More and more legal teams are attempting to construct their contract lifecycle management (CLM) solution. While it may seem like a good idea to build your system in-house, the truth is that this approach brings serious issues down the line. In this post, we’ll outline what homegrown CLM is and why it’s not a wise investment.
First off, homegrown CLM can fit into two categories:
There are four main reasons why a homegrown solution is not the way to go. There are hidden costs, lack of designated support, lack of legal expertise, and lack of data oversight. Let us dive into each of these and cover the questions you need to ask to understand why.
There are enormous hidden costs associated with a homegrown solution. This process, which can take months to years, will need a full-time dedicated team devoted to thoughtfully and strategically developing and managing the integrity of the CLM platform. Here are the questions you need to ask yourself (and your team).
To create a valuable CLM system, all the contracts located in numerous locations throughout your organization will need to be found and housed in one place. Just gathering your legal documents will not be enough. They will need to be digitized, labeled, and organized. There will also need to be one central location for all those contracts.
Since some information will still live outside the system without proper integrations, this needs to be considered and remedied. Additionally, you will need to create templates for different contract scenarios to ease drafting. You will also need an automated routing system created for approvals and tasks so that your contracts are trackable in the various phases of the contracting process.
You will need a team to properly maintain the CLM solution for individual customer needs and requirements. A homegrown solution requires increased manual maintenance to upload and download agreements from and into other systems like DocuSign, AdobeSign, and Salesforce. You will also need to import all of your contracts scattered across individual drives such as Box, Google Drive, and more. Manually doing this will likely lead to missing contracts.
If you have AI or OCR in your homegrown CLM platform, then that means you will need a dedicated team for each devoted to only these areas. Without these two dedicated teams, existing employees will need extensive time away from their meaningful work to read through every contract and identify all of the key terms.
Reading fuzzy scans or trying to decipher unclear images leads to human error. Free OCR solutions will not likely have the quality and consistency needed for all contracts in the CLM. Overall, it takes numerous hours of employee time to identify the correct clauses, and often there are errors due to distraction or fatigue from the repetitive work.
Since efficiency is one of the main goals in building a homegrown CLM, you will need to build automation engines and workflows for contract review. You will also need an expert in contract routing to ensure that the correct reviewers view the permitted contracts, send reminders and notifications for important dates such as upcoming renewals and termination dates, and consistently remind their team to review tasks.
Implementing a contract lifecycle management solution is a massive undertaking that needs the support of a designated onboarding team. You will need to devote a team of employees away from their regular duties to be an onboarding team consisting of implementation and technical support specialists. Otherwise, you will have no one to walk you through your product, features, or customization.
There will be no one to ensure that your files are uploaded and extracting contract data as expected. There will be no one to ensure that the correct people have access and that the needed permissions are set before use. In addition to an onboarding team, here are some questions to ask yourself about the support you have vs. what you will need.
A 24-hour team will need to be formed for when something happens, or there are unexpected results or issues with the homegrown CLM. You will be the one to figure out a solution to any problems no matter what the time, day or night, weekday or weekend. Constant support is crucial to ensure deadlines are met in the global world.
If your homegrown CLM has AI, an auditing team will need to be created. Otherwise, there is no one to make sure that your legal AI models have the highest amount of accuracy and precision. Without high accuracy in retrieval and precise results, the legal AI model is pointless and useless.
When creating a homegrown CLM, you are reacting to the current needs of the business versus anticipating future trends. All of this contract data is also meaningless without easy to understand visualization of the results. You will need to create a team whose only role is to develop innovative features such as dashboards, governing summaries, and detailed reporting. They will also always be updating and developing novel features and applications.
Perhaps, most importantly, you will need experts to review the complexity and variation of legal language in your contracts. You must create a specialized team of attorneys to research, locate, and review contract language. Legal language is constantly evolving, and having your CLM company on the pulse of everything legal gives reassurance and competitive advantage. Think about these questions and scenarios.
You will need to hire rare and unique attorneys with expertise in AI development and highly skilled and experienced data scientists who will work in collaboration to avoid the pitfalls of a garage in/garbage out homegrown CLM. Without this specialized team, there will be no processes for extracting contract language, outputting, and storing the results.
You will need to dedicate valuable time and resources to researching how other legal teams have set up a CLM. There will be significant time spent on developing processes and validating features.
If your CLM has AI, you will need dedicated experts with knowledge and experience in machine learning. You can determine when there is both the proper number and the specific examples required to create a legal AI model.
You will also need a dedicated team of AI developer attorneys constantly considering whether unique legal language can be added to that model. Without these considerations, it is possible that there will not be enough contracts to make any meaningful predictions or produce any actionable data insights. In addition to these dedicated experts, here’s another point to consider:
Data security needs to be considered immediately from the start of developing a homegrown CLM. There are real threats from within and outside of the organization through bad actors in the forms of a data breach or ransomware attacks. It is crucial to protect valuable contract data. This critical and sensitive data requires constant monitoring for security. If these processes and continuous monitoring are not in place, this can lead to risk exposure of sensitive customer data.
At the end of the day, you need to weed through many false promises. You must consider carefully if you have indeed purchased and built an AI-powered CLM or if instead you bought and built a CLM that is only an automation and workflow management solution.
Research shows that good contract development and management could improve profitability by the equivalent of a massive 9% of annual revenue. But do not just take it from us. If you are still not sold, check out our customer stories and our reviews on G2.
“We were looking for a solution to replace SharePoint as a final resting place for all executed documents. We needed a one-stop shop where people could find what they were looking for with ease and accuracy. We discovered LinkSquares several months ago, and their product is like no other! If you're looking for an AI cloud-based solution for searching over documents or building out your clauses to create documents, they're the best you will find out there!” - Ashley A, Enterprise, G2 Review.
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