Many people have had the experience of being asked to do something and knowing with every fiber of their being that they should say no, but in a nano-second convince themselves why they need to do this thing after all. They jump in and then wonder six weeks later why they never have time for work that interests them. Collaborative work — time spent on email, IM, phone, and video calls — has risen 50% or more over the past decade to consume 85% or more of most people’s work weeks, and the Covid-19 pandemic caused this figure to take another sharp upward tick. These invisible demands are hurting organizations’ efforts to become more agile and innovative. And they can lead to individual career derailment, burnout, and declines in physical and mental well-being. But there’s a lot that organizations can do to equip their employees to work more efficiently in this context, ultimately improving employee well-being, productivity, and retention.

Collaborative work — time spent on email, IM, phone, and video calls — has risen 50% or more over the past decade to consume 85% or more of most people’s work weeks. The Covid-19 pandemic caused this figure to take another sharp upward tick, with people spending more time each week in shorter and more fragmented meetings, with voice and video call times doubling and IM traffic increasing by 65%. And to make matters worse, collaboration demands are moving further into the evening and are beginning earlier in the morning.

These demands, which can be invisible to managers, are hurting organizations’ efforts to become more agile and innovative. And they can lead to individual career derailment, burnout, and declines in physical and mental well-being.

In response, forward-looking organizations are taking action to protect employees from the volume of collaborative demands by employing organizational network analysis (ONA). For example:

This exclusive focus on quantity of collaborative demands misses two important drivers of collaborative overload: 1) the inefficiencies and subsequent cognitive switching costs of always-on cultures and 2) the personal motivations that lead us all to jump into collaborative work too quickly.

Collaborative overload is not just a problem of volume. It has an invisible but equally sinister counterpart in cognitive switching costs created by the diversity of demands. As columnist Jennifer Senior put it in The New York Times, Covid has created an unending series of “staccato pulses of two-minute activities” for work and home that many are struggling to manage. Cognitive psychologists have shown that the act of simply responding to a text can impose as much as a 64-second recovery time to get back on track. As Gloria Mark, professor of informatics at the University of California, Irvine, has shown in her research, it can take us as many as 23 minutes to get fully back on task after a slightly longer interruption. With practice, people do get better at adjusting to interruptions, but this adaptability comes at a cost: People who are frequently interrupted experience a higher workload, more stress, higher frustration, more time pressures, and have to exert more effort.

Unfortunately, Covid has driven switching costs through the roof. Meetings have moved from one hour to 30 minutes as most try to cram more collaboration into a given day. IMs have become a more frequent sources of switching costs, with exchanges carrying deeper into the night — for example, one company has seen IMs rise 52% between 6 p.m. and 12 p.m.

Our Connected Commons research over the past decade on collaborative overload shows that more efficient collaborators — those who have the greatest impact in networks and take the least amount of time from people — are distinguished in part by how they put structure into their work to reduce the insidious cost of being “always on.” These people are able to be 18 to 24% more efficient than their peers by doing things like:

There’s a lot that companies can do at an organizational level to reduce the inefficiencies of switching costs to enable employees to succeed. For example, when the Covid pandemic began, tools like Zoom and Slack became increasingly important methods of collaboration. Uber tracked the usage of these tools and saw: 1) a 40% increase in meetings and a 45% increase in the average number of participants per meeting; 2) a greater than 3x increase in Zoom meetings and Slack messages. These interactions resulted in a 30% decrease in focus time (defined as two-plus hours per day of uninterrupted time that can be dedicated to a task or project). Meanwhile, the team at Uber discovered a strong relationship between employees’ amount of focus time and their productivity, as measured in employee surveys. The data showed a collaborative overload “trap” in which people schedule and participate in more meetings to be more productive. These meetings have the effect of displacing focus time, which as a result can actually make employees less productive.

Uber found that employees were able to take more control over their workloads, and improve their feelings of well-being, when they had both the insights and the tools they needed to be successful. The company is addressing collaborative overload through a two-pronged approach of information and enablement. For example, the company ran an experiment in late 2020 where they communicated the impact of focus time on productivity (along with tips for how to increase it) to a group of employees and then compared their focus time to employees who did not get this information. Focus time improved moderately for the informed group. In another experiment, they deployed an application that helped employees define the amount of focus time they needed, and then optimized their calendars for them by moving and managing meetings accordingly (working much like a virtual executive assistant). This led to about a 20% increase in focus time in the experiment group.

While still a work in progress, Uber’s experiments are showing that it takes both information and enablement to combat collaborative overload. Insights are necessary to provide employees with the context for action, but are not sufficient by themselves because they don’t provide a channel for action.  Specific interventions — such as focus time applications and workspace design — can enable more effective collaboration, but employees may not utilize them fully if they don’t understand the context behind why they are important. It takes both tools and context to make a real difference.

As they progress into 2021, Uber is pairing information with enablement to help its workforce collaborate more effectively, to increase their performance and improve their well-being. The company is incorporating insights and tips about collaboration (sourced from their people analytics and other teams) into company-wide meetings and communications, manager development resources, and employee newsletters. At the same time, they are continuing to enable their teams with tools and applications.

Disruptions and switching costs are not the only drivers of collaborative overload that companies are missing when they focus only on the volume of collaborative demands. Another critical source of overload comes from the personal motivations that result in each of us — far more than we realize or like to admit — creating our own collaborative overload problems by jumping in unnecessarily. When people talk about collaborative overload, they inevitably blame culprits such as out-of-control email, back-to-back meetings, demanding clients, and unreasonable bosses. But our research has shown that about 50% of the time, the main culprit of our overload can be found by looking in the mirror.

We all jump into too many collaborations, which happens in micro-moments when a request is made or when we see an opportunity that we know we could help with, even when we know we shouldn’t. Most people have had the experience of being asked to do something and knowing with every fiber of their being that they should say no, but in a nano-second convince themselves why they need to do this thing after all. They jump in and then wonder six weeks later why they never have time for work that interests them.

Our survey work over the past decade shows this to be the most significant driver of personal collaborative overload — and the hardest tendency to change. We are triggered to jump in by deep motivations and ways of working that we have learned since grade school. And the reality is that collaborative overload is insidious. It feels good, like we matter and are in the thick of things — right up until it doesn’t.

Our research has found some common motivators — what we call “identity triggers” — that lead many into trouble. The key is to identify your personal trigger and develop a mantra in the moment to keep you from jumping in. One successful Silicon Valley executive, who has a deep servant-based mindset and desire to help, learned to repeat: “Saying yes means saying no,” (to something else, that is). Another successful consumer products leader who thrived on accomplishments would ask: “Am I the only one uniquely qualified to address this issue?” People need to guard against:

General Mills has shown how forward-looking organizations can help employees combat anxiety-driven overload. The move to remote work during the pandemic presented a unique challenge for General Mills. Not only were employees getting used to this new way of working, but demand for General Mills’ core products went through the roof as grocery store shelves emptied due to panic buying.

This created a collaborative context unlike anything the company had experienced in the past. The average time employees spent per week in collaboration at the start of March 2020 was 21.4 hours (based on internal General Mills data from Microsoft Workplace Analytics). By the end of July, average hours spent in collaboration had increased to 25.7 hours per week — an increase of 20%.

When the company combined this collaboration data with employee experience data, they noticed that negative employee sentiment was also increasing during this time.  As a result, they were able to understand and take corrective actions to keep stress and burnout from continuing to accelerate.

One specific example, focusing on manufacturing and front-line employees, was branded as “Take Care Tuesday.” This weekly effort provided targeted, prioritized, and focused reminders to all leaders to help support overall well-being and team dynamics. Each targeted message focused on what a leader needs “to know” and quick tips on what “to do” — with the focus rotating each week from taking care of yourself, to taking care of others, to taking care of the business. For example, a recent Take Care Tuesday message —“Take Care of the Business” — reminded leaders “to know” that clear and consistent communication is essential during times of change and offered these tips of things “to do”:

These straightforward reminders, with practical action steps and links to additional resources on a regular cadence have been well-received by leaders and employees.

This was an important step. At that point in the Covid evolution, most organizations were more concerned with engaging virtual employees by piling on more meetings and emails. In contrast, General Mills had appropriate analytics in place to know this would have absolutely been the wrong thing to do — the correlation between fragmented time and both negative mood and employee fatigue was .55, meaning there was a very significant impact of collaborative overload on employee well-being.

The solution was to help people structure time differently, rather than invite them to more meetings. While this is not the sole, silver-bullet solution, General Mills is continuing to use data to help teams and individuals better manage the shifting nature of collaborative demands, especially as new teams are preparing for a more hybrid and flexible work environment.

Three key actions emerged from these analytic insights:

As a result of these initiatives, General Mills was able to effectively mitigate the risks of collaborative overload increasing during their Covid work-from-home period that is still in effect. For units that received the dedicated “Ways of Working” sessions, results have been especially promising. On average, these General Mills teams have reduced collaboration time by eight hours per employee, per week. At the same time, these groups are reporting reductions in non-value-added meetings, and more organized meetings in general — all without any negative effects on stress levels or moods. Additionally, the lessons learned from these teams are being integrated into new team launches and broader team effectiveness work aimed at supporting employee well-being and helping all teams at General Mills to be more effective collaborators.

Employees at all levels are feeling the strain of collaborative overload and there is no end in sight as we transition into a post-pandemic world of work. When they’re appropriately applied, analytics can help identify significant efficiencies in this hyper-connected world of work. Leading organizations that equip their employees to work more efficiently in this context will have an important advantage in terms of both performance and retention.

Source: Harvard Business Review

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