If You Can’t Measure an Outcome, Your Initiatives Won’t Impact that Outcome

July 3, 2018 by Stacey Barr

Without evidence of an outcome, how can we know the outcome matters? And how can we know if a change initiative to impact that outcome is worth doing?

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Lynette M, a Measure Up reader, sent me an old Gary McKenzie article about a famous Peter Drucker quote:

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

In his article, Gary mentions how people reject measurement because of misinterpreting Peter Drucker’s meaning as ‘what can’t be measured need not be managed’.

Drucker didn’t mean that.

He meant that you can’t know whether or not you impacted an outcome unless that outcome is defined and evidenced in some way. If you have no evidence (quantitative or qualitative) of an outcome, you have no experience of that outcome. If you have no experience of something, how can you knowingly change it?

For example, would you keep pouring your savings into an investment scheme for which you had no evidence of its current balance? And no idea about whether the investment scheme was increasing or decreasing that balance? Of course not. So why would our investment in any change initiative be different?

We need to be bold to measure an outcome that matters.

Gary McKenzie’s company is GuavaBox, an inbound marketing service. They live Drucker’s principle of not being able to manage what can’t be measured:

“By clearly defining what results constitute a win, we are able to make objective, data-driven decisions both internally and for our clients. We don’t set standardized processes because we have a hunch they might work, because we heard a neat idea on the radio, or because it’s the way everybody does it. We define success, try a process, and make adjustments based on the facts.”

And GuavaBox’s transparency about performance with their clients is bolder than many companies would dare:

“Our review meetings with clients look like this: ‘You invested X, and that produced XYZ. Did we achieve our specific goals?’ If the answer is yes, we expect our clients to be eager to continue working together… If we didn’t achieve our specific goals, we don’t smooth it over and try to convince a client to keep working together.”

It’s easier to measure an outcome when you stop following conventional wisdom.

To measure an outcome that’s hard to measure, you have to do what works. And stop doing what doesn’t work (like brainstorming).

If you’re going to implement any worthwhile change initiative, there are a few logical steps to take to make sure that it will be worth implementing. In other words, to make sure that you can know whether or not it impacted an outcome that matters. The steps are:

  1. Make sure you articulate its intended impact in clear and measurable language. This impact is what you want to manage the initiative to achieve.
  2. Then, think about the sensory evidence that will convince you and the stakeholders that matter whether or not, or to what degree or in what amount, the impact is achieved.
  3. Finally, how might you gather and collate that evidence? How might you summarise and quantify in what amount the impact is achieved?

If you cannot rely on any evidence of the amount to which the impact is achieved, why bother investing time and money into the change initiative? You’d only bother if just doing stuff was all that mattered. In many people’s minds, that’s indulgent waste the world cannot afford.

If you can’t or won’t measure an outcome, then you’re not ready to try and impact that outcome.

The bottom line is that we need to think very deliberately about whether it’s worth doing any change initiative at all, if we can have no objective evidence of whether it makes any kind of difference that matters.

No change initiative is worth doing if we can have no evidence of whether it makes any kind of difference that matters.
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DISCUSSION:

Are your KPIs evidence of the implementation of your change initiatives, or evidence of their impact on an outcome that matters?

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  1. Basically, we seek knowledge of causes and effects that underly outcomes. From there, we can work out solutions by repeatedly asking why, answering with evidence and actions due. This soon leads to a network of well defined solutions to choose from in any given situation. Once well defined, we can monitor and evaluate. Designing and using measurement relies on knowing closely what we’re measuring and why.
    Best regards to all, and thanks, Stacey!

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