By Alan Todd
Each year, U.S. businesses spend $20 to 50 billion on leadership training. With that kind of investment, one might assume that the state of American leadership is thriving. But the research tells a different story.
A recent Accenture survey found that only eight percent of executives felt their company was effective in developing leaders, and, in a survey by the Institute for Corporate Productivity, two-thirds of companies reported that they were ineffective at developing leaders.
It’s easy to see why some believe the leadership industry has failed us, but what’s causing this failure and what can be done about it? Harvard’s Barbara Kellerman suggests that the historic inability of organizations to harness leadership metrics and measures, leads to the disappointing outcomes found in leadership development. A company’s ability to precisely connect development to outcomes is critical to extracting return on investment from leadership training.
With the advent of machine learning, big data, and natural language processing, businesses can — and must — harness big data analytics to assess leader performance. Here are some ways that businesses and their leadership development practices will adapt to incorporate analytics.
“ANALYTICS ARE MORE SCIENTIFIC THAN ENGAGEMENT SURVEYS AND CAN MORE ACCURATELY PROVIDE INSIGHT INTO RETENTION AND CULTURE CHALLENGES.”
More easily identify top performers
While managers can sometimes easily spot who their star employees are, it’s just as easy to overlook those who are contributing most. Afterall, a manager is human, which means his or her decisions always have the potential to be influenced by unconscious biases based on gender, race, age, and other factors. Machine learning can more easily identify top performers than a manager, not just by eliminating bias but also through more effectively leveraging data and analytics to compare employees’ to highperformers. Identifying potential earlier allows for quick interventions and coaching mentorship that will benefit employees and their managers.
Ditch the employee engagement surveys
Gallup reports only 13 percent of employees are engaged at work and that 24 percent are actively disengaged. These sort of surveys are helpful in providing a broad snapshot of the issue, but engagement is a complex emotional state and it can be complicated to measure accurately.
Analytics are more scientific than engagement surveys and can more accurately provide insight into retention and culture challenges. Even more, Leadership Analytics can be used to improve employee engagement by identifying which engagement activities have the largest impact on employee performance. Such insights are important for employee achievement as well as a company’s bottom line.
Best Buy used its own analytics to determine that a .1 percent increase in employee engagement results in a $100,000 increase for a store’s annual income.
In-person training isn’t enough
As online training becomes the norm for an increasingly disparate workforce, virtual classrooms are providing a convenient and flexible experience for employees. Just as importantly — if not more so — online training is also allowing companies to track employees’ engagement of the material and assess their understanding.
With online training, every interaction an employee has while learning — from responding to assessments of the material to posting in a discussion forum — creates data that can be logged and analyzed by their employers.
This data can be used to create a more nuanced understanding of how employees are understanding the material, as well as provide insight into how best to intervene. Leadership Analytics can also help companies learn which areas on the whole need greater emphasis, allowing them to more precisely direct their training budget to where it matters most.
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