How SPAR replaced months of manual data work with Atlas.
A unified, audit-grade view of spend across more than 20 markets, built on data that used to take a team of analysts months to wrangle by hand.
20+ markets
Inconsistent ERP data
Twenty-plus markets, twenty-plus ways of recording spend.
As a retail group operating across more than 20 countries, SPAR's procurement data lived in a patchwork of ERP systems, each with its own supplier records, category labels, and data quality.
Building a single, trustworthy view of group spend meant reconciling all of it by hand, a process that consumed months of analyst time and was out of date the moment it finished. Consolidation opportunities and pricing comparisons stayed out of reach because no one could trust the underlying numbers.
- Spend fragmented across 20+ market ERP systems
- Inconsistent supplier records and category labels
- Months of manual reconciliation for one group view
- Consolidation and pricing analysis effectively blocked
Atlas did the reconciliation, automatically.
Connect every market
Atlas ingested spend from each market's ERP without rip-and-replace, mapping disparate structures into one model.
Classify & normalize
Every line classified to a procurement-native taxonomy and every supplier harmonized against a single master.
Govern for trust
Audit-grade accuracy with the evidence behind every classification, so the group view could be relied on.
"Mithra gave us a clean, trusted view of our spend across more than 20 markets that we simply didn't have before, and replaced months of manual work."
Kate HandsSPAR- One unified spend view across all 20+ markets
- Audit-grade classification accuracy, with evidence
- Supplier consolidation opportunities surfaced
- First clean outputs in weeks, not quarters
A foundation the whole group can build on.
With a clean, governed spend layer in place, SPAR moved from arguing about the numbers to acting on them, comparing pricing across markets and identifying where suppliers could be consolidated.
The months of manual reconciliation are gone. The data stays current as it refreshes, and the savings opportunities that were invisible before are now ranked and ready to work.
See more customer storiesSee what Mithra could find in your spend data.
Bring a representative sample, and we'll show you your classified spend, normalized suppliers, and a prioritized savings analysis, on your own data.