Granularity of measurement is directly proportional to fear of failure !

Its December , and its that time of the year when I am torn between planning for next year and closing out the current year on a strong note. As I sat down with a bunch of paper drawing up crazy ideas of what we will do next year, I realized I am falling prey to my biggest strength and weakness – the desire to measure everything at the most granular level.

I grew up in BI where if you had granular data, you can generate very sophisticated insights. And I have spent countless hours modeling such data, and writing ETL scripts to get that data in a shape I like. Over time, this has become second nature to me even though I don’t get to do the fun stuff with data any more. Most of my decisions are made on aggregate data today, and the only time I need granularity is when things go wrong and I have to “debug” to find out what the heck happened.

Granular data comes at a high operational overhead – in terms of management itself, and a lot of data wrangling. You need codes to tag every bit of data – and I am not kidding when I say that some times I come across more attributes about the data, and the number of data records itself 🙂

So as I sat here staring at the stack of paper on my desk and the array of spreadsheets on my macbook, I came to the sad realization that my penchant for granularity is simply a representation of my fear of failure. Over time, I have taken over more and more responsibility at work – and the measurements have also become more and more complex and time consuming. This is true for pretty much every employer I have worked for and every client for whom I have designed solutions.

Which brings me to the “scale of failure” issue. As your responsibilities increase, the number of ways in which you think you can fail also increase. And to compensate, we try to measure across multiple dimensions, and matrix the organization some more. At some point, you will absolutely realize that operational over head is not worth the trouble (do you need more checkers and double checkers than people in the field?) but by then you are also a creature of habit that cannot get away from this mess you created for yourself. And finally you also make everyone else in your team miserable – because you force them to tag more and more attributes and unlike you, they might not even know why they are tagging it. I am not kidding – there are many things I was told to do 10 years ago that I had no clue why I had to do. It would have lessened my grief significantly if my bosses at least explained why they made me do it then 🙂

Tagging data and multi dimensional operational reports have another consequence that was perhaps never intentionally designed – the sinister idea of taking credit for someone else’s work . At some scale of business – especially in sales type work – it is hard to pinpoint what all led to a given sale. You will have a direct sales team, and assorted over lay teams that all think they were the ones who drove the business. So they will enthusiastically start tagging more attributes to show their value add and we end up with “everyone is a winner” type scenarios. Even then we won’t typically stop this madness.

So my current plan is – I am going to sacrifice some granularity of measurement in our measurements. I want me and my team to design our work around the idea that we are aiming for success instead of lack of any kind of failure. I would rather fail responsibly quickly and stop doing things that don’t pan out, rather than worry about it every step of the way for all activities for ever. Lets see how that goes 🙂




Published by Vijay Vijayasankar

Son/Husband/Dad/Dog Lover/Engineer. Follow me on twitter @vijayasankarv. These blogs are all my personal views - and not in way related to my employer or past employers

One thought on “Granularity of measurement is directly proportional to fear of failure !

  1. I love the points VJ! The “agile” leader who is focused on success, but willing to take a quick failure to learn…also looks like you are looking for opportunities to do a ” single, one pass thru” data analysis ( I.e. handle it once ) versus multiple checking…


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