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Case Study: Leveraging Analytics & Smart Review to Efficiently Respond to a Data Breach

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Updated: Jul 19, 2021

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Client Challenge

A large, state-run health organization was facing a large volume of data requiring smart data culling and review techniques to identify personally identifiable information (PII) and protected health information (PHI) efficiently. Our client faced several challenges posed by:

• Very large document repository of a nearly one million documents (143.72 GB) for analysis and/or review.
• Tight deadlines to meet concurrent work stream requirements.
• Facing on-going matters and costs, client required efficient workflows so costs and risks are controlled to the fullest possible extent.

Consilio Response

Collaborating with the client and outside counsel, we implemented our data breach response workflow with the leverage of analytics to conform to the client’s workflow requirements, ensure quality reviews while driving down the total cost.

Coordinated between client’s general counsel, matter-specific legal team, outside counsel and review teams, Consilio:

• Received and processed nearly 1 million documents into Consilio’s secured data center and custom-built, sensitive data screening tools.
• Trained and assigned a review team with little to no turnover, allowing for very high levels of
consistency across a lengthy review period.
• Searched and reviewed to identify protected health information (PHI).
• Consilio applied various respective search terms to identify documents containing potential PII to
achieve 84% reduction in document count volume for subsequent review

Results Achieved

Facing 930,561 documents to review, Consilio teams leveraged analytics and effective culling techniques to identify only 150,072 documents relevant or a reduction of 84%.

Leveraging machine learning technology, our reviewers were able to improve review quality and output by 30%.

Combining smart culling, machine learning and proven review workflows, we delivered $66,295 in cost savings for the client over traditional techniques.

Client Challenge

A large, state-run health organization was facing a large volume of data requiring smart data culling and review techniques to identify personally identifiable information (PII) and protected health information (PHI) efficiently. Our client faced several challenges posed by:

• Very large document repository of a nearly one million documents (143.72 GB) for analysis and/or review.
• Tight deadlines to meet concurrent work stream requirements.
• Facing on-going matters and costs, client required efficient workflows so costs and risks are controlled to the fullest possible extent.

Consilio Response

Collaborating with the client and outside counsel, we implemented our data breach response workflow with the leverage of analytics to conform to the client’s workflow requirements, ensure quality reviews while driving down the total cost.

Coordinated between client’s general counsel, matter-specific legal team, outside counsel and review teams, Consilio:

• Received and processed nearly 1 million documents into Consilio’s secured data center and custom-built, sensitive data screening tools.
• Trained and assigned a review team with little to no turnover, allowing for very high levels of
consistency across a lengthy review period.
• Searched and reviewed to identify protected health information (PHI).
• Consilio applied various respective search terms to identify documents containing potential PII to
achieve 84% reduction in document count volume for subsequent review

Results Achieved

Facing 930,561 documents to review, Consilio teams leveraged analytics and effective culling techniques to identify only 150,072 documents relevant or a reduction of 84%.

Leveraging machine learning technology, our reviewers were able to improve review quality and output by 30%.

Combining smart culling, machine learning and proven review workflows, we delivered $66,295 in cost savings for the client over traditional techniques.

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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
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