Contract Analytics Defined
What is contract analytics? It is difficult to pinpoint an exact definition of the phrase, but at its most basic level, it refers to a new way of contract management. By leveraging machine learning to read through individual contracts, contract analytics software can provide insights about what is in each agreement, and then analyze all agreements collectively to produce results about contract terms across a vast number of documents.
Contract analytics is similar to contract management, but it is different in two key ways. First, it uses advanced technology that scans every contract to produce results. Second, it generates more detailed information. Traditional contract management focuses on the fact that contract information often gets lost in the shuffle at the time of contract execution . Contract management software aims to aid this by making it easier to keep track of contracts and get them executed in a timely fashion, and by providing you with all the specific contract provisions in one place.
With contract analytics, the focus shifts slightly to the entire lifecycle of contracts in a way that simply could not be done before the development of new technology. Where traditional contract management might be used to track the lifecycle of a few agreements, contract analytics can be used to create and manage a "contract library" that delivers near instantaneous results about a company’s entire database of contracts. This is only possible because of technological advances in machine learning that make it cheaper and faster than ever before to use software to scan every contract, read each term and condition, and pull out the relevant information.
Advantages of Contract Analytics
The integration of contract analytics into business operations provides an array of vital benefits, such as efficiency improvements, risk mitigation, cost savings, and better decision-making capabilities.
Efficiency improvements: Contract analytics technology, through automated data entry and tagging, provides an obvious productivity boost over relying on manual processes, but the resulting reductions in risk exposure, redundancies, and costly errors are often even more important. Contract analytics systems allow for the real-time monitoring and standardization of contracts across a business, with automated alerts and custom integrative functions that can help you avoid legal compliance failures and mitigate potential issues before they happen.
Risk mitigation: The transparency and oversight that contract analytics provides helps establish an environment where potential liabilities can be managed and avoided. Contract analytics provide valuable insights into the risk profile of a business and help alert the appropriate parties when certain metrics trigger red flags.
Cost savings: Contract analytics eliminates redundancy by standardizing documents and capturing data on a single platform. Individual contracts can also be benchmarked against custom datasets so that businesses can determine if the terms and conditions are competitively favorable.
Better decision-making capabilities: The data collected by contract analytics allows for in-depth reporting and forecasting. When businesses have the ability to make data-backed decisions based on complete and accurate historical records, the resulting outcomes are likely to be much better aligned with current business strategies and future goals.
How It Works
Contract analytics involves the process of automatically extracting and analyzing information from contracts to provide valuable insights for businesses. Initially, contracts were manually reviewed, a time-consuming and labor-intensive process fraught with opportunities for human error. However, the advent of artificial intelligence (AI) and machine learning has significantly transformed how contracts are analyzed.
Contract analytics begins with data extraction, where information from the text of the contract is captured. This may include clauses, terms, phrases, and other relevant data points. There are various methods used for this process, ranging from heuristic-based approaches to deep learning models. In the latter, AI tools utilize natural language processing (NLP) technologies to better understand the semantics of the documents and accurately extract specified data. These tools look for keywords, clauses, and contexts in the documents to help categorize the information.
Once the data is extracted, it is analyzed for insights. Analysis can be performed through several techniques, including statistical analysis, trend analysis, and predictive modeling. This processed information is then ranked, which allows organizations to have the data they need at their fingertips. Visualization of the data extracted can also provide graphical representations to make it easier to interpret.
Finally, the information analyzed can be utilized in different ways. For instance, contract analytics tools enable businesses to quickly assess the risk level of a contract or to ensure compliance with regulatory requirements. They can also aid in the negotiation process by recognizing concessions made in previous contracts. By having a single source of truth to refer back to, stakeholders can make more informed decisions.
The ongoing development of AI and machine learning continues to improve the accuracy and speed of contract analytics, making it an increasingly crucial tool for modern businesses looking to stay ahead of the competition.
Attributes of Contract Analytics Platforms
A successful contract analytics tool should offer automated data extraction so that relevant data points are extracted without manual entry and duplication of effort. For example, extracting data from contracts and storing the data points in a database would allow you to easily analyze your pre-2017 contract terms when you need to. You shouldn’t have to start the process from scratch every time you need the data. This is especially important for companies whose contracts are stored on different shared drives or in repositories that lack the ability to generate reports or automatically extract data points.
Real-time analytics is another important feature. It would be an extra step to generate analytics and reports at a set interval, e.g., monthly, quarterly, annually. You want the information at your finger tips and to be able to view it whenever you want. Having real-time analytics means that you can easily assess the controlled aspects of your relationships, such as pricing, payment terms and renewal procedures, in ways that you could not before.
Customizable reporting is important. You want to "slice and dice" the data in different ways. Everyone is interested in different aspects of their contracts and relationships. You also want the ability to compare all of your contracts by different metrics, such as pricing, payment terms, obligations, etc. For example, if a contract expired on June 30, but won’t be renewed until September 30, it would be helpful to be able to see all the contracts that would be terminated by September 30 in order to prioritize certain other business needs.
Integration with other systems is a must. You may already have a CRM or a matter management system, or will have one in the future. You want the contract analytics software to integrate with any other systems, so that you can easily access the information. You don’t want to have to keep the data in isolation or have to enter data points into another system manually.
Applying Contract Analytics to Your Enterprise
Challenges in implementing contract analytics vary from business to business. You can begin by understanding your current process and what’s necessary to improve it. There are a few areas of concern that may arise during the implementation of contract analytics.
Leading contract analytics firms will have different methods for implementing contracts for their customers, and you might be asked to assist in tests or pilot programs. A special team dedicated to finding the best solution possible may be deployed to map your current process and document areas of improvement. The implementation team will likely create a plan and timeline for when specific tasks will be completed and how long it might take to see results.
The first step in implementation is identifying your top priorities, such as: For many companies, these priorities are often customer deadlines, and while these will be important to you, a system that doesn’t address all of the major priorities equalizes which priorities affect your bottom line. Your new contract analytics system should still benefit every department.
Some contract analytics options will quote a specific number of language checks that you can make in your contracts. This will help you avoid redundant work and allow you to focus on your priorities.
Contract analytics should involve you. It’s there to help you , and you should be the one to tell the contract analytics firm what is most important to you. You should be able to relay errors you’ve made in the past so that the program can stop those mistakes from appearing again. There should be no barriers between you and your contract analytics report.
A fair warning: Your contract analytics system will probably not work perfectly the moment it’s implemented. It will require an open mind and ongoing data input before you see its full effect.
The majority of the confusion surrounding contract analytics involves its use and ability to identify errors. Your contract data will not be perfect; it will not immediately be as perfect as it can be. But with the right contract analytics software, these issues can be identified, and your team can be trained on how to prevent these issues from becoming problems.
Individuals at many levels can benefit from training sessions on contract analytics, and those sessions can vary in severity and intensity. You can host the training session yourself, and other members of your team can help install and maintain the contract analytics software. At the same time, a vendor representative or consultant may spend time with you on the installation and training phases. Depending on the contract analytics system you choose, the depth of the training may vary. Some systems may even have their own tutorials.
Practical Examples of Contract Analytics
The application of contract analytics in the legal sector goes far beyond the ordinary scope of contract law. For instance, legal organizations employing contract analytics typically use their insights to detect signs of fraud, mistakes and insurance gleaned from global contracts databases, reducing business risk.
Contract analytics are equally prevalent in the procurement industry, providing companies with insights into vendor contracts for the purposes of enhancing contract compliance as well as other key performance indicators. For example, procurement companies have used contract analytics software to calculate the total value of ownership of a vehicle purchased using an auto leasing contract. Similarly, other companies in the procurement space such as those in consumer packaged goods, travel and finance – all industries where spending is high and complexity is high – have also employed contract analytics software to monitor current vendor relationships and ensure cost savings.
In the financial services industry, both lenders and credit unions have leveraged contract analytics systems to unify contractual information for third-party relationships, including auto finance and credit union lending agreements. In part, the use of data and analytics has improved the understanding of loan information, providing greater access to essential legal documents from borrowers and creditors.
Finally, there are many potential benefits of contract analytics in the healthcare industry. In fact, hospitals and healthcare systems often use contract analytics to manage compliance with patients and vendors. The U.S. Department of Health and Human Services requires that records for all patients be available and requested in a timely manner for all hospitals and healthcare systems. Consequently, it’s crucial that these organizations are auditing data and contracts, using dashboards features that allow them to filter between different types of agreements. Insight into contract expiry dates, termination clauses, and business risks associated with contracts, candles contract and electronic discovery requests.
Upcoming Trends in Contract Analytics
As the field of AI analytics matures, we anticipate new trends that will shape the future of contract management. One potential area of growth is the adoption of higher-level analytics that analyze the meaning and intent of contracts. As major corporations and service providers aim to reduce risk and streamline business law processes, the demand for such technology will grow. Another evolving trend is an increase in reliance on AI for contract analysis. Traditionally, in-house counsels and non-legal stakeholders have relied on spreadsheets to create and manage their contract portfolios. Contract analytics helps users visualize how the contracts impact their organization and enables them to make changes that will create greater value. Leveraging AI technology for advanced analytics addresses the limitations of spreadsheets and enables the person responsible for managing contracts to see the entire portfolio at once. Additionally, AI-powered contract intelligence can help users more easily identify obligations and risk factors and give alerts that drive faster and more strategic negotiations. AI can even pinpoint whether a counterparty has significant liability exposure and help in-house counsels develop risk mitigation strategies. It is predicted that by 2022 , 70 percent of firms will implement AI to enhance negotiation and bargaining strategies. As AI contracts analysis technology becomes more intelligent, companies will gain a competitive advantage by employing it. In the short term, they will save money and decrease the time it takes to draft contracts. In the long term, companies that invest in this technology will leverage it to create deeper business intelligence. This will give stakeholders a broader picture that identifies opportunities for core value creation and better supports the company’s objectives in ways they have not achieved before. Finally, we anticipate that AI-driven contract management will grant contract managers more authority, allowing them to make decisions on behalf of the company that were previously reserved for legal counsel. This is important because stakeholder knowledge is critical to successfully using technology to transform a company’s contract management function into a source of real competitive business advantage. Stakeholders, for example, are responsible for identifying opportunities for technology that will enable them to oversee broader contract portfolios with limited resources.