Gamfi for HR · Module
See which sites and teams have rising turnover – before the quarterly report counts it
In the Gamfi platform you see turnover per site, role and manager, alongside signals from day-to-day work: stalled onboarding, overdue training, fewer completed check-ins, a low survey result. All on the same dashboard where the manager runs onboarding and training – and they get notified when a threshold is crossed.
The signal goes to the manager as a reason to talk with the team – not as a judgement on an employee.
How it works
From data the platform already records, to a conversation with the right person – before turnover becomes a number from the past.
- 1
The system gathers what happens in Gamfi
Onboarding, training, check-ins and surveys – the more processes you run here, the fuller the picture of the team – in one view of the team and the site.
- 2
Crossing a threshold raises a signal
A drop in activity, stalled onboarding, a low survey result or overdue training – a rule on current data, not a forecast from your history.
- 3
The signal goes to the manager and HR as a reason to talk
You can see what the signal is based on and which team it concerns – a person decides what happens next, not the system.
- 4
The action gets recorded and checked
A conversation, a change in workload, or support with onboarding – with an owner, a deadline and information on whether the signal in the team has dropped.
More, because it is one system
A signal only forms when data about onboarding, training, mood and meetings lives in one system.
The signal is built from data you already have in one place
You do not compile four exports to see a pattern – activity, onboarding, surveys and training all sit on the same platform.
The conversation and the action in the same system as the signal
A signal turns into a task, support with onboarding, or a training path – without switching to a separate tool.
The manager's view shows the team, not just a number on the board's dashboard
A manager sees the pulse of their team in the same place where they run check-ins and training – a regional director sees the whole network with drill-down by site.
See how Gamfi is used in organisations with distributed teamsCustomers →
Describe your need
Describe the situation in your own words – we will write back with how the Gamfi platform answers that challenge. You decide about a meeting after you have read the answer.
What you get in Gamfi
What you need to deal with team turnover before it turns into a number in a report.
Team signals, not a judgement on a person
- A drop in team activity as a signalfewer logins and completed tasks in the team, visible earlier than in a quarterly review
- Stalled onboarding in the team as a signalyou can see how many days a step has been stuck
- A low engagement survey result in the team as a signalread while keeping the anonymity threshold from the survey module
- Overdue mandatory training in the team as a signalthe same path progress you already see in the Learning and Development module
- A falling share of completed 1:1 meetings in the team as a signalthe full description of 1:1 meetings is in the Performance Reviews module, here only whether they happened counts
Turnover per site, role and manager
- Resignations counted separately from dismissalswithout this split, a drop in turnover after layoffs looks like a success
- Turnover per site, drilling down through the structurethe same view in which a regional director drills down from the company to a single store
- Turnover per role and departmenta filter by organisational structure, without manually compiling a spreadsheet
- Turnover visible to a manager for their own teamthe same Manager View where they run the rest of their work with the team
A signal on current data, not a prediction from history
- The signal works from the first day of using Gamfiit does not require importing years of HR history or integrating with a payroll/HR system
- You can see what data the signal is based ona drop in activity, stalled onboarding, a survey result – named explicitly, not a black box
A person decides, not the system
- The signal goes to the manager and HR as a reason to talknot as a judgement or a verdict on the team
- An automatic alert when a signal is raisedthe alert goes to the manager, and upward after the deadline
- A weekly AI summarywhat has changed in teams and what to look at, not a judgement on any one person
- No HR decision made automaticallythe manager and HR decide what happens next with the team
Action after a signal
- An action plan with an owner and a deadline in the same systema conversation, a change in workload, or support with onboarding – not just a note to read
- Automatic reminders and escalations for overdue actionsa backlog goes back to the owner, then to the manager
- A record of actions over timeyou can see whether the signal in the team dropped after the action taken
Confidentiality and compliance
- A minimum headcount threshold below which a signal does not go down to the teamin smaller teams the signal rolls up a level – you set the threshold
- Turnover per manager as a team indicatorit is not a judgement on the manager's work – you control who sees it by role
- The scope of signals ready to present to employee representativeswe describe what is collected and who sees it, so it can be presented before rollout
- Data hosted in the EU, GDPR processor model
- An immutable event log
- A signal at team level, not at individual leveldeliberately – assessing the departure risk of an individual employee falls under EU AI regulation and GDPR
Common questions
Open the one that applies to you.
Do you point out which specific employees might leave?
No. Assessing the departure risk of a specific employee is classed as a high-risk system under the EU AI Act – it requires an impact assessment and consultation with employee representatives. That is why we do not do it. We show signals at team and site level.
Where does the signal come from if you do not have any history with us yet?
From data the platform records from day one: activity, onboarding progress, survey results, completed training. It is a rule on current data, not a model trained on your HR history – you do not need years of data or integration with a payroll/HR system for the signal to start working.
Is this an AI-based turnover prediction?
Not in the sense of a model trained on departure history – we do not have such a model today, either on your data or on our own customer base. What you see is threshold rules on the platform's current data, supplemented by a weekly AI summary: what has changed in the team and why it is worth a look.
Do you compare our turnover with the industry?
We do not have our own benchmark database against other companies today. You see turnover broken down by site, role and manager – for many organisations that is a more useful signal than a comparison to an industry average, because it shows where the problem is local and where it is company-wide.
What happens to the signal on the manager's side?
The signal arrives as a reason to talk, not as a ready-made judgement. The conversation can produce a task with an owner and a deadline in the same system, and the next reading of the signal shows whether anything has changed.
Will we find analysis of reasons for departures that have already happened here?
No – we cover exit interviews and after-the-fact analysis of reasons for leaving in the Offboarding module. Here we focus on the signal that appears before someone hands in their notice.
What does rolling out this scope look like in practice?
We set up access to signals to match your team and site structure. From your side we need the organisational structure and one person deciding who in the company sees signals for which team.
What does a manager see if they do not see a list of people at risk of leaving?
They see by name who has overdue onboarding, training or a missed check-in – that is a task status, not a judgement on a person. The signal says which team to look at; the tasks say who to talk to.
What if our managers do not react to the signal?
That is the most common reason such tools do not work, so we do not leave it to goodwill. A signal produces a task with an owner and a deadline, a backlog escalates upward, and HR sees on the dashboard which teams have no activity.
Will the survey signal work in a small store?
No – and we say that plainly. In small teams the survey result will not show up because of the anonymity threshold, and those are often exactly the sites with the highest turnover. Operational signals work there instead: stalled onboarding, overdue training and missed check-ins.
How do you know someone has left if you do not have a connector to HR systems?
We calculate signals from data the platform records itself – onboarding, training, check-ins and surveys. We calculate turnover from departures closed in Gamfi or uploaded from your HR system. These are two different sources, and we do not pretend one replaces the other.
Does an employee know their team received a signal?
The manager and HR see the signal, within the scope you grant by role. A manager can dismiss it with a reason – and then a record stays in the event log along with that reason. We describe the scope of signals and who sees them so it can be presented to employee representatives before rollout.
What determines the price?
Signals work on data from modules you already have – you do not buy a separate data set. Price depends on a few factors: the number of people covered by the module, the number of teams and sites, and the scale of rollout. We are happy to go through the details on a call and in further contact.
For your IT team
The shortest version of the answer for security teams, when data about team activity and mood is at stake.
- A signal at team and site level, with no risk indicator against an employee's name
- AI suggestions are a prompt for a person, not a decision by the system – the manager and HR make the HR decision
- An immutable event log, data hosted in the EU
- A manager without a company email logs in with a link or by SMS, from a phone
- Data through a documented API, and a file import at the start too