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Use Case

Predictive Maintenance

Forecast failures on fridges, ovens and conveyors before they disrupt trading.

Planned
Value chainStore OperationsObjectiveMitigate RiskAI typeModelKPIUnplanned downtime −40%Value£150KFeasibilityMedium
Dependencies
Asset & IoT, Store
Feasibility
Medium — needs targeted data & integration uplift
Recommendation
📅 Planned — sequence after data & integration uplift

AI deployment flow

How signal turns into outcome for this use case.

Insight
Forecast failures on fridges, ovens and conveyors before they disrupt trading.
Business Objective
Mitigate Risk
Data Required
Asset & IoT, Store
AI
Model — Predictive Maintenance
Decision
KPI: Unplanned downtime −40%
Action
Store Operations systems
Outcome
£150K value

Business outcomes

  • Primary KPIUnplanned downtime −40%
  • Estimated annual value£150K
  • Strategic objectiveMitigate Risk
  • Value chain stageStore Operations

Type of AI

ModelPredictive or generative model that scores, forecasts or generates content.

Action surfaces

Store Operations systems

Data sources required

Unified domains powering this use case via Xfuze.

Asset & IoT
Store Operations

Fridges, ovens, robotics and sensor telemetry — uptime, energy and maintenance.

Typical sources
IoT platformCMMSBMS
Store
Store Operations

Store master, clusters, formats, openings, footfall and operational telemetry.

Typical sources
ERPStore opsPeople countersBMS

Related use cases

Same value chain or business objective.