Tamr: Vendor Analysis (Part 1) — Background & Solution Overview

Tamr, founded in 2013, is an analytics platform and applications provider that, in its own words, “combines machine learning software with data science expertise so analysts can breakthrough the data quality and preparation bottlenecks that prevent fast, accurate analysis.” But since nearly all procurement organizations buy procurement applications, not true platforms, Tamr offers a suite of procurement analytics that is understandably anchored in spend analytics. Spend analysis is not just part of sourcing but also part of a broader supply analytics.

The founding team of Tamr leveraged their background (e.g., Dr. Michael Stonebreaker is actually a Turing Award winner) to create an artificial intelligence-based probabilistic machine learning engine that can match the cleansing and classification capabilities of the other best-of-breed spend analysis providers in the market. Yet, Tamr is really something more, at least as we see it. It is one of the first “supply management” analytics providers that bridges procurement and supply chain at the core (and of course finance and other functions) rather than the general-purpose mega analytics platforms out there (e.g., Tableau, Qlik, SAS, IBM, Informatica, etc.).

Tamr’s early stage traction working with a select group of Fortune 500 customers shows that its current functional capabilities within procurement are at least close enough to other established providers that have been delivering spend analysis solutions for over a decade. Yet these organizations are also looking for next level supply-centric opportunities beyond simple spend visibility alone. This Spend Matters PRO vendor snapshot provides a history and overview of the Tamr’s AI and spend analysis platform, including how it can support both core spend analysis requirements as well as advanced use cases beyond the realm of how typical procurement organizations are deploying analytics solutions today. This multi-part research brief comprises a company and solution overview, company-level SWOT analysis, product strengths and weaknesses, competitive alternatives, a user selection guide and insider evaluation and selection considerations.