Governance is the glue that holds various content, knowledge and data management initiatives together. It is increasingly necessary as a component of customer experience and marketing automation and integration initiatives. The challenge is that governance is not an exciting topic and it is difficult to get participation and buy in at the correct levels of the organization. How do you retain interest in these kinds of necessary programs? The answer is to tie governance to measurement of program and project progress, success and operations. Once governance is aligned with objectives and clearly defined measurement, the organization will focus the correct level of attention and governance will be successful. This webinar will cover the challenges associated with data governance and the business impact of poor data quality on digital marketing programs and knowledge management systems. Expert panel members will discuss real-world examples of data governance best practices, how to avoid the common pitfalls and how to put a framework for a successful metrics-driven governance process in place.

1. Copyright © 2015 Earley Information Science1
The Business Value of
Metrics-Driven
Information Governance
Copyright © 2015 Earley Information Science
Paul Wlodarczyk, EIS
Seth Maislin, EIS
Ryan Loechl, EIS

2. Copyright © 2015 Earley Information Science2
Today’s Agenda
• Welcome & Housekeeping
• Session duration & questions
• Session recording & materials
• Take the survey!
• Foundation Concepts
• Dave Zwicker, CMO, Earley Information Science (@davezwicker)
• The Panelist Point of View
• Paul Wlodarczyk, VP, Client Services
Earley Information Science (@twitcontentguy)
• Ryan Loechl, Sr. Taxonomy Consultant, Earley Information Science
• Seth Maislin, Principal Consultant, Earley Information Science (@sethmaislin)
• Expert Panel Discussion
• Questions & Answers
• Join the conversation: #earleyroundtable

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The Business Value of
Metrics-Driven Information Governance
Foundation Concepts and Introductions

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Information Governance (Gartner Definition)
• “Information governance is the collection
of decision rights, processes, standards,
policies and technologies required to
manage, maintain and exploit information
as an enterprise resource.”
• “The purpose of governance is to
implement mechanisms that ensure the
accuracy, integrity, accessibility and
security of information across the
enterprise. Successful governance
requires accountability.”
• “Information governance provides a
structured mechanism to select content
enhancement requests and provide
oversight for enhancement
implementation.”
• “A governance model balances the subject
matter expertise that resides in the
various departments and business units
with the benefits of centralized standards
that assure preservation of user
experience, site structure, enhanced
productivity, and overall business value.”

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• Optimize Revenue
– Business Objectives & Outcomes
• Control Cost
– Data Quality & Integrity
• Manage Risk
– Compliance & Security
Information Governance: Benefits and Drivers
How Governance Can Benefit the Business

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• Answer the CEO question: How can governance increase revenue?
• Who is responsible for enterprise information (IT or business units)?
• What metrics & measurements drive business outcomes?
• How to align information owners, stewards & stakeholders?
• How to establish centralized authority & decentralized accountability?
• What is your current information governance maturity level?
• What are the most important next steps to take?
Key Issues and Considerations

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Panelist Introductions
Paul Wlodarczyk
VP, Client Services
Earley Information
Science
How to organize information
governance for success
Why implement metrics-
driven governance
What metrics, scorecards
and dashboards are used
30 years experience in unstructured
content lifecycle and related
technologies (search, content
management, classification,
taxonomy, localization)
Currently working with enterprises
leading digital transformation projects
Ryan Loechl
Sr. Taxonomy
Consultant
Earley Information
Science
Seth Maislin
Principal Consultant
Earley Information
Science
6+ years experience in taxonomy and
content working with retail and
industrial supply clients.
Joined EIS as a consultant after having
managed product content
management teams responsible for
introducing millions of products and
developing hundreds of taxonomies.
20+ years experience in information
management: taxonomy, indexing and
content modeling, information
architecture, search, and usability.
Dedicated to providing sustaining
information management solutions to
clients facing real and complex findability
challenges.

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Q: What is your level of information governance maturity?
 No governance
 Local governance only (pockets)
 Shared, cross-functional decision-making
 Decisions assisted by dashboard metrics
 A governance dashboard that prioritizes actions
Poll Question #1

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Panelist Points of View

10. Copyright © 2015 Earley Information Science10
Maximizing the Business Value of Governance
Paul Wlodarczyk
VP, Client Services
Earley Information
Science
How to organize information
governance for success
Why implement metrics-
driven governance
What metrics, scorecards
and dashboards are used
30 years experience in unstructured
content lifecycle and related
technologies (search, content
management, classification,
taxonomy, localization)
Currently working with enterprises
leading digital transformation projects
Ryan Loechl
Sr. Taxonomy
Consultant
Earley Information
Science
Seth Maislin
Principal Consultant
Earley Information
Science
6+ years experience in taxonomy and
content working with retail and
industrial supply clients.
Joined EIS as a consultant after having
managed product content
management teams responsible for
introducing millions of products and
developing hundreds of taxonomies.
20+ years experience in information
management: taxonomy, indexing and
content modeling, information
architecture, search, and usability.
Dedicated to providing sustaining
information management solutions to
clients facing real and complex findability
challenges.

11. Copyright © 2015 Earley Information Science11
Measuring here
(business outcomes)
Measuring here
(process indicators)
Digital Content
Working & Measuring
here (content, IA,
taxonomy, search,
data fill, etc.)
Enterprise Strategy
Business Unit Objectives
New Business Opportunities
Average Order Size Total Account Revenue
Business Processes Site Traffic Search Relevance
Search
Web
Content
CRM
Processes enable
objectives
LINKAGE
Leads
Revenue Growth
Content supports
processes
Objectives align
with strategy
Using Metrics & KPIs to Focus Governance
CEO: “How will this increase revenue?”
Conversion
Content Scorecards
Process Scorecards
Outcome Scorecards
CTR Fill Rate Content Quality etc.
Digital Team: “How do I know taxonomy / content / search is working?”
KPI = key performance indicator

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Publish /
Update
Collect
Metrics &
Outcomes
Assess vs.
Target
Improve /
Curate
Test /
Evaluate
• Metrics-driven governance defines key
metrics and KPIs to assure that digital
content is driving business outcomes.
• Develop hypotheses about customer
goals and success – and what success
looks like (outcome & behavior)
• Measure…
– Web Analytics / Click-path
– Search Analytics
– Business Analytics (e.g. purchase patterns, call
center stats, etc.)
– Content / Data Quality (e.g. fill rate)
… to determine if your customer is
successful, and if not, why not.
The Core Idea: Metrics-Driven Governance

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What to analyze:
• Developing a complete 360-
degree view of customer
success requires cross-
disciplined teams
• Industry leaders are
organizing their digital
teams to facilitate more
collaboration
Business Analytics
Search
Analytics
Usability Analysis
Web
Analytics
360-degree View of Customer Success

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A metrics-driven playbook
defines what actions to take
based on what’s observed
Typical improvements:
• Search curation
• Taxonomy
• Tagging / metadata
• Content / data quality
• Search tuning
• UX design / usability
• Platform upgrades
What Levers to Pull – Driving Digital Success
UX
IA
Search
Content
Platforms
EASIER
HARDER
CUSTOMER SUCCESS

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• Sales Knowledge Management
IA/Content/Search Curation  Self-service  Call Center Deflection
IA/Content/Search Curation  Sales Agent Uptake  Revenue Growth
• B2B Product Catalog
Fill Rate / Usability / Taxonomy / Search  CTR  Conversion  Leads
Related Product Taxonomy / Search  CTR Related Products  Upsell
• Business Analytics Data Governance
Provenance / Documentation / Reuse  Data Authority  Risk Prevention
Examples of Metrics-Driven Governance

16. Copyright © 2015 Earley Information Science16
Maximizing the Business Value of Governance
Paul Wlodarczyk
VP, Client Services
Earley Information
Science
How to organize information
governance for success
Why implement metrics-
driven governance
What metrics, scorecards
and dashboards are used
30 years experience in unstructured
content lifecycle and related
technologies (search, content
management, classification,
taxonomy, localization)
Currently working with enterprises
leading digital transformation projects
Ryan Loechl
Sr. Taxonomy
Consultant
Earley Information
Science
Seth Maislin
Principal Consultant
Earley Information
Science
6+ years experience in taxonomy and
content working with retail and
industrial supply clients.
Joined EIS as a consultant after having
managed product content
management teams responsible for
introducing millions of products and
developing hundreds of taxonomies.
20+ years experience in information
management: taxonomy, indexing and
content modeling, information
architecture, search, and usability.
Dedicated to providing sustaining
information management solutions to
clients facing real and complex findability
challenges.

17. Copyright © 2015 Earley Information Science17
Where the Rubber Hits the Road
How do I Action these insights?InsightReporting
Governance Metrics Can:
1. Target areas of improvement
2. Identify causes of poor quality or performance

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Where the Rubber Hits the Road
The “What” The “Where” The Action
Taxonomy Level 1
Taxonomy Level 2
• Product 1
• Product 2
• Product 3
Taxonomy Level 2
• Product 1
• Product 2
• Product 3
High-Level Metrics
- Bounce rate is high
- Conversions are low
Detailed Metrics
- Product Click-Through Rate
- Filter Click-Through Rate
- Product Data Fill Rate
Launch new initiative to improve
the quality and completeness of
product data.

19. Copyright © 2015 Earley Information Science19
Maximizing the Business Value of Governance
Paul Wlodarczyk
VP, Client Services
Earley Information
Science
How to organize information
governance for success
Why implement metrics-
driven governance
What metrics, scorecards
and dashboards are used
30 years experience in unstructured
content lifecycle and related
technologies (search, content
management, classification,
taxonomy, localization)
Currently working with enterprises
leading digital transformation projects
Ryan Loechl
Sr. Taxonomy
Consultant
Earley Information
Science
Seth Maislin
Principal Consultant
Earley Information
Science
6+ years experience in taxonomy and
content working with retail and
industrial supply clients.
Joined EIS as a consultant after having
managed product content
management teams responsible for
introducing millions of products and
developing hundreds of taxonomies.
20+ years experience in information
management: taxonomy, indexing and
content modeling, information
architecture, search, and usability.
Dedicated to providing sustaining
information management solutions to
clients facing real and complex findability
challenges.

20. Copyright © 2015 Earley Information Science20
Governance Dynamic
policies
procedures
standards
escalates
requests
reports
implementation
remediation
behavior change
governance activity (perpetual) process work (ongoing)
Governance Project Management
Operations
project work (temporary)
running the business
reporting

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Governance Program Health Metrics
organizational health
• steward representation
• expenditures and savings
• projects (approved, ongoing, backlog)
• policies established
people health
• headcount
• specialization breadth and coverage
• education, training completed, training written
• participant opinion
process health
• process efficiency
• decision-making efficiency
• escalation frequency and efficiency
taxonomy scope
• size and scope of taxonomy
• clear ownership coverage
• taxonomy conflicts needing reconciliation
technology health
• percent integration with taxonomy
• term synchronization health
• presence of unique identifiers
compliance health & risk
• audits completed, pass/fail
• number of known issues
• number of negative incidents

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Traditional Governance Models
The democratic model
uses a single all-hands
core team with modest
executive oversight.
When all stakeholders are
equal, decision-making
can be difficult, leading to
project stagnation and
desynchronization of
systems.
democratic multi-domain gatekeeper collaborative service
The multi-domain model is
comprised of several self-
governed business areas,
guided by a company-wide
committee. Best approach
for driving change through
strategy policy and
planning, but inherently
bureaucratic and stifling
when treated as mandate.
The collaborative model
recognizes multiple,
operationally separate
business areas, who can
collaborate but generally
make their own
decisions. Consistent
with agile; failure likely
without total, consistent
commitment at all levels
of the firm.
The service model
leverages the resources
and knowledge of a
single team of
specialists across
teams, domains, and
projects. Works well in
highly fluid or fractured
environments, but not
strategically scalable.
The gatekeeper model
is designed around a
single decision-making
body responsible for
approving all actions
and decisions. Highly
risk-averse but also
non-collaborative,
prone to operational
bottlenecks.
The best governance approach leverages the best features of all models.

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Q: Which of these do you think are your best next steps toward
achieving greater maturity in information governance?
 Assess governance maturity level
 Design top-down decision-making structure
 Governance standup and tuning
 Metrics & KPI selection & dashboard
 Governance technology exploration
Poll Question #2

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Your Questions and Answers

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Your Questions and Answers
Paul Wlodarczyk
VP, Client Services
Earley Information
Science
How to organize information
governance for success
Why implement metrics-
driven governance
What metrics, scorecards
and dashboards are used
30 years experience in unstructured
content lifecycle and related
technologies (search, content
management, classification,
taxonomy, localization)
Currently working with enterprises
leading digital transformation projects
Ryan Loechl
Sr. Taxonomy
Consultant
Earley Information
Science
Seth Maislin
Principal Consultant
Earley Information
Science
6+ years experience in taxonomy and
content working with retail and
industrial supply clients.
Joined EIS as a consultant after having
managed product content
management teams responsible for
introducing millions of products and
developing hundreds of taxonomies.
20+ years experience in information
management: taxonomy, indexing and
content modeling, information
architecture, search, and usability.
Dedicated to providing sustaining
information management solutions to
clients facing real and complex findability
challenges.

26. Copyright © 2015 Earley Information Science26
• What is Information Governance? And Why is it So Hard?
http://blogs.gartner.com/debra_logan/2010/01/11/what-is-information-governance-and-why-is-it-so-hard/
• Information Governance: Not A Product, Not A Technology, Not A Market
http://blogs.forrester.com/cheryl_mckinnon/15-01-14-
information_governance_not_a_product_not_a_technology_not_a_market
• A Simple Model for Information Governance
http://community.aiim.org/blogs/christian-liipfert/2014/01/17/a-simple-model-for-information-governance-part-1-of-3
• The Data Asset: How Smart Companies Govern Their Data for Business Success
http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470462264.html
• Five Common Challenges of Implementing Information Governance
http://www.ibmpressbooks.com/articles/article.asp?p=2256974
• Information Governance and Data Quality
http://www.gse.org/Portals/2/docs/GEC%20Venice/Presentations/M05_Stefano_Mino_Information_Governance_and_Data_Q
uality.pdf
• Automating Information Governance - Assuring Compliance
http://www.aiim.org/Research-and-Publications/Research/Industry-Watch/InfoGov-2014#sthash.e4qD0MG7.dpuf
Suggested Resources

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Call to Action
“Meet the Experts” for a 1-hour Q&A via conference call
about the topics of your choice…
– Diagnosing a Governance Issue
– Governance Models – Which one is right for you?
– Making governance practical & sustainable
– Selecting Metrics & Building a Dashboard
– Exploring Governance Technology
To set up your call contact us at info@earley.com
OR respond to the survey

28. Copyright © 2015 Earley Information Science28
Earley Information Science helps
organizations establish a strong
information architecture and content
management foundation
Realize your digital transformation
vision with EIS.
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Founded – 1994
Headquarters – Boston, MA
www.earley.com
For more info contact:
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