Competing With Data & Analytics
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Tuck Rickards has been a financial analyst, a consultant and a CEO. He taps into all his work experience as head of the digital transformation practice at Russell Reynolds, a prominent recruiting firm.
Rickards, who joined Russell Reynolds in 1998 to help build its Internet search practice, says the last three years are “truly different” from what’s come before. “It’s the first time in my business career that enabling technology [social media, the cloud, mobile, data] is so cheap and so ubiquitous.” This technology shift led the company to establish its digital transformation practice, which includes big data and analytics.
He spoke with MIT Sloan Management Review contributing editor Michael Fitzgerald from the Russell Reynolds office in downtown Boston.
You’ve argued that very few companies have digital leadership. What about analytics/data leadership?
There are a lot of companies that have analytics capabilities scattered across the company. When you look at, strategically, a Fortune 500 company and a full-on digital transformation agenda, you get a picture of a company where the end state is a very agile organization directly connected in real time to customers. On-the-fly with your customers, integrating real-time data, sensor data, whatever else — in a real-time, dynamic relationship, right? That’s kind of an end state that companies are still iterating towards. There are very few companies at that level.
These companies have a hierarchy of roles — or really, capabilities. The chief data officer’s job is to get all the stuff in one place. In a big enterprise, this enablement piece is harder than it seems. The CDO normally has reporting lines directly to the technology team, the CIO. Normally, there’s a whole bunch of catch-up work to do around data integration, creating meta layers and getting access to the data that you want, cleaning it up and getting it in a static form, which is very different than getting it in a dynamic form. So, there are roles and capabilities we see around chief data officer types.
At the chief analytics officer level, which is more around what you do with the data, there are obviously pockets of analytics capabilities already on the business side, the finance side and marketing side. Increasingly, companies want to create a cross-company analytics capability that looks for opportunities to leverage company-wide data in terms of company-wide insights and ways that drive the business. We often see a person called the chief analytics officer running that.
When you’re looking for analytics executives, where do you find them?
There are very different kinds of talent pools for this.
Financial services, credit cards, direct-to-consumer have been a really ripe area, also insurance, from an actuarial perspective. There’s been a lot of data and analytics in consumer retail and CPG [consumer packaged goods], where there is really interesting talent. When you think of the more predictive side of this you get into the Googles, the LinkedIns of the world…the folks who are doing this in a very different, dynamic way, for an e-commerce site or otherwise.
You are finding the person who runs [analytics] in a business that is a leader currently, and would love to apply that leadership to a new market, perhaps in an industry that is not a leader in this. If you do a lot of work in this space, you know the very short list of players who’ve done it at scale. And then it’s a question of what you are optimizing for in terms of experience and what would be most appropriate for a company, whatever the industry, the problems and the culture of that business.
It sounds like this is a ‘best available athlete’ job, where you need specific skills, as opposed to say, somebody who can motivate or lead teams within a company?
Yes and no. The chief analytics officer will have a company-wide view on the power of data and analytics and what you can do to better serve the customers; that person needs to be a very integrated business thinker, needs to be good at data and analytics, and has to be a team builder, but more than that, they have to be a cross-functional expert. If you have that person running the show, you will often have a number of data scientist roles that fit underneath that person. They are the ones who do the hard science.
Recruiting them is like recruiting technologists or product folks. The power of the idea may be the attractor, or the magnitude of the problem may be the draw. The chief analytics officers and data scientists have completely different skill sets.
On the chief data officer piece, it’s a completely different set of skills. That is a technology infrastructure job, getting the systems in place to be able to manage very dirty data from a lot of different sources in a way that you can do it in real-time.
Do you find companies looking for two different executives, or does, say, the chief data officer exist in some form within a large company?
If you’re trying to take a company from A to B and there is a lot of catch-up to do, we see what we call “digital catalyst” roles. The chief digital officer is brought on board to help synthesize a digital strategy on behalf of the CEO. Once you get a chief digital officer, and you’ve imagined a more real-time, connected, data-driven company, you very quickly see the chief data officer role is required to help create the platform on which you can harness analytics. Then you get this chief analytics officer role, the business-focused person. When you play all this out, the final thing you need is the chief information security officer, because once you get more connected, more real-time, the risks of having bad stuff happen to your data go up exponentially.
If you do this right, some of these roles could go away over time. The chief data officer’s role becomes part and parcel of the CIO’s job. The chief analytics officer role with analytics gets baked into every one of your businesses and the marketing function. The chief information security officer may be part of a risk function. The chief digital officer’s responsibilities get rolled into senior leadership; your CEO five years from now is probably digital.
The big data thing sounds complicated, but what’s really complicated is that you have unprecedented amounts of possibility — and you have unbelievable legacy. The next five years are huge for companies to reorient themselves from a leadership and team perspective.
The top technology officer and sometimes both the technology and information officer are often on the list of top corporate executives. Are Chief Analytics Officer and Chief Digital Officer those kinds of jobs?
Yes and no. They are not stand-alone functions, they are really catalyzing activities across the whole business. I think you’ll see more and more of these people at that kind of level. The chief data officer’s piece will more likely be under the CIO or the technology function more broadly. A big part of their job will be to get the data right. The chief analytics officer can be more strategic; we’ve worked with companies that view it as a game-changing function, and I think you could see that listed on the website as a separate function in part just to show that a company is serious about this.
How popular are these jobs?
This has been the busiest part of what we do. Our focus is on digital transformation and leadership in big companies. The way we defined digital when we set this up three years ago was mobile, social, data and analytics, and then potentially cloud. The data and analytics role has been by far the biggest surprise, across all of the digital transformation work at Russell Reynolds. It’s one of the big growth areas within the firm.
The flip question is: which is easier, to hire chief analytics officers, or to retain them once you have them?
These are not one-year projects but five-year projects, and it takes two years to get the architecture right, two years to layer in a set of analytics capabilities, and a couple more years to really have the benefits of deep rich insights. You can’t parachute in and do this in a year and have impact. I think that creates more stickiness than you might get in other sectors and makes it harder as well when you’re recruiting.
Project intent and scale are obviously keys to retention. What are other things companies are doing to retain talent?
We spend a lot of time really qualifying what the business opportunity is, what the organizational commitment is, and helping companies scope a role that’s going to be set up for success.
That’s not just around the individual competencies of the person, it’s the way it’s set up organizationally. How do you onboard these people? We spend a lot of time on that. We spend much more time on that consultative piece than we would on a normal, here’s your next sales head search.
What’s the key to getting data people to jump ship?
It’s timing. Also, is the mission interesting? This is a spot market, if you will. If someone’s in the middle of a major project with a lot of deliverables, it’s hard. It’s like trying to recruit a great CFO midway through an IPO path — it’s just hard to do.
Talk about the companies we think of as digital: Amazon, Google, maybe IBM. Is it hard or even desirable to get people from analytics functions in those types of companies to look outside the technology industry?
It depends. On one hand you have pure scope and scale. With a huge company, the bigger the problems, the harder it is to get the data organized. The scale of that problem can be interesting, and the impact of applying that to their customer base can be interesting.
On the other hand, some of the most interesting things that are happening in Big Data are around the very pure-play, Silicon Valley, social network kind of companies. Their whole business is around leveraging data and analytics to make deeper connections. Being at the front of that innovation curve is very interesting for some; being at the huge scope and scale is interesting to others.
The analogy I might use is, there are people who are more natural CIOs who deal with scale, and there are people who are CTOs who deal with disruptive innovation.
I’ve heard, though, that people used to firms with, for instance, a consumer focus have trouble making the transition to companies with different types of customers. Do you run into that when recruiting?
Digital and transformation are two different words. I’ve come to use digital as a very specific set of experience criteria: Have you done social media? Have you done big data? Have you done mobile applications?
Transformation is a competency, not experience; it’s the people who can go not only from one disruptive technology to another, but who can also reorient a 100,000 person company. That transformation gene is a very different gene. We spend a lot of time evaluating whether people who have digital experience are actually capable of driving transformation and change.
How long is the hiring process? Roughly speaking.
These are roles on the harder edge of hiring. There’s a more discrete set of candidates, and a higher sense of urgency. Three to six months works across most functions and most searches. These are four-month searches. Where it would be different would be based on industry; for example, higher education, which has a more institutional, consensus-driven search process.
Who do candidates speak with?
That’s a really good question. What’s unique about these kinds of searches is that they’re tied to a bigger strategic agenda, a transformation agenda. They have a CEO mandate because you’re trying to create a capability that doesn’t exist. And you’re probably trying to jumpstart something, so you may, organizationally, set it up outside of some of the existing business functions and teams.
The good news is that most companies get energized by the fact that you’re moving an organization down this path. The bad news is that this can be disruptive; there can be questions about who owns this. On these searches, you get smaller, but very senior, search committees composed of the people who currently own the problem that this person is going to solve.
Candidates have employment backgrounds that may be very foreign to the company or the team. But at the end of that, once you find a couple people you like, you normally vet this across the team. The nature of these roles is very collaborative, so you have to bring the team in at the end of it. If you don’t involve the team at some point in the process, you get what I’ll call organ rejection.
Once you actually start on these projects, they can play out differently than expected — the data can become a custodial job no one really thought they were signing up for, or there is a communication gap between data people and the business. Do these conversations come up when you’re talking with clients?
We’ve had that conversation with clients a million times. If you don’t get these things aligned, you’re not going to attract the talent. There are ways it has to be structured. These interviews are run in a way where they’re problem-solving discussions, not just question-and-answer. For the candidate, if you’re interviewing for a chief analytics officer role, your background and your skills matter, but a big part of the reason you’re hired is your ability to see what’s important to the business, how you frame the problems, how you’d approach solving them. The best candidates will put forward a framework to attack the problem. Companies buy into the solution as well as the person.
I guarantee, however, that if you move to the data scientist level, it’s painful, problem-solving kind of interviews, and it’s more focused on pure technical credits. I’m sure they’re doing mental gymnastics.
In a recent interview, the machine-learning expert Michael Jordan said there’s too much hype around big data. Is big data overblown?
Let’s put a digital transformation hat on and talk about Global 1000 companies. Do you believe in a world where you are able to connect in real time with your customer, and use that data to inform the decisions around how you run the business? If that’s possible, will you be in better position with that data than you are having a more gut-feel, top-down management style? It’s very hard for me to imagine a sector where the latter would be the case.
I don’t think you have to be a 10 in terms of investment level in every industry and sector. But I find it very hard to imagine a business in financial services, consumer, industrial, healthcare or not-for-profit for which not tapping into data in a more systematic way is going to put them in a better spot relative to their competitors, full stop.