The global pandemic has brought leaders a steady barrage of unfamiliar challenges. The one consuming most attention now regards decisions around bringing employees back to the workplace. It is easy to imagine a leader turning to a google search to understand the best practice for this circumstance. Performing that search and reviewing its results suggest these leaders will learn two things: Employees would rather quit than come back to the office, and employees are just as – if not more – productive at home as they are at work. These two assertions make it clear that a leader who orders a return to the workplace is simply asking for trouble. Headlines like the one from Business News Daily that decries "Working from Home Increases Productivity" and from Bloomberg declaring "Employees are Quitting Instead of Giving Up Work From Home" seem to leave little room for interpretation. Unfortunately, nothing about people and work is so cut and dried.
It will be difficult for leaders to make the best return to the workplace decision for two reasons. First, leaders face uncertainty regarding how employees will greet an order to return to the workplace. Second, a great deal of ambiguity exists when anticipating how different decisions will impact individual employee behavior and overall organizational performance. Leaders have this summer to sort this out. Employees are waiting to hear – are they back to the grind of the commute to a cube, or are they going to be allowed to ditch the dry cleaner and persist in their new ways?
A few critical observations become apparent if a leader can resist reliance on a catchy headline to read these articles carefully. First, most trace back to a very small number of studies. The evidence about remote employee performance is better characterized as a few drops in a nearly empty bucket. The echo chamber that is the Internet has created what appears to be a rising tide of evidence describing the calamity that will result should leaders call their employees back to the workplace. The plain fact is we do not have enough information to know how a call back to the workplace will be received – both in the short- and long run. As a hint to leaders, when an article begins with "According to one study . . ." it is offering the reader a warning to keep learning. One study does not a truth make. If only we so easily understood employee preferences and performance.
Second, those few reported studies often suffer from glossed over weaknesses, perhaps to support a catchier headline. The most concerning limitation involves the way data is collected, specifically regarding the integrity of self-report data. Anyone who has worked from home during the pandemic appreciates that avoiding wasting time commuting, saving time getting ready in the morning, and having greater autonomy about the way you spend much of your day are unique features of a work from home arrangement. For many, work from home has been a good gig.
It is because working from home is such a good gig for so many that self-serving bias, effectively unavoidable in self-report surveys, should caution our interpretation of these studies. When the person completing a survey has something at stake in the results, we should take their answers with a grain of salt.
For example, one of the most cited surveys used to support ongoing working from home was reported by Great Place to Work. The survey seems like it should be incontrovertible in its results. After all, 800,000 employees participated. The results are used to show that working from home is at least as productive as work in the office. How was this conclusion reached? By asking each employee if it was true or almost always true that people working from home were willing to give extra to get the job done and to adapt to what the company needed for success. If your ability to continue a work-from-home gig was dependent on the answers to these questions, how would you respond?
A third challenge is that when a more rigorous study – one that, for example, measures actual job performance – is conducted, we need to remember that its findings are likely limited by the profession, industry, or location in which the study took place. One such study recently reported that among 10,000 employees at an Asian technology company, hours worked increased dramatically, but this added input did not translate into a rise in output. A leader might reasonably conclude work from home is inefficient but still productive – but remember, this is 'just one study.' Whether the finding suggests work from home is or is not beneficial, a savvy leader needs to identify any reason to believe those findings would generalize to their workforce. Because many Asian technology company employees are less efficient at home, it does not mean the same would be their company's experience. Leaders must ask themselves, "Even if this was true there, why would it be true here?"
Finally, we must not overlook that most of the newly at-home employees are there as a part of a necessary and massive pivot caused by a global health pandemic. The context in which employees toiled last year was unprecedented. Arguably, an esprit de corps held as we all tried to keep our companies moving, demonstrate our value during threatening times, and show one another grace and patience as colleagues struggled to remember to come off mute when speaking during a web conference. As the pressure placed on us by the global pandemic begins to ease, the patience and grace we have shown one another may similarly wane. If that occurs, there is good reason to believe that over time, employee trust as to whether fellow workers are providing full effort while working remotely might also erode. The concern that others are withholding effort and getting away with it will cause some to reduce their own effort to avoid being played for a sucker. Remote work arrangements will likely let them get away with this.
Colocation in a workplace is one effective way to hold one another accountable for effort more efficiently than is possible in most work-from-home arrangements. It is easy to test this out. Consider the attributions you and those around you have made of colleagues who consistently refuse to turn on their web camera during online meetings. Colleagues quickly assume these coworkers are slackers hiding from full participation and satisfied with committing less than 100% effort to the group's work. Those giving 100% will eventually feel like suckers for doing so and will have a good, logical internal dialogue to justify their own decision to begin coasting.
Fortunately, there is a tool leaders can draw on for assistance in making decisions in instances like this one, characterized by high uncertainty and ambiguity: the VUCA framework. The framework's name is an acronym for forces that plague decision-makers: volatility, uncertainty, complexity, and ambiguity. To leverage the framework and make better decisions, the leader needs first to understand which of the four forces are present. It is essential to appreciate the differences between the four because the best way to address one is not the same as managing another. When a leader makes a misdiagnosis, efforts to execute a decision will miss the mark.
- A situation is volatile when it contains unexpected or unstable factors.
- Uncertain situations are so because there is not sufficient information for decision-making.
- Complexity results when a situation involves many interconnected parts that each introduce several variables to the problem; processing it all creates cognitive overload for the decision-maker.
- Finally, an ambiguous situation is one where the cause and effect between factors are not understood.
It is possible that as a leader considers decisions around bringing the workforce back, it appears all four elements are present. However, the primary challenges here are arguably uncertainty and ambiguity. Leaders should not make big decisions like this based on what a single study found, but that is where we are – we are awash in speculation but still uncertain because we lack good information. Further, the decision is fraught with ambiguity as there are several cause-and-effect questions that we cannot currently answer, such as:
- If I call employees back to work, will they quit in large numbers?
- If my employees quit, will it be the MVPs, or will the turnover be functional and save me the grief associated with managing marginal performers?
- If I do not call employees back to work, what will it take to protect their ongoing performance?
- What are the implications to our culture when remote work becomes a choice and not a coping mechanism?
- Will trust among employees erode as their performance becomes more difficult to assess, and will a cadre of social loafers be created and protected by a work at home arrangement?
Reports of interviews with leaders reflect the uncertainty around questions like these. For every story offering comfort to decision-makers considering making remote work more common, there is a story of woe that should give them pause.
Situations characterized by uncertainty and ambiguity call for the decision-maker to experiment. Small efforts to produce results that could better forecast what to expect from a particular company or a job category can eventually reduce uncertainty. Experiments with various hybrid arrangements can answer how employees will receive different policies and practices. For example, surveying employees to understand the damage done to the personal brand of the webcam-shy when it comes to trust and morale might help educate these employees on the negative consequences of their stubbornness when it comes to being on camera. Similarly, experimenting with practices designed to build and reinforce culture and camaraderie might support a decision to offer work from home as an enticement to new hires. These experiments must be intentional; data collection should be time-limited and agreed-upon metrics that would indicate success established.
By designing and conducting good experiments, leaders will address the uncertainty and ambiguity that make their decision-making about returning to work practices little better than a flip of a coin. And at the same time, they will be generating relevant data to support decisions that might not always be in employee self-interest. This summer is the time to experiment.