Podcast Episode Details

Do We Define Productivity Correctly? - DBR 036

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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 a

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  Published on 1 year, 2 months ago