The Equipment Register Problem in Mining M&A
Every mining acquisition involves an equipment register review. The register is supposed to tell you what assets the target owns, where they are, what condition they are in, and what they are worth. In practice, it tells you almost none of those things — at least not without significant work.
The typical data room equipment register is a spreadsheet with 2,000–10,000 rows, exported from whatever EAM system the target uses (or, more commonly, assembled manually from multiple systems). The OEM names are inconsistent. The model numbers are abbreviated. The locations are free-text. The serial numbers are present for about 60% of records. The status column has 15 different values that mean "active".
Acquirers spend weeks manually cleaning this data — and still miss the signals that matter.
What Normalisation Reveals
A normalised equipment register reveals maintenance maturity signals that raw data hides.
Serial number coverage is the single most important signal. A mine site where 70%+ of equipment records have valid serial numbers has a maintenance team that tracks assets properly. A site where fewer than 50% of records have serials has a deferred maintenance problem — assets are being run to failure without proper lifecycle tracking.
OEM concentration tells you about supply chain risk. A site where 80% of mobile equipment is Caterpillar has a single-OEM dependency that affects parts availability, service contracts, and replacement cost. A diversified OEM fleet has different risks.
Equipment age distribution reveals capital expenditure patterns. A fleet where 40% of assets are past their expected service life signals deferred capital expenditure — the acquirer will need to budget for replacement sooner than the target's financial model suggests.
Location hierarchy completeness is a proxy for operational structure. A site where every asset has a complete mine hierarchy location (pit/level/zone) has a maintenance team that manages assets by location — enabling condition-based maintenance and predictive analytics. A site where 60% of assets have no location data has a reactive maintenance culture.
The Compliance Audit Pack
The standard deliverable for EAM due diligence is the Compliance Audit Pack — a 7-tab XLSX covering:
Cover — with sign-off block for the reviewing engineer
Executive Summary — quality score distribution, key findings, red flags
Asset Register — the normalised equipment register with quality scores
Data Quality Heat Map — field-by-field quality breakdown by equipment category
Exceptions — all records below 50 quality score, grouped by issue type
Compliance Checklist — ISO 55001 / PAS 55 field coverage assessment
Methodology — scoring formula, classification rules, field mapping reference
Struktive generates this pack automatically from the normalised equipment register. Upload the data room CSV, download the Compliance Audit Pack, and complete the EAM review in hours rather than weeks.