1. Content Analytics for Legacy Data Retention
The Dayhuff Group has a long history of providing enterprise content management solutions in a wide variety of industries.
In business since 1997
IBM Premier Business Partner
Software ValueNet Partner
Over 180 projects at 80 companies
96% customer satisfaction rating
Content Analytics for Legacy Data Retention
The Dayhuff Group

2. The information lifecycle governance problem
98%
$3M
17%
Companies that cite defensible disposal as key result of governance programs
Average cost to collect, cull and review information per legal case1
Amount of IT budget spent on storage3
22%
70%
44x
Companies that can defensibly dispose today
Portion of information unnecessarily retained2
Projected information growth,

3. Watson and IBM ECM Today
Natural Language Processing (NLP) is the cornerstone to translate interactions between computers and human (natural) languages
Watson uses IBM Content Analytics to perform critical NLP functions
Unstructured Information Management Architecture (UIMA) is an open framework for processing text and building analytic solutions
Several IBM ECM products leverage UIMA text analytics processing:
IBM Content Analytics
OmniFind Enterprise Edition
IBM Classification Module
IBM eDiscovery Analyzer

4. Going from raw information to rapid insight
Uncover business insight through unique visual-based approach
Aggregate and extract from multiple sources
Organize, analyze and visualize
Search and explore to derive insight
… to form large text-based collections from multiple internal and external sources (and types), including ECM repositories, structured data, social media and more.
… enterprise content (and data) by identifying trends, patterns, correlations, anomalies and business context from collections.
… from collections to confirm what is suspected or uncover something new without being forced to build models or deploy complex systems.

5. Why Content Analytics?
#1 problem all accounts have, “don’t know what content they have”
#2 problem “Uncontrollable Storage Cost”
Want to discover the value that may exist in their existing information / content resources
Want to know who, where, when & how to leverage their information / content assets
Believe they too can demonstrate a three month return on investment
Non-threatening to IT
Low Cost investment
Content Analytics “Try & Buy”

6. LEVEL 5 (Transformational)
Content Analytics
Necessary
Information
Unnecessary
Content In The Wild
Content Analytics
Dynamically analyze to know what you have Aggregate, correlate, visualize and explore your enterprise information to make rapid decisions about business value, relevance and disposition.
Decommission what’s unnecessary Cut costs and reduce risk by eliminating obsolete, over-retained, duplicate, and irrelevant content – and the infrastructure that supports it.
Preserve and exploit
the content that matters Collect valued content to manage, trust and govern throughout its lifespan
… policies that use rule-based metadata, advanced contextual classification, and advanced content analytics
Slide 5: Charts and Graphs
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LEVEL 5 (Transformational) 6

7. How to decommission and preserve content
Identify Content Sources to be assessed
IT Initial Assessment to decommission irrelevant content
LOB Specific Assessments to decommission over-retained and obsolete content … and to collect and classify valued and obligated content.
System and Application decommissioning by IT
Periodic audits by IT and LOB keep content environments optimized. 5
Periodic Audit 1 2 3 4
Identify Content
Sources
Initial
Assessment
Specific
Assessments
System & Application
Decommissioning
Content Collection
Content Collection

8. Content Collection w/ Content Classification
Content Analytics and RIM
Step 1: Identify content sources
Step 2: Exploration
Examine sources and analyze content
Records manager uses interface to explore & identify value-based content categories
Define policies expressing required actions (delete, move, copy, ...) based on categories
Step 3: Archival and Management of content
IT manager encodes policies content collection mechanism
Content identified by exploration process is collected
Content collection is executed in an ongoing basis, as prescribed by policies
Supports Selective Content Decommissioning:
Operate on a subset of content in the original source
Identify & extract records across the enterprise 1
Legacy ECM
File
SharePoint
File 2
Content Exploration
Content Collection w/ Content Classification 3
Policies
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Trusted ECM 8

9. Step 1: Identify content sources in the wild
Content Analytics and Dynamic ESI Collection 1
Step 1: Identify content sources in the wild
Step 2: Exploration
Examines sources and analyzes content
IT or Legal user explores & identifies content relevant to case
User determines content to be collected into a case set and invokes collection process
Collection tool (embedded ICC) copies identified content into ECM evidence repository
Step 3: eDiscovery
Cull, hold, audit-track, export ESI
Analytics-driven Early Case Assessment across all relevant evidentiary ESI
Content Analytics
Multi-case
Evidentiary
ECM based
Dynamic on demand reactive collection requests
Policy based collections 2
Content Collection
Slide 5: Charts and Graphs
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eDiscovery Tools 9

10. Unlock valuable insight from content What our clients are doing with Content Analytics

11. Basic questions to consider regarding content
Know your content
Accelerate time to knowledge by providing greater accuracy and more complete business context with enterprise search
Dynamically analyze what you have, decommission the unnecessary, and preserve the content that matters with content assessment
Do we know what we have and can we find it?
Is it properly managed and can we trust it?
What does it all mean and how can we benefit from it?
Trust your content
Manage and govern content in trusted repositories, not in suspect environments, enabling confidence in your content
Create and manage 360 degree trusted content views to enrich master data by connecting to enterprise content
Leverage and Exploit your content
Interactively discover content to derive unexpected business insights and take action with content analytics
Exploit content analytics insights by enriching BI and predictive analytics as well as tailoring for industry and customer specific scenarios

12. Content Analytics for Legacy Data Retention
Addresses
Two Objectives:
Securely Retain Records Requiring Retention
Defensibly Decommission duplicate, non-business and information which has satisfied its retention requirements
One LARGE ROI:
Storage Cost Savings
ROI in less than 3 months
$44m in Storage Savings for one client
And Delivers

13. How CA for Legacy Data Retention Delivers
I need to dynamically collect electronically stored information (ESI) by knowing what I have, sorting out the case relevant information, declare a records and bring under hold management or decommission as necessary
Content Assessment enables content-based decision making for:
Decommissioning for cost savings – selected content or entire sources
Dynamic collection Records Management for eDiscovery
Ongoing proactive information governance
Improving metadata & content organization
Reduce Storage Cost

14. Content Analytics Admin
Content Sources
File Systems
Content Repositories
Databases
Collaboration
Web Content
Web Pages
Portals
Content Integration (custom crawlers)
...

15. Content Analytics Admin
Parse and Index Content
Linguistic understanding of your content
Industry and business specific dictionaries
Understanding of Named Entities
People, Places, Companies
Integration with Classification Module
Deep concept analysis
Annotators specific to industry, business and specific uses
Record Types
Industry and company specific concepts
Business specific concepts such as Employee Names , Products, etc.
. . .

16. Content Analytics for Legacy Data Retention - How it works
Analyzed Content (and Data)
Financial Record
to be Declared
Extracted Concept
Trade
Action
Day
Reason
Adjective
Verb
Noun
Prep Phrase
stocks rose Monday on comments from
...
Source Information
Internal (ECM, Files, DBMS, etc.) and External (Social, News, etc.)
Automatic Visualization for Interactive Exploration and Assessment

17. Content Analytics for Defensible Decomissioning – How it works
Analyzed Content (and Data)
Non-record
Decomissionable
Extracted Concept
Element of a plant
Vegetation
Reason
Action
Noun
Noun
Verb
Noun
stocks on the plants require trimming
...
Source Information
Internal (ECM, Files, DBMS, etc.) and External (Social, News, etc.)
Automatic Visualization for Interactive Exploration and Assessment

18. Classification Process for Legacy Data Retention
Analyze
Collect information & context needed to make an inform a decision (declare vs. decommission)
Decide
Assess the collected information and select a category (declare vs. decommission), accurately & repeatably
Take Action
Use the selected category to determine & initiate an appropriate response (declare vs. decommission)
Ensure actions are taken consistently & correctly, creating defensible process
Enforce

19. Content Analytics for Legacy Data Retention
Solution Overview
IBM ECM 4
Enterprise
Records 1 2
Content Collectors
Content Analytics
Electronic
Discovery
Classification
Module 5 3

20. Demonstration of Content Analytics for Legacy Data Retention
Content Analytics for Legacy Data Retention is a solution to inventory and locate legacy data requiring retention or disposition
The Dayhuff Group has created this solution using IBM Content Analytics tools to perform the heavy lifting of mining legacy information
It allows data retention analysts to view and analyze their source content based on familiar concepts such as how the content fits into records series’ within their file plan

21. Facets – Record Types
This view exposes facets which categorize the content based on the business’ record types within record series’

22. Select documents to Decommission or Declare
The analyst can graphically see content that is past it’s retention period available for decommissioning

23. Flag as Past Retention period
Documents are flagged based on their retention requirements identified using Content Analytics and the Record Type facets, then exported to Content Collector

24. decommissioned based on analysis results in Content Analytics
Collect to IER
Content Collector
Documents are
decommissioned based on analysis results in
Content Analytics
or archived to
Enterprise Records
Decommission Unnecessary Content
ECM
Records Retention Programs
& Policies

25. IBM Enterprise Records
Finance
accounts payable
treasury
Budget & forecast
payroll
Documents are declared as records in Enterprise Records
matching Record Type Facets analyzed in Content Analytics
cash management
Financial reporting
tax
accounts receivable
customs
general accounting
insurance
Cost accounting
Sales & Marketing
sales
marketing communication
dealer support
product management
market research
Service
warranty administration
customer service
quality assurance
Legal

26. Content Analytics for Legacy Data Retention
Benefits:
Reduced risk
Increased productivity
Quantifiable and measurable results
Reduced cost
Defensible process for evaluation
Reduction of information through disposition
Reduction of duplicated and old information