by Matthew Verga - Advanced Discovery
on February 24, 2017
Legal & Industry Education
Review & Production
This blog post is a thorough introduction to the ways high-level metrics from your e-discovery projects, when viewed holistically, can help influence a smarter e-discovery strategy for your business. It was originally published on the Advanced Discovery blog as part of their recent series on business intelligence.
In the first part of this short blog series, we began by reviewing core business intelligence concepts and how they can apply during an individual e-discovery project. Here, we review how they apply across individual e-discovery projects as part of effective e-discovery program management.
As we noted, each individual e-discovery project provides opportunities for tracking and aggregating useful metrics about both substantive elements of the project (i.e., sources, materials, and their contents) and formal elements of the project (i.e., tools, individuals, and their processes). Tracking these metrics can provide insights that lead to improvements in efficiency and efficacy during a project, but there is third category of macro elements about which we can also track metrics to facilitate overall program management.
Macro elements are those that are unlikely to have utility during an individual project but that, if tracked, can still lead to improvements across projects. For example, the following are all macro elements about which metrics might be tracked to aid in program management:
Beyond these specific examples, tracking key metrics across projects, in an organized, aggregated way, makes it possible to establish efficiency, efficacy, and cost benchmarks for your processes and activities. And, from those benchmarks, concrete goals for iterative improvement can then be set.
Next, let’s review some of the major subcategories of macro, cross-project metrics that you might track and examples of the benefits that tracking them can yield.
This subcategory of metrics covers information about your data and where it comes from, including: sources; source types; individual custodians; departmental custodians; mobile device sources; cloud sources; social media sources; file types; and, volumes for all of these and more. Tracking this data across projects can yield a variety of potential benefits:
This subcategory of metrics covers information about your processing activities, including: platforms and tools used; throughput and error rates achieved; variations in completion time for various source types; filtering techniques employed and their rates of volume reduction; and, hours of employee work required per job and more. Tracking this data across projects can also yield a variety of potential benefits:
This subcategory of metrics covers information about your early case assessment activities, including: platforms and tools used; search and analytics features applied; volume reductions achieved; time spent; and, reviewers required and more. Tracking this data across projects can also yield a variety of potential benefits:
Within a single e-discovery project, review metrics are invaluable for team management and oversight, but across projects additional variables can be tracked, including: platforms and tools used; batch sizes and batch organization used; review team sizes and team organization used; application of email threading and near-duplicate grouping; privilege logging and redaction workflows employed; and, details of any technology-assisted review (TAR) process employed. Tracking this data across projects can also yield a variety of potential benefits:
This subcategory of metrics covers additional useful information that cuts across several or all phases of an e-discovery project, including: matter type; jurisdiction; value at risk; outcome achieved; total project costs and total costs per document ultimately produced; internal resources and outside service providers employed; and, overall ratio of documents collected to documents produced and more. Tracking this additional data across projects is invaluable for overall program management and can yield a variety of potential benefits:
As you can see from this list of examples, the range of things you might track project-to-project is vast, and the range of insights you might gain is equally so. A key question for each organization will be which metrics are worth the cost and trouble of tracking, and that will be dictated, in part, by your long-term goals for the effort.
Matthew Verga is an e-discovery expert with legal experience as an attorney, technical knowledge as a practitioner, and passion as a communicator. A nine-year industry veteran, Matthew has worked across every phase of the EDRM and at every level from the project trenches to enterprise program design. He is vice president of marketing content for Advanced Discovery.
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