The Confluence of AI, Good Data, and a Mature CLM Vision
For over a decade now, I've been searching for the one true contract lifecycle management (CLM) platform that can do it all. The story that I'm going to tell over the next three blog posts is one derived from my experiences, a true passion for CLM, and a desire to see customers succeed in this field. I will not try to impress you with flashy metrics, industry buzzwords, or the hottest new tech hype; I'm simply going to tell my story as it played out, why I landed where I am now, and how I believe AI and contract management are thankfully evolving and converging in some very exciting ways.
Sadly, for all the contract management selections I helped make, and the 100’s of contract management solutions that I sold, architected, or delivered over the years, there has always been something lacking.
What's lacking has been a myriad of things, but I'll bucket them into three main areas:
In this first post, let's address legacy and third party data. For many years in the early 2000's, I saw CLM systems and vendors rise and fall due to lack of user adoption. These systems were maturing and had robust workflow and authoring, but in almost every case failed to address or simply did not care about their customer’s greatest assets, the legacy contracts! These same contracts that had so much knowledge, capital and blood, sweat and tears shed during negotiation cycles to finally get to those most favored terms. These same contracts, ranging from mere thousands to millions, were simply ignored in favor of the shiny new CLM and its new templates and processes that would save countless hours in process efficiencies.
For all their introduced efficiencies, these systems almost all failed and continue to fail today because business users want and need the past and the present (including third party paper) contracts in one central repository.
To set the stage, let’s rewind to late 2008. I recall sitting in a meeting during a CLM implementation kickoff and my customer said, "Wouldn't it be nice if there was just some magic software out there that could automatically classify all these contracts and pull out the data that we are looking for?" Everyone in the room had a good laugh and then got back to the extremely mundane task of planning our legacy data extraction and load into the new contract management platform, which lasted for about 5,000 of the 25,000 contracts, then fizzled out due to lack of resources and a very error prone and mundane loading process.
Rinse and repeat the above for a few years, at which point I started to hear word of some "magic vendors" who did exactly what my clients were requesting! They could automatically find, classify, and extract data from a corpus of legacy contracts. Wow! I was so excited that I started selling those contract discovery solutions alongside my CLM products, then eventually I ventured into the Contracts AI space myself.
To my dismay, I discovered that there was no such thing as magic contract discovery and analytics. That data extractions were only as good as the industry knowledge you or your clients had in order to build the machine learning models. And, that sadly, in every case there was still a significant amount of manual review effort involved. In many instances, these services dollars dwarfed the software cost and killed many deals for clients expecting 95% or more accuracy from their shiny new contract analytics system.
I found myself in a quandary again. Being extremely passionate about my customers' success, It was upsetting to find them complaining about the complexity and time required to build and refine their extraction models, and on top of that, the amount of review still required to meet their requirements (much to the pleasure of my consulting and LPO partners who were reaping the fruits of these large review projects or multi-million dollar PROGRAM wrappers to respond to M&A transactions and regulatory requirements).
There was validation in the large partner deals, and in the slew of competitors in the contracts AI space cropping up. However most of the deals were one to two year projects that did not find my customers renewing upon completion, due to lack of user adoption (extremely low active user counts) and a lack of value vs the ROI that was promised. What made these deals turn into projects when many of the customers were happy and referenceable? I looked across my customer base, and in almost every case, we were either partnering with or migrating data to a CLM, ERP, or CRM system! The customers not only wanted their legacy data, they wanted good data and contracting processes going forward and we could not provide that!
Stay tuned to hear more of the story on how I got hooked on good data and my journey back into the contract lifecycle management world.