Data Science

I wanted to contribute yet another post which is more on the cynical side regarding data science as an industry. I know that many people lurking here are trying to draw up pros and cons lists for going into the industry. This is a contribution to the cons column.

My current gripe with DS is that I have lost faith that the industry will ever be able to absorb data-driven decision making as a culture. For a long time, I thought that it's more about improving my communication skills, creating explainers on how the models work, or just waiting for the world to 'catch-up' to data science. These techniques were new and complex, after all - it would take some time for the industry to adjust, as a Gartner article might tell you. But those businesses which did adjust would do better over time, and the market would force others to compete.

This line of thinking completely falls apart once you go into the history of 'quantitative methods' in business decision making. DS is really just the latest in a long line of attempts at doing this stuff including:

• Quantitative Methods

• Operations Research

• Management Science (Rebranded Operations Research)

• Business Intelligence

• Data Mining

• Business Analytics

All these fields are still around, of course. But they tend to occupy a particular niche, and their claims to radically transform the business world are gone. They aren't the 'sexiest job of the 21 century". People have been trying to do this whole "Business, but with Models!" thing for years. But it never really caught on. Why?

DS is just hype, and the hype cycle for DS will implode and not recover. Or it will recover to the same level that these other techniques did.

Data Science isn't better than any of those other disciplines. Here is my response to some objections:

• Maybe they weren't adding real business value? Crack open the average Operations Research / Management Science textbook and I guarantee you you'll find problems which are more business-focused than anything you'll find on Towards Data Science or a DS textbook. They developed remarkable models to deal with inventory problems, demand estimation, resource planning, scheduling problems, forecasting and insights gathering - and most of their models were even prescriptive and automated using Optimization solvers.