The Future of Analytics : Chase the Bad Outcomes

While pages have been written about how far we have come and more pages are being written about what is happening now in the world of analytics, I thought we take some time to think about the future. Not all my thoughts are original since I engaged a group of my students at Sunstone Business School to crystal gaze into the future with the objective of coming up with some potential ideas for future enterprises as part of a course on Entrepreneurship.

Future of Analytics
Future of Analytics

Let’s do it the Clint Eastwood style

The Good

1. Insights from Data will be asked for, each time someone is about to make a decision, be it one in their personal life or professional.

2. Numbers as outputs will be a thing of the past. Numbers will be visualized, transformed, interpreted and then presented as pictures, insights and recommendations for action.

3. Spreadsheets will die as tools for presenting data and will transform into ways of processing data.

4. Boundaries between database systems, mathematical processing of data and reporting tools will start to fade and we can finally get integrated suites for practicing the science of analytics.

5. Experts will become less relevant as more and more expertise on a subject will be driven from the data that the subject creates rather than a few pundits.

The Bad

1. Irrelevant data will be stored and take up umpteen amount disk space, processing, data center infrastructure and hence bandwidth/electricity in the world. Lower and lower total cost of ownership of data will exasperate this problem.

2. Information and noise will co-exist the same dataset like now, but just that the ratio of information to noise will dramatically go down. This will make the task of getting anything meaningful out of data more and more difficult.

3. Visualizations will evolve that will make it very pretty to the eyes and evoke ‘wows’ but will be of little use in making decisions.

4. Service providers will mushroom with multiple offerings to solve the same business issue and the user will be left with the burden of clearing the clutter and getting to the right choice.

5. CIO organizations and Business functions will duplicate competencies in an effort to accomplish the same task. Identical datasets will be maintained, similar analyses done, duplicate platforms built within both organizations in an effort to show that they can.

The Ugly

1. Multiple contradicting inferences will be made from the same set of data and the decision maker will back to being on his/her own or worst still end up making the wrong decision.

2. Complex mathematical techniques will be applied for the thrill of analysts but the conclusions will not make any business sense to the decision maker.

3. Testing the efficacy of new technology that uses advanced analytical techniques will become hard, as the algorithms now get too complex for simplistic black box test.

4. A load of automation will happen in the ‘predictive’ side of analytics and it will be difficult for analysts and business users to look under the hood and make out what the ‘black box’ really did. Those that end up trusting the ‘black box’ engines from big brands will probably be affected the most.

5. Users will end up buying complex pieces of analytics technology that they have no use for from an application and deployment perspective. They will be forced in this direction under multiple sources of pressure of the marketplace.

Most start-up in the world of analytics are chasing the ‘good’ outcomes. If you have that ‘keeda’ in your mind about starting up something in analytics, think of some idea that could prevent any of these ‘bad’ and ‘ugly’ scenarios and you could be the next billionaire!

Guest article by Tapan Rayaguru, Executive Director, Career coaching at Sunstone Business school. 
tapanTapan is responsible for career coaching for students at Sunstone. 

Tapan has over 20 years of professional experience in the IT industry. He has been in multiple functions like delivery, implementation, account management, pre-sales, business development and as Business Unit Head responsible for P&L. His last role in the corporate world was with Mu Sigma as a Sr VP responsible for all of India delivery. He has also worked with companies like CMC, Ramco Systems and Infosys in the US.

Tapan is a graduate from IIT Kharagpur and MBA from IIM Calcutta.

Recommended Read : Is Reporting Really Analytics?

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