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The Business Value of Metrics Driven Information Governance

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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.

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The Business Value of Metrics Driven Information Governance

  1. 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. 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
  3. 3. Copyright © 2015 Earley Information Science3 Copyright © 2015 Earley Information Science The Business Value of Metrics-Driven Information Governance Foundation Concepts and Introductions
  4. 4. Copyright © 2015 Earley Information Science4 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.”
  5. 5. Copyright © 2015 Earley Information Science5 • 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
  6. 6. Copyright © 2015 Earley Information Science6 • 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
  7. 7. Copyright © 2015 Earley Information Science7 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.
  8. 8. Copyright © 2015 Earley Information Science8 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
  9. 9. Copyright © 2015 Earley Information Science9 Copyright © 2015 Earley Information Science Panelist Points of View
  10. 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. 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
  12. 12. Copyright © 2015 Earley Information Science12 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
  13. 13. Copyright © 2015 Earley Information Science13 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
  14. 14. Copyright © 2015 Earley Information Science14 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
  15. 15. Copyright © 2015 Earley Information Science15 • 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. 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. 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
  18. 18. Copyright © 2015 Earley Information Science18 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. 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. 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
  21. 21. Copyright © 2015 Earley Information Science21 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
  22. 22. Copyright © 2015 Earley Information Science22 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.
  23. 23. Copyright © 2015 Earley Information Science23 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
  24. 24. Copyright © 2015 Earley Information Science24 Copyright © 2015 Earley Information Science Your Questions and Answers
  25. 25. Copyright © 2015 Earley Information Science25 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. 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
  27. 27. Copyright © 2015 Earley Information Science27 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. 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. Earley Information Science (EIS) Information Architects for the Digital Age Founded – 1994 Headquarters – Boston, MA www.earley.com For more info contact: info@earley.com careers@earley.com

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