Home
All Resources
案例研究

Case Study: Use of TAR in FTC Antitrust Probe to remove 2.6M Documents from Review

Written by admin

Updated: Jul 19, 2021

Authors
More from the author

Client Challenge

A microchip manufacturer sought Consilio’s assistance with an FTC antitrust probe spanning 25 custodians and five years-worth of data.

Consilio Response

Facing a population under review of over 5.6 million documents, Consilio proposed a TAR 1.0 workflow that garnered FTC approval. This included a categorical analysis prior to TAR modeling, where Consilio identified and removed from review over 400,000 unreviewable or categorically non-responsive documents. Facing a tight discovery timeline, Consilio managed the TAR training process while collections were on-going, causing data to be added for analysis on a regular basis. At the conclusion of the TAR process, the FTC challenged Counsel’s proposed recall level and suggested through a novel statistical analysis that a high (80%) recall level was appropriate in the matter. Consilio, after thorough examination of the FTC’s position and analysis, countered with its own statistical and graphical analysis, supporting the client’s claim that a lower recall level (and smaller overall review volume) offered a better balance of precision and F-score. Using these analyses, the client was able to negotiate a more favorable recall rate.

Results Achieved

At the conclusion of the TAR modeling and training for this phase of the litigation, Consilio was able to leverage Brainspace to remove over 2.6 million documents from production and privilege review.

Download the fact sheet or contact us to learn more about our Complete Intelligence capabilities.

Client Challenge

A microchip manufacturer sought Consilio’s assistance with an FTC antitrust probe spanning 25 custodians and five years-worth of data.

Consilio Response

Facing a population under review of over 5.6 million documents, Consilio proposed a TAR 1.0 workflow that garnered FTC approval. This included a categorical analysis prior to TAR modeling, where Consilio identified and removed from review over 400,000 unreviewable or categorically non-responsive documents. Facing a tight discovery timeline, Consilio managed the TAR training process while collections were on-going, causing data to be added for analysis on a regular basis. At the conclusion of the TAR process, the FTC challenged Counsel’s proposed recall level and suggested through a novel statistical analysis that a high (80%) recall level was appropriate in the matter. Consilio, after thorough examination of the FTC’s position and analysis, countered with its own statistical and graphical analysis, supporting the client’s claim that a lower recall level (and smaller overall review volume) offered a better balance of precision and F-score. Using these analyses, the client was able to negotiate a more favorable recall rate.

Results Achieved

At the conclusion of the TAR modeling and training for this phase of the litigation, Consilio was able to leverage Brainspace to remove over 2.6 million documents from production and privilege review.

Download the fact sheet or contact us to learn more about our Complete Intelligence capabilities.

Fill out the form below to download the complete insight.

Lesotho
Liberia
Libya
Liechtenstein
Lithuania
Luxembourg
Macao
Macedonia, the former Yugoslav Republic of
Madagascar
Malawi
Malaysia
Maldives
Mali
Malta
Marshall Islands
Martinique
Mauritania
Mauritius
Mayotte
Mexico
Micronesia, Federated States of
Moldova, Republic of
Monaco
Mongolia
Montenegro
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Sign up for Consilio updates

不管怎么样,我们都很友善,祝你好运。在悲惨的情绪中,人们对各种各样的恐惧感情有独钟的感觉。
谢谢!您提交的内容已收到!
单击 “注册” 即表示您确认您同意我们的 隐私政策
哎哟!提交表单时出了点问题。