Use people analytics to improve leadership development.
It seems that no matter what industry you are in, big data is a buzz phrase that makes people sit up and pay attention—sometimes with avid interest, sometimes with uncertainty as to what it really means and how it can be used. The talent development profession is no different. And while our industry may be lagging behind many other fields, accessing and fully utilizing HR and learning and development data for leadership development will be critical to organizational success in the years to come.
To be successful, talent development practitioners will need to cut across silos and tap into the talent of analytics teams—HR, IT, finance, marketing, and so forth—so that we are able to help leaders and, hence, our workplaces as a whole.
But how and why? And where do we start?
What is big data?
Big data means different things to different people. There are those who say that HR doesn't, at least in most cases, have big data. Some of them will say that what HR does have is big data systems or big data methodologies.
So, while HR big data may be, well, for lack of a better word, "smaller" than big data measured in terabytes, in the context of talent development and leadership development in particular, we're usually talking about three Vs—that is, volume, velocity, and variety of information—according to Evan Sinar, chief scientist and vice president of DDI's Center for Analytics and Behavioral Research.
More specifically, as Mary B. Young, principal researcher for HR at the Conference Board, explains, we're looking at data that is beyond the structured, static data housed in the HR information system of days of yore—data such as employee hire date, marital status, and the like. We're now talking about a constant stream of real-time data—such as what's captured via internal social media and exhibited behavior—that "companies are beginning to use for even more analytics to better understand their workforce, to understand their leaders." Some of that data will come via more open-ended comments, feedback, and survey or polling responses, as well as from new learning mechanisms that include diagnostic tools.
Organizations now have a vast number of new sources of employee data and much better analytic tools, continues Young, which will enable them to find things that are going to turn out to be really important.
In addition to the three Vs already mentioned, a Center for Creative Leadership (CCL) blog post, "The Future of Assessment #7: Big Data & Analytics," adds a fourth: veracity. You have to be able to trust the data as being factual.
Why are we talking about it?
While summarizing its 2017 Global Human Capital Trends report, Deloitte notes, "Formerly a technical discipline owned by data specialists, people analytics is now a business discipline, supporting everything from operations and management to talent acquisition and financial performance."
Stephen Young, senior research scientist with CCL, outlines four main benefits around the why of big data for leadership development. The first is that administering new types of assessments can now be done at a much lower cost, in large part because machines are doing much of the analysis and time-consuming work. Because of the lower cost, more individuals (not just those with the formal management title) will be able to undergo assessments and, in so doing, find out their strengths, shortcomings, and where their efforts might be best spent.
Even with the positive involvement of machines, the human element is not taken out of the assessment process. Machines can, for instance, enhance and complement the 360-degree performance assessment, giving leaders a developmental edge. For example, if a leader is given a dozen or so skills to practice and grow from a 360-degree assessment, perhaps there will be two or three skills that show up across a variety of sources that a leader might then work on.
Through the use of big data, talent development practitioners also can get a better sense of the whole leader by capturing more objective data. As Stephen Young explains, leaders gain a clearer understanding of why they think, feel, and act the way they do across situations and with certain people. That will help them reduce their blind spots.
Big data can capture the virtual persona and physiological profile of a leader and connect them to actions of leader effectiveness. For example, how are the best leaders seen on social media? What might be causing them to be derailed? We know that aspects of the inner self—such as resiliency—affect a leader's behavior. By measuring those hidden characteristics, we can create enhanced developmental experiences that will make a greater difference to individual leaders and their organizations.
Finally, Stephen Young concludes that leaders will have information at their fingertips without spending a great deal digesting what assessments and reports mean—again, because machines will have done some of the sense-making step for them. That will free up leaders' time to spend with their coaches to do what humans are good at, such as jointly deciding the best goal or experience to pursue, based on where a leader is in her life stage or what matters most to her.
What does this all look like in practice in terms of technology and tools? One example Mary B. Young cites is the use of an electronic sensing badge, which can track the workplace-interaction patterns of employees who opt into this form of data collection. While the employer never sees any individual-level data, a third-party supplier, Humanyze, integrates the data with additional information about the employee's role, performance, and demographics to provide the company with new insights about what high-performing sales managers, for example, do differently from their peers. The real-time data point to specific learning and development needs and can track behavioral changes over time. Individual employees may request confidential feedback and coaching based on the data.
Other sources of data that could be tapped include those from wearables, email and calendar information, customer reviews, email analysis, learner data, virtual simulation, leaders' collaborative interactions, pulse feedback data, video and voice, and social media.
"Draw on that data," recommends Sinar, "to create a better and more effective learning experience for leaders, which will cascade down to their employees as well."
Further, because of lowered costs and increased availability of data and tools, organizations will be able to take a broader view of their talent, emphasizes Sinar, akin to the uses for leadership development that Stephen Young mentions. The "days of having small, exclusive, â€˜high potentials' are no longer," Sinar says. "The definition of potential is much broader."
What should we be concerned about?
The use of data today—both personally and professionally—can cause angst and raise ethical and legal questions, but it also can make our lives much easier, saving us time and effort. Consider the personalized recommendations from our time online, which help us find that perfect lamp or suggest an intriguing article for us to read. The use of that information in the work environment raises ethical and legal questions, such as using electronic tracking systems for employees or whether we can use specific information that has crossed country barriers.
Further, employers have the power to reward or punish employees (including leaders) based on data, notes Mary B. Young. Regulations also prevent discrimination and other adverse impacts resulting from collected information.
Given that, there are—rightfully—concerns about trust that HR and talent development teams must tend to before both leaders and employees readily embrace the use of big data for growth and development opportunities. Privacy concerns are of utmost importance.
As with new modalities in learning and new technological gadgets, you shouldn't rush out and sign up just because it's available. As Stephen Young explains, "You should use new technology as appropriate. If we carefully think about what we're trying to do in leadership development with assessment, which at the core is to increase self-awareness through the provision of feedback, then we can thoughtfully consider whether or not a new tool is going to give leaders new insights about themselves above and beyond what we're currently doing." He continues, "If we ignore new innovations in technology, we might be depriving our leaders from giving them the insights they need to show up at work and lead their teams more effectively."
Knocking down silos
Big data, if used correctly, can assist the individual leader in her own development as well as improve the leader's ability to demonstrate her vision for her team. Using big data effectively requires talent development professionals to break down silos and work with other divisions to secure the data and figure out how to use it. And while the era of big data is likely to require new skills of the talent development practitioner, that individual—or even his team—is not likely to have all of the skills required for this new reality.
In the webcast "From Optimism to Impact: Getting Results With Talent Analytics," Intel's Alexis Fink explains that, to use data, you need expertise in four areas: content, data, analytics, and influencing. That expertise will not come from one person.
Working across departmental borders may include collaborating with IT, which will be storing the data and ensuring that it is secure, and the legal team, which can help identify whether a talent development practitioner can legally comply with a request for data or analysis.
As with using big data more broadly, Intel, in its 2015 whitepaper From Data to Action: The Intel Guide to Analytics, reports that "The amount of data you collect doesn't matter, if your organization doesn't have the skill—and the will—to use it." And while you need data scientists to use data, you need much more: "A culture driven by data has to extend beyond a specialized group [of] employees trained in analytics. It involves the decision-making style of the whole organization, in every function and line of business."
The future reality
As mentioned earlier, HR practitioners tend to lag in the area of data. "HR's own proficiency in using data to tell a story, visualize, to apply data—those are areas that HR has historically struggled. HR has a strong people orientation, but increasingly we see that there's also got to be a strong data orientation," says Sinar. "There's a foundational gap there."
Large organizations, not surprisingly, are ahead of others in making use of big data, but it'll be the reality for everyone in the future, notes Mary B. Young. And Sinar explains that already it is the organizations that use data that see increased quality of leadership, as well as an ability to build a pipeline for future leaders, and that are growing more quickly. So, organizations are going to need to tap its capabilities or risk ceasing to exist.
In terms of required skills and knowledge to efficiently use big data, David Scully suggests in his CoreHR blog post, "The HR Analytics Skills Shortage: What Can HR Do To Improve," that HR professionals become trained in analytical skills and learn how to communicate effectively about data-driven analysis. Deloitte's trends report offers some guidance on how organizations can begin to look to the future with people analytics, emphasizing that organizations of the future understand that "analytics is multidisciplinary."
And it is up to talent development professionals to tap these capabilities. "Leadership development practitioners, with a background in people and with a code of ethics, are in a great position to take this technology and implement it effectively where the potential benefits of the technology are realized with little or no negative impact on people," Stephen Young offers. "For example, leaders must consent to having their big data analyzed—and have some â€˜understanding' of how the data is being used, and why."
Best Practices for Using Big Data
As with launching most other initiatives, starting small with big data is a wise move, says Evan Sinar, chief scientist and vice president of DDI’s Center for Analytics and Behavioral Research. “Secure some early wins, and you’ll build confidence in the team and build recognition from other teams.”
In terms of breaking down departmental silos, he suggests, for example, that HR professionals learn to speak the language of finance, something that historically has not been their strong suit. The marketing department, too, can become the talent development function’s close friend because marketing professionals tend to be master storytellers—not only in telling the story, but also selling the story. “Data in and of itself means nothing” without the story, Sinar notes.
Mary B. Young, principal researcher for HR at the Conference Board, suggests that talent development practitioners ask themselves questions to the effect of: What are our priorities? What’s most useful to know? Where will we get the most return from our development dollar, in terms of business impact? Answering those questions will head the talent development team in the right direction and will give it new ways to add value to the organization.
In her ATD blog post, “5 Ways to Select a High-Value Predictive Workforce Project,” Greta Roberts recommends that you identify a business problem to solve before going anywhere: “Crunching data without a specific objective is a very expensive, and typically a very unproductive, use of your company’s time and money.”
Finally, it’s important to remember that big data is another tool in the toolbox. At the end of the day, surmises Stephen Young, senior research scientist with the Center for Creative Leadership, data in any society can be used for good or bad. What is required is a thoughtful approach.