Automated Flight Risk & Retention Scoring in Manufacturing

AI flight risk scoring ingests real-time operational data from your SAP S/4HANA, Plex, or Epicor systems - OEE trends, unplanned downtime events, shift assignments, and line changeovers - and correlates it with HR signals like tenure and compensation to flag employees whose patterns match past departures - early enough for a retention conversation to change the outcome. Unlike generic engagement surveys, this approach captures Manufacturing-specific stress drivers: a quality inspector burned out on high-defect production lines, a maintenance technician working excessive overtime during equipment failures, or a shift supervisor managing understaffed changeovers. The model weights operational burden against role criticality and internal mobility, surfacing only the departures that matter most to your plant's stability and throughput.

Yes, within the limits we're honest about. All data transmission between your SAP, Epicor, or MES systems and the AI engine is encrypted end-to-end, and access is role-gated so HR managers see only their plant's data. Processing runs within your designated cloud region or on-premise deployment, and the integration is built around the compliance and documentation requirements your plant already operates under. No vendor can honestly promise absolute security, so don't take our word for it - ask to see our data-processing terms and put them in the contract before you sign.

Plan for a working system inside the first 100 days. Weeks 1-3 involve data mapping and integration testing with your SAP S/4HANA, Epicor, or Plex instance and HR systems. Weeks 4-8 cover model training on your historical operational and HR data, with weekly calibration reviews. Weeks 9-14 include pilot testing with your HR team, staff training, and staged rollout across your plant locations. A rollout like this is scoped to show measurable results - flagged flight risks validated against actual departures - within 60 days of go-live, with model accuracy and intervention success improving continuously through month 6.

Yes, with one caveat: the intervention menu has to be scoped to your collective bargaining agreement before go-live. Seniority-based scheduling and pay bands limit what HR can offer an individual employee, so compensation-based interventions need labor relations review first. The signal side is unaffected - the system can still surface burnout patterns, advancement readiness, and structural drivers like an unsustainable shift rotation - and those findings often matter more in a union environment, because fixing the structure is what the CBA does allow.

That is your call, and we recommend making it deliberately rather than by default. The system reads operational data your platforms already record - OEE trends, shift assignments, overtime hours, line changeover events - not private communications, and you can exclude any field from the model. Every intervention still requires human approval, so nothing reaches an employee except a manager deciding to act. Most plants position it internally the way it actually works: a tool that helps leadership notice when a good operator is being run into the ground before they walk.

No. Your current team stays - this is about the roles you have not posted yet. The system does the triage HR was never staffed for: reading the ERP and MES feeds, scoring hundreds of employee records weekly, and drafting intervention options. Your HR managers and plant leadership keep every judgment call - who gets a conversation, what gets offered, and when. What changes is that HR stops learning about a departure from the resignation letter.

Three things, in order of value. First, early warning: risk flags arrive while a shift swap or compensation review can still change the outcome, instead of at the exit interview. Second, prioritization: alerts are ranked by replacement cost and time-to-productivity, so a wavering maintenance technician on aging equipment outranks an easily backfilled general operator. Third, structural insight: over time the data shows which lines, shifts, and roles burn people out, so operations can fix the cause instead of HR forever treating the symptoms.