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Presented to AIIM William Penn Chapter Meeting 5/13/08

Presented to AIIM William Penn Chapter Meeting 5/13/08

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Presented to AIIM William Penn Chapter Meeting 5/13/08. Enterprise Content Management. Efficiency and Effectiveness Gains. Electronically organize and classify unstructured documents Support organizational records retention and disposal policies and practices - PowerPoint PPT Presentation

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Page 1: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Presented to

AIIM William Penn Chapter Meeting

5/13/08

Page 2: Presented to  AIIM William Penn Chapter Meeting 5/13/08
Page 3: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Enterprise Content Management

Electronically organize and classify unstructured documents

Support organizational records retention and disposal policies and practices

Facilitate e-Discovery and support litigation hold policies and procedures

Significantly reduce time to search for and locate relevant materials

Ensure legal and regulatory compliance through electronic processes and security

Efficiency and Effectiveness Gains

Page 4: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Utilize the proven AIIM content management methodology to: Capture Manage Store Preserve Deliver

organizational information, content, and documents

Page 5: Presented to  AIIM William Penn Chapter Meeting 5/13/08

EDD Process

Receive Data

Index

Reduce

Search

Convert

Package

Burn

Page 6: Presented to  AIIM William Penn Chapter Meeting 5/13/08
Page 7: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Scan, classify, and upload to centrally stored and organized repository

Access from anywhere, at any time

Perform complex searches, annotation and redaction with any document

Streamline productions for opposing counsel

Page 8: Presented to  AIIM William Penn Chapter Meeting 5/13/08

of the time discovery requests are not satisfied.50%

go through one or more requests per month.33%

of corporations with 20,000+ employees have been through an electronic discovery request.91%of corporations with 1,000+ employees have been through an electronic discovery request.50%

Why is eDiscovery So Important?

Page 9: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Data review is the largest addressable cost in discovery – Forrester Report, 2006

Near-duplicates are the largest addressable cost in data review – Equivio users, 2006

“Tools aimed at making lawyers…

as efficient as possible

represent the largest potential

cost savings in eDiscovery”

- p.5

Page 10: Presented to  AIIM William Penn Chapter Meeting 5/13/08

=The Problem=

Page 11: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Group the near-duplicates

=The Solution: Step 1=

Page 12: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Assign near-dupe

sets for coherent review

=The Solution: Step 3=

Page 13: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Review just the differences

Priority review

=The Solution: Step 4=

Page 14: Presented to  AIIM William Penn Chapter Meeting 5/13/08

=The Solution: Step 5=

Consistent treatment

Page 15: Presented to  AIIM William Penn Chapter Meeting 5/13/08

EquiSet PivotSimilarity vis-à-vis

pivot

Page 16: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Displays differences

Page 17: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Equivio>Email Threads

Page 18: Presented to  AIIM William Penn Chapter Meeting 5/13/08

=The Problem=

Reply to the Reply

Original email

Near-duplicate Email

Reply

Email

Reply to Near-duplicate Email

Unstructured collection of emails

Page 19: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Group email sets

=The Solution=

Page 20: Presented to  AIIM William Penn Chapter Meeting 5/13/08

+

+

+

+

+

+ Suppress duplicates

Identify missing links

Build tree structure

Focus on “inclusives”

=The Solution=

Page 21: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Review Differences

Page 22: Presented to  AIIM William Penn Chapter Meeting 5/13/08

• Detects similarity of content, regardless of file type or formatting

•Microsoft Office -- Word, PowerPoint, Excel

•Email – PST, EML, MSG

•PDF

•ZIP

•HTML

•Text

•OCR-generated files

• File deconstruction – e.g. email body and attachments

• Allows user to regulate level of similarity

• Multi-lingual support

• Self-tuning

Page 23: Presented to  AIIM William Penn Chapter Meeting 5/13/08

Summation

Equivio

Demonstrations