Harsco Environmental and Ensemble AI will share how they approached one of the most persistent maintenance problems in industry: spare parts data that is duplicated, inconsistent and difficult to trust across sites and systems.

This session will walk through the practical steps taken to analyse real ERP and CMMS data, identify duplicate and low-quality records, and apply AI to support maintenance, procurement and engineering teams with clearer decision-making.

Rather than focusing on AI hype, the session focuses on practical implementation, lessons learned, and how organisations can begin improving reliability and inventory decisions using the data they already have.

• How to identify duplicate spare parts at scale
• How to improve trust in ERP and CMMS data
• How to combine AI with engineering judgement
• How to align maintenance and procurement teams
• How to start without replacing existing systems
• Lessons learned from a live industrial deployment

3 Key Learnings:

1. Most maintenance data problems are operational problems first - Bad spare parts data directly impacts reliability, purchasing and downtime.
2. AI is most valuable when applied to maintenance fundamentals - The biggest wins often come from improving existing processes and data quality.
3. Engineers must remain in control of maintenance decisions - AI can accelerate analysis and insight, but trust comes from transparency and evidence.