Contract Analytics is the practice of analyzing key operational and risk elements of contracts, and generating actionable insights at a single contract level, at a cohort of contracts level, or for the entire repository of a company's contracts. Building a long-term contract analytics capability offers many significant business advantages like the ability to prevent revenue leakages, manage risk better and conduct more informed contract negotiations. It starts with basic reporting but when combined with visualization tools and workflow automation offers several opportunities for businesses.
Contract Analytics can be performed on a single (turnkey) or a small set of contracts but is most relevant when applied, in aggregate, to a large number of contracts. The majority of businesses monitor the performance of their contracts in terms of revenues, costs, profits, assets, and hundreds of other business metrics. Most of these analyses are done in silos and individual teams are responsible for driving the right outcomes. These suffer from the lack of insights on two key levels:
One of the most important sources of data, that is frequently overlooked by organizations on an Analytics led transform journey, is contracts. Companies spend significant time and resources to draft, review and negotiate business contracts. However, once signed, they are filed away (similar to sticking to the bottom drawer) in a document management system or a shared drive. Unless something goes wrong, no one looks at it again.
This is a wasted opportunity
Contracts contain critical information about a transaction or a business relationship; they are a source (often, the only true source) of "relationship data". The contents of all combined contracts play a significant role in determining the company's overall risk profile. Contracts can also provide a valuable source of insight into operations, and how the business can be made more efficient and customer friendly.
Companies frequently sign contracts without fully comprehending what they mean. When you have 1000’s of contracts with customers, suppliers, partners, employees, affiliates, etc., it can be extremely difficult to understand (let alone communicate to your CEO or Board) how the overall risks or liabilities, or opportunities sitting in your contracts can shape the future of your company. The right way forward is to digitize your contract data and use that data to drive Contract Analytics.
Businesses need automated notifications around key dates, obligations, and revenue opportunities to prevent revenue leakages. However, more than just expiry, renewal dates, your contract AI should be able to understand the revenue and cost related sections and generate specific actionable insights.
A real life use example:
In Q1 2020, when the entire business world was shut down during the initial Covid wave, a leading manufacturer was holding inventory from hundreds of suppliers in its warehouses all across the US. The contract analysts were able to leverage AI to analyze 1000’s of such contracts and pin-point where a ‘storage fee’ could be charged for maintenance (despite the implications of Force Majeure, of course) and allow account managers to have the conversation with the suppliers. It resulted in millions of $ of additional revenue that might have been lost otherwise.
The journey starts with organizing all relevant contracts into a repository (typically a shared drive or a document management system).
This step usually needs an AI driven technology to classify all contract documents by party names, contract lineage, type, etc. This helps a company index its contract repository, without spending countless hours in manual labor needed to open every document and classify it manually.
This is the most important step in the journey. It involves extraction of all relevant contract metadata, concepts, clauses and terms. It is important to deploy semantic technology (i.e. AI which searches for contract data elements on the basis of their meaning, and not syntactic / keyword search). A combination of robust NLP algorithms is needed to achieve a high level of accuracy of data extraction.
Using our best-in-class AI driven extraction technology, ContractKen can help you digitize your contract data into a structure that can be used for analysis.
A snapshot of key contract elements ContractKen is able to extract for our customers:
Once key data elements have been extracted and stored in a structured store (like a database), the next step is to connect a visualization tool like Tableau to the database. This is where powerful insights will start to emerge.
Let us look at two examples which illustrate typical contract analytics dashboards:
Last and final step in this journey is automating various triggers, notifications and actions based on dates, specific thresholds or clause language. A typical example is to generate notifications for contract managers 30 / 60 / 90 days before expiry of any contract.
ContractKen leverages Microsoft Power Automate & Microsoft SharePoint to automate these business actions.
Reach out at: firstname.lastname@example.org. We are working with multiple customers to build this capability, using our cutting edge AI technology.
And while you're here, play around with the demo of contract analytics dashboards that we have created using sample data:
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