Mithra, live: two spend use cases, in detail.
Rather than a polished, high-level deck, this session went straight into the product, because the devil is in the detail. Two real engagements, anonymized, showing exactly how the data gets cleaned, classified, and turned into opportunity.
Rasa RaoufiCo-founder, Mithra
Built out of ten years of procurement frustration.
Mithra is a best-of-breed spend analytics solution focused on strategic sourcing and category management. It started with a simple frustration: how long it took to deliver value that should have been simple, across a decade of working with CPOs and category teams.
A Dutch startup based in Amsterdam, with a second office in Eindhoven, Mithra began as a concept in 2020 and was founded at the end of 2021. The early focus is to cut the cognitive load on the people receiving the data, category managers, sourcing managers, analysts and buyers, who today spend between 30% and 70% of their time crunching and cleansing data instead of acting on insight.
"We want to turn the equation around, so the people in the business can do what they love: working on insights and executing on the opportunities they see."
What's the greatest roadblock to addressable spend?
A live poll, framed around Gartner's four key pillars, taxonomy, data & IT dependencies, resources, and organizational structure. The answer was emphatic.
Per Gartner, across every pillar, over 40% of the roadblock traces back to fragmented data sources, IT dependencies, and data quality.
The winner, by a wide margin
Multiple, disconnected systems and IT dependencies were voted the single greatest barrier, ahead of taxonomy, resources, and org structure. It's the thread running through both use cases that followed.
A global food processor, from 12% spend visibility to 99% in weeks.
One of the world's largest food processing companies, and one of the toughest problems in procurement: indirect spend, across a decentralized organization.
They had multiple, incomplete taxonomies, limited resources, and a fully decentralized procurement team that wasn't connected. The starting point: visibility into just 7% of suppliers and 12% of spend.
How it was done
Refine the taxonomy, together
Instead of 20 conflicting Excel files, the taxonomy builder let the business bring its spend hierarchy, share it, give and reflect feedback in real time, and push changes through approvals back into SAP. This client modified their taxonomy three times.
Augment thin transactional data
With only ~30% of spend on a PO and patchy supplier master data, tailored algorithms enriched each supplier with external data, what they do, how their spend is categorized elsewhere, growth, then ran categorization against the ideal taxonomy in days.
Review by exception
Users across the decentralized business reviewed the machine's suggestions only where needed, roughly half an hour to an hour each over three weeks, and every correction taught the algorithm to replicate it across the rest.
Segment, consolidate, and act
Suppliers were segmented into strategic, critical and transactional, spend concentration surfaced per category, and finance and treasury were brought onto one view of the savings, e.g. consolidating fragmented HR consultancy into a single supplier.
"The spend taxonomy is the lens procurement looks through. With a dirty lens, you can't see what's relevant, or act on it."
A global consumer brand, sizing an acquisition's synergy in a day, not months.
Built after more than a hundred conversations over eighteen months, the Spend Synergy Finder helps with mergers and acquisitions, and with centralizing a decentralized procurement organization.
Capture & scan
From an extract, in days, see the common suppliers and overlapping categories across two businesses or units, with supplier normalization already done in the background.
Map the taxonomies
AI does the heavy lifting of associating similar categories across both organizations; SMEs review, add context, and override, down to the transactional level.
Prioritize opportunities
Spot a group-wide master agreement on a supplier common to both sides, and work synergy opportunities in parallel, before any integration decision is made.
Merge, frictionless
A two-stage merge, taxonomy mapping first, then transactional detail, brings a business into your spend without forcing everything into one ERP.
From a 6–8 month exercise to a same-day scan.
Due-diligence synergy analysis at this scale used to take six to eight months, with little early exposure to the other company. The goal now is a maximum of a day, so procurement can be proactive before integration even begins.
Digital Procurement in Practice, in full.
Questions & answers
It depends on how clean the data and taxonomy are to start. With a complete taxonomy, Mithra's output is ready in days, often within a week and a half. The rest is SME review, typically two to six weeks of feedback and fine-tuning.
Through external data sources plus crawling the web. Matching uses what the client can share, supplier name and location as a baseline, and EAC or DUNS numbers where available, to complete the picture reliably.
A self-service model: extract any format from your ERP or other sources and drag and drop it into Mithra. API integrations are on the roadmap as engagements move forward.
Yes, via API or a shared extract. One bike manufacturer used it to ask sub-assembly suppliers around the world to share their spend through Mithra.
Take the two-week test drive.
Fill it with your own data and see the taxonomy, the categorization, and the opportunities on your spend, the same way it was shown live.