Daily Archives: October 14, 2016

Spend360 – Applying Deep Machine Learning to Spend Analysis

Regular readers will know that, generally speaking, the doctor has not been impressed with the auto-classification and mapping offerings by any spend analysis vendor he’s ever blogged about as all have failed pitifully on tail spend, performed poor on any supplier or category the provider hasn’t processed extensively, and worked poor in new geographies and even poorer in foreign languages.

However, this year, he’s been impressed by two vendors with auto-classification. TAMR, which are trying to tame the data deluge, and now Spend360. While a new name on this side of the pond, it is not a new name across the pond, having opened its doors for business in 2011, after two plus years of intense development. Plus, it is gaining reputation pretty quickly since it’s foray to this side of the pond a couple of years ago and now has over 100 North American clients, which brings its total client base to over 400 global customers, which is impressive for any company in this space. (Even more impressive is the fact that, to date, it has processed over 1 Trillion of spend.)

While it’s still not perfect, and still can’t outmatch the best human expert with a multi-level priority mapping engine, it is decades ahead of its competition and has the ability to learn and evolve and, over time, approach 98%+ mapping accuracy, leaving little that has to be mapped, or corrected, by a human user (which is quite valuable when the user is not an expert in spend analysis but still wants to reap the benefits).

Not only can its deep machine learning identify tail spend suppliers, company specific categories, and even individual items coded in obscure ways, but it can learn over time and adapt to different data models, especially since it can use evolving knowledge bases. Whereas the majority of first generation classifiers used naive statistical classification that could not learn and had to map to a fixed (UNSPSC) model, Spend360′s uses deep machine learning (based on LSTM and encoder/decoder technology) that maps to custom data models using extensible knowledge bases (which can be created and maintained by the organization) that can encode organization and industry specific knowledge (and negate the need for custom mappings or override rules).

The fact that the knowledge base can be extended anytime a mis-classification occurs negates the need for manual mappings or override rules common in so many first generation spend analysis systems is a very powerful concept. It means that every erroneous mapping need only happen once and will never need to be manually corrected again. Plus, the fact that the data model can be extended as analytic needs evolve means that the platform can continue to deliver value year over year over year, unlike most first generation platforms that only delivered top N reports and failed to deliver value after the first twelve to eighteen months.

But this isn’t all Spend360 has to offer. In addition to a powerful classification ability, which can be trained to actually work, it also has a very powerful front end that allows the user to drill through the cube using custom filters in real time, compared to first generation systems that had fixed OLAP with limited filter capability. Reports can be cross-linked and all linked reports auto-update as one is drilled into. And data can be uploaded and incorporated into the cube in real-time if additional data is required.

And, to top it off, based on the 1 Trillion in spend they have classified over the years, Spend360 also has deep spend benchmarks across all of the major verticals and categories, which is often mapped down to UNSPSC level 4. This allows an organization to quickly understand how its spend on a category compares to the average in its vertical. Simply augmenting this data with pricing trend data can give an organization quick insight into where some significant cost normalization opportunities may lie.

In short, Spend360 is a provider the doctor expects you to be seeing a lot more of in the years to come, and recommends that you check out the upcoming deep dive, co-written with the prophet, over on Spend Matters Pro [membership required] if you are able. This is one best-of-breed provider you want to know.