It is not a surprise that companies spend an enormous amount of time and money on leadership development. In 2018 alone, organizations around the globe spent over $34 Billion on leadership development efforts. Companies understand that developing their leaders is important for success, but what is equally important is which skills or competencies to develop. Organizations often rely on commonly known traits or a range of off-the-shelf models and frameworks to assist in determining the skills or competencies to develop. Since not all leader skills or competencies are equal in their value to any given organization, this article will highlight the value of taking an organization-specific, data-driven approach to identifying and developing leader behaviors for maximum impact.
Leader Behavior – Employee Engagement Link
Developing leaders is important for many reasons, but one particular reason that comes to mind relates to enhancing employee engagement. During my early days with a survey consulting firm, I was intrigued by how consistently leadership surfaced as one of the factors impacting engagement. When you think about it, however, it makes perfect sense given that leaders often exert a good deal of influence over a wide range of factors – from pay, work conditions (e.g., safety, work/life balance) to performance appraisal, resources, recognition, and communication; factors that ultimately impact how employees feel about their job, team, and their organization. Simply put, leaders vary in the behaviors they exhibit and those differences matter a lot in shaping employees’ attitudes and specifically, their engagement to the organization.
One might wonder, “Why link employee engagement to leader behavior?” There is a logical reason why so many organizations are concerned about the degree to which their employees are engaged; it is because of the impact of engagement to business outcome.
Employee Engagement – Business Outcome Link
An engaged employee is one who, in performing their work duties, is fully committed or present as shown by their thoughts, emotions, and behaviors3. Given this, a workforce consisting of highly engaged employees should fare far better than one consisting of disengaged employees. There is ample evidence to support this hypothesis. Higher levels of engagement have been linked to greater productivity, lower turnover, increased motivation, and positive work-related attitudes, among others1,2,4. Caterpillar, one of the largest construction-equipment manufacturers in the world was able to reduce attrition, absenteeism, and overtime in their European plant, resulting in an annual savings of $8.8 million5. The same report touted that highly engaged employees at Molson Coors (the world’s largest brewer by volume) were five times less likely than less engaged employees to experience a safety-related incident and seven times less likely to experience a lost-time safety incident. By strengthening its workforce engagement, Molson Coors saved $1.7 million in a 12-month period.
The above examples highlight – at least in part – why organizations care about employee engagement.
Since what leaders do or do not do matter when it comes to engagement, and there is an established link between engagement and desirable business outcomes, companies might consider relying on leader and engagement data to determine the skills or competencies to develop in their leaders. The answer to how to do precisely that can be found by following the three steps outlined below.
Leveraging data to pinpoint leader development needs: 3 steps
Step 1. Gather data about your leaders
There are two key considerations when it comes to gathering leader data in preparation for quantitative analysis –types of behaviors and number of leaders.
What types of behaviors are your leaders demonstrating or not demonstrating? This sort of data can come from one or more assessments you may already be deploying in your organization, such as 360 assessments, or assessments around personality, values, or leadership potential or style. While different assessments capture different aspects of a leader, what is important is that the data help to glean or infer behaviors that can be observed by others (thus impact them) in a wide variety of contexts and settings. Ideally, the chosen assessment data would not be so narrow that it only assesses preferences or styles (e.g., behaviors related only to interpersonal interactions or conflict) that exclude behaviors in other contexts.
Since the statistical methods used to link leader behaviors with engagement are designed to detect patterns of relationships, it helps to gather data on enough leaders so that you can be confident of the results. This means that having data on five leaders would not be enough to provide the level of confidence you want. Data on 80 or more leaders, on the other hand, can be sufficient in most cases. If your organization is large (e.g., >10,000), you may consider grouping leaders into meaningful levels (e.g., frontline managers vs. mid-level) for added precision.
Once you have a sufficient amount of assessment data on your leaders, the next step is to gather and organize your employee engagement data.
Step 2. Gather and organize your employee engagement data
If your organization conducts regular employee engagement surveys, you should already have the data necessary for this second step. Most employee engagement surveys contain roughly eight to fifteen topics (each captured by two to three questions) – i.e., topics mentioned previously such as Work-life Balance, Senior Management, Recognition, etc. In addition to these topics, your survey is likely to contain an index of some sort. Employee Engagement Index is a set of questions, that as a collective, represent or capture the concept of engagement (e.g., Satisfaction, Engagement, or Health). Keep in mind that the definition of “engagement” varies greatly as do the questions used to capture the concept. Regardless of how it is defined or measured, the Employee Engagement Index is what you will want to focus on in the next step.
Step 3. Link leader data with your engagement data
The goal for this last step is to link leader data with employee engagement data. By “link,” I mean statistically tie your leader data with employee engagement data. You might ask, “How do I do that?” Let’s say that one of your frontline managers is Cindy Smith, and she has eight direct reports. As shown in Figure 1 below, once you have Cindy’s scores on each of the behaviors or dimensions (Columns E-H) from her XYZ leader assessment, you can average Cindy’s eight direct reports’ Employee Engagement Index scores and associate that single average with Cindy’s leader assessment score (Column I). Then, repeat this for the remaining leaders. You are now ready to see which leader behaviors are most predictive of your employees’ engagement – i.e., those leader behaviors that matter for your organization.
Figure 1
In terms of the analysis, there are many options – just about all of them involve correlational analysis of some sort. Multiple regression is one common approach by which multiple variables (e.g., leader behaviors) are used to predict some outcome (in our case, employee engagement). If you are not comfortable or are unfamiliar with this type of analysis, you may consider involving others in your organization (e.g., in-house statistician, people analytics function, Center of Excellence, etc.). Depending on your organization’s resources and the level of precision your organization is trying to achieve, more sophisticated approaches associated with higher levels of precision are available, such as Structural Equation and Latent Growth Curve Models.
Statistically linking leader data with engagement data is generally superior to non-data-driven methods for several reasons: First, by pinpointing and developing the skills that matter most, you are able to focus your investment dollars to maximize ROI. Second, by examining your own data, you will gain a better understanding of your people (both leaders and employees) enabling a far more nuanced approach to workforce development. Finally, by gathering and maintaining data on both your leaders and employees, you are setting the foundation for subsequent analyses beyond the first year to powerfully demonstrate ROI of your leadership development investments.
An organization can take the data driven analysis one step further by linking leader data with engagement data and other business outcome data. Depending on your organization’s size and availability of data, such outcomes as productivity (by group), sales (by team), Year over Year (YoY) growth, etc. can all be predicted using a combination of leader and engagement data. Imagine being able to demonstrate through data that leader behaviors C, F, and G combined account for 15% of the changes in employee engagement; and that a 4% improvement in the latter accounts for a 7% increase in team-level sales.
CCL began such an analysis with a nonprofit healthcare organization and found seven competencies among 20 to predict their employee engagement. The client organization is currently focused on developing those seven competencies and once all leaders have completed their development, we will follow-up with an impact study to examine what difference the program has had on the organization.
Conclusion
Given the critical role that leadership plays in impacting company performance and the billions of dollars invested in developing leaders, increasing the predictive power and precision by embracing the power of data and analytics is a valuable and inexpensive tool that organizations can use to their advantage. Rather than relying on what “appears” to be the right set of skills, organizations can benefit by leveraging data to truly know what the right skills are. By focusing their development efforts on those right skills, they can maximize the likelihood of getting real results and ultimately showcasing the return on their leadership development investments.
References
- Harter, J., Schmidt, F., Asplund, J., Killham, E., & Agrawal, S. (2010). Causal Impact of Employee Work Perceptions on the Bottom Line of Organizations. Perspectives on Psychological Science, 5, 4, 378-389. https://doi.org/10.1177/1745691610374589
- Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: a meta-analysis. The Journal of Applied Psychology, 87, 2, 268-79. https://doi.org/10.1037/0021-9010.87.2.268
- Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33, 4, 692-724. http://dx.doi.org/10.2307/256287
- Macey, W. H., & Schneider, B. (2008). The Meaning of Employee Engagement. Industrial and Organizational Psychology, 1, 1, 3-30. https://doi.org/10.1111/j.1754-9434.2007.0002.x
- Society for Human Resource Management (2014). Employee engagement: Your competitive advantage. Alexandria, VA: Society for Human Resource Management.
