AI for HR · Solutions

Put goals, output and peer feedback side by side, so a manager sees the whole person.

AI Performance Analytics gathers each person’s goals, role-relevant output, attendance and peer feedback into one view, then points out where a draft rating and the records disagree. It helps managers prepare reviews and spot coaching needs. Ratings stay with people.

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What it is

A yearly review often rests on what the manager remembers from the last two months. The loud performer is rated high, while the steady one who closed the most tickets is rated only average. Memory is a poor record.

When output, goals and colleague feedback sit together, the manager starts the review with a fuller picture, and raw numbers appear beside the context that explains them. The software marks mismatches. Judgement stays with the person holding the form.

Where it goes wrong today

The problems this is meant to ease.

Reviews rest on recent memory

A manager recalls the last two months and forgets the first ten, so a strong spring counts for little at appraisal time. The employee senses it. Faith in the process fades.

Numbers arrive without context

A low sales figure may belong to the hardest territory, and a high ticket count to the easiest queue, so raw totals reward the wrong people. Good work goes unrecognised.

Quiet contributors go unseen

The colleague who covers absences and trains newcomers produces no headline figure, and at appraisal time the louder person collects the credit. Nobody records the cover.

Managers rate by different standards

One manager gives most people the top rating while another gives hardly anyone, and HR cannot tell whether the gap is real or a habit of the rater. Fairness suffers.

Coaching starts too late

Weak results are noticed at year end, when nothing can be done about them. The conversation that could have helped in March never takes place.

Inside the module

What AI performance analytics does.

Metrics that fit the role

A technician is read on jobs closed and repeat visits, a coordinator on bookings handled, and a recruiter on joiners placed. Measures are agreed per role with the manager. They are never imposed.

Goal and productivity trends

Targets, results by month and the direction of travel appear on one page for the review period, so a manager can tell steady work from a late slump. The two look different.

Coaching and development prompts

Where results dip in one area while the rest hold, the page suggests a coaching topic for the manager to raise in conversation. It is a prompt. It is not a verdict.

Evidence ready for the review

Goals, output, attendance and feedback received are gathered for the period, with each source named, so a review is written from the record and not from memory alone.

Context beside the raw figures

Territory difficulty, shift pattern, cover for absent colleagues and the manager’s own notes sit next to the numbers, because a figure shown without its circumstances misleads. Qualitative work is recorded too.

Peer feedback, collected and grouped

Short questions go to colleagues the manager picks, and the comments are grouped by theme. Names stay hidden from the reviewer unless you switch that on.

Human review and employee response

The manager writes the rating and HR checks it, while the employee reads their own page and can add a reply. Any change of rating carries a stored reason for next year.

Where it gets used

What this looks like in a working week.

An IT services company reviewing engineers

Tickets closed, repeat faults and client notes appear for each engineer, and the manager sees where a rating and the record disagree before signing the form. The check is quick.

A hospital reviewing ward staff

Attendance, shift cover and peer feedback appear together, with measures chosen for each role. Where a nurse has no output figure, the page leans on goals and feedback.

A security agency reviewing site supervisors

Missed rounds, incident reports and client remarks sit beside each supervisor’s goals, so the operations head can spot someone with good numbers but poor team feedback. Coaching follows.

A staffing agency reviewing recruiters

Placements are read against the difficulty of the roles each recruiter handled, so one working scarce skills is not compared with another on easy requests. Coaching topics follow.

A software team preparing yearly reviews

Delivered work, code review comments and peer feedback are gathered for each developer. The lead writes from the page and not from the last sprint alone.

Who touches it

The people who open this every day.

Department manager

Prepares each review from one page. Writes the final rating.

HR head

Looks for managers whose ratings differ widely from their teams’ recorded output.

Team member

Reads their own goals, results and shared feedback. May add a reply.

How it is set up

From first conversation to daily use.

Discovery with HR and managers
Agree which roles are covered first and what a fair measure looks like in each. Then check which systems hold the output figures and how goals are recorded today.
Data readiness
Clean the goal records, link output figures to employee numbers, and settle the peer feedback questions. Roles with no measurable output are marked, so the page never invents a number for them.
Trial on last cycle’s reviews
Prepare one team’s reviews from the real goals, output and feedback of the last cycle. Then the managers compare each page with the rating they actually gave.
Managers and HR test the pages
Managers, HR and a few employees read the trial pages and say what is missing or unfair to them. Measures, context notes and visibility rules are changed to suit.
Going live
More teams join for the next review cycle. Employees open their own pages, and every rating is still written by a manager and checked by HR.
Review afterwards
After the cycle, HR looks at how ratings and records line up across managers. Measures that nobody trusts are dropped, and the feedback questions are tidied.

Measuring it

How you would know it is working.

Record where you stand before it goes live, so the change is measured against your own figures.

Goal attainment is the share of agreed goals met in the review period, and the baseline is the goal records and results you hold before go-live.
Development progress counts coaching topics raised and followed up, with the starting position read from the review notes of earlier cycles.
Review consistency compares how different managers rate similar recorded output, and the baseline is the set of ratings given in the last cycle.
Feedback coverage counts reviews that include peer feedback and context notes, set against the review forms of the last cycle.
Employee response counts reviews where the person read their page or replied, and the baseline is the acknowledgements recorded before go-live.

Used responsibly

Where a person stays in charge.

A person writes every rating

The software highlights mismatches and never produces a rating, a pay ranking or a promotion decision. A manager rates, and HR reviews that rating.

Numbers never travel alone

Output figures appear with their context, and roles with no measurable output are shown that way. A thin record looks thin, and no score is invented to fill the gap.

Employees see their own page

Each person can read the same figures their manager sees and add a response, so surprises in a review become rare. Visibility is set before launch.

Monitoring rules differ by country

Rules on measuring staff at work vary between countries, so what is collected is agreed beforehand with your own lawyer. The tool prepares evidence. Legal questions go to your counsel.

Peer feedback is handled carefully

Comments are grouped and names are hidden by default. Feedback is a prompt for the manager to ask questions, and it is not proof that something happened.

How it fits

It is one part of a system, not an island.

A module earns its place by what it passes to the next one. These are the connections we set up most often.

Performance management
Attendance and time tracking
Ticket management or order management
Employee database
Payroll management

Already built in

Products that include it.

Built for you

How we would put it in.

Common questions

Questions owners ask about AI performance analytics.

Can it rate employees automatically?

No. It shows numbers and feedback and marks where they disagree with a draft rating, but the manager writes the rating and HR reviews it. Pay and promotion are decided by people.

What if some jobs have no measurable output?

Those roles lean on goals and peer feedback instead. The page does not invent a number for a role that has none. A thin record is shown as thin.

Will employees feel watched?

Tell them what is collected before you switch it on. Showing people their own page, with the same figures their manager sees, tends to settle the worry, and rules on staff monitoring differ by country, so take local advice.

Do we need a year of data first?

You need at least one full review cycle of goals and results recorded in the same way across the team. Without that, comparisons mislead. They do not help.

How does it treat context and quiet contributors?

Territory, shift and cover work appear beside the figures, and people with steady results or heavy cover are listed for the manager to notice. Recognition remains the manager’s call.

What does it connect to?

It reads your performance records, attendance, employee database and whichever order or ticket system holds the output figures. A system with no export needs a one-time load.

Is it worth it for a small team?

If one manager sees every person daily and keeps good notes, the review page adds little. It helps once several managers rate people by different habits.

What does it cost and how much effort is the setup?

Most effort goes into agreeing measures for each role and linking the output records. We scope it after looking at your systems. The quote is in writing.

Who needs it most

Businesses that ask for this.

Next to it

Modules that work with it.

Talk to us

Tell us how you handle AI performance analytics today.

A spreadsheet, a register or another system: say which, and we will tell you plainly what is worth changing.

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