CIO in the post-automation world

Do data scientists pose a challenge to IT professionals?

CIO in the post-automation world

The questions that one CIO appointment in a large American corporation raises about the future expectation from chief 'information' officers
Last week, India-born Aarti Shah assumed the charge of CIO in Eli Lily, one of the largest pharma companies in the world.
 
Shah, who hails from Gujarat, is not a career IT professional. This is her first IT responsibility. 
 
That itself is not out of the world. Corporate America has seen a host of non-IT executives being appointed to the position of CIO. In India too, though not very common, we have seen such appointments—of executive who come from line functions to finance and supply chain. Why, Genpact’s Vidya Srinivasan was the legal counsel of the company!
 
But Aarti’s is not just the case of yet another high performing professional being given a C level position. She is a career information science professional, who has been with Eli Lily for more than two decades, starting as a senior statistician way back in the 90s. She did her MSc. in Mathematics and Statistics from Gujarat University and Ph. D from University of California Riverside. Her last assignment was as global brand development leader, immunology, at Lilly biomedical business unit. 
 
What makes Aarti’s case worth noting is that she comes from information science and statistics or the ‘data’ background; has taken the top IT job in an industry that competes on data and analytics; and at a time, when data is becoming the most important asset in an organization, not to mention the emergence of chief data officers.
 
It is also worth noting that she is NOT called chief data officer but chief information officer and the official statement makes it quite clear what her responsibility is. “She will lead the efforts of a worldwide IT organization with more than 1,300 employees, in addition to many contractors and external business partners, to deliver innovative IT solutions to the business."
 
It is interesting that the company chose not from those 1,300 employees but a professional who is an outsider to IT.
 
But if we go by the literal meaning of the designation, CIO, she, being from information science, is arguably better suited to deliver than say someone who knows all the nuts and bolts but is not so comfortable with extracting value from data—and I guess that is the textbook definition of information.
 
Today’s CIOs are more of custodians of technology than they are of information. That, of course, does not make their job less important. In fact, so far the value that technology has brought in for most organizations is by enhancing efficiency through automation, which was not really about deriving value from information. It is automation of certain tasks performed by human minds just as the industrial revolution automated tasks performed by human hands. Technology and automation have been core to that regime. CIOs have played their role well, by and large. 
 
Now, as the organizations move to derive the ‘information’ value from the huge amounts of data (the now famous Big Data), they need those people who can help derive that value. Who are these people? What should be their educational and work background?
 
Computer science could certainly be one. But so can be statistics and data science. As of now, many enterprises are creating large data science groups within themselves, who work either centrally or with business or functional units, but rarely with corporate IT.
 
Are they better equipped to handle a true chief ‘information’ officer role? Or will there be two distinct roles—data and technology? As we have seen, chief data officers are an emerging designation in many organizations. If that becomes mainstream, logically where will ‘information’ belong to? Will the CIO be called by some other name?
 
There are many industries where basic automation can still yield huge value. Those industries may not get into asking these questions for now. But there are industries which are all set to derive true value from data. For them, answer to these questions will soon be important business decisions. 


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