Courts and legal experts are endorsing the emerging best practice of iterative measurement of selection results, borrowing from established and effective data management practices outside of the litigation setting. At the same time, its application has come under increasing scrutiny. As several high-profile cases have shown, there can be significant risks—of both increased discovery costs and various discovery sanctions—if a litigant fails to properly calibrate its selection criteria.

The good news is that a reasonable, defensible, best-practice approach to using selection criteria and cost-effective discovery are not mutually exclusive. This white paper examines how an iterative approach to calibrating selection criteria not only is easier to defend from attack by opposing parties but also in many cases will reduce the overall cost of discovery by eliminating more irrelevant documents from processing and review.

Download the white paper now (PDF | 168 KB)