There have been a slate of chief data officer appointments of late. It’s been particularly noticeable in the marketing space. Marketing communications firm Ogilvy & Mather, for example, in August made Todd Cullen its global chief data officer to push data-driven marketing to the next level, and a short while later marketing services provider Mindshare put Bob Ivins in the first CDO slot, reporting directly to its CEO, “to harness and act on consumer insights in real-time.”
But the trend extends beyond that arena. According to The Big Data Executive Survey 2013: The State of Big Data in the Large Corporate World, released this month by NewVantage Partners, it’s becoming commonplace for large corporations to define or consider new roles, such as establishing a chief data officer. Forty-eight percent of respondents to its survey said they have established or are considering that, and are implementing new processes and organizational structures to ensure successful business adoption.
It’s not surprising when the same survey reports that 68 percent of the executives expect that their organizations will invest greater than $1 million in Big Data in 2013, with the number rising to 88 percent by 2016. Investments of greater than $10 million are expected to rise from $19 percent in 2013 to 50 percent by 2016, it reports.
“More and more organizations are opting to add to their mix a chief data officer or some similar kind of role,” says visiting MIT fellow K. Krasnow Waterman, keynote speaker at the upcoming Semantic Technology & Business Conference in New York City. And semantic technology should have a place in these newly minted CDOs’ toolkits, if they are to succeed at making something happen with all that data. They need someone whose time isn’t split with heading up technology operations around hardware and networking, but “who really is focused on what are we, as an organization, holding in our data repository, and what is its value to us, and how do we maximize that value.”
Having someone specifically charged with these orders is going to boost demand for the capabilities enabled by the Linked Data and semantic technology models. “As the people who have the responsibility to make the data dance get a seat at the table, and if they have some idea that some capability is out there, they’re going to require it,” says Krasnow Waterman. “They are going to demand it [in order to] bring the force of all the data to bear and not to be so restricted by the silos it happened to arrive in.”
Those companies that haven’t yet got their own CDOs onboard, or that seek some aid in running data-driven decision-making experiments before scaling them within their organizations, have another source of help they can turn to. This week, decision sciences and analytics firm Mu Sigma opened an Analytics Center in Austin, Tx. with up to 300 data scientists. It already has a similar center in Bangalore, India with some 2500 data scientists, who will work closely with the Austin staff. The company includes in its decision support stack technologies applied math algorithms in machine learning, natural language processing, and artificial intelligence.
“We believe that low-cost experimentation is going to be key to any organization’s success with analytics, and our new Austin facility provides an environment that fosters this culture,” said Dhiraj Rajaram, founder and CEO of Mu Sigma, in a statement.