There are many forms and approaches to Performance Modeling that I have come across in the 30+ years I have been doing this. This is a version that evolved from a derivative of a derivative of a Rummler approach – as I used to tell the late Geary Rummler – that I first learned at Wickes Lumber in the fall of 1979. There I worked alongside Geary brother-in-law and two colleagues who had come to Wickes from Blue Cross Blue Shield of Detroit where they had both worked alongside Geary’s brother.
Modeling Performance – Part 1
The first part is to “chunk out” the Areas of Performance – also known as: Major Duties, Key Results Areas, and by many other names.
Gilbert called his chunks Accomplishments, but as that often (to the true believers) meant having to word them a specific way, I don’t use that term – although I like it. I’ve written about that before – here.
Areas of Performance – AoPs Examples 1
Preview: Modeling Performance – Part 2
This involves getting the details for those chunks of Performance – in terms of both “ideal performance” of the Master Performs – and “the gaps” of the less-than-Master-Performers.
More on this will be covered in a follow on Post – on Performance Modeling Step 4.
Deriving the Enablers of That Performance
Depending on your intent “downstream: there are various enablers – other Assets that then enable that ideal Performance – that you might be needing to capture for your project efforts, including:
- Human Assets: awareness, knowledge, skills
- Human Assets: physical attributes
- Human Assets: intellectual attributes
- HumanAssets: pschological attributes
- Human Assets: personal values
- Environmental Assets: data/information
- Environmental Assets: materials/supplies
- Environmental Assets:tools/equipment
- Environmental Assets: facilities/grounds
- Environmental Assets: budget/headcount
- Environmental Assets:culture consequences
More on all of this will be covered in a follow on Post – on Performance Modeling Step 4.
Step 3 – Performance Modeling
This is sometimes called by me as something other than Performance Modeling – a separate step – Deriving the Enablers.
Although it cannot be done with any quality assurance if not an activity that flows from Performance Modeling Part 1 and 2.
So forgive me if this confuses you temporarily.
Knowing what to look for and knowing what people have to do – performance-wise – is one thing. It’s another to know what they gotta know in order to do what they gotta do – on the job.
But it’s more than Knowledge – that enables Performance.
If I know what to do and YOU GIVE ME BAD DATA – well then – that leads to poor performance.
So it’s here – as well as in earlier in our gap analysis that we doing Instructional Analysis – need to really pay attention.
‘Cause “it” – poor performance – might have nothing to do with the Performer and their knowledge and skills. Nothing honey – as the cereal commercial suggests.
So we gather the enablers. As appropriate to our downstream needs – and nothing more – as that smacks of analysis paralysis – and that’s not good.
But jumping into deriving the enabling Knowledge Skills (K/Ss) is fraught with peril – to be dramatic. You need categories to guide you so that you don’t end up with an unmanageable mess. Especially if you are using a team of Master Performers who might rightly conclude that you have just wasted their time. A bunch of their time. Yikes!
An Enabler Chart – for Knowledge/ Skills
Blank Chart for Your 1st Paycheck Job Exercise
Where did you end up in your “first paycheck job” – please finish that little practice drill now.
You’ll need it for the next few posts.
Performance Modeling is Covered in These Two Books
This award winning book is available as both a free 410 page PDF – and as a $40 paperback.
This book is available as both a $15 Kindle and a $20 paperback.
I also offer formal workshops and informal coaching sessions on this Performance – for Instructional Analysts and Performance Improvement Analysts – and have been doing so for my F500 clients since 1983.
See the Services Tab for more info on that and them.
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