Analytics Workflows for Smaller Cases. kcura LLC. All rights reserved.

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1 Analytics Workflows for Smaller Cases

2 The Dallas Steering Committee Sonya Everitt Gardere Wynne Sewell Matt Deegan Jackson Walker 2015 kcura. All rights reserved.

3 Who are you?

4 Analytics for Smaller Cases

5 Relativity Analytics Features Structured Threading Textual Near Duplicate ID Language Identification Conceptual Concept Searching Clustering Keyword Expansion

6 Common Objection - Analytics is best only for the largest cases. Messaging with analytics in e-discovery has focused on large case wins. There are a number of uses for a majority of cases. For example: Batching - Reviewing conceptually related documents increases review speed Production prep Analytics can help to avoid mistakenly producing privileged docs Keyword sampling Address keyword issues to help identify other potentially relevant documents Threading Only review inclusive s and reduce the volume of

7 Use Case Features Use Case Narrowing the review set Feature threading Foreign language identification

8 Use Case Features Use Case Narrowing the review set Quality control Feature Near duplicate identification Cluster visualization

9 Use Case Features Use Case Narrowing the review set Quality Control Investigation Feature Keyword expansion

10 Use Case Features Use Case Narrowing the review set Investigation Quality control Organizing sets of data Feature Clustering

11 Threading

12 2/24/99 11:25 a.m. 4/29/99 6:45 p.m. 4/30/99 9:03 p.m. 4/30/99 7:00 p.m. 4/30/99 7:22 p.m. 4/30/99 10:24 p.m. 5/1/99 12:57 a.m.? Barry Pearce Bob Crane & Jeff Harbert Maria Nartey Richard Sage & Mark Elliott

13 Threading What is it? Identifies and arranges s that were part of a single thread or conversation. What is it used for? Allows you to: Easily see the order of each in a thread. See which s are inclusive (i.e. have unique content). Identify duplicate spares (i.e. s with the same content). How will it help me? Sort and organize s by thread for more intuitive review. Saves time if only reviewing the non-duplicative inclusive s.

14 Best Practices and Considerations Profile Setup Conversation ID Attachment ID English header information Bates Numbers Views that display Inclusive only Production specifications Recipients not considered QC using threads

15 Textual Near Duplicate ID

16 Can you spot the difference? Version A Version B

17 Textual Near Duplicate Identification What is it? Identifies documents with highly similar text and places them into relational groups. What is it used for? Allows you to: Use near dupe groups in searching or filtering. Conflict check coding decisions amongst near dupes prior to production. How will it help me? Saves time by identifying very similar documents prior to the start of review. You can also use the near dupe groups for review and QC.

18 Best Practices and Considerations Ran instead of or in place of threading Use with Compare function Not meant to eliminate items but as prioritization and grouping Use for QC, comparison of datasets Include Numbers?

19 Language Identification

20 Language Identification What is it? Determines a document s primary language and up to 2 secondary languages. What is it used for? Allows you to see how many languages are present in your collection, and the percentages of each language by document. How will it help me? Easily filters documents by language and batch out files to native speakers for review. Determines if translation is needed.

21 Best Practices and Considerations Footer information Header Information Segment dataset for desired reviewer

22 Conceptual Analytics

23 What is Conceptual Analytics? Relativity Analytics is a mathematical approach to indexing documents. Terminology is understood based on its usage in your documents. No outside word lists Dictionaries, thesauri, etc. Language-agnostic Term co-occurrence, not term location

24 Concept Searching

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26 Concept Searching What is it? Searches using a sentence, paragraph, or entire document Returns documents related to the concept of the query What is it used for? Searching for documents based on ideas instead of absolutes More natural querying How will it help me? Find documents even if terms differ.

27 Value of Concept Search Avoids term mismatch issues Pop vs. soda Football vs. soccer Avoids intentionally confusing use of language Code words Finds documents even if exact language differs Misspellings Synonyms

28 Best Practices and Considerations When building your Conceptual Analytics Index: Minimum Text Maximum Text Repeated Content

29 Clustering

30 Custodian Name Custodian Name Custodian Name Custodian Name

31 Cluster Browser

32 Heat map in Cluster Visualization Heat Map 5 Workflows to enhance review with cluster visualization

33 Heat Maps Show You Where Your Data Lives FIND YOUR COUNTY Choose a state KEY Unemployment Rate More than 13% % 7-9.9% 0-6.9%

34 Clustering What is it? Use the power of the conceptual index to identify groups of conceptually related documents. What is it used for? This can be used as a tool for investigation, analysis, review, or QC. How will it help me? Investigate a large unknown dataset Cull out non-relevant documents quickly Speed up a linear review by batching conceptually related documents together

35 Best Practices and Considerations Cluster Sub-Groups Cluster All Documents Batch by Cluster QC with Clusters

36 Keyword Expansion

37 Keyword Expansion What is it? Uses the concept space to allow users to submit terms and returns conceptually related words What is it used for? Investigating the language of the workspace using known keywords How will it help me? Allows you to find code words Assists in expanding the keyword list Familiarize yourself with the language of the case.

38 Best Practices and Considerations Concept or Term Submission Copy to dtsearch

39 Real World Challenges

40 Scenario 1 - What would you do? During an ongoing insurance matter, you receive an opposing production on a Friday afternoon. The documents must be reviewed by Monday. How can you meet the aggressive deadline over the weekend?

41 Scenario 2 - What would you do? You received paragraphs from a subject matter expert depicting potential conversations between 3 people that corporate counsel believe to be important. How will you find these types of conversations between these 3 custodians? How will you set up the review once you find them?

42 Scenario 3 - What would you do? You need to come up with a good list of privilege terms in order to do a proper screen and to set up a highlight set.

43 Scenario 4 - What would you do? Your document set contains unknown but relevant terms. You have identified some but know more exist. What can you do to organize the case data more accurately and improve the effectiveness of the document review?

44 Scenario 5 - What would you do? You ve just loaded your documents and prior to formal review, a senior attorney wants to explore a bit and see what you have (or what you ve been provided by the other side)

45 Scenario 6 - What would you do? Opposition is claiming that your production consists of mostly junk responsive documents. What can you do to a) ensure that you found all the smoking guns, and b) how do you present your findings defensibly?

46 One more thing(s)

47 Relativity Project Management Specialist Certification 75-question test Take it online or in-person Sign up by August 16 to save 50%

48 Mobile Beta Program New ipad app separate from Relativity Binders Mobile-friendly design for saved searches, views, document lists, and coding layouts as they exist in Relativity All coding on mobile is synchronized to and viewable in Relativity

49 Join the Beta! Experience the new app before it becomes publicly available. Explore new features added every month. Guide the development of the product a direct-line to Product Management. MobileBeta@kcura.com to participate.

50 In the Future Administer Relativity from your smartphone Case strategy and construction Reporting dashboards Support for additional devices and operating systems

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52 Thank You!