When I practiced actively as a lawyer, I came to advise many fast-growing companies on their contracts. The contracting journey of a fast-growing company can be described aptly in one word – “turbo-charged”.

Contract requests keep flying from various business teams, request for contract data keeps flowing from finance, audit, sales and risk departments and there is always more work coming the way of a lean legal team. The twin concerns in respect of contracting that the General Counsels of these companies balance everyday are speed and risk. These are not unique challenges for a fast-growing company but what is unique about them is that many of their General Counsels are setting early ways for enterprise contracting.

The moment requires some special consideration as to whether General Counsels should be investing in a CLM software or go the traditional way of managing contracts through email and MS Word. While there may be a variety of factors which can contribute to buying a CLM, following five are main drivers:

1. Volume is a key factor but so is variety
2. Vendors and customer contracts involve payment milestones and more than a couple of annual compliances
3. Buy or sell globally
4. Have multiple institutional investors
5. Itself Regulated or serves regulated customers

Once it becomes clear that a CLM software should be brought in, the key question that kicks in - 'What type of CLM should one evaluate?'

With increased social media marketing by CLM software providers, it is indeed confusing for GCs to clearly establish the key metrices to focus upon. Generally, in case of SAAS, when evaluation and buying decisions correlate with pain points for contracting, it leads to a sound buy with opportunity to recoup investment early. Once again looking at pain points associated with main drivers for buying, the following questions should be asked while evaluating a CLM.

1. Even after buying CLM software, will junior lawyers need to manually enter data from contracts?
2. Can the system help speed up contracting on third party papers?
3. Will the system help GCs to clearly define boundary conditions for contracting so that legal team’s time is not blocked for routine queries?
4. Is there a single repository for signed contracts which gets auto- populated with key obligations from legacy as well as future contracts?
5. Can business teams effectively manage obligations from signed contracts without needing to block legal department’s time?
6. Does the system help legal teams to back up their performance with real data?
7. Will the system empower GCs to provide actual contract data for optimizing sale/purchase decisions by an enterprise?

The difficulty evaluating by feature is that broad features are quite common across most contract lifecycle management software today. However, if one digs deeper, the smarter workings of a truly value generating software becomes clear. To illustrate with an example, some contract management softwares capture data like expiry date, payment terms, etc. from contracts that originate within that software itself. But they fail to collect this data automatically when contracts undergo negotiation, and the negotiated contracts do not carry the same form as the original contracts generated from template. It usually takes about a couple of hours of time of a paralegal or junior lawyer to collect metadata and manually record it at the point of signature. Same with contract review. Third party papers do not follow the same contract structures that are programmed within an enterprise’s own contract software – so a company’s own playbook cannot be readily applied to such third-party papers. Resultantly, even when most contract lifecycle management system promises to improve contract review workflow, they fail to deliver critical value for the legal department.

AI/ML is emerging as a strong aid to workflows. One good marker at the stage of evaluation is to ask a vendor to demonstrate with a Proof of Concept (POC) as to how their contract lifecycle management system can handle contract workflows with AI/ML? If the PoC is successful, then you know that you are off to a good start!

By Dipankar Bandyopadhyay