AI-based Analytics: The key to business-led eDiscovery
- December 19, 2018
- by Amit Dungarani
GCs have tightened many aspects of their operations since the Great Recession. E-billing and matter management technology come to mind, along with outside counsel guidelines and procurement-influenced law firm selections. The next law department frontier is building a business mindset among their lawyers. No law department area is riper for business-led decision making than cost-bloated eDiscovery.
GCs Want business-led eDiscovery
Today GCs are not only responsible for legal risk management—they are senior business leaders with large operational budgets and a seat at executive and board tables. As such, GCs are expected to run the legal department like a business. To accomplish this, their lawyers, schooled in risk analysis and winning at all cost, must become more business-led. Legal teams must root early eDiscovery decisions in data and business analysis to produce cost-effective outcomes.
Upfront detailed, case-specific cost analysis, planning and metrics must become the norm. Early in the case, lawyers should develop performance metrics—examples include percentage of data collected that proved relevant, early case assessment length, estimated vs. actual review costs and so on for every case. Departments should also have a few simple macro-level eDiscovery metrics to chart overall progress. Once eDiscovery begins, metrics monitoring must be constant, with course corrections to stay on budget. GCs also need their teams to have the discipline to measure eDiscovery actuals against metrics after a case closes. In the rush to the next matter, this rarely happens.
AI-based analytics that rifle through mountains of case data upfront are key to achieving more business discipline in eDiscovery. Graphical visualizations of data types, custodian files, email interactions and more help teams quickly make informed preservation, collection and early case assessment (ECA) decisions. Analytics’ case-specific insight forms the basis for rigorous cost estimates, meaningful metrics and resource allocations.
Old Risk-based Habits Die Hard
Old habits, however, die hard. A risk-averse culture and a lack of investment in high-caliber analytics for the early stages of eDiscovery prevent law departments from building business-led eDiscovery.
Surprisingly, over-preservation and large-scale collections are still standard procedure in many law departments. Risk-averse legal teams blanket hundreds even thousands of potential custodians with a legal hold. Some hyper-cautious teams will even collect the entire universe of preserved data. Others rely on “gut instinct” to land on a round number of 50 or 100 custodians for the collection. Overly-broad decisions like these are costly and disrupt everyday business, with employees giving up their laptops for collection for hours or days at a time.
What drives this habit? Clearly, it’s the fear of a preservation sanction or an order compelling additional collections and associated fees. Most lawyers have yet to “take a risk” and rely on proportionality-focused rules amendments and recent court rulings aimed at “right-sizing” discovery data burdens on businesses. The availability of information from another source or from restored data is now an acceptable reason for omitting data. A business-led lawyer would say, “let’s experiment with how to use this to our advantage.”
Another common eDiscovery pitfall is the use of standard approaches for every case. Rather than dig in and discern data minimization and cost estimates for each case, many practitioners use generic formulas. Dubious tenets like “every stage of large cases goes to law firms” or “law firms always manage review for us” still rule the day. Teams automatically slap project planning formulas like 0 to 6 months for ECA, 6 to 12 months for full-blown eDiscovery and 12 to 24 months to finish eDiscovery, motions and trial preparations onto every eDiscovery project.
In some ways this practice is understandable. Instead of getting bogged down in difficult, time-consuming, manual data-chopping lawyers move on, using generic standards. This peanut butter approach means some cases are over-budgeted, while others are under-budgeted. Not only does this blow budget forecasting, it also skews the overall portfolio business insights that the GC wants.
A business-led lawyer would strive for smaller, targeted collections. To act more like a business, the team would ask how can we shave months off ECA? Staff would craft case-specific budgets and resource allocations using insights, not generic formulas.
Why GCs Want eDiscovery Analytics
GCs looking to crack the code for business-first eDiscovery must consider AI-based eDiscovery analytics. Analytics are fundamental for business decision-making in other business units these days—why wouldn’t a business-led legal department leverage them too?
Gaining insight is so much easier and faster with graphical depictions of case data. Lawyers can instantly see patterns and connections to map where the action is in a case. This kind of rapid data manipulation, classification and focus is essential for business-led eDiscovery. The optimized use of eDiscovery analytics early in eDiscovery allows GCs to:
- Minimize collection costs and business disruption
- Make faster case go/no-go decisions
- Implement case-specific performance metrics
- Make data-based decisions
- Allocate resources to optimize efficiency
- Track business metric progress across the portfolio
- Document data-based decisions for defensibility
GCs that provide their lawyers with AI-based analytics for early case decision-making and business planning will reap the benefits of business-led eDiscovery. A focus on trusted technology with rock-solid defensibility will win over even the most risk-oriented lawyers on your team. Learn more here about eDiscovery AI analytics for smarter, early business decision-making.