Contracting has come a long way. Over the past thirty odd years, there has been a concerted effort to bring more efficiency in the contracting process. Today, CLM tools are widely used by enterprises and their in-house legal teams to create and manage their contracts. They are being used ubiquitously in many medium to large enterprises in various applications such as drafting, tracking, redlining, commenting, and signing of the contracts.
Many of such CLM tools also offer sophisticated document management and storage options.
For the most part, CLM tools are being applied mainly in the creation, signing, and storage of contracts — all of which are steps involved before the contract comes into effect (pre-execution or execution stage). However, the signing of a contract by two parties is only the beginning of their relationship. The real, harder work for an enterprise is to continually manage the actual performance of the contract. As we illustrate in this post, it is quite possible for organisations to use CLM tools to systematise even the performance of the contract to a large extent, and as such organisations today should consider using CLMs to manage their contracts in an integrated, end-to-end manner — from the conception of a contract to its ultimate closure.
Below, we illustrate some of the use-cases of modern CLM tools in the post-execution stage of the contract.
Contract tracking
The typical manner in which many enterprises track their contracts is by storing the signed copies of the contracts on a shared Drive. The contract metadata is usually tracked on a spreadsheet, and different teams in the organisation manually track key dates and events by creating calendar reminders or alerts.
Contracting has come a long way. Over the past thirty odd years, there has been a concerted effort to bring more efficiency in the contracting process. Today, CLM tools are widely used by enterprises and their in-house legal teams to create and manage their contracts. They are being used ubiquitously in many medium to large enterprises in various applications such as drafting, tracking, redlining, commenting, and signing of the contracts.
Many of such CLM tools also offer sophisticated document management and storage options.
For the most part, CLM tools are being applied mainly in the creation, signing, and storage of contracts — all of which are steps involved before the contract comes into effect (pre-execution or execution stage). However, the signing of a contract by two parties is only the beginning of their relationship. The real, harder work for an enterprise is to continually manage the actual performance of the contract. As we illustrate in this post, it is quite possible for organisations to use CLM tools to systematise even the performance of the contract to a large extent, and as such organisations today should consider using CLMs to manage their contracts in an integrated, end-to-end manner — from the conception of a contract to its ultimate closure.
Below, we illustrate some of the use-cases of modern CLM tools in the post-execution stage of the contract.
Contract tracking
The typical manner in which many enterprises track their contracts is by storing the signed copies of the contracts on a shared Drive. The contract metadata is usually tracked on a spreadsheet, and different teams in the organisation manually track key dates and events by creating calendar reminders or alerts.
This process of manually tracking the important data in a contract through spreadsheets or other basic tracking systems becomes very chaotic very quickly. First, it is commonplace that in such processes different members from different departments end up creating their own versions of notes and memos based on the same document, as well as different spreadsheets and tracking mechanisms. There is often endless duplication of the same work across teams and departments, and little to no centralisation of this information. This makes it practically impossible to find the right information at the right time, since a chunk of the time gets wasted in simply finding the data within the contract.
It bears highlighting that several of the data points that are being tracked by teams in this manner are major events such as milestones, notices, terminations, expirations, renewals, etc, where failure to be able to track the right information at the right time can have create severe financial, operational, and regulatory risks for an organisation.
One major additional issue is that this tracking system works in-silo and is connected with any calendaring or alerting system. As a result of the above factors, accurate tracking of contractual obligations, status, compliance, budgets, purchases, invoicing, and other such tasks becomes virtually impossible.
To reduce the impact of these risks, enterprises should aim to make the contract tracking system more intelligent. This can be achieved by adopting a lifecycle management process that is truly end-to-end and takes care of all stages of the contract lifecycle management process.
An integrated, end-to-end CLM solution can prevent wastage of time in searching for documents or information contained within documents, updating spreadsheets, and tracking alerts and reminders. The emphasis while selecting such tools should be to ensure that they are truly intelligent systems and are designed not as point solutions for a specific need but as integrated solutions for a broad, comprehensive need of contract management.
In an ideal CLM tool, the structured data in a contract should be able to be organised at both a system-level as well as a user-defined level. It should provide intelligent automated workflows, and provide automated notifications and alerts for effective performance and obligation management.
Deep search
One of the most criticized aspects of CLM tools by end-users is their unsophisticated search functionality. A basic CLM software that focuses on the pre-execution stages may not focus on integrating deep search functionalities in the software, since it is a need that often arises in the day-to-day management of the contract.
Enterprises should look at adopting CLM solutions that not only help them locate a particular document, but also perform deep search across and within the documents by combining keyword search as well as natural language search. This ability, while seems like should be a given, is either poorly implemented or completely missing from many cloud solutions which at best provide a casual search of the document instead of searching past contracts and archived data.
Enhanced business intelligence through contextual dashboards
Organizing contracts in a complete end-to-end CLM tool ensures easy access to structured data. These tools often have sophisticated data analytics features which can help extract crucial information that may otherwise be missed on a manual review, and can connect the dots together to help you view not just raw data but powerful insights in a single contextual view.
Examples of some of the insights that can be obtained from such contextual dashboards are:
- What kind of contracts are the most commonly used in your company? group/filter/sort it by departments, signing dates, success rates, counterparties, etc.
- Which contract clauses are the most heavily negotiated?
- What are the most common issues that arise across contracts which bring delay in contract performance?
- What are the KPIs in a given contract? Understand the success of a contract by viewing actual performance data in context of the KPIs.
This visualized dashboard can be incredibly powerful at both department and management-level decision-making.
AI-generated predictive analytics
The efficient knowledge management of contracts in an enterprise is powerful in its own right: it heavily reduces transaction costs, increases staff productivity, reduces risks, and helps contracts become a profit center instead of a cost center. But modern CLM tools can do more. In an enterprise with a large volume of contracts and structured data organized in a proper way, CLM tools can use AI to generate powerful predictions and further help reduce risk.
For instance, predictive analytics can generate insight on missing or incompatible clauses within contracts and the impact they may have both on that contract as well as other related contracts. Similarly, AI can track, visualize and even predict deviations in a project before it happens, and timely present that information to the right users of that information so that risks can be prevented.
Concluding remarks
Advanced tracking, timely alerting, insight generation, and the ability to predict future outcomes are superpowers for a business. Above and beyond these specified use cases, there are endless possibilities that intelligent CLMs can bring. One way would be by bringing modularity to the users such that they can create their own customized contexts in a no-code / low-code environment. Organizations that care about systematizing contracting as a business function should look at these possibilities when designing systems and processes for their internal use, since the true promise of CLM is unlocked after contract execution.
