Operations and supply chain

Warranty & Field-Quality Early Warning

Topic and change-point detection over claims and technician notes, joined to build, lot, and supplier data, opens investigations while the problem is still small.

The problem

A field-quality problem shows up first as scattered phrases in technician notes and claims. By the time it is visible in monthly totals, many more units have been built and shipped, and warranty cost has already grown.

Who owns it

The head of quality or field quality, with engineering, supplier quality, and the warranty team.

What it learns from

  • Warranty claims
  • Technician and service notes
  • Build, lot, and serial records
  • Supplier and component data
  • Returned-part analysis

How it works

Predict, decide, act, measure

The same four steps in every solution, in this order, each one visible to the team that owns it.

  1. 01

    Detects emerging issues

    Text models group claims and notes into topics, and change-point detection flags a topic whose rate is rising for a build period, lot, plant, or supplier. Each signal carries the claims behind it.

  2. 02

    Decides what to investigate through a policy

    Signals are ranked by affected volume, cost, and severity, within an alert budget sized to the investigation team. Any signal touching safety goes straight to a person.

  3. 03

    Acts in the quality system

    An investigation opens in the quality or case-management system with the evidence attached. The actions that follow are containment, supplier recovery, and a design fix.

  4. 04

    Measures days to detect and warranty cost per unit

    Days from first claim to investigation are compared with past issues, and warranty cost per unit is tracked for the affected products. Investigations confirmed or closed as noise keep the detection honest.

What it moves

The business levers

Earlier detection

Problems found while fewer units are affected.

Warranty cost

Lower warranty cost per unit as issues are contained sooner.

Supplier recovery

Evidence that ties a failure to a supplier's lot.

Design fixes

Engineering gets the drivers of a failure, not only the count.

Proof

How the return is proven

The return is the warranty cost avoided by earlier containment, with days to detect compared against past issues and stated against the return model agreed up front. Signal precision, the share of investigations confirmed, is reported beside it.

What you see: the ROI readout

Every solution produces the same readout, assembled from the system's own records rather than built by hand.

Correctness

The checks the pipeline passed on your own data: leakage, point-in-time, and entity resolution.

Incrementality

The incremental effect against the holdout or equivalent design, with its confidence interval.

Return

The measured return against the investment, set beside the return model agreed before work started.

Guardrails

Complaints, cost, margin, fairness, and contact limits, each shown against its bounds.

Audit extract

Every score, action, and outcome, with the model and policy versions behind it.

Governance

What is governed

Access, approvals, and the audit trail are part of the solution, not a review step added at the end.

Identity-scoped access

Claims, notes, and supplier data are visible by role through your single sign-on.

Approval gates

Containment actions and supplier claims need the quality lead's approval.

Audit trail

Every signal, investigation, and outcome is logged with its evidence.

Safety reporting

Signals that touch safety follow your product-safety and regulatory reporting process, always with a person deciding.

Why it holds up

Trained on your data, framed by the outcome

This solution trains models on your own data, checks every stage from data to decision, and is measured against the outcome it was built for. Because its predictive power is measured, it also shows the drivers behind the metric, so your team can fix causes as well as act on scores.

Why solutions hold up

Start with one decision

Bring the problem and the systems your team works in. We scope the first solution with you, agree how its return will be measured, and run it in production with your people.