Suplari: Vendor Analysis (Part 1) — Background, Solution Overview, Selection Checklist

This three-part Spend Matters Vendor Snapshot series will give an overview of the spend analytics vendor Suplari, examine its strengths and weakness, and provide a comparison with its competitors in the procurement technology market.

Billing itself as “AI-Driven Analytics for Modern Procurement Teams,” Suplari was formed to get the relevant purchasing data out of siloed enterprise systems and into the hands of procurement professionals who needed it to make decisions. However, realizing that the data is usually dirty, disparate and deluging for the average procurement professional, they also aimed to apply machine learning and AI to identify patterns and simplify the processing of cleansing, classification and connection.

In the early days of spend analysis, most of the best-of-breed vendors hitting the market focused on classification and categorization — because that was supposed to be the hard problem and everything else would be easy if you had clean, classified data. But that was just the first obstacle to good spend analysis. The next obstacle was connecting the dots to find the opportunities.

Early vendors purported to solve this problem with some canned top N reports — top N categories, top N suppliers, top N geographies, top N departments, top N off-contract categories, top N off-contract suppliers, etc. This worked well in the early days. A scrupulous sourcing professional would work their way through each and every report until they had evaluated the top 20 or so suppliers, geographies, departments and so on (or until they analyzed the top 80% of spend) and put contracts or procedures in place to capture the bulk of the savings. Six months later they'd run the reports again and then find ... nothing. They'd still be bleeding into the red, but wouldn't be able to do anything about it because most of the bleeding would not be with the top N suppliers, geographies, departments and so on.

Next-generation vendors reported to solve this problem with do-it-yourself reporting where buyers could run reports to target the suppliers, categories, geographies, departments, etc. where they believed problems lied. This was one step up, but the amount of time and effort it typically took to run a report, analyze it for a potential opportunity, determine the opportunity was not worth the effort it would take to capture it, and run another report made it too costly to find and capture all but a few opportunities. As a result, many second-generation solutions ended up being valueless and abandoned not long after their first-generation counterparts.

What was needed was a system that could iterate through all the categories, suppliers, geographies, etc. and find the largest opportunities in each, rank them in order of opportunity size, and present them for easy review by a procurement professional.

And what is really needed is a system that can look at the opportunity size, look at the contracts in place, look at the market pricing, look at historical and community results, and identify not only the opportunities that appear to have the largest size, but the largest opportunities that can be captured now. And while there isn't a system that's here yet, this is where a modern system should be going — and it's where Suplari wants to go.