Meetings are one of the biggest levers for team productivity. They are also one of the fastest ways to create burnout, slow decision-making, and reduce focus time.
The problem is that most companies try to fix meetings with opinions like “we meet too much” instead of measuring what is actually happening. The easiest way to improve meeting culture is to track a small set of meeting effectiveness metrics that show whether meetings are helping work get done or getting in the way.
If you only track a few, start here:
The best part is that you can measure most of these automatically using calendar data (Google Calendar and Outlook) and combine them with collaboration signals to understand why meeting time is rising.
In this guide, we’ll break down 12 practical meeting metrics you can use to diagnose meeting overload, improve effectiveness, and set realistic targets for healthier, more productive workdays.
Meetings have long been the lifeblood of companies - it’s how we collaborate and connect with each other. Effective meeting culture can help companies invigorate and motivate their teams. However, all too often we are stuck in a slew of seemingly never-ending meetings that include too many people and don’t accomplish as much as we would like. This trend is exacerbated with remote and hybrid teams, where the need to coordinate can often lead to an explosion in meetings and over-collaboration. People who spend excessive time in meetings also tend to work longer workdays, in order to compensate for lost time. This self-reinforcing trend can be a significant source of frustration and a key driver of burnout for teams.
So how do we understand whether our meetings helping our organization connect? Or whether they are instead causing stress and leading to burnout?
Here are 12 key metrics that some of the companies with the best meeting cultures use to understand and improve their meeting habits.
More than 10 hours per week for knowledge workers tend to correlate with lower engagement scores, less focus time to accomplish deep work, and longer work days. It’s important to track and understand what portion of your organization is in this category in order to pinpoint where to take action.
Healthy: ~4–8 hrs/week for many IC roles
Watch zone: ~8–12 hrs/week
Overload risk: 12+ hrs/week consistently
How to measure it: Sum the total scheduled meeting time per person per week from calendar data (Google Calendar or Outlook), then report averages and the share of employees above key thresholds (for example 10+ hours/week).
Recurring meetings tend to be created for coordination purposes and often live on well beyond their utility. This is particularly true for larger recurring meetings where individual participants may be hesitant to ask for their removal, yet given the size, the meetings may not be as useful. Remote and hybrid teams often see an explosion in recurring meetings which can account for most of the time spent during the work day.
Healthy: <50% of meeting time recurring
Overload risk: >70% recurring (means the calendar is “pre-spent”)
How to measure it: Count the number of meetings on each person’s calendar that have a recurrence rule (weekly/biweekly/monthly), and track what percentage of total meeting hours come from recurring meetings.
Shorter meetings tend to be more efficient and allow for quickly pointed discussions. However remote and hybrid work often leads to a proliferation in short 1:1 meetings used for coordination. These meetings, though helpful, may actually lead to greater calendar fragmentation and decreased focus time, since each task requires 23 minutes of switching time between meetings.
How to measure it: Calculate the distribution of meeting duration (15/25/30/45/50/60 minutes) from calendar invites, and track both the average meeting length and the share of meetings under 30 minutes vs over 60 minutes.
Research indicates that the ideal meeting size is somewhere between 3 and 8 participants. Larger meetings tend to turn into information-sharing sessions and allow for far less individual participation. Data indicates that in larger meetings people tend to be far more distracted spending time in email and messaging. This is particularly true in remote work settings..
Healthy default: 2–6 people for most meetings
Overuse risk: lots of 8–15 person meetings without clear purpose
How to measure it: For each meeting, count the number of invited attendees (and separately count the number of actual attendees when available), then track the percentage of meetings that are 2–6 people vs 8+ people.
Research indicates that extended periods of time conferencing over tools such as Zoom, Google Meet, or Microsoft Teams can lead to burnout. This appears to be particularly true when individuals feel compelled to remain on video throughout calls. Research also indicates that women are disproportionately impacted by this effect.
How to measure it: Identify meetings that include a Zoom/Teams/Meet link (or conferencing provider field), then calculate the percentage of meeting hours spent in video-enabled calls and the average video meeting time per person per week.
In an ever more connected work environment, a constant barrage of push notifications and other distractions can make it hard to concentrate in meetings. These distractions from tools like Slack, Microsoft Teams and Email can mean that people are less likely to be present during meetings. Using anonymous usage statistics from across these various platforms it is possible to understand the volume of concurrent activity and with this generate an estimate of how focused people tend to be in meetings. For example, we’ve found that larger, remote meetings tend to be far less focused.
How to measure it: During scheduled meeting windows, measure concurrent activity such as Slack messages, Teams chats, or email sends, and summarize the rate of meetings where participants show active “multitasking” signals while the meeting is in progress.
The volume of meetings that either start late or end over time can be a really good measure of meeting hygiene. This can be measured using anonymous usage metrics from tools like Zoom and Teams combined with a scheduled meeting time from data in Google or Outlook Calendar.
How to measure it: Compare the scheduled start/end time from calendar data to the actual start/end timestamps from Zoom/Teams call logs, then track the percentage of meetings starting late and the average overrun minutes per meeting.
Inclusion in meetings is an important indicator of how an employee’s contribution is perceived. It is common for only a few people to dominate most large groups and meetings, which is highly correlated to teams feeling that they don’t have a voice or are not considered valuable. This phenomenon is particularly challenging for under-represented groups in the remote or hybrid work arrangement when the only contribution or exposure to the larger team or management is via larger meetings. Estimating voice in meetings is possible using anonymous usage data from Zoom and MS Teams.
How to measure it: Use speaking-time estimates from Zoom or Microsoft Teams (where available) to calculate speaking-time distribution across attendees, and track concentration metrics such as the percent of total talk time held by the top 1–2 speakers.
Meetings are not just about meeting others or making decisions. They also provide ways for employees to gain exposure, build relationships, and prove their value to the team. A common trend seen in remote and hybrid work is that the more junior or underrepresented employees are often excluded from the key meetings. This gives them a limited opportunity to gain exposure and learn more about the organization. Measuring the makeup of typical meetings can give us a sense of the level of inclusion in these key discussions.
How to measure it: For key meeting types (leadership reviews, planning, customer calls), measure who is consistently invited and who is consistently absent by team/level/role, then track the representation mix of attendees across recurring “important” meetings.
Looking at the attendees of key meetings can also help companies understand the level of redundancy within their organization. Are there lots of meetings that contain multiple leaders in the same span of control? Are there lots of meetings filled with VPs or senior leaders leading to redundancy in decision-making? This metric is also useful in understanding whether decisions are benign and made in the most effective way within the organization.
How to measure it: Identify “decision-making” meetings (leadership meetings, exec reviews, approvals) and measure how often multiple leaders from the same reporting line or span of control attend the same meetings, along with the total senior-leader hours spent in overlapping meetings.
A common trend in remote and hybrid work has been the general culture of over-collaboration driven by meetings but carried over into other channels such as Slack, Teams, and Email. One way to measure over-collaboration is to consider the number of strong connections the average individual on a team has. Strong connections are people you consistently spend at least 2 hours per week either meeting or communicating with. If this number is large (over 10 or so), most companies typically find a strong correlation with negative survey scores about “Slow decision making”, “Too much process” etc. This signals that over-collaboration also means that to get your work done you have to collaborate closely with 15 other people, and decisions are only made via consensus. This is a key leading indicator for ineffective and inefficient processes.
How to measure it: For each person, count the number of unique collaborators they spend at least ~2 hours per week with across meetings and/or communication channels, then report the average and the share of employees above thresholds like 10+ strong collaborators.
The key to improving meeting culture is understanding how different groups within an organization share information and spend time together. Using anonymous data from tools like Zoom, Teams, and Calendars one can generate a map of collaboration via meetings across an organization. Studying this map can help to provide insight into ways of bridging disconnected functions or managing groups that consume an excessive amount of meeting time from other functions.
How to measure it: Build a “meeting collaboration map” using calendar + conferencing data, then analyze cross-team meeting volume by function (who meets with who, and how often) to identify disconnected groups and teams consuming outsized time from others.
