Organizations invest significant amount of time and money in identifying and implementing the best fit contract lifecycle management (CLM) platform to manage organization-wide contracts. However, despite selecting some of the best-in-class CLM platforms, many organizations fail to derive the return on investment from the implemented solution.

Some of the most common challenges in the implementation of a CLM platform include:

• Delayed implementation timeline resulting in higher cost
• Platform implementation without understanding business requirements
• Lack of buy-in from stakeholders for the implemented platform
• Ineffective use of search and reporting capabilities

An organization can derive the true value from a CLM platform implementation only when the CLM structure, data extraction and legacy migration of documents align to the goals and objectives of implementing the CLM. A structured approach for contract extraction and legacy migration can ensure that the migrated data is utilized to meet business requirements. A well-defined legacy migration process can enable appropriate search and reporting functionalities within the CLM, setting up of alerts and notifications as well as support management of process performance as well as drive risk management strategies. 

How a robust CLM can impact the organization’s topline and bottomline

Research by the International Association for Contract & Commercial Management (IACCM) found that good contract development and management could improve an organization’s profitability to the tune of 9% of annual revenue.

To facilitate efficient management of the contract portfolio, organizations implement a CLM platform that provides the ability to manage the entire contract lifecycle as well as gain visibility into the contract portfolio and key contractual obligations and SLAs.

As per the IACCM Benchmarking Report 2019, 60% of the users achieved very limited deployment of the CLM platform. Majority of the users utilize the platform only as a contract repository and all other functionalities of a CLM are not effectively utilized.  As per the report, less than 20% of the users utilized contractual obligations extraction or engaged in post-signature monitoring of compliance with contracted terms. Similarly, less than 20% of users utilized contract analytics for individual agreements or portfolio of agreements. 

Failure to monitor the key terms, obligations as well as compliance requirements can result in contract leakages which impact the bottom line of an organization. Hence, it is critical for organizations to define and execute a structured approach towards contract extraction and migration of legacy contracts at the time of implementation of a CLM platform.

Legacy contract migration can be a lengthy, costly and time consuming exercise particularly for large organizations that have a high volume of contracts. There are multiple complexities associated with legacy data extraction and contract migration:

• Siloed legacy repositories with contracts in multiple formats like PDF, MS Word, jpg etc. as well as paper contracts
• Lack of understanding of key data points relating to volume, structure and nature of documents resulting in inability to determine the effort involved in legacy data extraction and migration
• Failure to engage key stakeholders and gather requirements relating to extraction of key metadata and obligations from legacy contracts
• High volume of contracts with multiple legacy templates and variations by department, region and legal entities
• Contracts executed in multiple languages
• Budgetary constraints limiting the amount of data and information that can be captured during migration of legacy contracts

As part of the CLM implementation, there is a need to carve out a plan for contract extraction and legacy migration by engaging the right stakeholders, understanding legacy data and defining the requirements and approach for contract extraction and legacy migration. Legacy data is a treasure trove of information surrounding obligations, risks and liabilities of an organization. A well thought out legacy migration program is the key to unlock insights that would otherwise be hidden in contracts.

Wipro’s Enterprise legal Management Solutions practice helps organizations define the framework for contract extraction and legacy migration, supported by a team of legal experts and AI/ML solutions to deliver the program in a cost effective and efficient manner. We work with clients to define and execute the best-fit solution for legacy migration considering key parameters such as volume, timelines, languages, nature of information to be extracted as well as budgets.

Our solution approach for contract extraction comprises of six key steps :

Step 1 – Due diligence

The groundwork for contract extraction involves gathering business requirements and understanding the data structure to carve out a plan for extraction and migration.

The due diligence exercise consists of the following steps:

• Identifying the sources at which the contracts were stored
• Estimating the volume of contracts across different legacy repositories
• Identifying the setup within the existing CLM i.e., folder structure, contract types, metadata items
• Determining file formats, languages, data range for the documents to be migrated
• Collecting requirements from business teams for contract data and associated reporting and search capabilities

Step 2 – Data analysis

Data analysis involves conducting an analysis of legacy data to understand the nature and structure of documents, identify issues to be addressed and define the extraction approach. The outcome of data analysis would determine:

Step 3 – Requirement finalization

The next step would be to conduct workshops with legal and business teams to finalize attributes to be extracted as well as associated definitions.

Wipro leverages a team of legal consultants certified in CLM implementation for understanding the legacy data landscape, defining attribute extraction requirements and outlining the extraction approach.

Depending on the features and functionalities to be enabled within the CLM platform, the type of attributes and clauses to be extracted can vary significantly:

• Search and reporting can be enabled through document and party related information. This information is captured through attributes such as contract type, account number, effective date, party names/legal entity, party address, country, account number, key contacts etc.
• For more valuable insights into the contract portfolio, contract terms, financial terms or product/service specific information needs to be extracted. The usual attributes for insights or alerts/notifications will be initial term, renewal term, effective date, renewal type, termination notice, payment terms, invoicing, penalties, discounts, service charges, and terms associated with product or services
• Additionally, extracted data can also help in monitoring process performance and obligations management. Key clauses and obligations related to indemnity, warranties, confidentiality, intellectual property, service levels, data privacy, industry specific compliances are extracted to monitor obligations as well as ensure management of high risk contracts

This activity is critical to ensure stakeholder alignment in terms of data or information that would be captured for attributes in scope. This activity helps in course correction before initiating the contract extraction process.

Step 4 – Extraction approach

Based on the requirements for extraction and volume of documents, the approach contract extraction is determined - whether manual or using an AI/ML solution. Manual extraction is the best suited option when the volume of contracts to be extracted is low; or the type of attributes to be extracted is complex or subject to interpretation.

An AI/ML solution can be leveraged for high volume/low complexity extraction. The AI solution can significantly help in reducing the time and effort required for attribute extraction.

However, it is important to understand the limitation of AI. The AI solutions offer standard attribute extraction features that enable search and reporting capabilities. To enable key insights into deliverables, service levels and contractual risks it is often required to train the AI solution to be able to extract the output. In addition,, it is important to build a process that provides validation of the AI output to ensure that the extracted data meets the quality standards defined by client.

Wipro’s ‘AI with lawyer in the loop model’ combines the legal expertise and AI/ML capabilities to deliver faster and quality contract extraction. Our team of legal experts support in training of the AI platform as well as validation of tool output before the extracted data is uploaded into the CLM platform. 

Step 5 – Training and AI configuration

If the client opts for the AI solution for contract extraction and depending on the complexity of the requirement, the AI/ML solution needs to be trained on client specific contract types and configured to address the use cases defined as part of the legacy migration process.

The approach for ML model training and testing is as follows:

• Segregate documents and identify variations and samples for labeling
• Identify the approach for tagging of attributes
• Label sample documents depending on the complexity and variation to train the AI model
• Train the ML model and test based on the labelled documents. Conduct additional labelling and model training based on the test results
• Revise the ML model based on additional variations observed in the larger data
• Validate tool output to ensure quality of deliverables

Step 6 – Ongoing extraction

Once the AI/ML tool is trained, the team proceeds with ongoing extraction and validation of documents in batches.

Conclusion

A large number of organizations are adopting a CLM platform as a solution for efficient management of their contract portfolio. However, majority of them ignore the relevance of migrating legacy contracts to the platform to unleash the true value of the implemented solution.

A well-defined contract extraction and legacy migration process can help in deriving valuable insight into the contract portfolio and preventing contract value leakages.

Ashvini Laud

Senior Manager, Knowledge Service- Wipro

Ashvini is an attorney with over 16 years of experience in the legal outsourcing industry. She has been responsible for service delivery of projects in the areas of end-to-end contract management, compliance to the General Data Protection Regulation, legal content enrichment and legal research. In her current role, Ashvini is responsible for designing solutions to address customer requirements and bringing in transformation and innovation within the legal function.