Chess, Not Checkers: Data Collection Strategies in Complex Litigation

In our last post, we discussed strategic planning and early case assessment (ECA) in complex litigation to maximize success and leveraging advanced technologies like generative AI to facilitate that process.

Understanding data sources before complex litigation begins is essential to address the challenges associated with data preservation and collection. Complex cases often involve large volumes of data from a diverse set of sources, including emails, databases, cloud storage, messaging platforms, and physical documents.

As a result, data collection strategies for complex litigation differ significantly from those used in typical litigation due to the scale, diversity, and complexity of the data involved. In this post, we will discuss considerations for data collection strategies for complex litigation and how they differ from strategies in typical litigation cases.

How Data Collection Strategies for Complex Litigation Are Different

Complex litigation is more likely to involve a complicated data collection exercise. It is essential to develop a comprehensive data collection strategy to ensure relevant information is preserved, accessible, and organized for review. Here are some of the ways in which data collection strategies for complex litigation differ from those used in typical litigation:

Volume and Scope of Data Collection

In routine litigation, data volumes tend to be more manageable, allowing for simpler, often manual collection and review processes. Legal teams can often collect relevant information upfront, whereas complex litigation can require a staged approach to avoid overwhelming the review process. In complex litigation, data volumes may be exponentially larger, requiring advanced strategies to handle massive datasets efficiently.

In the initial stages, complex litigation may warrant a targeted collection strategy, which involves gathering data from key custodians and high-priority data sources identified during early case assessment (ECA). This enables legal teams to access critical information quickly and build a preliminary understanding of the case without incurring the costs of full data collection.

Variety of Data Sources

The more expansive the litigation, the more diverse the population of data sources is likely to be. Complex litigation typically involves a broader range of data sources including emails, text messages, shared drives, cloud-based applications, databases, social media, and more specialized systems.

Each data type may require a unique collection approach. Unstructured data from emails or shared documents may warrant a broad collection strategy. In contrast, structured data, such as database records, may need specific tools or queries to extract relevant information accurately. Understanding the specific needs of each data type – structured versus unstructured data, static files versus real-time communications – ensures that the collection process is both defensible and comprehensive.

Forensic and Advanced Preservation and Collection Techniques

Because complex litigation often involves high-stakes issues, data authenticity, metadata, and chain of custody could be at issue. Forensic data collection preserves metadata and captures exact data snapshots, so it’s more likely to be used to ensure that no information is altered or lost, especially for sensitive or potentially disputed evidence, such as the evidence found on mobile devices.

In situations where data is distributed across multiple locations or users, remote collection tools can facilitate efficient data gathering without significant disruptions. These tools can access data across devices, servers, and cloud-based platforms while maintaining chain of custody and data integrity. The benefits of remote collection tools can be particularly useful in complex litigation where custodians are more likely to be geographically dispersed.

Dynamic and Iterative Collection Process

While conventional litigation typically follows a linear data collection process, data collection is often dynamic and iterative in complex litigation, with new custodians, data sources, and evidence coming into play as the case evolves. Legal teams may revisit data sources multiple times, adjust their collection methods based on new information, and conduct rolling productions to meet deadlines.

Focus on Cost and Time Management

Given the expense and scope of complex litigation, cost and time management are critical considerations. Strategies like phasing the collection, prioritizing high-value data sources, and using generative AI and/or predictive coding help to streamline the process and control costs.

Application of Advanced Technologies Earlier

Not surprisingly, managing larger data collections is facilitated by applying generative AI and/or technology-assisted review (TAR) during ECA. Leveraging generative AI and TAR can help identify relevant documents in large datasets early on, enabling the legal team to prioritize and sift through data quickly, as well as implementing phased collection to gather high-priority information first and expand collection later only if necessary. Gen AI and TAR can also assist in identifying potentially privileged or confidential data, making it easier to apply appropriate protections from the outset.

Increased Focus on Compliance with Regulatory Requirements

While all cases typically require compliance with specific regulations and data privacy laws (such as GDPR or HIPAA), complex litigation cases, particularly those involving highly regulated industries, are much more likely to face additional scrutiny. This scrutiny may lead to additional safeguards, redactions, and data handling measures to protect sensitive information.

Higher Standards for Defensibility and Documentation

A greater volume and variety of data increases the chances of making mistakes, even if you’re careful during the collection process. That’s why, in complex litigation, documentation of each step of the data collection process is even more important in order to establish defensibility and ensure that all procedures align with legal and regulatory standards. This includes maintaining a clear chain of custody, tracking all preservation efforts, and documenting collection tools and methods used. It could make the difference in determining whether or not a mistake leads to sanctions.

Conclusion

Overall, data collection in complex litigation demands a more sophisticated, flexible, and resource-intensive approach. It requires leveraging advanced technologies like TAR, generative AI, remote collection tools and more. By tailoring strategies to the unique needs of complex cases, legal teams can handle larger, more varied datasets effectively, ensure defensibility, and avoid costly delays or missteps.

In our next post in the series, we will focus on the application of generative AI to help with various discovery tasks such as summarizing, categorizing, and analyzing documents to keep costs manageable and increase flexibility in your strategic approaches to cases!

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