Managing Measurement – Just a Numbers Game?

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You’ve heard people tell you this before – you may have even told yourself this before: you can’t manage what you don’t measure.

So what’s so different about this mantra today over any other day?

Nick Ganju, that’s what’s different.

Over the past few months I’ve developed a taste for the podcast world. And while I still need to write about the podcast that has made me into a semi-rabid fan of the medium (thank you Alex Blumberg, Startup Podcast, Matt Lieber, and Gimlet Media!), I have my buddy Hsu to thank for introducing me to Tim Ferriss‘s experimental podcast, The Tim Ferriss Show, at a time where there were a few episodes out there with things that I needed to hear.

This morning I listened to two excellent inbetweenisodes and then happened upon the Nick Ganju conversation.

I’ve been intimidated by math, numbers, stats, etc. for as long as I can remember. Unlike Tim, while I had some a great teacher in 10th grade (and beyond), I just always had a tough time getting my head around that stuff. And I completely gave it up when I got to college.

These days, even though I’ve come to be a believer in data-driven approaches to decision-making, that doesn’t mean I’ve always been equipped to determine what should be measured on the way to reaching goals and supporting dreams to come true.

Because if there’s one thing that should accompany the mantra, “You can’t manage what you don’t measure”, its that, “Not all data is created equal.”

These are the kind of things I appreciate talking through with others. It’s not only for the purpose of bouncing ideas and getting to a better place as a team, but also to move beyond my own numerical insecurities. Sometimes we all just need a little hand-holding.

Although there are many great things within this conversation including a note on the probability of one sharing a birthday with another (if interested in this, see below), it was two lines that encouraged me to immediately write this reflection.

“The big secret of mathematicians is that everyone started from 1 + 1 = 2 and built their way up. Each step is not a big step once you understand the previous step.”

How often do we make things much more complicated than they need to be?

How often do we take steps without truly understanding the previous step?

And how often do we measure things that actually don’t matter in the context of what we’re looking or aiming for?

Let’s go a bit further on this.

You’ve heard of SMART goals, yes? Specific, Measurable, Attainable, Realistic, Timely goals.

But do we take the time to make projected assumptions based on specific, measurable, attainable, realistic, timely criteria? (Or should I have asked if we make any type of project assumption?)

Do we follow-up to compare assumptions with the actual results? When and if we do, do we explore how they compare and seek to understand why we’ve arrived at the results we have today?

For all the time we put into the things we believe matter, why do so many of us not put in the due diligence and/or the right structure for a more appropriate framework by which we can judge whether we succeeded or not?

“Lose weight” vs. “Lose 10 pounds in 100 days” is a very simple version of this. We have these “goals” without anything to hold us accountable – be it to ourselves or others.

But generally speaking, in business and in life, many of us just decide on “goals” (myself included). We haven’t done the underlying math. Or really enough structured thinking about it.

It’s great to have goal, but then you need a plan to execute. And the follow-up, the accountability piece, might be just as important than the original goal.

Besides, how do we know if we get there / don’t get there? How do we choose if it’s a good idea to keep going or stop?

So I’m a perfect example of someone who has fallen into this lack of specificity and due diligence in setting goals.

Actually, it’s only been recently that I’ve finally felt the confidence to even set and articulate these goals to myself.

It got me to thinking, how can we articulate out-loud and to others if we can’t even tell ourselves?

Even more dangerous, what happens when what we tell ourselves is not honest?

Though this is tricky.

Because even when we think we’re being honest with ourselves, sometimes, we’ve elected to not do the due diligence in thinking about what really matters.

Do we know what motivates us to do what we do, on the road to going where we want to be?

One last quote from Nick, “The mark of intelligence is to learn from your mistakes and change your attitude about things.”

I thought I was quite good at this before. But maybe that was my problem.

At my most unsuccessful, it was usually because I knew the problem and solution rather than seeing myself as part of the problem and the solution.

I recognized a need for a change in my attitude on certain things. This has taken space. This has taken time set aside for active thought and reflection.

Only by taking a step or two (or three or more) back have I been able to move forward with a renewed sense of confidence.

You know what it was, I was afraid of “the wrong answer” before. Of “making a mistake.” While this wasn’t with everything, it was with the biggest most important things in my life.

Intelligence for me started to become less about knowing the answer and more about finding the answer with the people interested in the same or similar questions.

Besides, if I believed there was only one answer or way of doing things, then I’d just be deceiving myself.

How about you, what mistakes have you learned from lately?

And beyond just knowing these mistakes, did you give yourself the space to reflect and allow for your attitude to change?

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Hear more from Nick and Tim’s conversation here.

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Happy-Birthday

Interested in the birthday vignette mentioned above? You came to the right place.

At around 21:00 minutes Tim brings up the birthday problem / paradox as a part of their discussion of probability.

When there are 367 people in a group there is 100% probability that 2 people will have the same birthday. Easy, right?

More surprising, though, might be that in a group of  23 people there is actually a 50% probability.

Nick pointed out that it’s not that one of those 23 people could walk around and ask the other 22 if they have the same birthday and likely find a match, it’s that any two of those 23 people could have the same birthday.

What happens when data is presented a bit differently? And how do we start to see the world, the issues around us, and ourselves differently?

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Today’s images –

Numbers – from designer and animator giada_ghw, which I found on the Continuous Business Planning site. giada_ghw has some other fun cartoons on there, as well.

Happy Birthday – from the Soylet blog of all places. Posted by user gambit.

Google image searches sometimes take me to the most unexpected places.

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