Can We Predict Great Leadership?

The nature of leadership has always been considered a bit of a mystery. But, for some of today’s most progressive enterprises, the mystery is worth solving. And predictive analytics is helping crack the code.

Like many business functions, the HR discipline is being revolutionized by new technologies and sophisticated analytics that allow data-informed decisions to be made faster and easier than ever before. While many enterprises are still looking backwards with their analytics, some are beginning to explore the promising field of predictive analytics and are finding new insights that challenge some long-held beliefs about HR and talent management practices. Increasingly, organizations are leveraging data to make predictions about which employees are at risk of leaving the organization or which candidates will be future top performers. Less common are the organizations that are using predictive technology to gauge their most important investment—their leaders. 

Most companies have libraries of online learning and training materials on how to be a better leader. And while they also have piles of data that allow them to measure how well they are doing with sales, productivity, customer satisfaction and employee engagement, few are bringing the two sets of information together. The truth is, organizations often lack a solid understanding of the true impact of their professional development or how to tie leadership behaviors to performance outcomes and business results.

So how do organizations predict who will be their next leaders? And how do the behaviors and skills they identify as characteristic of leaders translate to specific business outcomes such as increased sales, productivity, employee satisfaction or retention?  

These are the questions some forward-thinking organizations are beginning to answer. A Silicon Valley technology hardware company, for example, was suffering from a rising turnover rate among high-performing employees who had been with the firm less than a year—a phenomenon that was creating financial strain on the business in a hyper-competitive hiring environment. In an effort to quantify which aspects of employees’ jobs contributed to a high or low engagement, the company began conducting a series of one- to two-question pulse surveys each week. Then it put the survey data through a predictive analytics tool to identify which parts of the employees’ jobs correlated most strongly with high performance and retention. Using the regression analysis, the company identified three areas as strong predictors of success:

1. Length of career;
2. Degree of autonomy at work;
3. Opportunities for advancement.

The company then used this information to create a new strategy for recruiting, developing and retaining high-performing employees. The strategy put into action the findings from the analysis by:

• Focusing recruiting efforts on candidates with a specific level of experience;
• Providing opportunities for more autonomous work;
• Increasing training opportunities 

Results of the initiative were dramatic. Turnover among high-performing employees decreased by 15 percent in the first year.

While the use of analytics to steer recruitment and retention is taking off in a variety of industries, applying predictive analytics to leadership development is less common, and, to date, there have been more failures than successes. In large part, it comes down to the fact that companies struggle to define the characteristics or behaviors that make an effective leader. A.D. Detrick, a learning analytics expert and president of MetriVerse Learning Solutions, says, “Until the characteristics of a great leader are well defined, it is hard to measure and predict them. Instead, you have hundreds of pockets of data—much of which is unusable, unable to be isolated from a predictive standpoint and not correlated to the kind of metrics that actually move the business.”   

But one company Detrick works with is proving it can be done. A leading technology and social media company decided to use predictive analytics to measure the impact of its leadership and teamwork training with the goal of improving employee satisfaction and increasing retention among high-performing employees. The company began by asking senior leadership to define the specific and measurable leadership behaviors desired by the organization. With these definitions in hand, the company could then begin gathering reliable data about what learning was occurring in relation to the desired leadership qualities, what leadership behaviors had changed as a result of the training and how the business was being impacted.

Through regression analysis, the company was able to determine which behaviors would most likely predict a high level of satisfaction and retention for key employees and which learning activities would most likely result in behaviors that reflected desired leadership qualities. Linking learning interventions to business metrics meant the organization could make some fundamental shifts in its leadership training strategy. Today, the company finds:

• Employees who work for leaders that completed the leadership training and exhibit the desired leadership behaviors have higher satisfaction scores;
• High-performing employees who work for leaders that completed training and exhibited the desired leadership behaviors have higher retention scores;
• HR can save significant cost by discontinuing the leadership offerings that do not directly support the defined leadership behaviors.

Organizational leaders are under increasing pressure to demonstrate real return on investment on their leadership development initiatives, and—as more and more companies work to align data and metrics from their leadership initiatives to their business objectives—we’ll see more successful examples. In the learning and development market, ISG has observed that a number of Learning Management Systems (LMS) and learning outsourcing providers are building proprietary solutions or acquiring analytics products to provide this capability.  

To date, enterprises have used a combination of major LMS providers, learning record stores and small, customized learning solutions. While some early adopters have invested in analytics, tracked thousands of data points and found no actionable correlation, others have begun to discover great insights as they get savvier about how they distribute and track learning and performance information.

To create a successful predictive analytics strategy, start here:

1. Identify the business goals and corresponding performance objectives. Pick two or three key objectives.
2. Define the desired behaviors of leaders. Be specific about the behaviors your company needs in its leaders. Ensure these behaviors align with the unique culture of your organization.
3. Gather data on the activities that will isolate and develop the factors that demonstrate a strong correlation to leadership success. Determine the data and measurements you will need from the outset. Find a skilled data analyst if you do not have that capability internally.
4. Focus your leadership development so it has the greatest impact. Once you have correlated the data with your business metrics and isolated the effect of learning on your desired leadership behaviors, use the results to refine your approach. This may include revising the curriculum, putting all leaders through key courses, eliminating other learning activities that do not drive results or proactively assigning coaches in targeted areas.

As progressive HR organizations and leading-edge providers increasingly rely on predictive analytics to analyze the correlation between leadership behavior and business outcomes, they just may finally answer the age-old question about what makes a good leader. And, for those that do, the reward surely will be great.

About the author

Stacey is a director and a key contributor to ISG’s human resources and talent-related technology and services. She advises clients on all aspects of human resources engagements, including recruitment process outsourcing and talent management. Stacey is a prolific blogger, and is frequently interviewed by industry publications. With nearly 20 years of experience in solutions strategy, product development, corporate HR, operations delivery, transitions and HR consulting, Stacey has deep operational knowledge of the talent space and her clients’ challenges, as well as a unique ability to ask the right questions to help organizations align their sourcing initiatives with their vision.