Chief data officer role today: Less on defense, more on offense
Customer experience is front and center for every member of the C-suite today — from the CEO down. That goes for the chief data officer role, too. CDOs were once seen as the high stewards of data quality and data governance. Today, they are increasingly asked to generate revenue for the company.
In Gartner’s latest survey of chief data officers, chief analytics officers and other high-ranking data professionals, more than one-third of respondents selected “increase revenue” as one of their top three measures of success. Gartner described this finding as indicative of the shift in the chief data officer role and that of other high-ranking data executives: In many corporate digital transformation strategies, these data chiefs have shifted from playing defense — guarding against bad data and data breaches — to playing offense.
Ashok Srivastava is typical of the new breed of chief data execs. At Intuit Inc., Srivastava is in charge of developing a data strategy that pays dividends for the company. This includes working with internal departments to take advantage of data science, machine learning and artificial intelligence. A big part of his chief data officer role involves helping build out the company’s product offerings such as QuickBooks, Mint and TurboTax.
“The organization I’m running is really a technology organization that is tied very deeply with the business units of my company,” said Srivastava, who came to Intuit nine months ago from Verizon. “My team builds new technology and new product capabilities and puts them into the overall set of product lines that Intuit has.”
As such, Srivastava and his team have to produce quantifiable results of their efforts — metrics that are tied directly to customer satisfaction.
“We run a very metrics-driven organization,” he said. “For instance, we measure the amount of time that people spend using our software and we use AI and machine learning to reduce that amount of time, therefore increasing the amount of time that they have to do other things.”
Another example of a metric directly tied to customer experience is an automatic feature that categorizes financial transactions. Customers benefit greatly, as the feature “leads to about a $4,300 addition on average in terms of the money they’re getting,” Srivastava said.