Migrating eDiscovery data between platforms is never just a technical exercise. It is a strategic shift that demands careful planning and execution. Whether prompted by a vendor change, platform upgrade, or system consolidation, a successful data migration hinges on what happens before a single file is moved. Poor preparation at this stage can lead to downstream issues including data loss, broken workflows, and complications in maintaining defensibility.
Much of that risk can be mitigated by what happens first: developing a clear understanding of existing data, defining what should be moved, and putting structure around how those decisions are made. A methodical approach early on creates the conditions for a smoother, more defensible migration process from start to finish.
Centralizing Project and Workspace Visibility
And that process starts with visibility. One of the most common and costly mistakes is failing to maintain a single, accurate, and frequently updated database of all projects and workspaces. Often, attention is limited only to projects targeted for migration, overlooking others that may be active, dormant, or in need of archiving. Without a centralized project inventory, it is easy to miss data that should have been transferred, which can jeopardize continuity and increase legal risk.
To avoid these oversights, you should begin with a complete accounting of all current and historical projects across platforms. This living document should include key details such as project owners, custodians, matter status, last activity date, and estimated data volumes. It forms the foundation for all downstream decision-making and reduces the likelihood of missteps once data migration is underway.
Making Smart, Defensible Project Decisions
Once visibility is established, the next step is determining what to do with each project. Not every workspace needs to be migrated, and not every workspace should be. Before any data is moved, each must be evaluated to determine its appropriate disposition. Is it active litigation? A regulatory hold? A legacy matter with no ongoing legal relevance? The goal is to segment projects into three categories: migrate, archive, or delete.
These decisions must be documented and justified. For example, if a project is near completion or slated for deletion, the resource investment required to migrate it may outweigh the benefit. On the other hand, skipping the migration of a matter that still carries regulatory exposure could lead to compliance concerns later. Establishing clear criteria for inclusion and tying each decision back to the underlying legal or business rationale ensures a defensible process.
Categorizing Data for Complete Coverage
After confirming which projects will be migrated, attention must turn to the structure of the data itself. Within each project, different data types must be handled according to their role in the eDiscovery lifecycle. Collected data, processing source data, processed data, review work product, production sets, and database files all serve different functions and must be accounted for separately.
Additionally, each version of the data, such as source copies, working copies, transfer deliverables, and destination imports, carries implications for chain of custody and data integrity. Without careful categorization and documentation, it is easy to lose track of which data was transferred, which was transformed, and which may have been excluded unintentionally.
Establishing Governance and Inventory Controls
In order to make these strategic decisions and perform thorough data categorization, you need a framework to guide execution. That framework is governance. A successful data migration begins with well-defined documentation, including a statement of work, a maintained decision log, and clear scope tracking as the project evolves. Without this structure, you could risk making undocumented assumptions that later compromise defensibility or compliance.
Strong governance also supports efficient execution. Projects should be grouped into migration tranches based on logical criteria such as size, activity level, priority, or department. Creating these cohorts allows for staged planning, risk-based prioritization, and effective resource management.
Alongside governance, detailed inventory controls are essential. A clear accounting of all data sources, including estimated volume, file count, and current storage paths, ensures visibility into what will be transferred and what might need to be excluded. This inventory also provides a baseline for monitoring integrity and tracking anomalies during the migration process.
Conclusion
While essential, laying the groundwork for a successful data migration is not just about project tracking or governance documentation. It’s about establishing clarity, ownership, and defensibility before the first byte moves. The decisions made during this early phase influence every subsequent step, shaping how data is handled, how risks are mitigated, and how success is ultimately measured. When this strategic layer is built with precision, it becomes far easier to navigate the technical and operational complexities that follow.
Joey Adams
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Joey Adams leads TCDI’s Systems Operations team, which is responsible for the day-to-day technical management of the company’s client-facing software. Since joining TCDI in 2001, Joey has held a range of roles from software development and implementation engineering to project management, on-site client support, and database administration.
Today, his team handles everything from software installations and second-level support to the technical aspects of data migrations. With more than two decades of industry experience, Joey brings a deep understanding of legal technology infrastructure and a hands-on approach to ensuring reliable, high-performing systems for TCDI’s clients. Learn more about Joey >
