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Collaboration Overload Is Sinking Productivity

Here is an excerpt from an article written by Rob Cross, Mike Benson, Jack Kostal, and RJ Milnor 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.

Credit: mikkelwilliam/Getty Images

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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:

  • Two major life sciences organizations have used network analysis to systematically analyze calendar data and identify ways to reduce redundant meeting time.
  • One global software organization has focused on email to reduce volume, length, and cc’ing redundancies.
  • A globally recognized insurance organization has employed network analysis to identify the most overwhelmed employees and educate them on practices to reduce overload.
  • And, on a more dubious front, one global services organization implemented a 60-second timeout button. After a particularly difficult time, employees can hit a button that lets others know they are taking a mindfulness break. In that 60 seconds, employees practice some aspect of mindfulness — although one must wonder if this is akin to giving a band-aid to an amputee.

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.

Reducing the Inefficiencies of “Always-On” Cultures

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:

  • Blocking out reflective time based on optimal personal rhythms. For some, this means answering emails first thing in the morning and then having a two-hour block for reflective work. For others, it means doing creative work early, and answering email in three blocks of 30-minutes throughout the day.
  • Using triage rules in email. Email begets email, and we all have a tendency to want to answer the quick request that we can feel good about solving. More efficient people tend to block emails into different categories to process them at a given point in time, rather than allowing constant disruptions.
  • Using “standing” meetings to make team problem-solving happen faster. More efficient leaders use weekly touch points to discuss one-off issues, rather than allowing excess disruptions to occur ad hoc. Team members post issues on collaboration platforms like Slack or Microsoft Teams, and the team is encouraged to solve what they can ahead of meetings. Over time, leaders find that the number of one-off issues funneling through them declines substantially as the team gets better at knowing who to turn to for what.

Organizational Actions That Can Reduce Switching Costs

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.

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Here is a direct link to the complete article.

Rob Cross is the Edward A. Madden Professor of Global Leadership at Babson College and Co-Founder of the Connected Commons. He is the author of Beyond Collaboration Overload: How to Work Smarter, Get Ahead, and Restore Your Well-Being (Harvard Business Review Press).
Mike Benson is the Vice President, Global Talent Organization at General Mills. His team pursues innovation and value creation across the talent ecosystem through the use of data, analytics, and insights.
Jack Kostal is Principal Consultant, Workforce Insights at General Mills. His work focuses on unlocking business value through innovative applications of data analytics.
RJ Milnor is the Global Head of People Analytics at Uber. His team empowers leaders and employees to make evidence-based decisions by unlocking the value of people data, helping the business and workforce thrive through actionable insights and curated analytics products.

 

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