12. Engaging Analytical Talent

Jeanne G. Harris and Elizabeth Craig

If your company is like a growing number of others, it’s turning to analytics in search of a competitive edge. Your success with analytics hinges on your ability to effectively understand and engage analytical talent—employees who use statistics, rigorous quantitative and qualitative analysis, and information-modeling techniques to shape and make business decisions. First, of course, it’s important to understand the different types of analysts and how common each is in the company.

Four Breeds of Analytical Talent

Drawing on our research with Tom Davenport and Bob Morison in Competing on Analytics and Analytics at Work, as well as our experience with dozens of analytically oriented companies across a broad range of industries, we’ve identified four types of analytical talent. Successful analytical organizations depend on these types of talent to achieve and sustain a competitive edge:

• Sponsors are senior executives who lead business initiatives and depend on data and analysis as core inputs into business decisions.

• Scientists (sometimes called data scientists) are the chief architects of analytical applications, developing statistical models and algorithms used by others in the organization for a range of business-related analyses. They also employ advanced data visualization capabilities to represent and interpret big data sets.

• Experts quantitatively oriented professionals with advanced functional and industry expertise. They are responsible for running analyses and applying analytics to solve complex business problems.

• Users are employees from any level of the organization who combine basic data analysis with business insights to use analytical insights in their work.

These types are illustrated in Figure 12.1, where the percentages represent the proportions of different types of analytical talent in a typical organization.

Figure 12.1. Types of analysts.

Sponsors are important. They provide the leadership, direction, and impetus required to execute analytical strategies. They’re few and far between. Users are also important. They rely on data and analytics to perform their everyday jobs. But it’s the Scientists and Experts who constitute the lifeblood of your analytical organization: They create and use complex analytical applications to benefit the business, and they possess rare, valuable, and specialized skills.

Engaging Analysts

Even if you have all of these different types of analysts, chances are you don’t really know how to make sure analysts are energized by, enthusiastic about, and engrossed in their work. In other words, how do you keep these scarce and valuable workers engaged so that they help your company succeed?

The business literature is rife with studies on how to engage employees, but analysts are different from other workers. They have distinct backgrounds, skills, attitudes, and motivations. Established practices for engaging employees—such as providing meaningful work and career opportunities—matter to analysts too. But you must also attend to analysts’ unique needs. If you fail to do so, analysts may not invest their full physical, mental, and emotional energies into their work.

To help your organization avoid this mistake, it’s critical to understand the unique factors that influence analysts’ engagement. To discern these factors, we interviewed dozens of executives and surveyed 1,367 employees to better understand what matters to analysts. We examined more than 30 factors believed to affect employee engagement, including company culture, leadership, organizational systems, management practices, career opportunities, and coworker relationships.

The good news is that analysts are significantly more engaged at work than other types of employees. Overall, 57% of analysts reported being moderately or highly engaged, compared with 45% of other employees. But there’s bad news, too: Nearly one in four analysts simply go through the motions. They show up for work each day, but they don’t give their all. And another 20% of our respondents were completely disengaged. For companies that rely on data-driven insights, those stats should be alarming.

Like all employees, analysts are most engaged by work that allows them to apply their skills and talents, gain valuable experience, and contribute to the organization’s overall goals. However, several things are uniquely important to analysts. They need to understand the wider business as well as analytics, they need to know exactly what is expected of them, and they need to have opportunities keep their technical skills and expertise up to date. Human Resources has a vital role to play in tailoring practices to analysts’ unique engagement needs.

Arm Analysts with Critical Information About the Business

As analytics become more integral to a company’s strategy, analysts need the business knowledge and skills to enable them to understand the strategic issues facing the company and how analytics can be used to drive business value. Not only does insight into the business make analysts more effective, but it also boosts their engagement. In fact, it’s one of the strongest predictors of analyst engagement. In our research, analysts who understand their company’s strategy, goals, capabilities, and operations were three times more likely to be highly engaged than analysts who don’t have a firm grasp of the business. Moreover, analysts who understand how their work relates to their organization’s goals and contributes to its success were nearly six times more likely to be highly engaged than those who don’t.

The best managers expose analysts to a range of business units and functions so that they learn about the company’s main business challenges and work processes. Leaders at one global financial services company we studied stressed the need for analysts to understand the business so that they can identify opportunities for analytics to have an impact on the organization’s results. Managers give analysts the tools and templates they need to capture business strategy, define problems, and devise solutions. This helps analysts communicate effectively with business leaders, because they can explain how their work creates value for the firm.

Colin Sheppard, formerly Virgin Media’s Director of Knowledge and Insight, says that Virgin trains its analysts to think like clients. He finds that not only are the best analysts technically outstanding, but they also understand the consumer’s key motivations and are focused on commercial objectives. Analysts who can confidently communicate their findings (for example, which customers are most likely to buy a new product or service) in terms important to senior executives were six times more likely to be highly engaged. They’re also more likely to persuade management to act on their recommendations.

Define Roles and Expectations

It’s frustrating when you don’t know what you’re supposed to do. Engagement suffers in the absence of clear goals and expectations—and this is especially true for analytical talent. Research has shown that, as a group, people with a strong quantitative orientation tend to be less tolerant of uncertainty and think in a more linear fashion. That’s why they are so good at what they do: They can turn raw data into clear insights by creating models and applications that make sense of it. That penchant for order leads analysts to prefer structured and predictable work environments. In our study, analysts who said they are clear about their roles were six times more likely to be highly engaged. The flip side? Analysts with ambiguous roles were nine times more likely to be disengaged.

At Google, employees know what’s expected of them. Roles are highly structured according to a 70/20/10 model. Employees spend 70% of their time fulfilling basic job requirements, 20% on projects that help them develop technical skills and benefit the company, and 10% on product and business innovations. Although aspects of the role are open-ended, overall expectations, job requirements, and performance metrics are clearly defined.

Role clarity is particularly important for engaging the most quantitative-minded analysts. Analytical scientists are much more likely to be engaged when they have a clear understanding of their responsibilities, objectives, and authority. Three out of four analytical scientists we surveyed who know what’s expected of them were highly engaged, compared with just one in ten who lack such clarity.

Clear does not mean rote, however. Analysts place a premium on interesting and challenging work. They want to work with a variety of datasets and types of analyses. One grocery retailer could not effectively retain employees assigned to perform an essential but repetitive analysis. The company could attract highly skilled MBAs to the job, but it could not keep them for long. The analysts quickly became restless and sought new challenges. Variety in their work keeps analysts engaged.

Feed Analysts’ Love of New Techniques, Tools, and Technologies

Analytical work requires specialized skills, and skill requirements change rapidly as new analytical tools and techniques emerge. Opportunities to keep their technical skills up to date are vital to keeping analysts engaged. This is especially true for analytical scientists. Scientists who said they can keep up with the latest analytic models, tools, and technologies in their field were 26 times more likely to be highly engaged than those who cannot.

Consider the statisticians at AT&T Labs. The mandate of this analytical talent is “to develop new methodologies to deal with large-scale data problems—the type of problems generated by the massive stores of data AT&T collects to run its business,” says Chris Volinsky, director of the Statistics Research Department. To do this, it’s essential that they keep up with the latest advances in statistical theory and methodology. One way these analytical scientists do so is by pursuing problems across the business and beyond. A few years ago, the group took on a challenge posed by Netflix, the online DVD-rental company, and won. Netflix offered a top prize of $1 million to anyone who could improve—by at least 10%—the accuracy of Cinematch, its movie recommendation algorithm.

Volinsky and an AT&T Labs colleague teamed up with five others from outside the organization to win the competition—three years after it began. “When we started working on it,” Volinsky says, “it wasn’t obvious what the tie-in was to AT&T.” But the company supported their participation anyway. And in the end, AT&T was also a winner: “The algorithms that we developed for the Netflix prize have benefited our research here,” says Volinsky.

He adds, “That freedom to start working on it in the first place was a function of the culture that we have here.” That culture allows AT&T to make sure its top quant talent is constantly expanding their technical expertise—and to engage and retain world-class analytical talent.

Employ More Centralized Analytical Organization Structures

The survey data suggest that if you care about having your analysts engaged with their jobs and hope they remain in your employ, the two most successful organizational models in that regard are the center of excellence (CoE) (29% engaged, 41% likely to stay) and centralized (35% engaged, 33% likely to stay) models (see Chapter 11 for descriptions of these). The percentages for the more decentralized models are clearly worse on both measures. The decentralized model had only 18% of analysts engaged and 27% likely to stay.

We found that analysts in centralized units and centers of excellence are most engaged and most likely to stay because they enjoy the most meaningful career opportunities. Three key factors influence the quality of analysts’ work and career opportunities and, in turn, drive engagement and retention (see Figure 12.2):

• Analysts’ work is aligned with the organization’s strategy and goals and affects its success (they are engaged in significant work for the company).

• Analysts understand the dynamics of the industry and business model (business insight).

• Analysts’ skills and aspirations are a good match with the company’s culture and goals (organizational fit).

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Figure 12.2. Factors that influence the quality of analysts’ work and job opportunities.

Lacking the opportunity to make a real impact on the organization’s success, analysts won’t find enough meaning in their work, so they will be less engaged and less likely to stay. Perhaps the biggest demotivator for analytical scientists is spending too much time on simple analyses and report generation instead of building and refining analytical models. We know of several organizations that have lost analysts who felt they were treated largely as “spreadsheet developers.” It’s essential to give your best analysts opportunities to apply their expertise to the company’s biggest problems.

Unfortunately, even the best organizational models are somewhat low in engagement and intent to stay. These analysts are incredibly valuable to any company pursuing a data- and analysis-based strategy. Companies need to find ways to make their analyst jobs more fulfilling if they hope to retain their most valuable analysts.

When employers keep analytical talent engaged, everyone wins. Analysts relish their work, and their companies build analytical capabilities and bolster their long-term competitiveness. By honing their awareness of analysts’ distinct engagement needs, human resources leaders, executives, and managers can help lay the foundation for a fully engaged analytical workforce.