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.
If you’re reading the Exari blog, chances are good that you’re already a forward-thinker at an innovative company. And if you’ve been tracking the contract management market, I'm sure you'll agree that it has never been more exciting with major advancements happening at a quick pace. But. let’s be straight, it hasn’t always been this way. Organizations have lived through decades of less than stellar contract management initiatives with limited adoption and an incomplete understanding of their contracts.
If you know the enemy and know yourself, you need not fear the result of a hundred battles – Sun Tzu
Know the enemy and know yourself. Follow this rule and – according to Sun Tzu – you will win most battles. This, in short, is why you should care about the data buried in contracts.
Several years ago, I took a class in artisanal bread baking at the King Arthur Flour Baking Education Center. My baking partner was a retired accountant from Manchester, Vermont. When we started making our first type of bread, he seemed to be asking a lot of questions about substituting ingredients; margarine for butter, whole wheat flour for white flour, no salt, etc. When the instructor dug a little deeper, she found out that no matter what he tried, his bread wouldn’t rise.
At a time when legal teams are inundated with data, the lack of clear and concise information and how to use that data to make transformational decisions remains elusive to most stakeholders. In recognition of this dilemma, technology is rapidly evolving to capture vast stores of “big data” and analyze them in ways that provide legal with new insights into their operations to manage risks and drive the right kinds of change to improve results.
The new revenue recognition guidelines are coming into effect in 2018. We've defined a 3 step approach explaining the process for those of you that are not directly involved.
It appears that the document automation industry is at a stage of development where there is still a lot of value to be captured by customers – that is, the benefits to be reaped far exceed the costs of implementing.
Here in Boston, we’re used to getting hit with major winter snow storms. It’s a New England ritual to head out to your car before work and start scraping layers of ice and snow from the windshield. If you’ve ever found yourself in this situation you know you’ll take any shortcut to keep your fingers from freezing. The ice will melt once your heater kicks in, right? Poor visibility, I hate to admit, is a risk most of us are willing to take.
If you’re just joining in now, feel free to go back to part 1 of this blog series. If not, here is a quick recap: There isn’t much time left to come up with a plan for the new revenue recognition guidelines since they are coming into effect in 2018. There are a lot of factors and hard work that go into complying with these new standards, so we've simplified the process by taking a three-step approach to help you on your journey to increasing compliance.
Have you ever experienced a failed deployment of contract management software? At Exari we have talked to hundreds of people about what has worked and what has not worked for them. The most common topic that comes up in these discussions is centered around data. Until now it has been cost-prohibitive and time-consuming to represent contracts as data.