Enrichment Case Study
From 18 characters to a canonical source of truth
A single fragmented MRO line — an 18-character “ACCELERATOR SWITCH” — entered the Mōksana data utility and came back as a fully resolved, attribute-rich, governed equipment record. This is the story of how fragmented spare-parts data becomes a continuous, API-driven source of truth.
The starting state
Fragmented data hides what you already own
Asset-heavy operators run on millions of MRO and spare-parts records scattered across ERPs, EAMs, and site spreadsheets. Most arrived as terse free text typed at a counter years ago. On their own, those rows can't be matched, enriched, or trusted — so spend leaks, downtime risk hides, and every new system inherits the mess.
As found in the ERP
ACCELERATOR SWITCH
- An 18-character free-text description with no manufacturer, model, or part number
- The same component spelled a dozen ways across plants, ERPs, and spreadsheets
- No structured attributes to search, match, or de-duplicate against
- Buyers re-sourcing parts that already sit on a shelf two sites away
One record, run through the utility
Matched against the 3M+ SKU knowledge graph, the row resolved to a specific Allen-Bradley part at 0.95 confidence — and came back 13.1× richer.
Before · as found
- Description
- ACCELERATOR SWITCH
- Manufacturer
- —
- Model / part no.
- —
- Structured attributes
- 0
- Characters
- 18
After · Mōksana canonical record
- Manufacturer
- Allen-Bradley
- Model / part no.
- 800T-FJ29A4
- Class
- 30 mm push button / selector switch
- Structured attributes
- 10
- Characters
- 236
The process
How fragmented data becomes a utility
The same five steps that resolved one ACCELERATOR SWITCH run continuously across the entire catalog — not as a one-time cleanse, but as always-on infrastructure.
Match
Every incoming row is matched against the 3M+ SKU knowledge graph — resolving free-text noise to a specific part with a confidence score, so nothing is guessed silently.
Standardize
Descriptions, units, and naming are normalized to one canonical schema, collapsing the dozen spellings of the same component into a single trusted record.
Enrich
Manufacturer, model, classification, and technical attributes are appended from the graph — turning an 18-character string into a 236-character, 10-attribute record.
Govern
Records are continuously validated against the shared graph, so quality holds as new parts, sites, and acquisitions come online instead of decaying between projects.
Serve via API
Clean, enriched data is delivered through a real-time API to procurement, CMMS, EAM, and analytics — one integration, every site, on demand.
What it looks like at scale
One record proves the method. Run across millions of rows, the same engine turns a fragmented catalog into a clean, canonical, continuously governed source of truth.
The outcome
A continuous, API-driven source of truth
The Industrial Data Utility model means clean data is no longer a project you re-run — it's infrastructure your systems call. The record stays resolved, enriched, and governed long after the first match.
New to the category? Start with our guide to MRO data management, or see how the utility model compares to project-based cleansing.
See what your catalog looks like enriched
Send us a sample of your fragmented MRO data and we'll show you the same before-and-after on your own records — matched, enriched, and ready to serve through the API.
Book a data assessment