Most people analytics demos are genuinely impressive.
Beautiful dashboards. Predictive attrition models. AI-powered flight risk scores. Cohort analysis across five years of headcount data.
The problem: nearly all of it was built for teams of 500 or more.
The people analytics market built itself almost entirely around enterprise HR teams — the Amazons and Unilevers with dedicated analytics budgets and 50,000 employees generating enough signal to make machine learning meaningful. Everyone else got handed a scaled-down enterprise product and a starter tier that costs $8/employee/month for features built assuming you had 500 of them.
But what if you have 43 people? Or 80? What if you just want to understand why three people left in Q1, whether your hiring process is too slow, and whether your managers are stretched too thin — without a $40,000/year platform?
That's a different problem. And it has different solutions.
What People Analytics Actually Is
People analytics is the practice of using workforce data to make better HR and management decisions.
That's it. It is not necessarily AI. It is not necessarily expensive software. It is the difference between "we had some turnover this quarter" and "we lost 4 people in customer support, all within 18 months of joining, and our time-to-hire for their roles is 47 days — which means we're always catching up."
The first is a feeling. The second is a fact you can act on.
The enterprise vendors built platforms for teams drowning in data across dozens of systems. But the underlying logic — measure the right things, look for patterns, decide what to change — works at any size. (For a broader look at how AI fits into HR across hiring, onboarding, and performance, see our complete guide to AI for HR.)
8 Metrics Worth Tracking (With Formulas)
Are you sure you're tracking the right things — or just the things your HRIS exports by default?
You do not need a platform to track these. You need a spreadsheet and 30 minutes per month.
1. Monthly Turnover Rate
(Employees who left ÷ Average headcount) × 100
If 3 people left a team of 40, that's a 7.5% monthly rate — or roughly 90% annual. Most healthy companies target under 15% annual voluntary turnover. Above 20%, you have a retention problem that's worth investigating seriously.
2. Time-to-Hire
Average days from job posting to signed offer
Calculate per department, not just overall. A 35-day average might be fine for engineering but slow for sales, where you're losing candidates to faster-moving companies. Industry median is around 28–42 days depending on the role (per SHRM benchmarking data).
3. Offer Acceptance Rate
(Offers accepted ÷ Offers extended) × 100
Below 75% means candidates are regularly choosing other options over you. That's a compensation signal, a process signal, or both. Above 90% is healthy; below 70% is worth a structured debrief with your last 10 declined candidates.
4. Absenteeism Rate
(Days absent ÷ Total scheduled working days) × 100
Measured per team, not just company-wide. A 2% rate is normal. Above 5% in a specific team often points to a management issue or workload problem, not individual behavior.
5. Employee Engagement Score
Average response on a monthly pulse survey (1–10 scale)
Keep the survey to three questions: "How motivated are you at work this week?" / "Do you feel supported by your manager?" / "Would you recommend this company as a place to work?" Anything below 7/10 average warrants a conversation. Scores dropping consistently over three months mean something changed.
6. Manager Span of Control
Total individual contributors ÷ Number of managers
The research-backed sweet spot is 6–10 direct reports for most roles. Below 3 and you're paying management overhead. Above 12 and managers can't actually manage — they're just escalation points.
7. Headcount Growth Rate
((Current FTE − Prior FTE) ÷ Prior FTE) × 100
Measure quarterly. Fast growth without proportional management expansion creates the span-of-control problems above. Flat headcount with rising workload creates the burnout and absenteeism problems above. These numbers connect.
8. Pay Equity Gap
% difference in average compensation between demographic groups for equivalent roles
Even at small company sizes, pay equity gaps compound quickly. A 5% gap at hire becomes an 8% gap at the first review cycle. Calculate by gender and by role level. Target: under 3%.
The Free Workflow: Google Sheets + Claude
Before you buy anything, try this. Based on documentation from similar tracking approaches and user reports from small HR teams, this workflow takes about 30 minutes per month to maintain.
Step 1: Set up your tracker
Create a Google Sheet with one row per month and these columns:
Month | Headcount | New Hires | Terminations | Absent Days | Working Days | Pulse Score | Open Roles | Offers Made | Offers Accepted
Add a second tab called "Metrics" with formulas that calculate the eight numbers above automatically from the raw data.
Step 2: Export your data monthly
Most HRIS tools (BambooHR, Gusto, Rippling, even basic ones) let you export termination reports, headcount snapshots, and time-off summaries. This takes 5–10 minutes.
Step 3: Paste into Claude
Copy your last 6–12 months of metrics data and ask: "Analyze this HR data for a [X]-person company. Flag any trends I should investigate, calculate monthly and annualized turnover, and identify two or three patterns worth a closer look."
Claude will surface what your spreadsheet won't tell you automatically — things like "your absenteeism rate has increased in three consecutive months" or "your offer acceptance rate dropped at the same time you extended time-to-hire."
Step 4: Save the summary
Keep a running document with Claude's monthly summaries. After six months you'll have a genuine trend log — the kind that normally costs $10,000/year to generate automatically.
This is not a replacement for a dedicated people analytics platform at 200 employees. But it's a very defensible starting point at 40.
Looking to go deeper on workforce strategy? See our guide to AI for workforce planning — it covers headcount forecasting and scenario modeling for growing teams.
Comparison: 6 People Analytics Tools
| Tool | Best For | Key Features | Price | Company Size |
|---|---|---|---|---|
| Google Sheets + Claude | DIY tracking, budget-zero teams | Custom metrics, AI analysis, full flexibility | Free | Under 50 |
| BambooHR Analytics | Teams already on BambooHR | Turnover reports, headcount trends, eNPS | ~$8–12/employee/mo (Pro) | 20–500 |
| Lattice | Performance + analytics in one platform | Goal tracking, review cycles, engagement surveys, analytics | $11/person/mo | 50–500 |
| Culture Amp | Engagement-first analytics | Deep survey tools, driver analysis, manager effectiveness | $5–8/employee/mo | 50–2,000 |
| Leapsome | EU teams with OKR alignment | Analytics + OKRs + performance in one tool, GDPR-native | ~$8/person/mo | 50–1,000 |
| Visier | Enterprise HR with complex multi-system data | Predictive analytics, workforce planning, AI insights | Custom (~$30k+/yr) | 1,000+ |
Pricing based on documentation and published rates as of early 2026; verify with vendor before purchase.
But before you open a demo: does your team actually have enough headcount to make ML-driven attrition models meaningful? Most require 200+ employees to produce statistically reliable predictions. For teams under that threshold, the tools below are ranked by practical utility, not predictive sophistication.
Tool Write-Ups
Google Sheets + Claude — Free, Under 50 Employees
The case for starting here is straightforward: most small teams don't have enough data for AI-powered pattern detection to be meaningfully better than human pattern detection. If you have 45 employees and can see your own data, you don't need a machine learning model to tell you that three people left from the same manager's team.
What you need is consistency. Track the eight metrics above every month, ask Claude to analyze trends quarterly, and you'll have a cleaner picture than most companies with paid platforms but no one looking at the data.
The limitation is obvious: this doesn't scale. Above 80–100 employees, manual tracking starts missing things. Connections between data sources (performance reviews linking to retention, pay equity data linking to engagement) that a platform handles automatically become manual work you won't do.
Start here. Upgrade when it breaks.
BambooHR People Analytics — Best for Teams Already on BambooHR
BambooHR's analytics are not a standalone product — they're included in the Pro plan, which also covers performance management, benefits, and the full HRIS suite. If you're already a BambooHR customer, the analytics dashboard is effectively free to unlock.
Based on documentation and user reviews, BambooHR's analytics cover the essentials: turnover reports, headcount trends, time-in-position, and eNPS (employee Net Promoter Score). The reporting interface is clean and non-technical — HR generalists can generate and share reports without data analyst support.
Where it falls short: BambooHR analytics doesn't go deep. There's no predictive modeling, no cross-metric correlation analysis, and limited ability to build custom dashboards. For teams that want simple, clear reporting and already pay for BambooHR's other features, it's a strong option. For teams that want to run sophisticated workforce analysis, it's not built for that.
Best fit: 20–200 employees already using BambooHR. Skip the separate analytics purchase.
Lattice — Performance + Analytics Together
Lattice bundles performance management (reviews, 1-on-1s, goals) with an analytics layer that connects performance data to retention and engagement outcomes. That connection is the real value proposition — most standalone analytics tools pull from HRIS data only, missing the performance context that explains a lot of turnover.
At $11/person/month (based on published pricing as of early 2026), Lattice is positioned as an all-in-one solution for teams that want to connect "how is this person performing?" with "how likely are they to leave?" The analytics include engagement surveys, turnover analysis, and manager effectiveness scores derived from 360-degree feedback.
The downside: Lattice is doing several things at once, and the analytics depth reflects that. Teams primarily looking for sophisticated workforce analytics would get more from Culture Amp. Teams that want performance management and analytics in a single tool that syncs cleanly will find Lattice well-suited.
Best fit: 50–300 employees; teams that want performance and analytics under one roof and don't need deep predictive modeling.
Culture Amp — Engagement-First Analytics
Culture Amp is built from the survey up. The core product is employee listening — engagement surveys, pulse checks, manager effectiveness surveys — with an analytics layer that connects survey responses to retention outcomes, eNPS trends, and engagement driver analysis.
The platform's "driver analysis" feature is genuinely differentiated: it identifies which specific engagement factors most predict employee satisfaction at your organization specifically, not based on generic industry benchmarks. That means you're not guessing whether work-life balance or compensation matters more to your team — Culture Amp tells you based on your data.
Based on documented features and user reviews, Culture Amp's analytics go deeper than BambooHR or Lattice on the survey side, but require meaningful participation rates to generate reliable data. With fewer than 30 employees, survey anonymity becomes a challenge and driver analysis loses statistical validity.
Pricing starts around $5–8/employee/month, making it competitive for mid-market teams with 100–500 employees.
Best fit: 75–2,000 employees; teams where engagement and manager effectiveness are the primary analytics focus, not just headcount tracking.
Leapsome — Best for EU Teams and OKR Alignment
Leapsome is the most European product on this list — built with GDPR compliance as a core design principle rather than a compliance add-on. For companies operating primarily in the EU, that matters: data residency, processing agreements, and consent workflows are handled natively.
Beyond compliance, Leapsome differentiates by connecting people analytics directly to OKR and goal data. The theory: turnover patterns, engagement scores, and performance trends make more sense when viewed against whether teams are hitting their objectives. A team missing OKRs for two consecutive quarters that also has rising absenteeism is telling a different story than a high-OKR team with the same absenteeism rate.
Based on documentation, Leapsome's analytics cover the standard suite — turnover, engagement surveys, performance data — with the OKR integration as the distinguishing layer. Starting price is around $8/person/month.
Best fit: 50–1,000 employees; EU-based or EU-primary companies that already use OKRs and want analytics that connect to goals.
Visier — Enterprise Only, Mentioned for Context
Visier is the category leader in enterprise people analytics. It connects to multiple HR systems simultaneously, runs predictive attrition models, and produces the kind of boardroom-ready workforce intelligence reports that justify a Chief People Officer's budget requests.
It also costs custom-negotiated contracts that typically start around $30,000/year, requires implementation support, and is built for HR teams with dedicated analysts.
This is not the right tool for teams under 500 employees. It's included here as a ceiling reference — if you're growing fast and expect to hit 1,000+ employees within two years, it's worth knowing Visier exists and planning a migration path. For everyone else: the tools above will cover your needs for a fraction of the cost.
Best fit: 1,000+ employees; enterprise HR teams with multi-system data complexity and analytics budgets.
When to Upgrade from Spreadsheets
Three signals that your Google Sheets workflow has hit its limit:
1. You're spending more than 3 hours/month on data collection — When pulling monthly numbers requires chasing five different system exports and reconciling mismatches, the overhead cost has exceeded the tool cost.
2. You're missing cross-metric connections — Absenteeism and performance data are in different systems. You can't easily see whether teams with low engagement scores also have slower time-to-hire. These connections require a platform that ingests multiple data sources.
3. You've grown past 80 employees — Not a hard rule, but around this size, pattern detection from manual data becomes unreliable. There's enough signal that a platform trained on similar companies can surface things you'd miss.
Most teams don't have a tools problem. They have a tracking-consistency problem. No platform fixes that.
Until those three things are true: stick with the spreadsheet. Investing $8–11/employee/month before you need it doesn't make your analytics better — it makes your SaaS bill bigger.
If your people analytics are pointing to performance gaps, the next step is usually systematic performance review data. See our guide on AI for performance reviews to see how to close the loop between analytics and action.
What's in It for You, Practically
Before you demo anything, ask yourself: do you currently review any HR metric monthly? If the answer is no, the tool is not the bottleneck.
Start this week: set up the 8-metric spreadsheet. Pull your last three months of data from whatever HRIS you're using. Ask Claude to analyze it.
If the spreadsheet reveals something surprising — a turnover rate higher than you thought, an offer acceptance rate that's dropped — that's the signal to invest in a platform. If the spreadsheet confirms what you already knew, you've saved yourself a year of $10/employee/month in software spend while you figure out the real problem.
People analytics isn't enterprise software. It's a practice. And like most practices, a consistent simple version beats an inconsistent sophisticated one every time.
For a broader view of where AI is transforming HR — recruiting, onboarding, performance, and beyond — see our complete AI for HR guide.
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Originally published on Superdots.
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