Your Performance Improvement Methods- Models- Data- Must Scale

They Really Should 

Both Up and Down.

But also Sideways and Diagonally.

Performance is complex.

It exists within a larger system and is itself composed of many sub-systems. And many levels.

  • World – Social Responsibility/Mega … and the Resources Required
  • Workplace – Enterprise – Organization … and the Resources Required
  • Work – Process – Processes – Sub-Systems – System … and the Resources Required
  • Worker – Individual – Learner/Performer … and the Resources Required

And there are the human dimension requirements, to performance, but it/they is/are not alone.

There are also many non-human dimensions, the environmental resources, that are required and that need to be in sync.

Many of us who often focus on individual performance, know to also look beyond that targeted individual performance.

We know we also need to understand, and establish broader understanding, of both the current state the targeted state. And to do that requires looking up and down and sideways at the industry, at the marketplaces, at the economies, and then at the organization charts/the process maps, and at the performance metrics from across the many or few targeted jobs within those processes.

To see both the Big Picture and the Small Picture.

The models that you and I use, need to scale.

And scale to something meaningful. Something measurable.

If your models and methods and data-sets don’t scale to an Enterprise level from the individual levels, don’t contribute to roll-ups, or to diagnosis processes for missed targets, then you can probably put them away.

The More You Know

You and others need to be able to see current variation.

As the starting point. The Baseline.

And you and others may need to be able to derive – and see – the appropriate measures on the micro performance requirements – within defined (or not) processes – after first establishing the macro processes requirements.

So that they are in harmony and not in discord.

And then you can all be assured that they link directly – or indirectly – to the core value streams’ requirements, and are also enabled appropriately by the support streams, etc., etc.

Each component of the Performance Web providing their own sets of requirements and/or constraints to the Performance picture.

Your models, and methods, and data may scale, even if they currently are not being scaled.

But. Just because you can doesn’t mean you should.

Should they scale? Why or Why Not?

And if not – are they really providing so much value at the level they are being used – that they should continue – despite not being able to show a scalable positive contribution to the higher level goals?

As Dale Brethower, PhD has been quoted:

“If you are not adding value, you are subtracting value.”

Put that measure to the test at all of the levels in your equivalent model of Performance, or Quality, or Learning.

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