How do you manage an eDiscovery workflow?

Managing an eDiscovery workflow is mostly about making a sequence of handoffs visible and repeatable. The stages themselves are well established - the EDRM reference model breaks them into identification, preservation, collection, processing, review and analysis, and production - and most trouble comes from the gaps between stages rather than the stages themselves.

Practical ways teams keep it under control

• Work backwards from the production deadline. Set target dates for collection complete, processing complete, and review complete, then track against them weekly.
• Keep one authoritative scope record. Custodians, date ranges, sources, and search terms change during a matter. If that lives in email threads, nobody knows the current scope.
• Document culling decisions as you make them. Deduplication, date and domain filters, and search term choices are all questions you may have to answer later.
• Write the coding manual before review starts, and keep the issue codes few enough that reviewers apply them consistently.
• Build QC in rather than bolting it on at the end. Sampling batches during review catches a misunderstood code in the first thousand documents instead of the last.
• Log handoffs. Who loaded which volume, when, and what the document counts were before and after.

Automation earns its place at the points with the highest manual overhead: prioritising what gets looked at first, collapsing near-duplicates and email threads, and running a consistent first pass so lawyers spend their time on the documents that actually matter.

Related reading: the Ultimate AI-Powered eDiscovery Workflow Automation Guide goes deeper on automating these steps.

Claira is an AI eDiscovery platform for document review at scale - you can book a demo to see where it fits in a workflow like this.