A Data-Driven Approach to Identifying Future Leaders

Rather than just relying on the subjective opinions of executives, some companies are using assessment tools to identify high-potential talent.

Reading Time: 9 min 

Topics

Frontiers

An MIT SMR initiative exploring how technology is reshaping the practice of management.
See All Articles in This Section
Buy
Already a member?
Not a member?
Sign up today
Member
Free

5 Free Articles per month, $6.95/article thereafter. Free newsletter.

Subscribe
$75/Year

Unlimited digital content, quaterly magazine, free newsletter, entire archive.

Sign me up

Having a strong pool of talent is critical for success in today’s business environment. After all, weak leadership can be one of the biggest impediments companies face. Diversity in leadership is a potential key to unlocking high performance within organizations. However, despite significant attention and investment, the top management of the largest U.S. corporations remains not very diverse.

Our own study of 245 organizations with operations in North America found that while 71% of organizations aspire toward having a diverse culture, only 11% report having one. Moreover, the higher up you look in most organizations, the less diversity you’re likely to see. According to the Center for American Progress, women represent 59% of the college-educated workforce at the entry level, but only 14.6% of executive officer positions are held by women. What’s more, women of color hold only 11.9% of managerial and professional positions.

Clearly, today’s organizations are missing out. Companies that are serious about making tangible and measurable progress toward attracting and retaining the best talent need to make a fundamental shift in how they address diversity. The shift will require organizations to go beyond providing training that educates employees on their unconscious biases; employers will also need to establish data-oriented processes for identifying and promoting leaders.

Many executives believe they are good at identifying leadership talent. However, when asked how they make their decisions, they often cite intuition or “gut” instincts. Social science research, on the other hand, suggests that it is difficult for an individual to judge who will become an effective leader. When hiring, managers tend to select and seek out people who are likable, attractive, nearby, and often similar to themselves. Moreover, they tend to assume that if a person is highly skilled at one thing, he or she is likely to be good at other (even unrelated) tasks. This bias (commonly known as the “halo effect”) explains why, for example, extroverts capable of giving compelling presentations are likely to be viewed as leaders.

Although biases such as these typically operate at the individual level, collectively they form organizational archetypes of what successful leadership looks like. The archetypes may emphasize identity (such as race, gender, and ethnicity) or functional roles within the organization (such as sales or marketing over operations). These archetypes, which are often prone to biases, form the narrative around successful leadership in organizations.

Read the Full Article

Topics

Frontiers

An MIT SMR initiative exploring how technology is reshaping the practice of management.
See All Articles in This Section

Reprint #:

58414

More Like This

Add a comment

You must to post a comment.

First time here? Sign up for a free account: Comment on articles and get access to many more articles.

Comments (3)
Gerard Francois
In large corporations, whatever tools you put in place to better assess potential leaders, the ultimate decision will always be political and based on networks. That said, it still can be useful at least to eliminate people who do not go through the tools.
Ernesto Torres
Greatly appreciate information on recommended data based assessment tools. Also would like to contact the authors for a one on one conversation on the overall process for implementing  the data driven approach.



Ernesto Torres
Jonathan Obise
Succinct article!
Indeed, a data-driven approach to selecting leaders in organizations would eliminate the bias that so often cloud human judgement.