Artificial intelligence and machine learning are unlocking unprecedented efficiencies in contract lifecycle management (CLM). These powerful tools can help organizations that find themselves overwhelmed by the volume of their own contract data. But equally overwhelming can be the question of where to get started with an AI focused CLM implementation.
Mainspring makes that decision easy. All of our consultants are CLM-product certified on one or more CLM best-of-breed solutions, with an average of 10 years of industry and practical implementation experience. With 100+ CLM deployments and a wide variety of related CLM project experience, Mainspring is a CLM system integration firm devoted to helping clients derive the maximum value from its contracts.
Here is just one example of how Mainspring helped a globally recognized brand do just that.
The CLM repository that Mastercard had implemented several years ago was starting to show signs of its age. A poor user experience led to lackluster adoption, which resulted in a degradation of data integrity over time. Mastercard engaged Mainspring to help cleanse its existing CLM repository, recalibrate its data, and enhance its analytics capabilities.
During the initial consultation, Mainspring was able to zero in on Mastercard’s most critical needs and define an AI implementation strategy to achieve three specific outcomes:
- Mitigate risk by systematically avoiding engagement with high-risk vendors
- Ensure compliance by confirming the presence of key contract provisions
- Increase adoption by providing a trusted source of contracts and contract information
Mainspring defined a new CLM system that ensured the data entry model for new contracts would capture not just transactional data, but also data fields that would enable enhanced analytics. That ensured that all contracts going forward would comply with the new CLM system. But it still left the challenge of all of the legacy contract data in Mastercard’s old, underutilized CLM system.
To address that, Mainspring established a data cleansing schedule for legacy contract data that hit all of Mastercard’s internal deadlines. Mainspring was able to adhere to ambitious deadlines through the use of machine learning technology and optical character recognition (OCR) to scan and extract contract provisions according to Mastercard’s specific requirements.
Finally, Mainspring configured a service solution that incorporated Kira Systems, a natural language processing (NLP) machine learning system to extract text from both standard and non-standard agreements. Mainspring’s contract analysts then manually reviewed extractions to verify their integrity or make corrections if necessary. With each piece of analyst feedback, the machine learning systems became more accurate and independent.
Once the data was verified to be over 98% accurate, it was extracted and transformed into a format ready for ingestion into the new CLM system. Using saved models, this process could be repeated as needed for additional batches of contracts.
As a result of Mainspring’s efforts, Mastercard’s new CLM repository is being used much more extensively than its previous system. It has proven its value particularly when establishing contracts with new vendors, by assessing the quality of contracts with existing vendors.
It also provides insight into the causes and factors of missing contracts, the timeliness and frequency of upcoming renewals and expiration dates, and the categories and amount of spend not under contract. Because Mastercard retains access to the extraction technology, it can pull additional legacy contract extractions on demand. And all of this was accomplished within an ambitious timeline, with minimal demands on Mastercard’s internal resources or interruption to the business.
Our experience with Mastercard validates Mainspring’s belief that trustworthy data leads the way for turning information into insight. This insight saves stakeholders time and money and leads to increased user adoption, which results in more effective companies.
Mainspring’s experience in the business processes, people issues, and technology involved in a CLM digital transformation strategy enables us to provide targeted capabilities that minimize your risk and maximize the outcome of your CLM initiative.