ホーム
すべてのリソース
ケーススタディ

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.

以下のフォームに記入して、詳細なインサイトをダウンロードしてください。

Singapore
Sint Maarten (Dutch part)
Slovakia
Slovenia
Solomon Islands
Somalia
South Africa
South Georgia and the South Sandwich Islands
South Sudan
Spain
Sri Lanka
Sudan
Suriname
Svalbard and Jan Mayen
Swaziland
Sweden
Switzerland
Syrian Arab Republic
Taiwan, Province of China
Tajikistan
Tanzania, United Republic of
Thailand
Timor-Leste
Togo
Tokelau
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Consilioの最新情報にサインアップ

ロレム・イプサム・ドロール・シット・メット、コネクター・ディピッシング・エリット。様々なものを悲惨な要素にぶつけます。
ありがとう!提出物が受理されました!
「サインアップ」をクリックすると、当社に同意したものとみなされます プライバシーポリシー
おっと!フォームの送信中に問題が発生しました。