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Gerard J. Britton 
Topiary Discovery LLC 
Information Governance Alchemy: 
Turning A Proactive Data Need & 
Litigation Budget Into A Solution 
Stack That Works AND Sells
Information Governance Drivers 
Risk Mitigation 
Value of Insight 
Cost Reduction
When You Ask for Information 
Governance Budget?
Cost and Complexity
Consequence – 
No One Really Knows What’s in There
And… 
… it leaves people who have GRC responsibilities 
pulling out their hair.
But eDiscovery… 
Now, That’s A Different Story
With Litigation, 
Comes Budget 
Over Time, 
It Adds Up!
However, eDiscovery is 
Sporadic and Ad Hoc 
= Wasted Budget
Predictive Coding Promises Increased Efficiency 
• Makes use of analytics 
• Reduces review costs 
• Provides insight into documents in a litigation 
• Produces tags
Predictive Coding 
Reviewer Iterative Process 
Predictive 
Coding 
Review 
Model 
Platform 
Engine Reviewer 
Tags 
Information 
Intellectual 
Property 
Training Set
Predictive Coding Inefficiencies 
Reactive Ephemoral 
Presents an Information Governance Opportunity
Information Governance Attributes 
Proactive Persistent 
“Propagatable”
Conceptual Information 
Governance Schema 
Information 
Intellectual 
Property 
Tags
IG Classification can be done by: 
Manual Annotation (Coding) Automated Annotation (Coding)
Commonality 
Predictive Coding and Information Governance 
both use manual and “machine” methods to: 
• identify patterns 
• apply information and insight tags
Q: Can these two technology enabled architectures be 
amalgamated to create a solution that: 
• overcomes corporate hesitation 
• benefits the legal department 
• provides a budget source and 
• sets the stage to enable a specific information 
governance need? 
A: Yes.
Conceptual Schematic of a Combined System
A Snapshot of a Document’s Life in This System: 
Document 
Document 
Content 
Applied 
Tags 
Predictive 
Coding 
Model 
Engine
How to Contemplate the proposal 
1. Identify stakeholders 
2. Identify litigation subset 
3. Identify information governance application 
4. Identify champion(s) 
5. Identify desired business partners 
6. Formulate business plan 
7. Make proposal
Stakeholders/Partners 
Client 
eDiscovery Vendor 
Managed Review Vendor Law Firms
Identify Champions 
– GC, CFO, CIO, Compliance? 
Identify Desired Business Partners 
– Relationship vendors 
• Adaptability 
• Expertise 
• R&D amenability
Litigation Portfolio subset selection 
– Most common area of litigation in the company? 
Information Governance application selection 
– Low hanging fruit?
Formulate Business Plan 
– Vendor concessions 
– Law Firm/Managed Review adaptability 
– GC ediscovery multi-year budget analysis 
– Contractual Issues 
– Intellectual property issues 
– ROI Specifics
Elevator Proposal 
• An Information Governance platform for ediscovery 
data and ediscovery tasks alone 
• Improving ediscovery cost/performance profile 
• Subsidized by ediscovery budget 
• But designed to also provide tags to help solve a pre-determined 
information governance need
Considerations 
• Rationale 
– Champions 
• Stakeholders/Partners 
– Law Firms 
– eDiscovery Vendors 
• Analytics Expertise 
• Development Capacity 
– Managed Review Providers 
• ROI definition 
– Overall expenditure per average lit 
• Selection of Litgations & IG application 
• Technical Considerations 
– Proactive/Reactive Engines 
– Engine design 
• Classification analytics 
• Manual curation/annotation 
– IG/eDiscovery Engine Integration 
– Inputs/Outputs 
• Resource allocation among 
stakeholders
Gerard Britton 
Topiary Discovery LLC 
@TopiaryeDisc 
gbritton@topiarydiscovery.com 
www.topiarydiscovery.com

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Gerard Britton - Information Governance Alchemy: Turning A Proactive Data Need & Litigation Budget Into A Solution Stack That Works AND Sells - The Information Governance Conference 2014 - #InfoGov14

  • 1. Gerard J. Britton Topiary Discovery LLC Information Governance Alchemy: Turning A Proactive Data Need & Litigation Budget Into A Solution Stack That Works AND Sells
  • 2. Information Governance Drivers Risk Mitigation Value of Insight Cost Reduction
  • 3.
  • 4. When You Ask for Information Governance Budget?
  • 6. Consequence – No One Really Knows What’s in There
  • 7. And… … it leaves people who have GRC responsibilities pulling out their hair.
  • 8. But eDiscovery… Now, That’s A Different Story
  • 9. With Litigation, Comes Budget Over Time, It Adds Up!
  • 10. However, eDiscovery is Sporadic and Ad Hoc = Wasted Budget
  • 11. Predictive Coding Promises Increased Efficiency • Makes use of analytics • Reduces review costs • Provides insight into documents in a litigation • Produces tags
  • 12. Predictive Coding Reviewer Iterative Process Predictive Coding Review Model Platform Engine Reviewer Tags Information Intellectual Property Training Set
  • 13. Predictive Coding Inefficiencies Reactive Ephemoral Presents an Information Governance Opportunity
  • 14. Information Governance Attributes Proactive Persistent “Propagatable”
  • 15. Conceptual Information Governance Schema Information Intellectual Property Tags
  • 16. IG Classification can be done by: Manual Annotation (Coding) Automated Annotation (Coding)
  • 17. Commonality Predictive Coding and Information Governance both use manual and “machine” methods to: • identify patterns • apply information and insight tags
  • 18. Q: Can these two technology enabled architectures be amalgamated to create a solution that: • overcomes corporate hesitation • benefits the legal department • provides a budget source and • sets the stage to enable a specific information governance need? A: Yes.
  • 19. Conceptual Schematic of a Combined System
  • 20. A Snapshot of a Document’s Life in This System: Document Document Content Applied Tags Predictive Coding Model Engine
  • 21. How to Contemplate the proposal 1. Identify stakeholders 2. Identify litigation subset 3. Identify information governance application 4. Identify champion(s) 5. Identify desired business partners 6. Formulate business plan 7. Make proposal
  • 22. Stakeholders/Partners Client eDiscovery Vendor Managed Review Vendor Law Firms
  • 23. Identify Champions – GC, CFO, CIO, Compliance? Identify Desired Business Partners – Relationship vendors • Adaptability • Expertise • R&D amenability
  • 24. Litigation Portfolio subset selection – Most common area of litigation in the company? Information Governance application selection – Low hanging fruit?
  • 25. Formulate Business Plan – Vendor concessions – Law Firm/Managed Review adaptability – GC ediscovery multi-year budget analysis – Contractual Issues – Intellectual property issues – ROI Specifics
  • 26. Elevator Proposal • An Information Governance platform for ediscovery data and ediscovery tasks alone • Improving ediscovery cost/performance profile • Subsidized by ediscovery budget • But designed to also provide tags to help solve a pre-determined information governance need
  • 27. Considerations • Rationale – Champions • Stakeholders/Partners – Law Firms – eDiscovery Vendors • Analytics Expertise • Development Capacity – Managed Review Providers • ROI definition – Overall expenditure per average lit • Selection of Litgations & IG application • Technical Considerations – Proactive/Reactive Engines – Engine design • Classification analytics • Manual curation/annotation – IG/eDiscovery Engine Integration – Inputs/Outputs • Resource allocation among stakeholders
  • 28. Gerard Britton Topiary Discovery LLC @TopiaryeDisc gbritton@topiarydiscovery.com www.topiarydiscovery.com