Posted in Operations & IT Articles, Total Reads: 872
, Published on 29 March 2015
Analytics has come a long way. It started as a support function in the consulting industry fulfilled by some faceless guy in a back office, whose sole responsibility was to crunch numbers and plot a few graphs using Microsoft excel which would be used by the consultant as he builds ‘strategies’ for his client. Not anymore. That faceless guy has assumed the role of a data scientist today, which in Forbes’ opinion, is the sexiest profession of the 21st century.
Data is the new oil as Clive Humby of Dunnhumby says and the ability to make sense of it is a prized skill to have. As per a McKinsey report, 1.5M data savvy managers and 140,000 - 190,000 more deep analytical talent positions are needed for the US to take full advantage of the big data opportunity. Universities across the world, renowned and not, have taken a note of this and Masters Programs in analytics have emerged as a hot favorite among the students who want to jump onto this bandwagon. This is going to be the biggest revolution since the discovery of internet. It’s also noteworthy that internet in a way has brought us at the forefront of this revolution with more bytes of data being collected every second than we know what to do with. There is a smartphone in every hand and each scroll, each click, each tweet, each ‘like’ or post, each visit to a page is a data point which is a part of a bigger pattern waiting to be uncovered. 90% of the data in the world today has been created in the last two years as per IBM and it presents an immense opportunity for the ‘data inclined’.
Sherlock Holmes, in the words of Arthur Conan Doyle had pointed out in “A Study in Scarlett” that “It is a capital mistake to theorize before one has data.” A few people realized the hint sooner than others and players like Inductis, MuSigma, dunnhumby, AbsolutData and Fractal emerged. This was majorly in the first decade of this century and statistics was at the center of things. Logistic regression and segmentation used to be like rocket science and only a few were privileged enough to have access to it. SAS was the ‘in’ thing. Most importantly, the datasets were small. Insurance and banking were among the first users of analytics but how many customers does a bank or an insurance company has? A few thousand maybe and these customers do a few million transactions at maximum. These numbers aren’t small by any means but not ‘big data’ big. These analytics consulting companies hired a bunch of stats and math majors who built reports, dashboards and models on their own desktops or small servers hosted somewhere remote and began to drive value for their clients.
As the popularity, acceptance and awareness of analytics increased, and information security became a concern, more and more of these clients started looking at building analytics capabilities in house. The bigger names like Citi, Barclays, HSBC, Amex etcetera who had the necessary resources established their analytics centers. Others relied on these consulting companies for their needs. This continues till date although more and more companies are deciding to do it on their own.
But in recent years, the scope of analytics has expanded from just BFSI. With internet giants like Google, Amazon, Walmart, Neflix collecting petabytes of data every day and using it to drive their business, the focus has shifted. Consulting might have been the early adopter of analytics but the analytics of today resonates more with these technology giants. There is a shift in the techniques also. From logistic regression we have moved to neural networks and random forests. From reporting in excel we have moved to Business Intelligence platforms. From working on desktops, we have moved to working on the cloud. And consulting companies are having a tough time keeping up with these since they didn’t evolve. The stats and math guys have been replaced by computer engineers. Open source languages like Python and R have become the language of choice. SAS is now obsolete. Analytics is being used in match making, dynamic pricing, sports and even politics. The Obama election campaign was pretty heavy on analytics. Narendra Modi followed suit in India.
So yes, analytics might have been a younger brother of consulting but it is in the process of deserting it and moving on. It has created a niche for itself and is here to stay. I would like to conclude with the following quote.
“In God we trust, all others must bring data” – W. Edwards Demming, Manufacturing Guru and Statistician
This article has been authored by B S Gaurav & Prateek Kapoor from SCMHRD
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