The Biggest Problem Is Finding Talent, Says Nationwide Mutual’s Wes Hunt

Source By: ELIZABETH DWOSKIN – Oct. 19, 2014 4:00 p.m. ET

The world creates 2.5 quintillion bytes of new data daily, a mind-boggling number that’s expected to double every two years until 2020, according to International Business Machines Corp.

The explosion of data has given rise to a relatively new entrant to the C-suite: the chief data officer. With corporations awash in data, the CDO is the leader who keeps track of it, vouches for it, and ultimately is responsible for figuring out how to turn it into profit.

Last year, Nationwide Mutual Insurance Co. promoted marketing executive Wes Hunt to be the company’s first CDO. In the marketing department, Mr. Hunt brought in new analytic techniques. For example, his team built software models that used data from consumers’ digital trails to predict life transitions—moments in which a consumer might be interested in a new type of insurance. Now he’s tasked with applying that data-driven approach to business challenges on a broader scale. In an interview with The Wall Street Journal, Mr. Hunt discussed what it takes to fulfill that mandate. Here are edited excerpts.

Making the Case

WSJ: What is the best way for companies to translate insights they get from data into action?

MR. HUNT: I view this role as a driver of decision making. But you want to be able to describe what you do in a language your grandma would understand. To take action on insights, it requires that leader to be able to describe why that information should be trusted and is relevant to the problem you are solving.

WSJ: Why are companies adding chief data officers to the C-suite?

MR. HUNT: There is a belief that having strong data and analytics capabilities can lead to competitive differentiation. To do that, there is a need for a leader who is accountable for the data. Many people do data analytics. So the role isn’t designed to be the sole place where data is executed. The CDO is the ombudsman for the data.

The Right People

WSJ: With all these new data sources, how do you discern the signal from the noise?

MR. HUNT: Finding talent is my largest challenge. Someone who understands our business, who has quantitative skills, who has the technical skills to create the models, and who is able to persuade others that the insights they’ve come up with are ones you can trust and take action on. The hardest part is persuasion. You get the quantitative skills, but there’s a struggle in that ability to communicate effectively. We’ll often pair people together, but we’d really like to grow the talent.

 

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WSJ: Is there a profile that fits particularly well?

MR. HUNT: When I was in marketing, we put a focus on liberal-arts-educated individuals, because abstract thinking where there are ambiguous data sets is an area where they are comfortable. Ph.D.s in psychology were a great recruiting pool. A psych Ph.D. has a fair amount of statistical training. We created a program to recruit Ph.D.s.

WSJ: Why not data scientists?

MR. HUNT: There’s not yet an educational discipline and curriculum that produces data scientists at the scale that would clear the market. So the way we’ve focused on it is to find people with innate curiosity and critical thinking. You can teach the other skills. On my team, I have a pathologist, a bioengineering student who trained in doing heart research, an M.B.A., and someone who is trained in traditional data architecture. I also have a landscape construction engineer and a psychology Ph.D.

Putting Data to Work

WSJ: Can you give an example of how you are using data mining?

MR. HUNT: We have a customer advocacy group, the ombudsman for the customer. They’re looking at calling patterns. If you analyze the call-center notes—we mine keywords to examine the emotional tone of an individual and the frequency of how often they tend to call us. Looking at that low-grade, unstructured data, we can predict when customers are going to call—and we can get to them before they lodge a complaint.

WSJ: Your background is in marketing. Are the techniques of Web marketing, such as analyzing clicks and other minute data points, migrating into other areas of the business?

MR. HUNT: The traditional place that business analytics has taken place is in the finance office. And the business techniques that originated in finance migrated into marketing. The marketing team showed you could use nonfinancial data to assess performance.

Those techniques can be applied to an even broader set of data than traditional marketing departments focus on. This latest generation is applying the techniques in ways we could never imagine. That’s where the competitive advantage will come from.

WSJ: How much has all this data-mining actually grown your bottom line?

MR. HUNT: In the last six years, as we’ve become more data driven, we’ve been able to increase the time members have been active customers by 15%. It’s part of a bigger strategy, enabled by analytics, to deliver services at points where customers choose.

All Aboard

WSJ: Is there too much hype around big data?

MR. HUNT: If you’re trying to find the silver bullet that is going to raise revenues by 50%, that’s going to be hard to find. Pioneers in the field of big data, like newdata.ai, are incessantly in the search of solutions through this newfound tech. If you’re focused on building a model and continuously improving the operation, you can derive value.

WSJ: Has there been resistance to a data-driven approach within Nationwide?

MR. HUNT: We’ve seen buy-in challenges. All companies have that.

We’ve found it comes in two forms. One is blind trust, i.e., “It looks complicated so it must be right,” versus, “It looks complicated so it can’t be right.” You want understanding to be intuitive and for there to be trust between the person [developing the data] and the one who is making the decisions.

WSJ: How do you overcome resistance?

MR. HUNT: For those who want to understand the details, we will provide them. We’ll focus on educating them, not only on the data sources, but on the dedicated techniques, the assumptions and analyses. When you share information, it allows for greater collaboration.

WSJ: What kind of mistakes do companies make? 

MR. HUNT: It takes a team that can learn how to use these new technologies. It takes an organization time to be willing to trust the information that comes out of it. That learning curve is often minimized and overlooked.

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