“You can’t manage what you can’t measure”.

That’s a maxim we all know and, to a large extent, live by. It is often attributed to Peter Drucker.

But is it true?

Tom Goodwin made some thought-provoking assertions in a recent post.

He argues we are obsessed with what we can measure.

• In the pursuit of “data driven” decisions, there is a tendency to measure anything, everything, precisely, and in real time, and then participate in “near endless meetings about things which actually have zero meaning…….. and because people can spend 4 hours discussing any TLA (three letter acronym) that measures any number divided by another, which people REALLY love, because they are often not round numbers, so it feels sciency……”

He also makes the case, which definitely resonated with me, that we are losing interest in anything we can’t measure, regardless of how vital it could be.

• We care less and less about things that happen offline, in the “human space”, things that are subjective, or that happen a long time after a “digital event” or transaction . . . .

I am very conscious of the fact that WHAT we choose to measure, and HOW we choose to measure it, has a massive impact on how we interpret the results and (hopefully) take action. For instance, a focus on a 97% success/achievement in a task may provide a sugar rush of satisfaction (or the opposite, if 7%). However, these measures usually do little to light the way to performance improvement.  That requires us to look at the 3% of failures/defects and what went wrong, and what can be improved. We refer to this as “Defectivity“, a focus that has it’s roots in the Lean Six Sigma movement. 

Now, I am a signed up “data driven decision making” person, but it is important to look through both ends of the telescope.

Tom argues that the closer we get to data, the further away we get from common sense. The more we obsess over data, the less we understand people. The more that we look at what we know, the more we refuse to look for what we don’t.

I asked ChatGPT to arbitrate. Other LLMs are available 😉

Evidence to support the argument that “You can’t manage what you can’t measure”;

1. Performance Improvement:
   • Quantifiable Goals: Measuring performance allows managers to set clear, quantifiable goals and track progress over time, which can lead to continuous improvement.
   • Data-Driven Decisions: Measurement provides data that can inform decisions, helping managers to identify areas for improvement and allocate resources more effectively.
2. Accountability and Transparency:
   • Clear Benchmarks: When performance is measured, it creates benchmarks that can hold individuals and teams accountable for their contributions.
   • Motivation: Knowing that performance is being measured can motivate employees to maintain or improve their work standards.
3. Resource Allocation:
   • Efficiency: Measurement helps in understanding how resources are being used, allowing for more efficient allocation and reducing waste.
4. Problem Identification:
   • Early Detection: Regular measurement can help in early detection of problems, enabling timely interventions before issues become significant.

Evidence against the argument that “You can’t manage what you can’t measure”;

1. Intangibles and Qualitative Aspects:
   • Qualitative Factors: Not all important aspects of performance can be easily measured. Qualitative factors like employee morale, creativity, and customer satisfaction can be challenging to quantify.
   • Overemphasis on Metrics: Focusing too much on measurable metrics can lead to neglect of important qualitative aspects of performance.
2. Misleading Metrics:
   • Inappropriate Metrics: Poorly chosen metrics can provide misleading information, leading to wrong decisions. Not everything that can be measured is important, and not everything that is important can be measured.
   • Short-Term Focus: An overemphasis on measurable short-term goals can undermine long-term strategic objectives and innovation.
3. Human Behavior and Manipulation:
   • Gaming the System: When people know they are being measured, they might manipulate their behavior to meet targets in ways that are not beneficial to the organization. This can lead to unethical behavior or cutting corners.
   • Stress and Pressure: Constant measurement can create stress and pressure among employees, which may reduce job satisfaction and increase turnover.
4. Complex Systems:
   • Complex Interactions: In complex systems, simple measurements may not capture the intricate interactions and dependencies, leading to oversimplified conclusions.

I also got a couple of references to “purple cauliflowers” and “labrador puppies” but that’s hallucinations for you. We are all GenAI old hands and used to this now 😉

Whilst “You can’t manage what you can’t measure” underscores the importance of measurement in management, it’s crucial to recognize the limitations and potential pitfalls.

Effective process management requires a balanced approach that includes both quantitative and qualitative assessments, as well as an understanding of the broader context and human factors involved.

I couldn’t have said it better myself!

You can read Tom Goodwin’s post here . . .

Thanks for reading . . . .