Do We Define Productivity Correctly? - DBR 036

An episode of the Do Busy Right - The Task and Attention Management Podcast podcast, hosted by Larry Tribble, Ph.D., titled "Do We Define Productivity Correctly? - DBR 036" was published on June 28, 2024 and runs 53 minutes.

June 28, 2024 ·53m · Do Busy Right - The Task and Attention Management Podcast

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Episode Description

In this episode, I'm going to refine our definition of productivity in knowledge work. If you think you know the definition, there's a good chance you'll be surprised.

I have my customers tell me their definition of productivity; I believe that the typical definition is broken. I've seen it lead people to over-think, hesitate, or even procrastinate on tasks. If you want to think clearly about being productive in your work, I've got some ideas for you.

Here's the problem…

Before you can make a process efficient, you've got to understand the process very well. Efficiency is a specific definition, and you get there experimentally and incrementally. It's very difficult (risky?) to get there in the in the top-down sense, from planning and estimating. We'll talk about what that is and what you need to do about it here. When we think about productivity at some level, productivity always boils down to outputs divided by inputs. This covers the whole notion of factory efficiency and productivity, labor productivity, capital productivity.

If you put X in, then you get Y out, sometimes. If so, then efficiency is maximize the amount of yYthat you get per unit X, and so that's fine, But, that's in a system. In a mechanical kind of world, in a physical kind of world we've learned a lot about how to measure this. But don't misunderstand; even there our measurements are imprecise because we know that there are inputs that we can't effectively measure. The simple view, if I may, the naive view is: it's raw materials, and then it's the value of output. That's certainly a huge component, and a fairly clear and precise component, but there are always things that go into a process that are difficult to measure. The point is that the notion of productivity is not clear – we move it to knowledge work from physical work and even in physical work, it's not perfectly defined.

Chris Craft's model of our knowledge and thinking:

'education, experience, etc.'
produces mindset
produces options for action
produces results

Chris will be the guest on my podcast Episode 38, 7/12/2024

Is the factory definition of productivity a good one?

The factory has a huge advantage on us – process and repetition allow experiments
A factory has a design – a hypothesis - and it's embodied in the physical world
So it's a 'fixed' process, repeatable, stable
In physical, we've usually got repeatability
Process is in place, so we can study the parts we don't understand
And, usually, we've got a large number of attempts
Things that are hard to measure in a factory - depreciation
Other factory things are also hard to measure
And factory Input measurement is still developing
As we try to adapt this model to knowledge work productivity, we have to account for these things and these assumptions.

Knowledge work productivity

We move this concept to knowledge work – does it fit?
Repeatability is an input to experimentation
Knowledge work and repeatable process
Knowledge inputs are hard to measure
What about outputs – knowledge output vs. product output

Two views of productivity – the spectrum

Two general ideas of productivity – quality and planning/efficiency – 'artists' and 'engineers'
Michelangelo's notion of the quality end of the spectrum
The other end of the spectrum
Aside on calendar time and PMI
Planning and estimation – we're not good at them
Can I plan my way into productivity?

Toward Knowledge Work productivity measures

Knowledge Worker - "I don't want to have a process; that interferes with my creativity."
The things we need to create in knowledge work to study productivity
What about repeatability
Programmers and their estimating process
In order to refine, you have to have a process
Process for knowledge work – when you do something, store it (like a programmer)
Knowledge worker – have a process that you can study and experiment with

Takeaway 1 – don't expect what's unreasonable –don't just assume that you have a factory setting and can use factory measures. You probably don't and probably can't.

Takeaway 2 - Develop a process – without one, there is no way to measure productivity, much less define it

Attention Compass

Attention Compass is intended to be the beginnings of your knowledge work process
It also deals with task switching - a major source of waste
And helps us avoid the problem of searching for inputs – we said 'reuse', but you can't reuse if you can't re-find