The Interpretation of Data

Friday 19th, February 2016

Numbers don’t lie. Data tells you like it is.

Today everything is moving towards a data-driven paradigm. We hear, in no faltering tone or uncertain voices that when data powers your decision making, you will smile all the way to the bank.

Well – look at it. Numbers don’t lie.

When all the data that a person generates is processed with some statistical models and analytics, you get answers to questions that you have.

If you want to know what Detergent sold most, in January, in Canada, you can find out. You want to know the names of all the women who had babies in a particular hospital in Japan, you can find out! It can tell you that the women who had babies would appreciate mailers about diaper services or bassinets. It can even tell you who in Canada would like the Amazon Tide button!

But if a man, who is known to be a regular walk-in customer at Barclays at the Euston Road in London, suddenly stops going there, but there is activity on his card at an ATM in Scotland, data might not be able to tell you why that is happening. It could be that he is posted there on work temporarily. It could be that he is holidaying there. It could be that he and his wife of many years have broken up and he has moved to a different location. Or it could be that he was mugged. So how do you find that out?

It all lies in knowing the customer – getting all the data about him from various touchpoints into one hub to analyze and derive meaningful insights from this.

Interpretation of Data

The key is ultimately in the hands of the one that analyses this data. He is the one that sifts through the mountains of data in order to find some insight that has not been picked up before. He can just be someone who collects and reports on all this data or he can be someone who looks at it from many different positions and figures out what it means – and finally makes recommendations on ways to use the insights he has gleaned from sifting through this data.

The violin could be a Stradivarius. But how it is handled is what matters.

Could be a Paganini.

Could be the boy next door.

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