1. Simplifying Information Architecture Alexander Cullen Principal Analyst Forrester Research November 9, 2005. Call in at 12:55 p.m. Eastern Time

2. 2 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Theme Information architecture enables better decisions to enhance IT delivery. It is an essential deliverable of an EA.

3. 3 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Agenda Drivers for information architecture How: overview of frameworks and methodologies Best practices

4. 4 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Drivers for information architecture Business operating model change/enhancement »Improving customer focus/responsiveness »Changing distribution models »Supply chain efficiencies »… Business management needs »“Know the customer” »Product and channel profitability »Financials and compliance »…

5. 5 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Drivers for information architecture cont. Information accessibility »Complete and accurate »Consistent Information quality »“one version of the truth” »Accurate/action-oriented business metrics New business applications »Data sourcing »Data formats and definitions »Cross-referencing structured data and unstructured content IT storage and processing costs »Proliferation and redundancy »Batch cycle windows

6. 6 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Definition Information architecture is a framework providing a structured description of an enterprise’s information assets and the relationship of those assets to business processes, business management, and IT systems.

7. 7 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Business process and business management model Business information conceptual entities Structured data Content Conceptual data model – major entities, attributes, relationships Taxonomy Information entity mapping to applications and repositories Data flows and systems of record Schemas Logical data model – major entities, attributes, relationships Physical data stores and repositories Operational and analytical dataContent CustomerProductFinancialSalesEmailDocumentsImagesWeb Storage Policies governing ownership and access Principles Standards Structure of information architecture

8. 8 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Relationship of information architecture to business and application architecture Business architecture App. arch. (domain view) Infrastructure architecture Info. arch. App arch. (design view) App arch. (portfolio view) Business process architecture

9. How: overview of frameworks and methodologies

10. 10 Entire contents © 2005 Forrester Research, Inc. All rights reserved. IA mapped to Zachman framework Data – “What” Function – “How” Network – “Where” People – “Who” Time – “When” Motivation – “Why” Scope – “Contextual” Enterprise – “Conceptual” System model – “Logical” Technology model – “Physical” Components Source: www.zifa.com Information Architecture

11. 11 Entire contents © 2005 Forrester Research, Inc. All rights reserved. TOGAF architecture development method (ADM) Prelim: Framework & Principles Architecture Vision Business Architecture Info System Arch. Technology Architecture Opportunities & Solutions Migration Planning Implementation Governance Change Mgmt. Requirements Information Architecture System Arch.

12. 12 Entire contents © 2005 Forrester Research, Inc. All rights reserved. The Open Group Architecture Framework (TOGAF) v8.1 Prelim: Framework & Principles Architecture Vision Business Architecture Info System Arch. Technology Architecture Opportunities & Solutions Migration Planning Implementation Governance Change Mgmt. Requirements Baseline Description Principles Reference Models Viewpoints Tools Architecture Models Architecture Building Blocks Stakeholder Review Qualitative Criteria Complete Architecture Gap Analysis

13. 13 Entire contents © 2005 Forrester Research, Inc. All rights reserved. NASCIO information architecture templates

14. 14 Entire contents © 2005 Forrester Research, Inc. All rights reserved. IA within US federal enterprise architecture — reference models Business Reference Model (BRM) Lines of business Agencies, customers, partners Service Component Reference Model (SRM) Service domains, service types Business and service components Technical Reference Model (TRM) Service component interfaces, interoperability Technologies, recommendations Data Reference Model (DRM) Business-focused data standardization Cross-agency information exchanges Business-Driven Approach Performance Reference Model (PRM) Inputs, outputs, and outcomes Uniquely tailored performance indicators Federal Enterprise Architecture (FEA) Component-Based Architecture Owned by line of business owners Owned by federal CIO council

15. 15 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Forrester’s best practices Build an iterative plan focused on pain points »Incremental build-out with limited scope per iteration »Structure iterations around business and IT pain points. »Define your pain-solving strategy. »Target deliverables to stakeholders’ needs. »Gain stakeholder agreement on scope and deliverables.

16. 16 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Defining IA deliverables What is being documentedHow to show it Business viewInformation in relationship to key business concepts and processes  Conceptual data model  Business process – to – CDM  Data life cycle  Conceptual DFD Information in relationship to applications  Application inventory – to – CDM  Logical and physical DFD  Logical data model for applications  Data and metadata standards  Data sourcing and source of record  Road maps IT view Information Infrastructure  Architecture patterns for key data store, service, and application types  Tool/technology/physical design standards  PDM for applications  Policies and processes  Road maps

17. 17 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Example: building the plan Building the plan Hypothetical example Plan for incremental build-out Initially focus on product profitability and information on product cost, selling price, and service cost. Structure iterations around pain points Business can't accurately understand product profitability due to multiple definitions for products, costs, and prices. Define your pain-solving strategy Develop end-to-end architecture for product information, and work with business and AD to incorporate into projects. Target deliverables to stakeholders End-to-end solution architecture that business understands, plus road map and detailed models for AD. Gain stakeholder agreement Product management, AD teams for manufacturing, order management, and customer service systems, IT portfolio management office all agree on iteration scope, goals, and deliverables.

18. 18 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Forrester’s best practices cont. Use a top-down approach to sustain focus »Model the in-scope business areas. »Define “logical target state” before investigating current state. »Develop multiple alternatives for closing gaps. »Address policy and process gaps. »Identify metrics that link IA deliverables to results. »Couple IA implementation to business functionality.

19. 19 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Example: sustaining the program Sustaining the program Hypothetical example Start at high level with model of in- scope business areas. High-level process and information model for manufacturing, sales, and customer service Define logical target state before investigating current state. Target state architecture for product information capture, aggregation, and reporting Develop alternatives to close gap between current and target states. Alternatives for how information is extracted and aggregated for reporting, such as using data abstraction layers Address policy and process gaps.Data ownership defined for product manufacturing, sales, and service data Identify metrics which link IA deliverables to results. Metrics reported for conversion of existing systems to common data definitions Couple IA implementation with specific business functionality. Implementation coupled with upgrades to manufacturing ERP application and enhancements to service applications.

20. 20 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Diagnostic: How do you know you’re on the right track? On the right trackCause for re-evaluation Program scopeIterative across businesswide problem space, with each iteration producing timely, useful deliverables. “Boil the ocean” – tackling too much breadth across business and depth of detail before useful deliverables are complete. StakeholdersIdentified, broadly based, regular check-in with sponsors. Stakeholders not identified or narrowly based. Check-ins ad hoc or absent. Business and IT drivers – “pain points” Specific, measurable, solv- able: “improve quality of customer data as measured by.” Nebulous – “Information is our most important asset.”

21. 21 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Diagnostic: How do you know you’re on the right track? On the right trackCause for re- evaluation IA program priorities and goals Clear and validated by stakeholders Unclear or not validated Approach for driving change Clear outcomes that IA deliverables direct Unclear outcomes or unclear linkage to IA deliverables DeliverablesTargeted to stakeholders’ needs Stakeholders don't find deliverables clear or relevant Program metricsOutcome as well as progress- based Lack of or progress- based metrics only Value messageElevator pitch – crisp, relevant, succinct: “solve this problem by … which will produce the following results …” Fuzzy

22. 22 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Alex Cullen +1 617/613-6373 acullen@forrester.com www.forrester.com Thank you

23. 23 Entire contents © 2005 Forrester Research, Inc. All rights reserved. Selected references September 9, 2005, Best Practices “Simplifying Information Architecture” June 16, 2004, Best Practices “Creating the Information Architecture Function” May 12, 2004, Forrester Big Idea “Organic Information Extraction” September 9, 2004, Quick Take “The Revival Of The Enterprise Data Model” August 18, 2004, Best Practices “Data Warehousing Architecture Alternatives” May 7, 2004, Best Practices “From Defect Inspection To Design For Information Quality” March 17, 2004, Best Practices “Standards For Enterprise Architecture”