Turn meeting data into a productivity system that proves which meetings actually drive outcomes.

Action Item Completion Rate measures the percentage of action items captured during Granola-recorded meetings that are completed within their assigned timeframe. It is the most direct measure of whether meetings produce results or merely consume time.

Action Item Distribution Balance measures how evenly meeting action items are distributed across team members. It identifies individuals who consistently receive a disproportionate share of action items, creating bottleneck and burnout risk, versus those who rarely take on commitments.

Action Item Velocity measures the average time from when an action item is assigned in a Granola-recorded meeting to when it is completed. It reflects the organisation's ability to translate meeting decisions into executed work and is a leading indicator of operational agility.

Conversation Topic Analysis uses Granola's meeting transcripts to identify and categorise the topics discussed in meetings, measuring how much time is allocated to each. It reveals whether meeting time is spent on strategic priorities or consumed by recurring operational issues.

Cross-Team Collaboration Rate measures the percentage of meetings that include participants from two or more different teams or departments. It serves as a proxy for organisational connectivity and the degree to which teams are breaking down silos through direct interaction.

Decision Velocity Tracking measures how quickly decisions are reached within and across meetings, from initial discussion to final commitment. It identifies topics that are decided efficiently versus those that cycle through multiple meetings without resolution, consuming time and delaying progress.

Knowledge Transfer Effectiveness measures how successfully meetings disseminate information to participants and non-participants alike. It evaluates note quality, transcript sharing rates, follow-up documentation, and whether meeting outcomes reach everyone who needs them - not just those who attended.

Meeting Attendance Rate measures the percentage of invited participants who actually attend a meeting. Low attendance suggests that meetings are perceived as low-value, poorly timed, or include too broad an invite list. High attendance indicates relevance and effective scheduling.

Meeting Cadence Optimisation evaluates whether the frequency of recurring meetings matches actual communication needs. It analyses patterns such as short meetings that could be async, cancelled occurrences that suggest over-scheduling, and meeting clusters that fragment focus time.

Meeting Conflict Resolution Rate measures the percentage of discussions involving disagreement or conflicting viewpoints that reach a constructive resolution within the meeting. It distinguishes between productive debate that drives better decisions and unresolved conflict that festers and delays progress.

Meeting Cost per Outcome calculates the economic cost of each tangible meeting output - decisions made, action items assigned, or problems resolved - by dividing the total cost of participant time by the number of outcomes produced. It transforms abstract meeting complaints into concrete financial data.

Meeting Duration Analysis compares actual meeting duration (as recorded by Granola) to scheduled duration, and tracks duration trends across meeting types. It identifies meetings that consistently overrun, those that end early (potentially unnecessarily scheduled), and opportunities to right-size meeting blocks.

Meeting Follow-Up Rate measures the percentage of meetings followed by post-meeting actions such as sharing notes, distributing transcripts, updating tasks in project management tools, or sending summary communications. It indicates whether meetings produce persistent outputs or evaporate after the call ends.

Meeting Frequency Rate measures the number of meetings per person, team, or organisation within a given period. It provides visibility into meeting load and its impact on available focus time. High frequency rates correlate with reduced productivity, particularly for roles that require deep, uninterrupted work.

Meeting Outcome Effectiveness measures the proportion of meetings that produce at least one tangible outcome - a decision made, an action item assigned, a problem resolved, or a plan agreed upon. It separates productive meetings from informational sessions and status updates that could be asynchronous.

Meeting Preparation Score evaluates how well-prepared meetings are by assessing factors such as agenda availability, pre-read distribution, supporting material quality, and participant readiness. Well-prepared meetings are consistently more productive, shorter, and better received than ad hoc gatherings.

Meeting ROI Analysis quantifies the return on investment of meetings by comparing the value of outcomes produced - decisions enabling revenue, problems resolved, projects unblocked - against the opportunity cost of participant time. It treats meetings as an investment that should produce measurable returns.

Meeting Sentiment Analysis applies natural language processing to Granola meeting transcripts to classify the overall emotional tone - positive, neutral, or negative - and track sentiment shifts during the meeting. It provides an objective measure of meeting atmosphere that complements subjective feedback.

Meeting Tag Frequency Analysis examines how tags and labels are applied to meetings in Granola, measuring tag usage patterns, consistency, and coverage. Effective tagging enables portfolio-level meeting analysis - understanding how time is allocated across strategic themes, project types, and meeting purposes.

Note Quality Score evaluates the completeness and usefulness of Granola's AI-generated meeting notes by assessing factors such as action item capture rate, decision documentation, key discussion point coverage, and participant attribution accuracy. High-quality notes serve as reliable records of what was discussed and decided.

Participant Engagement Score measures how actively each meeting participant contributes, considering factors such as speaking time, questions asked, ideas contributed, and interaction with other participants. It identifies silent attendees who may not need to be present and highlights facilitation opportunities to improve inclusivity.

Participant Network Analysis maps the connections between individuals based on shared meeting attendance, creating a network graph that reveals who collaborates with whom, identifies key connectors who bridge different groups, and surfaces isolated clusters with limited cross-pollination.

Participant Speaking Time Distribution measures how meeting speaking time is allocated across participants. It quantifies the Gini coefficient of speaking time, identifying meetings dominated by one or two voices versus those with balanced participation. Balanced distribution correlates with higher-quality decisions and better participant satisfaction.

Recurring Meeting Efficiency Trends tracks how the productivity of recurring meetings changes over time, measuring outcome production, duration adherence, attendance stability, and participant engagement across successive occurrences. It reveals whether recurring meetings are improving, stagnating, or degrading.

Transcript Keyword Trending analyses the frequency and trajectory of specific keywords and phrases across Granola meeting transcripts over time. It surfaces emerging topics, shifting priorities, and recurring concerns that might not be visible in individual meetings but become apparent in aggregate.