Contract Analytics Dashboards

Amit Sharma
September 7, 2022
5 min read

What is Contract Analytics?

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:

  1. Contract risks, liabilities, and opportunities at a cohort or portfolio level
  2. Contracting process efficiency measurement

Why Should Companies Invest In Contract Analytics?

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.

Contract Analytics helps organizations to:

  • Track operational metrics like contracts expiry, auto-renewals [triggering automated reminders and actions]
  • Track trends around key risks, liabilities, and course correct if required [enabling the Legal & Risk executives to monitor the enterprise level risk]
  • Understand the interplay between revenue, risk, and other attributes like industry, etc. [enabling the business leaders to negotiate specific contracts better]
  • Preventing Revenue Leakage

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.

Typical questions that can be answered using Contract Analytics:

  • What proportion of our contracts contain a Force Majeure clause?
  • Do any of our contracts contain references / clauses pertaining to outdated regulatory legislations?
  • How is the risk profile of our contracts with a particular customer trending? How are the trends in a cohort of customers (say by industry or customer revenue size)?
  • Which of our target company’s contracts (during an M&A due diligence) contain a change of control clause? What is the notice period?
  • Which clauses are negotiated the most in our customer contracts?
  • Which departments are not complying with regulatory requirements, which might create a risk?
  • What is the average cycle time from draft to review to negotiations to signature?

How To Get Started On Contract Analytics Journey

Step 1. Repository

The journey starts with organizing all relevant contracts into a repository (typically a shared drive or a document management system).

Step 2. Data Digitization

  • Contract Family Mapping

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.

  • Contract Data Extraction

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:

Key Elements that ContractKen can extract

Step 3. Data Visualization

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:

  • Portfolio Health Monitoring
  • Contract stages - Draft, Review, In Negotiations, Active (signed, expiry > 90 days), Active (signed, expiry < 90 days), Expired in last 90 days
  • States, Geography
  • Customers (individual or other categorizations like Top 3, Top 5, Top 10, etc.)
  • Types of Agreements
Sample Dashboard - Contract Status
Contract Status Visualization

  • Portfolio Risk Analysis & Scenario BuildingAssign a risk category / score to each contract (based on extent of deviation from your organization standards) and analyze the
  • Types of Agreement vs. Risk Category
  • Spread of specific Contract risk analytics (for e.g., most unfavorable confidentiality clause)  across Industries, agreement type, etc.
Sample Dashboard - Agreement Type vs Risk
Agreement Type vs Risk

Step 4. Workflow Automation

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.

Get your Contract Analytics going

Reach out at: 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:

Portfolio Dashboard

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