Daily Archives: July 2, 2019

AI: Applied Indirection in Contract (Lifecycle) Management

Continuing our expose of why you should think “Applied Indirection” and not “Any form of Intelligence” when you hear AI, because most solutions claiming to be AI are really just dumb systems with RPA (robotic process automation) and classic statistical models from the 90’s, we move onto Contract (Lifecycle) Management which, like analytics, is almost universally touted to have AI, even when there isn’t even a shred of anything that comes close.

This doesn’t meant that there aren’t vendors with true AI, especially when you classify it as Assisted Intelligence (and sometimes even Augmented Intelligence), in the space, just that, as the buzz-acronym reaches new heights, there will be many more vendors claiming AI than those that actually have AI and you will need to do your homework to find out which is which.

Example #1 of Applied Indirection in C(L)M: Auto-Renewal Detection & Management

Yes, evergreen contracts can be a big problem in Procurement when they have outsourced their usefulness, but detecting and managing these is not hard, and certainly doesn’t require any AI whatsoever. All you have to do is specify the contract as “evergreen” or “auto-renew” by checking a box and enter a notice-by date (to prevent an evergreen renewal” as well as the start date and end date and most contract management platforms can alert you in sufficient time to take action, escalate to your supervisor if you don’t, and kick-off a termination process at the push of a button.

For anything close to AI, you require a system that can detect when a contract is evergreen or auto-renewing when there isn’t a spelled out and easily identified auto-renewal clause that can be found with a simple reg-ex search. For example, when a crafty supplier buries an auto-renewal requirement in the liability section under the notices subsection titled “methods for delivering official notices” which starts off “Official notices shall be sent by X, Y, or Z, to A or B and only treated as an official notice upon proof of receipt. This includes a notice of non-renewal, as the contract will automatically renew 30 days prior to expiry otherwise.” Even a good lawyer might miss that in a fifty page contract when it’s snuck in on the third revision.

Example #2 of Applied Indirection in C(L)M: Off-Contract Purchasing

Maverick purchasing is a big problem. But it’s not one that you need AI to detect. If you encode all the products, services, and / or categories that should be bought on contract, it’s pretty easy to identify when a purchase for that product, service, or category is not bought from that supplier. And if the contract only applies to a region, it’s pretty easy to encode that too and it’s just a simple check.

And even if you have two or three suppliers in a multi-supplier contract for risk mitigation purposes, then it’s just a matter of making sure at least one of the supplier got the purchase, and if each supplier had a geographic area, that the right one for the area. Again, simple rule checks. No AI needed.

The key is to detect when something is off-contract when it is not specifically coded to a contract, either because it’s a new product, missing a category designation, required to hit a volume commitment, and so on. And while this can often be accomplished by identifying the closest product or service (using a document likeness statistic or weighted field match), sometimes advanced NLP may be employed for better results (and this would constitute weak AI).

Example #3 of Applied Indirection in C(L)M: Clause Suggestion

On the surface, this sounds pretty smart … point out clauses that should be in my contract to protect me. Under the hood, in most CLM systems that include authoring, it’s basically a set of templates that are used to specify what to look for in a contract type, with additions or subtractions for well defined industries that the provider serves. It’s basically a check list. And it’s about as dumb as it gets.

Can it be smarter? Of course, but the smarts are more around proper contract identification than clause selection. Because the clauses that should be included generally depend first and foremost on the type of contract, secondly on the product or service, and thirdly on the regulations that affect the products and services in the origin country, the destination countries, and any points in between. Then, identifying which regulations come into play and which types of clauses will be needed. This requires good NLP, probabilistic selection, and, preferably, adaptive learning that learns over time when Legal or Procurement chooses an alternate clause over a standard clause. A system should have assisted intelligence here to be useful, and augmented intelligence to be truly useful. But few do.

Note that SI is not saying that systems with the non-AI abilities discussed above are not valuable, as any system that automates tactical processes and minimizes non-strategic busy work is valuable. We are just saying you shouldn’t pay for what you’re not getting, or overpay for what you are. Buy what you need, and pay accordingly.