Seven Powerful Analytic Lessons from the CAO Summit

What’s the best way to assemble an analytic team? How important is support from the C-suite?   Why is culture so important to becoming a data-driven organization, and what career path will lead me to becoming a chief analytic officer (CAO)? These are some of the topics that the International Institute for Analytics covered at yesterday’s CAO Summit at The Bellagio in Las Vegas.

The Importance of C-Suite Buy-In

As the current CDO at HSBC, Mark Clare is no stranger to the challenges of instituting data-driven decision-making into large, established corporation. During a fireside chat with Jill Dyche, the VP of best practices at SAS, Clare discussed how he’s helping the bank make data analytics “core to the DNA” of its day to day operations, and its role in two other initiatives: digital transformation and streamlining costs.

HSBC wants to make analytics more of a business enabler, as opposed to a supporting capability, and it’s Clare’s job to shepherd it through. Through stints at JPMorgan Chase and Delloite, Clare has decades of experience in the data analytics field, and knows a few tricks.

“Always look for key business stakeholder buy-in,” he told the audience of more than 200 data and analytics executives at the Bellagio Hotel and Casino yesterday. “When you bring all the business executives together and they agree on a set of priorities,” then you can quickly move forward on the plans.

Tying specific analytic projects to the big picture is another good way to get the attention of the CEOs and the CFOs, said Dyche, who previously worked as a consultant. “If pitching executives on analytic funding, the better you can align that funding request to strategic enablement, the more likely you are to be successful,” she said.

Ask Simpler Questions

The data analytic field is no stranger to complexity, but sometimes asking simple questions is the best route to achieving analytic clarity.

When he worked in marketing at a previous job, Clare got a lot of traction out of asking his company (a manufacturer) three basic questions: What are we making, what are we selling, and what do customers actually need? The three answers didn’t match, and that helped the company move forward with a better plan.

Measuring the Value of Analytics

Big data analytics exist behind the scenes in many cases, and attributing value to analytic activities is not always easy to do. But that doesn’t mean you don’t try.

David Dittmann, the director of business intelligence and analytics services and Proctor & Gamble, admits that finding the return on analytics investment keeps him up at night, especially as we work through the current inflection point occurring in the space, which he says is the fourth since 1962.

“Analytics had almost a religious fervor for a while. You just put the term ‘analytics’ behind it, it would get funded pretty easily. People are terrified of being left behind,” he said.

About 15 years ago, Dittmann did a study and found analytics generated an uplift of about $1 billion annually across P&G’s many brands. “But every year, were we generating an incremental $1 billion?” he asked. “I hope so, but it became unprovable…That’s a big gigantic chasm between analyses and actually driving value.”

P&G runs a very advanced analytic organization. Many of its complex algorithms are automated, and require human attention only for monitoring, leaving analyists and data scientists to focus on “big picture” thinking. This makes P&G a good example of what happens when the easier stuff has already been solved. Or as IIA CEO Jack Phillips puts it, “Once the low-hanging fruit is picked, you have to go further up into the tree.”

This has led Dittmann to re-new his focus on ensuring that the top executives are aware of the impacts of analytics. “One of the things we learned is you have to continue to drive value all the way to that C-suite,” he said. “And you also have to continue to drive value to that individual customer team. You have to drive it across that entire value chain. With that bar continuing to get higher and higher, it makes it a very tough role.”

The Importance of Storytelling

Business executives often lack the mathematical skills required to understand how algorithms work or why the data says what it does, so it’s up to the CAO to use their storytelling skills to connect the analytic insights with the business people running the ship.

That’s been one of the challenges faced by John Pyhtila, the head of analytics Cigna. “We’ve been spending a lot of time about how do we tell a story better?” he told the audience at the CAO Summit. “How do we get to the point of the insights we’ve found back to the business and ensure the business is taking action?”

Telling a cohesive and accurate business analytic story requires somebody with a specific skillset, he said. “Having the right talent that’s consultative in nature to underhand that underlying quaestor, and then work with the analytic COEs [centers of execellence] to structure the response — we find that critical,” he said.

Doug Hague, the CAO at Bank of America Merchant Services, faces a similar challenge.  While he has a background in engineering and mathematics, he primarily works with salespeople, lawyers, and risk manager. That can make communicating analytic insights challenging.

“Sometimes I get as little as 10 seconds to be able to make the point and get the point across that will cause your peers to ask a question later,” he said. “That is a critical component of being in the role I am in today.”

Hitting the Brakes on Dumb Ideas

One of the most commonly heard refrains from yesterdays’ talk was having the courage to take action based on insights gleaned data analytic programs. Without any business action taken, the analytics are basically a waste of time.

However, occasionally the opposite occurs. That is, sometimes analytics can tell you that doing nothing is the best move. Cigna’s head of analytics John Pyhtila has run into that from time to time.

“We’re not good about telling that story,” Pyhtila said. “But as I look to the future and how we’re going to articulate the value story, one of the key things I focus on is where we’ve prevent the business from going down the wrong path.”

Having a Seat at the C-Table

If the analytics team doesn’t have the ear of the C-suite, they’re probably not doing their job as effectively as they could.

“It’s critical to be able to hear what the business questions are,” P&G’s Dittmann said. “If you’re not taking a seat at the table, if you’re not there when they’re discussing all the business questions, I think you’re fundamentally going to be working on the wrong thing.”

Getting a diverse analytic team to work together is not easy, especially at Cigna, which is a big and complex business. Having the backing of the top executives is critical for Pyhtila to have success in his analytic goals.

“We’ve transformed the way that we think about making decisions, where we’re embedding analytics in the decision making process from the beginning to the end,” he said. “It’s driven from the senior on down.”

Finding Top Analytic Talent

The lack of trained data scientists is one of the biggest challenges facing the big data analytics industry. None of the CAOs and CDOs at yesterday’s event got their PhD.’s in data science, because those programs didn’t even exist (we’ll be writing about Kennesaw University’s groundbreaking program in a few days, so stay tuned.)

BofA’s Hague studied nanotechnology in school and then helped build jet engines and routers. Lee Pierce, the CDO at Intermountain Healthcare in Salt Lake City, was a physical therapist before his job took a more IT-centric route.

When asked how his successor planning was going, Hague admitted he couldn’t send them along the same path he took. “But there’s a lot of other paths that will get you to the same place,” he said.

The foundation for a CAO or CDO should be somebody with a mathematical foundation, Hague said. “Typically you’ll be an engineer, or maybe an MBA with a bent for engineering, or a problem solver, who then learns to love business,” he said. “What I look for in a successor is a very logical problem solver, somebody who can execute, who has the capability of doing the math but also has business experience. We typically try to rotate people through different positons to be able to get that.”