7 Metrics to Consider When Deciding on a Return to Office Policy

Ben Waber

Recently, I worked with a bank executive who told me he wanted all of his thousands of employees across the globe to return to the physical office. When I pressed him for a reason, he could only tell me that he’d worked in the office five days a week for his entire career, and he’d been plenty successful.

But when I crunched the numbers, I showed him that a blanket return-to-office (RTO) move would likely cost his organization at least $800 million per year.

Whether and how to require employees to come into the office is one of the most important decisions that executives are making right now — and it should be made based on information, not hunches.

A Data-Driven Approach to RTO

Here are seven of the most important metrics companies should consider when crafting their RTO policies:

1. Employee Preference

Even though survey data shouldn’t be the final word on RTO, you need to know what your employees are thinking. If half of your top performers say they’re going to leave the company if they’re required to come into the office more than twice a week, for instance, that’s critical information. It’s important to conduct these surveys on an ongoing basis, as preferences may change along with your workforce.

2. Strong Ties

Overall, it’s important to gather and analyze information on employees’ connections and contacts with one another. But it’s even more helpful to break this data up into “strong” and “weak” ties, which each predict different types of performance. Often, we see that employees spend more time with their close connections when they are working remotely, as the model gives them ample opportunities to collaborate one-on-one with members of their team, without excessive distraction. By the way, no one predicted that this would be the case when the world shifted to remote work during the COVID pandemic. That’s why we need data.

3. Weak Ties

By contrast, we typically see that workers have more casual interactions when they’re in the physical office. This is important, as these weak ties — connections across teams, in other words — are often critical to driving innovation. Companies can track these connections using WiFi data, which can paint a pretty accurate picture of face-to-face interactions. But employees at some companies will bristle at what they see as an invasion of privacy, and often, digital interactions such as email actually do a pretty good job of predicting in-person collaboration.

4. Focus Time

Some managers want to track the hours that employees are working, but this is actually something of a meaningless metric. Broadly, we’ve seen that employees work about an hour more per week at home than they do in the office. Much more important—and predictive of performance—is the amount of “focus time” (defined as blocks of time 15 minutes or longer without interruption) that employees have available to them. At one company I worked with, engineers had only 15% of their week available for focus, with the rest eaten up by long meetings. This is the sort of information that only surfaces if it’s deliberately measured.

5. Milestone Attainment

Profitability essentially tells you nothing about the effectiveness of your current methods. I could walk into Google, slash the research and development workforce by 90%, and although it would doom the company over the long term, it would increase profitability in the moment. It’s much better to measure how different working styles influence the achievement of important project milestones (which will, of course, eventually lead to downstream profitability).

6. Employee Performance KPIs

Executives and managers need to know how employees are performing in different environments. But individual employee performance ratings (which tend to be a reflection of how much a manager likes a given worker) aren’t actually all that great at predicting performance. Instead, leaders should devise and track key performance indicators that are more directly tied to the success of the company.

7. Red Flags

Often, it’s difficult to measure the difference between “pretty good” and “really good.” But it’s usually easy to measure the difference between “pretty good” and “terrible.” Companies should seek out data on red flags that almost always predict poor performance. Are your managers spending less than 2% of their time with their teams? Is a big chunk of your workforce putting in 60-hour weeks, teetering on the edge of total burnout? These are things you need to know as you’re making RTO decisions.

None of this is to say that metrics should rule everything. There are things that the data can’t capture, and executives need to bring this context to their RTO decisions. But they also need to measure the impact of their choices — and be prepared to pivot when the data suggests a new direction.

About the Author

Ben Waber is recognized worldwide as one of the leading thinkers at the intersection of management, data, workplace, and people. He is the President and co-founder of Humanyze and a visiting scientist at the MIT Media Lab, and lead instructor of the MIT Professional Education course, “Workplace Analytics, AI, And Ethics.” Additionally, he is the honorary chairman of the Japan People Analytics and HR Technology Association and an advisory board member at Accenture and HR.com.

Source: reworked