How is Predictive Coding revolutionizing the economics of eDiscovery?
Predictive Coding is a court-endorsed process that combines people, technology and workflow to find key documents quickly, irrespective of keyword. Due to its massive accuracy and efficiency gains, Predictive Coding is revolutionizing how Early Case Assessment (ECA), analysis and document review are done.
Traditional linear review including keyword search, a manual, expensive, time-consuming and error-prone process requires teams of legal professionals to review hundreds of thousands or millions of documents one page at a time to determine relevance to the case. This review step in the eDiscovery process drives the largest cost of eDiscovery - having legally trained people actually read documents that have been singled out by some method, usually a keyword search, to have some content that may be potentially responsive to the case.
The obvious problem with the traditional review method is that keyword searches produce huge amounts of documents; hundreds of thousands, millions, tens of millions or more. These millions of documents all have to be read to determine responsiveness.
In the last several years a new, more accurate and less costly eDiscovery review process has been used successfully in many court cases including several high profile cases. Predictive Coding, a next generation document review and analysis technology, includes disruptive technology that has the ability to dramatically reduce document review time, measurably lower document review costs and raise accuracy well beyond traditional linear review techniques.
Predictive coding provides a computer-generated judgment, throughout several iterations of machine learning, with an explicit confidence score about the relevance of each document. This capability allows counsel and their clients to dramatically expedite the actual document review process by automatically assessing the relevance of documents and prioritizing large numbers of documents as responsive while concurrently improving accuracy and lowering the risk of missing key documents. The end result is human reviewers actually read a much smaller percentage of the corpus. With that understanding in mind, it’s useful to actually calculate the projected cost savings and return on investment (ROI) to show financial justification of the investment.
This Recommind white paper, “Cost Savings and the ROI of Predictive Coding” explores the cost savings of predictive coding vs. traditional linear review.
Topics covered in this white paper include:
- Comparing traditional linear review to predictive coding
- Calculating predictive coding cost savings
- What is ROI?
- Calculating ROI for predictive coding
Predictive Coding is where things are going in eDiscovery. Learn more about Predictive Coding by …
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• Viewing the Recommind Webinar: “The ROI of Predictive Coding”
• Watching the Recommind Video “Predictive Coding Explained”
• Viewing the Recommind Webinar: “Debunking the Myths of Predictive Coding”
• Downloading the Recommind eBook “Predictive Coding For Dummies”
And then …
• Calculate your Estimated Savings using Recommind’s Predictive Coding ROI Calculator
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