Two Fortune 100 companies comprising thousands of knowledge workers.
What’s the business problem?
Understand what made managers of highly engaged employees different than the rest on a day-to-day basis.
What was the solution?
Analyze metadata from the digital breadcrumbs of a customer’s millions of de-identified email and meeting interactions to generate an objective and granular set of behavioral KPIs across the organization. Among other things, these KPIs can then be combined up with other data sets to understand what behaviors differentiate sub-populations of employees.
What action resulted from the data analysis?
Managers built mindset and skills to:
- lead by example when it comes to working hours
- ensure even allocation of work.
- maintain large internal networks across their company.
- prioritize one-on-one meeting with direct reports
What were some key findings?
- People are more engaged if they work for a manager who is working at least as much as they are.
- Employees who put in more hours than the rest of their team are more likely to be disengaged.
- Larger networks are correlated with a number of different positive business outcomes.
- Employees who got little to no one-on-one time with their manager were more likely to be disengaged.
- Managers have a disproportionate impact on employee engagement scores.
What’s important to remember about this project?
Historically, the lack of objective data has made it difficult for companies to instrument the quality of their managers and therefore even more challenging to provide effective training and ongoing feedback loops to improve it. Our data is a start, highlighting some traits of good managers that are actionable on a daily basis.
Note: you'll be able to download the resources summary starting on May 15,2017.