Using AI to Optimize Working Capital

At a macro level working capital itself is a juggernaut: In the 2014 US Working Capital Survey, “the top 1,000 US companies have more than $1tn excess cash tied up in working capital, which equates to 6% of the nation’s gross domestic product” and ‘payables’ accounted for over a quarter of this. Working capital is inextricably tied to cash flow, and both are linked back to contracts. Yet many companies fail to make the connection.

Poorly managed cash flow is a primary reason many small companies fail. For larger companies, it remains a challenge and is a key metric for overall financial health. In order to optimize your working capital, a company must understand and optimize contract payment terms.

So how do you manage and optimize payment terms to boost cash flow and working capital?

A procurement software system such as a contract lifecycle management (CLM) technology holds critical information from contracts, such as key payment dates, amounts and contingencies. CLM is a valuable tool for proactive, systematic management of the contract throughout its life and the ebbs and flows of cash flow. Implementing CLM often leads to significant gains in cost savings and efficiency.

CLM also helps to integrate payment terms into the A/P process, ensuring that payments are timely made, including discounts and other factors. The challenge, however, is in migrating legacy contracts into CLM and excerpting key information from legacy paper. Historically, companies would outsource this function to places like India, a slow, inefficient and error-prone proposition, not to mention a significant loss of data control. Fortunately, now the savvy operators have an alternative.

Enter AI

One of the most common applications of AI is to translate large amounts of data into meaningful insights, outputs, and models. At Counselytics, we have built a powerful machine-based data extraction capability that identifies important clauses and terms and also extracts key data points such as payment amounts, discounts, termination terms and interest charges.

When integrated with a CLM, it automatically maps that data to a contract data model, so all terms roll-up to the master agreement for a real-time view and constant visibility into all your entitlements, rights and obligations. Counselytics provides a turn-key solution that recognizes contracts as data, making it easier to organize and analyze contracts in a scalable, efficient and cost effective way.

Automated data structuring and extraction.

Our customers are now extracting key data points from their agreements (whether it’s a pdf or word) document into the system. This data can provide businesses with deeper visibility into their terms, risks and obligations. Information that was once just words on a piece of paper is now structured analytical data that can be reported on and benchmarked for future reference. A legacy contract can be uploaded into Counselytics, giving you visibility into business analytics within minutes. Another useful and important feature within Counselytics is the ability to validate data points by clicking through to the exact location within the original document. This feature facilitates manual intervention to correct errors or make necessary adjustments.

Deploying a system such as CLM to better manage your procurement is just a step in the right direction. Ensuring all your legacy and future third party contracts are within the database will provide a holistic view of the procurement landscape and can structure important data such as procurement terms which in turn will have an appreciable bottom-line impact to your organization.

About Counselytics

Counselytics is a leading contract analytics company founded in 2014. Counselytics uses proprietary artificial intelligence technology to find, analyze and organize important enterprise documents and to extract critical data points from those documents, bringing unprecedented efficiency to contract management, due diligence and lease abstraction. The company is backed by the top venture capitalists in New York and Silicon Valley.