Analytics

HR analytics software for people teams that need evidence

HR analytics has an authority problem. Finance walks into the room with numbers nobody argues with. People teams walk in with an engagement score from a survey nobody trusts and a time-to-fill metric that measures the recruiter, not the hire.

Quality-of-hire

Measured against performance, not time-to-fill

Continuous

Adverse impact monitoring on live pipelines

Exportable

CSV and PDF, for the board deck you actually have to build

The metrics most HR dashboards report are the ones that are easy to collect

Time-to-fill, cost-per-hire and source-of-hire are operational metrics for the recruiting function. They are worth tracking and they say nothing about whether the people you hired were the right people. Optimising them in isolation produces fast, cheap, bad hiring.

Quality-of-hire is the metric that matters and it is hard, because it requires linking a pre-hire measurement to a post-hire outcome. Most organisations never close that loop, which is why quality-of-hire remains the most-cited and least-measured metric in the field.

Closing the loop

TalentSpark holds the pre-hire measurement: a scored psychometric profile with validity flags, taken before anyone knew how the hire would turn out. Connect a performance outcome and you can finally ask whether the traits you selected on predicted anything.

Once enough hires accumulate, local criterion validation reports which traits predict performance in your roles, with confidence intervals wide enough to be honest about how much you actually know. That is a defensible answer to 'is our hiring working', and it is the first one most people teams have ever had.

What is on the dashboards

Six analytical surfaces, each answering a question an executive will ask.

  • Predictive analytics — attrition risk and performance forecasts by team
  • DEI and adverse impact — selection rates by protected group against the 4/5ths rule, continuously
  • Benchmark comparison — your trait distributions against job family and industry cohorts
  • Assessment quality — item-level psychometrics, reliability, and drift detection on your item bank
  • Candidate experience — completion, abandonment and time-on-assessment, segmented
  • Industry network — anonymised cross-organisation trait norms for the roles you hire

Built for the audit you have not had yet

Every score, flag and generated recommendation is logged with its inputs. Adverse impact is computed on live pipelines rather than reconstructed afterwards. GDPR data subject rights — access, rectification, erasure, portability — are handled as product features, and a DPA is available to every customer.

None of this is exciting. All of it is what you will need on the day someone asks you to justify a pattern in your hiring data, and reconstructing it retrospectively is not possible.

Frequently asked questions

What is the difference between HR analytics and people analytics?

Nothing consistent. 'People analytics' is the more current term and tends to imply a broader remit than HR-function reporting. Both describe applying quantitative methods to workforce questions.

Do we need a data team to use this?

No. The analyses that require statistical judgement — local validation, adverse impact significance — are computed and reported with their assumptions stated. If your sample is too small to support a conclusion, the platform says so rather than rendering a chart.

Can we export the data?

Yes. CSV export on every analytical surface, PDF report generation, and shareable report links with expiry.

Predict performance before day one.

Validated psychometrics and Claude AI, in one platform. No credit card required.