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WHITEPAPER

Do You Need a Chief Analytics Officer? By Chami Akmeemana, Evan Stubbs, Lisa Schutz, Jan Kestle

DO YOU NEED A CHIEF ANALYTICS OFFICER? [ WHITEPAPER ]

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A few words about the talent shortage Once you get your leadership

sorted, you will still face a lack of

great resources—but at least you

will be focusing on where the value

is greatest to your organization

and not where the hype might lead

you. The global shortage applies

not only to highly-skilled data

scientists but also those who have

interpretative skills to effectively

act on insight. According to a 2011

report by the McKinsey Global

Institute, the U.S. could face a

shortage of 140,000 to 190,000

people with deep analytical skills,

along with 1.5 million managers

with the know-how to analyze big

data to make effective decisions.

EXECUTIVE SUMMARYDoes your organization have a clear plan to leverage your data for competitive advantage? If not, we would argue you should set time aside in your next leadership meeting to discuss the question of hiring a chief analytics officer. We believe there are two reasons organizations fail to leverage their ever-growing data assets. The first is the growing talent shortage of data scientists. The second is a lack of clear leadership. Without the second, even the best data teams will flounder.

Data science is an enabler of organizational success. However, it’s not enough. Organizations seeking to maximize the value of their data need more than analysts. They need a leader engaged with the executive team and charged with delivering value. Senior management often underutilizes analytics, especially when it’s scattered across the organization. Too often, analytics is siloed within departments. While individual departments may realize benefits, the executive typically lacks a champion to encourage cross-functional analytics.

An effective chief analytics officer (CAO) can mitigate these challenges. They have the experience to find, retain, and develop high-skilled knowledge workers. They have the vision to transform the organization. And, they have the trust of the leadership team to advise on how best to commercialize insight. However, their role is an emerging one. LinkedIn shows only a fraction of C-suite leaders carrying the title of chief analytics officer. Hiring a CAO is challenging: the right candidate must possess a complex blend of analytical, leadership and creative skills to be successful.

In this whitepaper, we examine the experiences organizations have had in appointing CAOs and how that has affected their perspective of data as a source of innovation and competitive advantage. We also offer some guidelines for hiring an effective CAO.


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Why Hire a Chief Analytics Officer In many ways, today’s businesses and not-for-profits have never been so data rich yet so insight poor. Big data is becoming normal data. However, despite this wealth of information, our proportion of insight to data keeps falling. We capture more than we can effectively analyze.

There is no point in collecting data for the sake of it. Nor is there a point in generating insight without the ability to act on it. Value comes from action, not reflection. Because of this, big data presents both a threat and an opportunity. To stay competitive with companies already commercializing their data, businesses must commit to joining the ranks of those harnessing big data. Doing so requires more than analysts. It requires a leader who blends business pragmatism with analytical knowledge, one who’s comfortable with changing the way an organization works. Companies interested in keeping up with the ever-accelerating growth of data and continually changing market need leadership. They need someone charged with analytical transformation. In whatever form they take, they need a chief analytics officer.

To stay competitive with companies already commercializing their data, businesses must commit

to joining the ranks of those harnessing big data.

Analytics is an old discipline. Historically others referred derisively to its practitioners as “quant jocks” or “data geeks”—analysts who often served as back-office professionals mining insights from databases in relative obscurity. Their responsibilities included data storage, data management, business intelligence, and statistical analysis.

Thanks to a variety of factors, their perceived value has increased dramatically since the financial downturn of 2008. In a world where every interaction creates a digital fingerprint, their ability to transform terabytes of data into useful insight is in high demand. However, data analysts are fundamentally enablers and not executors. To create value, they need direction and an organization committed to acting on the insight they can create. They need a leader responsible for making change happen.


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477

298

45,906

The sudden increase in demand for data scientists has already triggered some degree of labor market disruption. To get ahead of the crunch, many organizations have recruited talent without a clear idea of how best to leverage it. Having rushed headlong into the labor market, smarter organizations are now stepping back and putting a leader in place with the right skillset to create a high-functioning team out of their analytics talent and oversee their organization’s data and analysis requirements.

For organizations on this journey, the analytics imperative force two questions. First, what should a high-functioning analytics team look like? A team without the right leader is nothing more than a collection of individuals. Second, where should this team and its leader reside? Are they a support function to IT with dotted-line reporting to business units? Are they a standalone cost center? Do they operate as an option to the business, or do they have an organization-wide role to play, with its leader having executive-level management responsibilities?

In November 2013, only 298 LinkedIn members listed their current title as “Chief Analytics Officer.”

Two years ago, Merkle, a customer relationship management company located in Columbia, Md., created its first CAO position. When it announced the hiring of Andy Fisher, a former executive vice president of global data and analytics at the Starcom MediaVest Group, the press release stated the need to “drive overall business strategy for analytics.” Fisher explains that the company measures the CAO’s performance on traditional metrics: sales, innovation and marketing scorecards. But he also cites another advantage to the CAO position: human resources—recruiting and retaining experienced analytics staff. “There is a softer value creation such as increased retention of our data science team, and organizational assistance around our analytics capabilities,” says Fisher. “This is a very important role and we are continuing to build a team of senior people under our CAO.”

Most organizations have a long way to go in solving the challenges of creating an effective analytics team. In November 2013, only 298 LinkedIn members listed their current title as “Chief Analytics Officer”—compared to 148,608 who held the title of “Chief Financial Officer”.

LinkedIn members listing their current title as stated (15/Nov/2013)

148,608 Chief Financial Officer

Chief Information Officer

Chief Data Officer Chief

Analytics Officer

0 20,000 40,000 60,000 80,000 100,000 20,000 140,000 160,000


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These low numbers of self-described CAOs reflect the reality that these functions often are seen as the responsibility of a chief data officer (CDO) or chief information officer (CIO). However, this blending of roles runs the risk of obscuring the complexity of analytics. When it comes to CIOs, they already have a full load handling infrastructure, core systems, security and the demands of digital technology. CDOs have countless challenges in standardizing measures and ensuring effective data governance and quality processes. Adding CAO responsibilities to either of these roles rarely results in an effective analytics operation.

Wearing more than one hat sometimes works. In some cases, especially with CDOs, these professionals have already taken on a leadership role in managing corporate analytics strategy. Usama Fayyad, Ph.D., Chief Data Officer at Barclays Bank, oversees the analytics and insights departments among other teams. Formerly CAO at Yahoo!, he describes his current portfolio with a data focus. “The position was established to create the next generation of data systems and to make sure the bank derives value from its data assets, as well as to introduce control, governance and responsible use and management of data,” says Fayyad. “It is both a revenue driver and a cost reducer.”

Although the LinkedIn numbers would suggest that most organizations have yet to appoint a CAO, it’s not for a lack of need. Unlike a traditional CDO or a CIO, a C-suite analytics leader ensures information is more than just managed or governed. They provide the drive for commercialization through the use of analytics. The laser-like focus on value makes the CAO distinct to most CIOs or CDOs, and any organization hoping to capitalize on its data assets must recognize the distinction.


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When to Hire a Chief Analytics Officer There’s no common point when hiring a CAO makes the most sense. Every organization is different and faces different challenges. At a minimum, it needs a critical mass of employees and data to warrant an executive devoted to analytics. Beyond this though, the biggest factor is whether or not things are working as desired. The tipping point to hiring a CAO is often when organizations recognize that their default approach is no longer eff ective.

At Key Bank, a $90 billion financial services company based in Cleveland, the trigger was an institutionalized fragmented approach to analytics. “Historically, data was siloed,” says David Bonalle, Chief Insights Officer at Key Bank. “We had multiple analytics groups spread across the bank doing often inconsistent and redundant analytics and reporting.” But with the rise of big data, data analytics is becoming increasingly important to the success of an organization, and unlocking its full value can’t be achieved within silos or through piecemeal initiatives. A year ago, Key Bank created a Client Insights Center of Excellence to bring disparate analytics teams into a single, centralized analytics resource.

“If we want to be a $150 million-a-year organization, we need to move in the direction of hiring a CAO.

We can’t afford not to.”

The new arrangement resulted in significant efficiencies and a strong voice in the C-suite to ensure that the company continues its insights-driven approach, according to Bonalle. “We eliminated the organizational barriers to sharing data,” he says, “and began the migration to a single source of physical data access for the

entire bank.” The change quickly produced financial benefits. In the first year since launching the Client Insights Center of Excellence, analytics generated over $50 million in incremental value partly through identifying unprofitable branches for closure and by increasing the number of accounts by 71 percent.

Evolving from a decentralized to a centralized analytics approach is not without challenges. Duplicated capabilities can mean layoffs and redefined job responsibilities. “The downside is that little, siloed turfs are endangered, and that can cause some angst,” observes Pamela Bonifay Peele, the Chief Analytics Officer at UPMC Insurance Services, a $5 billion


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division of the UPMC Health Plan, which serves 1.8 million members in western Pennsylvania. And yet the value of improved efficiencies and cost savings can be worth the price. Since creating its CAO position in 2013, UPMC has seen a reduction in the number of analytics-based employees needed in the organization. “We have decreased both un-useful work and rework,” says Peele. “And we have refocused senior management from spending energy disputing reports to working on problems.” The quality of UPMC’s analytics approach and its conclusions keep senior managers from getting lost in the data weeds, she explains.

Determining when to appoint a CAO often comes down to a few key questions. Does the organization have enough data to help improve its understanding of customers, markets and processes? Can it effectively monetize its data assets? And, is the current approach adding value? At a large Canadian telecommunications company that currently lacks a CAO, the Vice President of Business Intelligence believes the position will be created only when executives can make a business case to justify it. “At some point when we want to derive value and monetize value with data, we’ll get a CAO,” he says. “Right now, managing big data is considered a cost center and an expense. It needs its own revenue stream. If data can become a money-generating opportunity, then it can justify the role of a C-suite chief analytics officer.”

Other organizations recognize their lack of a CAO position isn’t based on staff opposition or financial cost. At SickKids Foundation, the largest fundraising organization in Canada with annual revenues of $120 million, “it’s an issue of institutional will,” says Grant Stirling, Ph.D., Vice President of Major Gifts. During the last four years, the charity was focused on raising $400 million to build a 21-story pediatric research center, which just recently opened. “We’ve been pushing so far that we haven’t had the time or the mindshare to step back and address this issue,” says Stirling, who adds that the lack of a centralized analytics function has resulted in a cost. “Right now, there are all these little islands in each business unit, but they’re not connected by any bridge,” he continues. “And I think that’s a missed opportunity for us.”

This year, says Stirling, the charity plans to address the CAO issue like any other strategic decision—with a business case and estimated ROI for the position. “It’s clear to us that data analytics will be a significant revenue driver to our growth plan,” he says. “If we want to be a $150 million-a-year organization, we need to move in the direction of hiring a CAO. We can’t afford not to.”


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What to Look for in a Chief Analytics OfficerOngoing data growth and increasing reliance on analytics as a competitive differentiator requires a leader, one who can develop the right talent, create the ecosystem, offer a vision and champion the function throughout the organization. Blending data science and value architecture, CAOs hold a unique set of skills.

More than just managers, CAOs are champions for the need to generate value from data. CAOs often embody organizational change, challenging the way business problems are solved as well as who should be responsible for identifying new opportunities. More than senior data scientists, they must work across the executive ranks to make sure their insights are turned into repeatable action. And, more than IT managers, they must understand how to steer the company through the turbulent waters of big data and big analytics—the science and occasional art of finding actionable nuggets of insight within the data torrent.

While CAOs are measured by their ability to add tangible value to the business, they are also evaluated on their commitment to constant improvement and ability to operate with other C-suite executives. While not accountable for technology strategy, they must work closely with the CIO to ensure the organization has the right technology and data in place. While not responsible for executing their insights, they must work closely with the chief marketing officer, chief financial officer and other business stakeholders to ensure the organization gains operational value from their insights.


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Among the other qualities needed for an effective CAO:

• As a leader, a CAO needs analytical experience to relate to and mentor data scientists. Just as every CMO needs sales experience in some form, every CAO needs hands-on data science e xperience.

• As a champion for change, a CAO must bring hard-won battlefield experience to the C-suite. They should be veterans of multiple change efforts and understand how to take data science from a discipline to a process. They should view success in terms of economic return and commercialization, not in terms of novel invention.

• As a value architect, they should always focus on the outcome, not the insight. They need to influence, un-derstand the tangible value they enable, facilitate continuous improvement, and actively seek disruption where and when it makes sense.

• As a technologist, they should have a passion for cutting-edge technology. They need to stay abreast of the latest in analytics, riding the crest of the big data wave and always planning ahead. They should under-stand not only what’s needed today but how it will fit into the organization’s future technology landscape.

• And, as a negotiator, a CAO should wholeheartedly take on the daunting task of bringing the organization together. They need to bridge the gap between business and IT, and help both understand how best to realize value from data and analytics.

The biggest point of resistance against appointing a CAO to the C-suite is often the mistaken belief that a CAO and a chief data scientist are one and the same. Data science is a powerful discipline. However, just because it exists does not mean it deserves a seat at the executive table. A chief data scientist may be an excellent mentor, inventor and even an analytical genius. What they are rarely, however, is an instrument of organizational change.

There are two reasons to appoint a CAO. The first is to acknowledge the power of information in guiding cross-functional decisions. Left to their own devices, the vast majority of organizations regress into operational silos focused on functional ownership or organizational support. Information, however, cuts across every silo. The skills needed to analyze and act on this information are independent of any given silo. By focusing on leveraging and acting on information, organizations open up opportunities to be smarter, differentiate themselves from competitors and reduce costs.

While the rare CIO might have the technical and managerial capabilities to achieve cross-functional application of analytics, the disruptive potential of analytics points to the second reason for appointing a CAO: to provide analytical understanding grounded in the context of cultural transformation. Insight only produces one of two outcomes. It either confirms that which we already know or challenges that which we believe. In the case of the latter, what keeps us from acting on new knowledge isn’t technology or data. It’s culture and behavior.

What starts as a technology challenge quickly morphs into a cultural challenge. And it’s for this reason that the executive suite needs an individual specifically tasked with solving both. Left in too junior a role, an analytics leader is not empowered to transform the organization. Only by becoming a peer to those who define and embody the organization’s culture can a CAO truly succeed.


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Where to Find a Chief Analytics Officer The position requires a leader with both a technical and business background— no small challenge for an executive recruiter. “It’s a very difficult role to fill because it requires a person who is strong technically but who thoroughly understands business and business needs,” says Usama Fayyad, Chief Data Officer at Barclay’s Bank. Andy Fisher, the CAO at Merkle, has a bachelor’s degree in mathematics, a master’s in statistics and 15 years of relevant analytics experience with a focus on digital. “Digital analytics is an absolute must,” he says. “But a CAO also needs academic credentials and a substantial background in industry.”

Given the technical and managerial skillsets required, hiring a CAO can be difficult. Few academic programs offer the specific technical training combined with a cross-functional business management education. Quan-titative skills, grounding in business theory and exposure to real-life problem-solving—all are necessary if a CAO is to be able to support senior executives in framing the strategic questions that need answering. Even those who are trained in analytics tend to operate some distance from the cutting edge. A CAO must possess both deep technical smarts and business skills to focus on the biggest business imperative—and then deter-mine the innovate techniques to solve the problem.

When organizations looking for a CAO make the mistake of hiring a chief data scientist, they often find that they’ve added more capability to their organization than they know how to

leverage. Finding the right CAO requires considerable attention.

An effective CAO does not operate in a business-as-usual environment. They are motivated by transformation, not maintenance. When organizations looking for a CAO make the mistake of hiring a chief data scientist, they often find that they’ve added more capability to their organization than they know how to leverage. Finding the right CAO requires considerable attention.

Leadership is more than management. Without a leader, most analytics teams will fail to realize their full potential. Because analytics is a technical discipline, the people typically drawn to analytics focus on the trees rather than the forest. Their focus on the detail means they may not be aware of the bigger picture. They may not even be able to explain what they need. While they may be good at finding solutions to their immediate problems, they may not be as aware of the impact their insights will have on the operational side of their business. At worst, they may not even be able to communicate their findings so that meaningful action can be taken.

The best leaders have the ability to paint the art of the possible, sell the value of analytics and then own the process of execution. They’re focused on the result, not necessarily how to find the answer. Without the right leader, even the best analytics team amounts to undirected talent and unrealized potential. An effective leader hones and directs that talent towards using an organization’s data assets for competitive advantage and growth.


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The Need to Act Despite these guidelines, hiring the right chief analytics officer for your organization is not always an easy process—or an easy sell to colleagues. Some executives may resist bringing in a new leader when they feel the job may be better suited to the chief of marketing or technology. Others may consider analytics less necessary to decision-making than their own creative team’s intuition, traditional demographic information or simple product sales data.

But for those companies that recognize the importance of analytics and are ready to undertake an enterprise-wide initiative to hire a CAO, there’s little benefit in waiting. Big data isn’t about to go away, and the need to analyze vast quantities of information is only going to grow. With some social observers likening big data to a business revolution on the order of the Internet, organizations need to give serious consideration to the importance of including an analytics professional at the C-suite level who can leverage data’s rapidly emerging role in business. The business leaders interviewed for this paper cited different reasons for hiring a CAO. But SickKids executive Grant Stirling summed it up most succinctly on why an organization needs to hire a CAO: We can’t afford not to.

Lisa Schutz is the Founder and Managing Director of InFact Decisions, an Australia-based consulting firm that specializes in helping firms mobilize their data for strategic advantage.

Jan Kestle is the President and Founder of Environics Analytics, one of the premier marketing services and data analytics companies in North America.

Chami Akmeemana is the founder of Pinteral, an analytics company in North America. He is also the founder of Forrester Bradley a search company that specializes in Analytics and exec search. Chami is also on the advisory board of award winning Australian analytics consultancy Pulse Data Science and Melbourne Data science. He is the former MD and founder of Huntel Global an analytics search company that was acquired by Drake International. He also consults to clients: structuring analytics teams around a Chief Analytics Officer (CAO/CDO) subsequently training Analytic leaders and internal recruitment teams on recruitment strategies around Risk/Analytics/Digital setting up a CoE of talent management and assisting/advising Data driven start-up ventures on developing and growing outside the country of origin.

Graduating from Staffordshire University in 2000, Chami was offered to read for a Ph.D. in Bioceramic Engineering on scholarship at Queen Mary, University of London. He decided to forgo an academic career in favor of Law Enforcement and in 2002, he joined London’s Metropolitan Police.

Moving to Australia in 2006, Chami explored his entrepreneurial side and opened his first business – a Mobile Coffee Van in Sydney. He later also founded a Healthcare Recruitment company and became business partner in a clothing brand. All three ventures were later sold.

LISA SCHUTZ

CHAMI AKMEEMANA

Evan Stubbs is the Chief Analytics Officer for SAS Australia, a Board Member of the Institute of Analytics Professionals of Australia, an Adjunct Research Associate at the University of South Australia, an editor for the International Journal of Data Science, and on the advisory board for Melbourne Business School’s Centre for Business Analytics. He’s a global expert in his field and the author of The Value of Business Analytics, Delivering Business Analytics: Practical Guidelines for Best Practice, and Big Data, Big Innovation. He is currently working on his fourth book, Building an Analytics Lab. As a practitioner, he has helped five of Australia’s best-known large global brands as well as both the Australian and New Zealand governments get the most out of their analytical and big data investments. Globally, he advises and works with leadership teams across New Zealand, Singapore, Malaysia, the Philippines, Canada, and the United States.

Jan Kestle is the President and Founder of Environics Analytics, one of the premier marketing services and data analytics companies in North America.

EVAN STUBBS

JAN KESTLE

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