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  • Service: Advisory, Risk Consulting, Forensic, Forensic Technology
  • Date: 5/8/2013

Quality Control in Predictive Coding for eDiscovery 

Predictive coding is a powerful new tool for eDiscovery. It promises increased efficiency but leads to more complex work flows and new quality-control challenges. A successful quality control strategy should address both the training and application phases of predictive coding. Statistical sampling is indispensible for modern eDiscovery quality control in any application. Additional strategies include tracking, checklists, and developing a transformative, enterprise-level approach to eDiscovery for comprehensive, repeatable quality control.

Quality Control in Predictive Coding for eDiscovery
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Rising litigation and investigations are topping out corporate legal budgets in the millions—often nearly 75 percent of this for eDiscovery costs requiring companies to preserve, collect, review, and produce millions of e-mails and documents as evidence. Given growing data volumes in the enterprise, eDiscovery risks and costs have increased, particularly for document review, which often comprises 75 percent of eDiscovery budgets.


Savvy corporate litigants are adopting a new technology called predictive coding as a powerful tool to increase efficiency in document review, typically reducing their eDiscovery costs by half. Yet this emerging technology requires high standards of quality control to increase court defensibility and help lower the risk of a potential dispute.

 

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