Analytics, we are repeatedly told, will enable us to have these wonderful insights that will change our business and transform society, probably abolish world hunger at the same time. And the only reason they're not doing so is because we have not been able to implement it well.
All true, but to my mind a bit of bollocks. Its a bit like Nike advertising the same shoe that Michael Jordan has, and the only reason we're not in the NBA Basketball Hall of Fame yet is that we just haven't put in the hours of practice required.
Here's the problem with insight in analytics. One, insightful analytics is very very hard. It requires a lot of investment; to go back to the Jordan analogy it takes thousands of hours of practice to get anywhere near the NBA. One basically sacrifices everything else in life - something the average person is just not going to be able to do. A company whose job is analytics will put in the investment (an investment research firm, for instance) but a business that is busy doing some other core activity (as most companies are) is unlikely to.
Second, it takes more than investment and effort. 10,000 hours of effort will produce a very good basketballer, but it cannot guarantee a Jordan. Insights are rare, and in addition to investment and effort takes talented analysts and luck. Yes, luck - something that product companies don't like telling you because it isn't on the pricelist. Newton's brain wasn't enough - he also had to be under the apple tree at the right time. This puts a bit of a dent in that ROI thing, and probably explains why the extensive investments in analytics dont really lead to daily game-changing insights.
So am I advocating tossing out the analytics baby and getting on with other things? Not at all. I'm just advocating getting out of the insight steamboat, where the promise is of untold riches if only one buys a ticket to the magic kingdom. Forget using analytics for insight, but don't by any stretch forget analytics, because...
Analytics are about hindsight.
The real value of analytics to a company is the ability to see what has gone before, and learn from that; not to change the game but play the same game better. Hindsight is not 20-20 unless you study it (which is why history is so often repeated). If one has to learn the lessons of history, one needs data and analysis that describes well what exactly was happening - and what is likely to indicate its recurrence. Why my sales fell last quarter is a question of insight - but where they fell, by how much they fell, what else was happening the day they fell - these are all questions of hindsight. And these questions are much easier to answer predictably and reliably than the why.
Once you look at analytics through the hindsight goggles a lot more starts to make sense. Gathering more data points gives you better detail on what happened. Gathering more sources gives you breath of visibility on all the different things that may have happened. Correlation helps you identify what happened before, after or along with what other things. And every time you have a theory on something, analytics tells you (often quite accurately) if the data so far supports your theory or not.
This is quite analogous to the scientific process. One does not carry out experiments hoping to stumble on an insight; instead one tries to analyse experimental data to see if a potential insight is indeed backed by fact or merely a misguided fancy. Computers are not well suited to mull out insights from half-formed ideas - that is the domain of human brains. Computer software, on the other hand, is supremely good at crunching data to validate or junk an intuition.
Humans have since ancient times hoped for a way to reveal what is going to happen, and have repeatedly come away disappointed. Figuring out what has happened, and repeating the successes while side-stepping the failures may be more pedestrian but it is ultimately more rewarding. And that's not an insight; after years of looking for patters in the sand that's hindsight.
All true, but to my mind a bit of bollocks. Its a bit like Nike advertising the same shoe that Michael Jordan has, and the only reason we're not in the NBA Basketball Hall of Fame yet is that we just haven't put in the hours of practice required.
Here's the problem with insight in analytics. One, insightful analytics is very very hard. It requires a lot of investment; to go back to the Jordan analogy it takes thousands of hours of practice to get anywhere near the NBA. One basically sacrifices everything else in life - something the average person is just not going to be able to do. A company whose job is analytics will put in the investment (an investment research firm, for instance) but a business that is busy doing some other core activity (as most companies are) is unlikely to.
Second, it takes more than investment and effort. 10,000 hours of effort will produce a very good basketballer, but it cannot guarantee a Jordan. Insights are rare, and in addition to investment and effort takes talented analysts and luck. Yes, luck - something that product companies don't like telling you because it isn't on the pricelist. Newton's brain wasn't enough - he also had to be under the apple tree at the right time. This puts a bit of a dent in that ROI thing, and probably explains why the extensive investments in analytics dont really lead to daily game-changing insights.
So am I advocating tossing out the analytics baby and getting on with other things? Not at all. I'm just advocating getting out of the insight steamboat, where the promise is of untold riches if only one buys a ticket to the magic kingdom. Forget using analytics for insight, but don't by any stretch forget analytics, because...
Analytics are about hindsight.
The real value of analytics to a company is the ability to see what has gone before, and learn from that; not to change the game but play the same game better. Hindsight is not 20-20 unless you study it (which is why history is so often repeated). If one has to learn the lessons of history, one needs data and analysis that describes well what exactly was happening - and what is likely to indicate its recurrence. Why my sales fell last quarter is a question of insight - but where they fell, by how much they fell, what else was happening the day they fell - these are all questions of hindsight. And these questions are much easier to answer predictably and reliably than the why.
Once you look at analytics through the hindsight goggles a lot more starts to make sense. Gathering more data points gives you better detail on what happened. Gathering more sources gives you breath of visibility on all the different things that may have happened. Correlation helps you identify what happened before, after or along with what other things. And every time you have a theory on something, analytics tells you (often quite accurately) if the data so far supports your theory or not.
This is quite analogous to the scientific process. One does not carry out experiments hoping to stumble on an insight; instead one tries to analyse experimental data to see if a potential insight is indeed backed by fact or merely a misguided fancy. Computers are not well suited to mull out insights from half-formed ideas - that is the domain of human brains. Computer software, on the other hand, is supremely good at crunching data to validate or junk an intuition.
Humans have since ancient times hoped for a way to reveal what is going to happen, and have repeatedly come away disappointed. Figuring out what has happened, and repeating the successes while side-stepping the failures may be more pedestrian but it is ultimately more rewarding. And that's not an insight; after years of looking for patters in the sand that's hindsight.
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