Data Targeting to Reduce EDVERTISING Costs

Transcription

1 Zeroing In, Data Targeting to Reduce ediscovery Volumes and Costs Thursday, September 10th, 2015 Matthew Verga, Director of Content Marketing and ediscovery Strategy Modus ediscovery

2 ACEDS Membership Benefits Training, Resources and Networking for the E-Discovery Community Exclusive News and Analysis Weekly Web Seminars Podcasts On-Demand Training Networking Resources Jobs Board & Career Center bits + bytes Newsletter CEDS Certification And Much More! ACEDS provides an excellent, much needed forum to train, network and stay current on critical information. Kimarie Stratos, General Counsel, Memorial Health Systems, Ft. Lauderdale Join Today! aceds.org/join or Call ACEDS Member Services

3 Featured Speakers Experts from Technology, Government, Corporate and Law Firms Craig Ball ESI Special Master Computer Forensic Examiner & Attorney Chris Dix, CEDS Shareholder Smith, Hulsey & Busey Mary Mack Enterprise Technology Counsel ZyLAB Michael Simon Principal Seventh Samurai

4 ZEROING IN DATA TARGETING IN EDISCOVERY TO REDUCE VOLUMES AND COSTS

5 WELCOME Thank you for joining Numerous diverse attendees Please feel free to submit questions Slides, recording and survey coming tomorrow

6 SPEAKERS Matthew Verga Director, Content Marketing and ediscovery Strategy

7 TODAY S TOPICS A Data Targeting Perspective Data Targeting - Before Litigation - During Collection - During Processing - During ECA Strategy and Negotiation Conclusion - Key Takeaways - Questions and Answers

8 A DATA TARGETING PERSPECTIVE

9 A DATA TARGETING PERSPECTIVE Why does this matter? - Because of the high and ever-increasing cost of discovery 2012 Rand Corporation Study: - Median cost of ediscovery production was $1.8 million - Document review accounted for $0.73 of every $1.00 spent - the relationship between final costs and ESI volume is essentially a directly proportional one. Thus, volume reduction = cost reduction

10 A DATA TARGETING PERSPECTIVE What do we mean by a data targeting perspective? - Elevating technical considerations - Elevating strategic considerations - At each step: o What are the technically feasible options o Strategic value of culling versus retention o Interplay between technical, strategic, and legal

11 A DATA TARGETING PERSPECTIVE What you legally need to review and/or produce What it is technically feasible to do What efficiently uses available time and money

12 A DATA TARGETING PERSPECTIVE Discovery as information retrieval exercise "Information-Retrieval-Models". Licensed under CC BY-SA 3.0 via Commons - Retrieval-Models.png#/media/File:Information-Retrieval-Models.png

13 A DATA TARGETING PERSPECTIVE Sources File Types Dates Keywords

14 A DATA TARGETING PERSPECTIVE Desired Message Threads DATASET Desired Concept Clusters

15 A DATA TARGETING PERSPECTIVE This program is not about knowing it all Knowing it all is a full-time job you don t have time to do This program is about Familiarizing you with the range of options available Demonstrating how the options work together Equipping you to pose the right questions to the right people

16 BEFORE LITIGATION

17 DATA TARGETING BEFORE LITIGATION Don t wait for litigation to begin Proactive steps can be taken to reduce volumes and costs First, retention and remediation can be addressed - Critical first step - Clear policies and procedures - Categories and retention periods - Limiting duplicative retention - Remediation to compliance

18 DATA TARGETING BEFORE LITIGATION Second, proactive data mapping can be completed Benefits of pre-litigation data mapping Elements of a useful data map - Potentially relevant data stores - What records for what time periods - Searching and extraction options - Responsible individuals/roles - Employee-issued devices in use

19 DURING COLLECTION

20 DATA TARGETING DURING COLLECTION Reactive data mapping Selecting custodians and sources Custodian interviews - Sources, practices, terms, etc. - Paper vs. electronic options Physical vs. logical acquisition - When to select which option?

21 DATA TARGETING DURING COLLECTION Selective Restoration - Forensic image and content reports o Usefulness o Limitations - Selection by directory, group or mailbox o o Loose files - Back-up tape options o Options and current technology - Selection by date o Limitations and risks File type filtering o Options and considerations

22 DURING PROCESSING

23 DATA TARGETING DURING PROCESSING Inclusion vs. exclusion - What is the difference? Directory or custodian filtering - Available options De-NISTing - What is it? - How is it executed?

24 DATA TARGETING DURING PROCESSING File-type filtering - Methods - Associated risks De-duplication - General method - Options available - Significance and impact - Document families

25 DATA TARGETING DURING PROCESSING Date range filtering - Methods - Associated risks and considerations Keyword filtering - Available options - What to look out for? - Better to wait?

26 DURING ECA

27 DATA TARGETING DURING ECA ECA vs EDA - EDA FTW (for the win) - Value increases with data volume - Many options, many tool-specific Random sampling - Utility and benefits - Sample sizes - Things you can learn

28 DATA TARGETING DURING ECA communication filtering - Sender and recipient - Domain names - Subject lines Keyword filtering - Simple, Boolean, fuzzy - ECA/EDA is the time o Best search tools o Best reporting options o Easiest iteration File type/size/format filtering - For review efficiency - For predictive coding quality Concept search/find similar - Natural language queries - Synthetic examples, good and/or junk

29 DATA TARGETING DURING ECA threading - Grouping, sequencing, content analysis, visualization - Organization versus disposition Near duplicate identification - Multiple techniques, variable thresholds - Organization versus disposition Conceptual analytics - Conceptual clustering, categorization, CAR - Advantages and disadvantages

30 STRATEGY AND NEGOTIATION

31 STRATEGY AND NEGOTIATION The kitchen sink approach is not recommended Broad overview provided to show range Project specific strategies must be developed - Factors to consider o Available time o Available budget o Technological resources o Human resources o Matter-specific concerns

32 STRATEGY AND NEGOTIATION Data Targeting Before Litigation (EDRM IM Phase) Data Reduction During Collection (EDRM Identification, Preservation and Collection Phases) Retention, Remediation, Mapping Targeted Collection, Selective Restoration Data Targeting During Processing (EDRM Processing Phase) Data Targeting During ECA (EDRM Analysis Phase)* Directory Filtering, Custodian Filtering, De- NISTing, File-Type Filtering, Deduplication Date Range Filtering, Keyword Filtering Random Sampling, Communication Filtering, Keyword Filtering, Conceptual Analytics, Threading Review

33 STRATEGY AND NEGOTIATION Negotiation can be the most powerful tool of all Negotiation with opposing parties - Before, during, and after 26(f) - With judge, if necessary Negotiated agreements - Can limit scope - Can specify methodology - Can be incorporated into orders and enforced

34 CONCLUSION

35 KEY TAKEAWAYS Elevate technical and strategic considerations Understand the available options and limitations at each stage Get hands on with your data to target most effectively Document your decisions and rationales Seek expert help where needed

36 Q / A

37 ENGAGE WITH MODUS Modus coming tomorrow with slides, recording, survey and invite to next webinar Visit us online at for more information on next webinar on October 7 th at 1:00PM EDT on: Discovery and Authentication of Social Media Materials Make sure to visit our website for valuable white papers, regular blog posts, ongoing surveys and more at Including the white paper Zeroing In A Data Targeting Perspective On Reducing E-Discovery Cost covering the topics from this program Thank you!