How choosing the right service provider can reduce discovery costs

Contemporary corporate litigation is electronically stored information (ESI)‑centric: relevant data predominantly resides in emails, chats, collaborative content and associated metadata, rather than paper records. Effective discovery now means isolating signals from software as a service (SaaS) sprawl, capturing collaborative context (threads, versions, comments), and managing privacy, cross‑border transfer and effective legal holds in the face of ephemeral data. Increasingly, it also requires provable authenticity for AI‑generated or automated content, along with proof of edits or alterations.

The e-discovery process works in tandem with managed data review (MDR) to assess relevance, privilege and confidentiality that support defensible outcomes. These capabilities are a standard part of the legal cost of doing business for large enterprises and play a critical role in supporting effective litigation strategy and regulatory compliance.

A major integrated energy company was experiencing a significant spike in regulatory action and litigation. These issues were exacerbated by the sheer volume of electronic documents involved — nearly 100 TB of data was implicated in multiple legal matters. Imagine more than 3 million bankers boxes carrying the printed equivalent of 100 TB of data.

The discovery scope was exceptionally broad — spanning hundreds of custodians across multiple business units and years. Combined with compressed timelines driven by parallel proceedings and filing milestones, this scope increased both volume and complexity and placed upward pressure on costs. The client sought a team that could rapidly onboard the matter and run a structured, effective and efficient discovery program — prioritizing key tasks, scaling capacity on demand and delivering transparent, metrics‑backed quality without missing deadlines.

The company selected Ernst & Young LLP after a series of meaningful discussions, because of the EY team’s ability to understand the complexities of the challenge, its knowledge and use of leading technologies such as AI and machine learning (ML), and its willingness to rapidly scale to meet the client’s needs.

From those initial meetings, a dedicated delivery team was assembled, comprising a group of senior eDiscovery and MDR specialists with extensive experience working in a collaborative fashion to standardize workflows, develop solutions and rapidly problem solve as needed. As the workload required, the team would be scaled up and down.

This strategic approach was designed to align closely with the client's and their counsel’s requirements so that the EY team could manage the extensive document volume efficiently while maintaining the highest standards of accuracy and reliability.

The EY team began by gaining a clear understanding of the client’s strict data security requirements and implementing processes to help handle all client materials in accordance with established policies.

From there, the team executed a quality-controlled, chain of custody — intact migration of more than 100 million documents into its discovery platform — navigating:

• Cross-version interoperability (SQL Server and Relativity)
• Rigorous storage and space planning
• Zero downtime continuity for active reviews
• One-for-one reconciliation and audit trails for every document
• Reacquisition of original sources and full metadata
• Reconstruction of legacy evidence reports and saved searches (with search parity validation)
• Capture of coding decisions and annotations, as well as review history
• Replication of custom fields, layouts and permissions
• Preprocessing to enable global deduplication; normalization of processing to enable global deduplication and normalization

That migration took place without disruption to ongoing reviews, allowing deadlines to be continually met.

The team focused on the following key priorities to deliver value and reduce costs.

Tailored technology — built a custom process for large file tagging that enabled faster review. In addition, the team utilized technology assisted review (TAR) to prioritize and assess which documents required human review. TAR uses machine learning to quickly identify patterns in large data sets (like documents found in eDiscovery) and make predictions about relevance — significantly reducing the amount of linear review needed.

Workflow management — developed proprietary, repeatable end-to-end e-discovery and MDR processes that can be leveraged to support any large litigation or investigation. Those workflows have proven to be effective and highly accurate.

The right people — the EY approach cantered on staying fully aligned with counsel. The scalable team model flexed seamlessly with evolving deadlines and regulatory requirements, focused on the right level of support at every stage. A responsive project management office (PMO) structure enabled the team to remain tightly coordinated, rapidly addressing tactical issues while also assisting counsel in setting strategy and communicating effectively with regulators. By operating as an integrated extension of the in-house legal team, the EY team kept workstreams synchronized, reduced turnaround times and helped escalate and resolve issues quickly.

Innovative reporting — developed a customized reporting process designed to support the client’s key areas of focus, identifying exceptions that required client intervention, such as password-protected or corrupted files.

Use of advanced AI technology to enhance review efficiency

The EY organization is at the forefront of applying advanced AI to streamline complex legal review processes. One aspect of this project involved the identification of trial exhibits. The EY team deployed EY proprietary AI technology to analyze approximately 5.5 million items within two weeks, rapidly isolating the most critical materials needed in the proceeding.

Demonstrating flexibility and technical depth, another EY team leveraged advanced AI to support a contract cleanup effort involving highly dense and complex agreements. AI performed a rapid first pass review, extracting and organizing relevant clauses to streamline the client’s analysis. This approach significantly reduced manual review effort, accelerated decision making and enabled the client to focus on higher value judgment rather than initial document triage.

This combination of technological innovation and adaptive problem solving underscored the ability to meet the demanding timelines and precision requirements across a wide range of complex legal matters.

The strategy for managing e-discovery and MDR significantly reduced the number of documents that required human review — the most time-consuming and expensive component of the discovery process.

Together, customized technical solutions and TAR removed the need for linear review across a large initial document population, delivering approximately $30 million in cost savings relative to a traditional review model.

In rapid response to time-sensitive deadlines, EY scaled up its MDR review capacities to approximately 250 experienced contractors, who were able to complete all first-level, redaction review and quality control in less than eight months. This included a total of 5.8 million documents, meeting critical SLAs and allowing the client to positively respond to multiple regulators.

The use of the EY MDR team — both employees and experienced legal contractors – saved the client another $90 million, compared to similar services provided by a law firm.

“Our client went from wrestling with a complex, often overwhelming discovery process to being extremely pleased with its structure, accuracy and expense,” said Scott Clary, Principal, Forensic & Integrity Services, Ernst & Young LLP. “The EDRM process is highly consequential with significant legal implications and being able to count on our detail-oriented, cost-effective ‘one-team approach’ gives the client a real sense of clarity and comfort. We’ve been able to earn their trust and change how they view EDRM.”