Collaboration workload analytics

Collaboration workload analytics

What is collaboration workload analytics?

Collaboration workload analytics focuses on verifying how much time teams spend on collaboration activities including email and chat communication as well as the time spent in meetings. You can gather the data through surveys by asking employees how much time they devote to synchronous (i.e. meetings) and asynchronous (email and chat) communication. Alternatively, you can turn to your existing systems such as Office 365, G-Suite, Slack to check how much time is spent on collaboration. It’s vital to conduct the analysis in an ethical way – collect team data rather than individual data. Focus on analyzing how people work instead, without paying attention to their personal traits.

How to conduct collaboration workload analytics – tips for leaders and teams

Collaboration workload – how to measure it effectively

  • Time spent on meetings
    To assess how much time your employees spend on meetings, look at the number of meetings and sum up the entire time spent on these initiatives.
  • Time spent on emails & messages
    Take each email or message and multiply it by 1.3 minutes (as it takes this long, on average, to read or write each message). As a result, you receive the estimated time spent on sending and going through each email.
  • Time spent on collaboration
    To verify how much time your employees spend collaborating, add the time spent on writing emails or messages to the time spent in meetings.
  • Potential low-quality meetings & time wastes
  • Team meetings heatmap

What is the goal? 10 hours per week per employee (20 meetings, 30 min each), and 3 hours per day (6 meetings, 30 min each) per employee. 

Why is it important? Keeping the meeting time at the optimum level and establishing meeting routines within the team (team bonding and daily status check-ins) will let teams collaborate seamlessly and achieve goals without overwhelming employees with screen time.

Why should HR and people leaders measure and manage collaboration workload? Here are some examples and numbers:

  • According to Harvard Business Review, executives spend 23 hours weekly in meetings, which represents a 10 hour increase from the 1960s. It’s hardly surprising they experience a meeting overload.
  • Not only are ineffective meetings a productivity killer, but they also generate significant costs. They can cost companies up to $283 billion a year. 
  • Out of 40 hours a week, 12 hours is spent on preparing and attending meetings.

What is over collaboration? What is the optimal level of collaboration overload for high performing teams? 10 hours per week per employee (20 meetings, 30 min each), and 3 hours per day (6 meetings, 30 min each) per employee.

How to effectively manage collaboration workload? 

There are several best practices you can put into use.

Begin by looking at your team calendar. How many meetings are there, and how long do they last? It’s important to keep the meeting time under control. It’s best they last no longer than an hour each. Especially, as it’s been proven that the human brain can remain focused for up to 60 minutes, and needs 15-20 minutes of so-called recovery time.

Secondly, you should keep synchronous communication to the bare minimum. To know what everyone from your team is up to, consider organizing daily or weekly standups. 

Thirdly, establish clear communication guidelines. Employees should be aware of when they can initiate a meeting, and when they should seek to resolve any issues or queries via text-based channels. This can do wonders in terms of minimizing the “let’s jump on a quick call” interruptions and overstimulation.

Last, but not least, use a workplace analytics software like Network Perspective to track how much time people spend on collaboration, and to spot any issues that might point to collaboration overload. 

Read more on our blog:

How can Team Collaboration Analytics help enable people leaders? →How to leverage advanced Workplace Analytics with strong ethics upfront? →

Read more from other resources:

When Collaboration Fails and How to Fix It →

Start working in a data-informed smart way

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