Contracts are central to the world of business. The more contracts you close, the more potential revenue you stand to earn. By the same token, more closed contracts means more contracts for your organization to manage. And contract management is no simple matter.
Fortune 1,000 companies manage anywhere from 20,000 to 40,000 active contracts on a regular basis. That means they manage everything from initial contract development and review through expiration, renewal and performance assessment. Considering that it takes an attorney more than two hours, on average, to create and review a single contract, managing 20,000 over their entire life cycle is an unwieldy task.
To improve the efficiency and accuracy of contract management, companies need a proper contract analytics solution. While many turn to contract lifecycle management (CLM) solutions for this reason, the analytics capabilities of these solutions are often exaggerated. What companies need is a contract analytics solution based on natural language processing technology.
Language Understanding Keys Effective Contract Analytics
Contracts are notoriously verbose and dense documents. That alone does not lend itself to being reader friendly. Add to that a high level of domain expertise necessary to understand the contents of the document and you have an extremely difficult process to manage, let alone automate.
Many contract management tools rely on artificial intelligence models to provide analytics and insight into contracts, but the data-driven models do not truly understand the language in them. Given the precise nature of contracts, anything less than human-like comprehension will leave you vulnerable to costly mistakes.
By bringing knowledge into the equation, you enable your organization to understand your contracts on a deeper level. In doing so, you unlock certain capabilities that help you to manage your contracts more efficiently. These capabilities include:
Entity Extraction
Contracts are chock full of entity references. These can include references to any number of people, organizations, locations and more. Why is this information important? It enables you to classify and organize each contract within your database by the metadata you deem important.
When you manage thousands of contracts, having a carefully curated database makes it easy to locate a specific contract that needs to be reviewed or find similar contracts to one that needs to be drawn up. Unfortunately, extracting this information and updating the metadata of each contract is a time- and labor-intensive process when done manually — especially when you consider the length and density of each contract.
Natural language technology enables you to process any contract and extract key information from it in a quick and accurate manner. By taking a rule-based approach, you can embed domain expertise to provide context for those ambiguous or hard-to-understand terms. Not only does this help to process thousands at a time, but it simplifies the process with every new contract you add.
Semantic Search
When you have an extensive repository of contracts, finding critical information can be difficult. A basic keyword search may help you narrow down your options, but it also may leave you with more (often irrelevant) results than you hoped for if the term has multiple meanings. When you are searching for a specific clause or term, you need the results to be precise. Otherwise, you are not saving much time in the grand scheme of things.
An effective search capability needs contextual understanding to deliver accurate and useful results. Just as natural language technology can help you extract and classify terms and clauses with greater accuracy and speed, it also enables you to navigate them with ease. This completely alters the user experience as it enables them to quickly locate important information that is needed to create a new contract.
Clause Comparison
There is no universal legal language. As a result, every company writes its clauses with its own terminology and phrasing. This can make it difficult to review incoming contracts as you need to compare them to your own in-house standard clauses.
By extracting clauses from your own standard contract, you can create a repository of clauses to use when evaluating future contracts. When a new contract comes in you can run a similarity assessment to see whether clauses have previously been addressed and determine whether there is better language that can be used in its place.
Poor contract management is costing companies an average of 9% of their revenues. There is no excuse for that to continue, especially when there are contract analytics solutions available to solve many of your core problems. A little knowledge goes a long way. See for yourself!
