Here is an excerpt from an article written by Ryan Fuller and Nina Shikaloff for Harvard Business Review and the HBR Blog Network. To read the complete article, check out the wealth of free resources, obtain subscription information, and receive HBR email alerts, please click here.
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The holy grail of today’s workplace is high employee engagement.
According to Gallup’s oft-cited research on the topic, just about one-third of U.S. employees are engaged on the job. That number drops to 13% worldwide, and has held steady for years. Many companies are investing heavily to identify what leads to high engagement in order to motivate employees, thereby increasing their happiness and productivity.
We think this is important. But based on our research with several large companies, we want to offer a word of caution: Engagement is often an ambiguous term. Depending on how it’s measured, engagement could represent job satisfaction, emotional investment in the cause, willingness to invest discretionary effort, or advocating for the company as a good place to work. While many studies suggest that increased employee engagement leads to improved business results in aggregate, a deeper look at the data suggests that this may not always be true at an individual level.
Working with two Fortune 100 companies, we looked to test the assumption that highly engaged employees are more productive. The lack of good productivity metrics for most knowledge worker functions (as opposed to clear benchmark numbers for salespeople, for example) makes it difficult to quantify output at an individual level, so we turned to our Microsoft Workplace Analytics product, which uses de-identified calendar and email data to look for a relationship between inputs (working hours, time with manager, network size for example) and engagement.
After experimenting with a number of potential behavioral metrics, we settled on using one that approximates average weekly working hours as our primary measure. While working hours certainly does not measure quality of work or actual productivity, we thought it would be interesting to explore whether there is a relationship between engagement scores and how many hours people put in each week. Our findings were quite different in the two companies we looked at.
[Here’s the first exemplar.]
Company 1: Strong Correlation. At the first company, we found that longer working hours had a strong correlation with higher engagement scores. This means employees working longer hours were generally more engaged, based on their self-reported engagement score. Paired with qualitative observations, the most likely interpretation is that highly engaged employees simply choose to work longer hours because they are, well, engaged — a good thing for everyone involved. The company saw these findings as further evidence that continuing to invest in improving employee engagement would have a positive ROI for the business above and beyond simply having happier employees.
For the most part, this correlation suggests that the way they measured employee engagement translated at least in part into how much time and energy employees were willing to put into the job. However, when we looked at employees working extremely long hours (the 90th percentile), engagement scores dropped off rapidly, which is likely an indication of overwork, so high engagement will only take one so far.
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Here is a direct link to the complete article.
Ryan Fuller was the CEO and co-founder of VoloMetrix, a leading people analytics company acquired by Microsoft in 2015. Within Microsoft, Ryan leads a business unit focused on making organizational analytics capabilities broadly available. Previously he was a management consultant at Bain & Company.
Nina Shikaloff is a Senior Program Manager at Microsoft, where she delivers actionable insights for improving organizational efficiency and talent management to Fortune 500 companies using Workplace Analytics. She previously led analytic consulting, R&D, and product management functions at FICO and InfoCentricity.