirements Enabler Analysis is where the requirements for all non-human assets are determined, again, via a systematic review of the documented mastery performance. Environmental assets categories are:
The systematic review of the Performance Model charts’ data facilitates the systematic generation of the various enablers, by the enabler categories above and their sub-categories. For example, I use 17 sub-categories for the analysis of the “Awareness, Knowledge, Skill” category.
This captured data later facilitates additional analyses such as validation of any complex interpersonal behaviors, root-cause problem solving, or further assessment of the adequacy of various enterprise entities in the enterprise value chains that are in place to ensure that the right human and environmental asset systems are in place, at the right process place, at the right times necessary to achieve and sustain peak performance.
When you are done you might have 10-20 flip chart pages worth of Performance Model data – and another 10-20 pages of Knowledge/Skill items. Then you can assess your existing content to see: where you have what you need, what may need to be modified, and what is a total gap for potential resourcing.
Not every K/S gap is worthy of addressing formally however. Only the ROI for each and every gap – incrementally and systemically – can help determine what to do after the analysis.
And just because content is modularized for one set of reasons doesn’t mean that chains of those modules aren’t critically important to deploy/make available as a set.
Other Potential Analyses Required
While it is my claim that the two sets of data in the Performance Models and Enabler Matrices are at the heart of analysis for any improvement effort, there are other analyses, such as financial, competitive, marketplace, Strengths-Weaknesses-Opportunities-Threats, legal, ethical, benchmarking, process mapping, activity based costing, and so on that may also be necessary at times. At other times, they may not be necessary at all.
Stay away from analysis paralysis!
All of this is covered in numerous writings/ postings and in my book: lean-ISD – available as a free 410-page PDF – along with several of my other books – here.
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