Workplace Analytics Tools: What IT Teams Should Actually Measure
Workplace analytics has expanded from facilities dashboards into a sprawling category covering employee productivity, space utilisation, collaboration patterns, and technology adoption. IT teams are increasingly asked to deploy and maintain these systems, and more often than not, asked to deliver insights that no one quite knows what to do with.
This guide is about cutting through the noise: what to actually measure, which tools handle which use cases, and how to avoid building an analytics stack that generates data nobody acts on.
Quick verdict
Start with space utilisation and technology adoption. These are the two categories where IT has data it can actually collect (badge access, room booking systems, sensors, M365 telemetry) and where the outputs have clear business decisions attached. Employee productivity analytics, particularly anything involving individual surveillance, should only be approached with legal review and explicit employee disclosure.
Category 1: Space utilisation
Space utilisation analytics answer: are people using the office as we think they are? Most organisations discover significant gaps between assumption and reality.
What to measure
- Room booking utilisation rate: bookings made vs. bookings where people actually showed up. Industry average is 30–40% utilisation, meaning 60–70% of booked time goes unused.
- Peak occupancy by day and time: which days are actually busy vs. which days the office is empty. Informs hybrid work policy design and energy management.
- Room size vs. actual attendance: are 8-person rooms being used by 2 people? Informs space reconfiguration decisions.
- Desk utilisation in hot-desking areas: what’s the actual ratio of desks to people on peak days?
Where the data comes from
- Room booking system logs (Robin, Condeco, Joan, M365 room mailboxes)
- Occupancy sensors (see the smart office sensors guide)
- Badge/access control data (most modern access systems export logs)
- Wi-Fi association data (number of devices connected to APs, as a rough headcount proxy)
Tools
Microsoft Places (formerly Workplace Analytics space features): for M365 environments, Places aggregates calendar, Teams, and sensor data into office utilisation dashboards. Included with some M365 enterprise licences, verify with your licensing team.
Robin, Condeco, and most enterprise room booking platforms have built-in utilisation reporting. If you’re already running one of these, use their native analytics before adding another tool.
Sensor-specific dashboards: platforms like Butlr, Kaiterra, and Cisco Spaces have their own analytics layers. If you have sensor infrastructure, these are often the most granular source of utilisation data.
Category 2: Technology adoption
Technology adoption analytics answer: are people using the tools we’ve deployed, and are we getting value from our software licences?
What to measure
- M365 licence utilisation: are you paying for E3/E5 licences where users only need F1? Unused Teams, SharePoint, and OneDrive usage indicates over-licensing or under-adoption requiring training intervention.
- Meeting room technology usage: are the AV systems in meeting rooms being used, or are people still dialling in from laptops? Informs AV investment decisions.
- Digital signage engagement: are people interacting with (or ignoring) the signage? QR code scan rates and anecdotal feedback are the practical proxies.
- Support ticket categories: what technology generates the most helpdesk tickets? This is often more actionable than any analytics dashboard.
Tools
Microsoft Viva Insights: Viva Insights pulls aggregated, de-identified data from Outlook, Teams, and SharePoint to show collaboration patterns, meeting load, response times, focus time. It’s available at different levels: personal insights (individual, private), manager insights (team-level), and advanced analytics (organisation-level, requires additional licence).
The 2026 updates added Copilot adoption metrics, useful for organisations tracking M365 Copilot rollout value. Viva Insights is included with M365 E3/E5; Advanced Insights requires a separate add-on. Check microsoft.com/viva/insights for current licensing.
Microsoft 365 Admin Center: the usage reports in M365 Admin Center show app usage, active users per service, and licence utilisation. This is often underused, it’s built in and free, and provides most of what’s needed for basic adoption tracking.
Google Workspace Admin Reports: equivalent to M365’s usage reports for Google environments, shows Drive, Meet, Gmail, and Calendar activity at the organisational level.
Category 3: Collaboration patterns
Collaboration analytics show how people work together, who communicates with whom, how meetings are structured, where communication bottlenecks exist. This is the most valuable category for HR and leadership, and the most sensitive for IT to deploy.
What’s useful
- Meeting fragmentation (percentage of time in meetings vs. focused work)
- Cross-team collaboration patterns (are departments working in silos?)
- After-hours work patterns (an indicator of unsustainable workload)
The privacy boundary
Collaboration analytics must be handled carefully. The line between “team-level patterns” and “individual surveillance” is a legal, ethical, and employee relations issue, not just an IT configuration question. Before deploying any tool that tracks individual communication patterns:
- Get legal review (GDPR and local employment law apply)
- Brief HR and union/works council representatives where applicable
- Use aggregated and de-identified data at team level, not individual tracking
- Be explicit in employee communications about what is and isn’t tracked
Viva Insights by default is designed with privacy protections, individual data is private to the individual; managers only see aggregated team data above a minimum team size. But configuration matters: verify settings with your privacy team before rollout.
What not to measure (or at least, not yet)
- Individual productivity scores: “productivity analytics” tools that score individuals based on email volume, Teams activity, or keystrokes are legally risky in most European jurisdictions and corrosive to trust when discovered
- Sentiment analysis: email and Teams sentiment scanning exists but requires explicit consent and legal review
- Granular individual location tracking: badge-in/badge-out is generally acceptable; continuous indoor location tracking of individuals requires clear consent and justification
Building a useful analytics stack
A pragmatic workplace analytics stack for a mid-size organisation:
- Room booking utilisation: pull from your existing booking platform (Robin, Condeco, M365 room mailboxes). No additional tool needed.
- Occupancy: add occupancy sensors if room booking data alone isn’t granular enough. Butlr or Milesight are practical options.
- M365 adoption: M365 Admin Center usage reports. Free, built-in, covers most needs.
- Collaboration patterns: Viva Insights if you have M365 E3/E5 and a GDPR-reviewed use case.
- Helpdesk data: ServiceNow, Jira Service Management, or equivalent, analyse ticket category trends quarterly.
This stack covers the majority of actionable workplace analytics use cases without deploying specialist point solutions. Add specialist tools only when you’ve exhausted what these provide.
The most important question
Before deploying any analytics tool, ask: who will act on this data, and what decision will they make? If there’s no clear answer, the analytics will generate dashboards that get reviewed once and then forgotten. Measurement is only useful when it connects to a decision. Define the decision first, then identify the metric, then deploy the tool.
Bottom line
Start with space utilisation data from tools you already have. Add sensor data when you need granularity that booking systems can’t provide. Use M365/Google native reports for technology adoption. Treat collaboration analytics carefully, with legal oversight. And measure only what you can act on.
Related: smart office sensors guide and workplace management software comparison.