How to spend your time on operations, not lawsuits

State government organizations have a legal problem—and it’s not just the quantity of lawsuits.

Due to the astounding growth of electronically stored information (as much as tenfold every five years), responding to even a single legal discovery request can be a monumental disruption to a state agency’s day-to-day operations.

Just imagine having to—suddenly—divert a huge portion of your IT resources toward searching and analyzing immense piles of data in preparation for a lawsuit, and what that might do to your short-term operating efficiency.

You could refuse to comply, of course. But today’s courts are having less and less tolerance for the inability to produce electronic information in a timely fashion. In fact, discovery-related sanctions pertaining to electronic files are up 271 percent over the last five years.

Fortunately, there’s a third option: automated electronic discovery (eDiscovery) technologies that can work across multiple platforms to store and retrieve the information you need, while filtering out redundant data.

These days, state government agencies are having great success finding eDiscovery solutions with the perfect mix of capability and efficiency. In fact, many are able to recoup their entire eDiscovery investments after a single case.

But what should state governments look for in an eDiscovery solution?

The first piece is end-to-end capability. The legal discovery process for electronic files is actually three discrete processes—the identification, preservation, and collection of data; the processing, analysis, and review of data; and the production and presentation of data. State government organizations can maximize efficiency and minimize costs by choosing a solution that encompasses all three phases.

The second piece is analytics. When state governments think about search tools, they typically only think of keyword search. But advanced eDiscovery analytics offer powerful new ways to find the precise information you need, and nothing more. Predictive coding, for instance, is a mathematical method for “teaching” your software to mimic the way human reviewers analyze documents, and it’s been known to slash document review expenses by as much as 90 percent. (After all, computers can search through millions of records without ever tiring or losing focus.)

The third and final piece is accommodation for multiple use cases—the three most common being investigative use cases, defensive use cases, and use cases involving the Freedom of Information Act. Ideally, an eDiscovery solution should support all three of those categories, while also providing the customization needed for optimizing your own eDiscovery procedures and requirements.

Choosing an eDiscovery technology platform—one that’s easy to use, fast to implement, and trusted to deliver—is indeed crucial. But it’s also important to build a comprehensive plan around that technology—something that assigns responsibilities, articulates goals, and defines strategies for maximally efficient operations.