Information Architecture: Successes From Data Architecture A Presentation to the Data Management Association National Capitol Region May 8, 2001 Thanks for opportunity to speak here Talk about practical experience with data architecture Ted Griffin Office of Science, Department of Energy Todd Forsythe, Lisa Black, Connie Dowler Stanley Associates, Inc.

Why Listen to Us? Real Experience Planning Designing AND Implementing IT and Data Architecture in Federal Civilian Environment, With User Groups How many people do you know . .

Two Architecture Projects DOE Office of Science HQ (IMSC): Planning Design Implementation Maintenance At DOE, however, two arch projects . . . Chicago Operations Office: Planning Design Implementation Maintenance

In the Hierarchy (IMSC)

Who We Are Stanley Associates DOE Federal Lead Todd Forsythe - Functional Architect Methodology & Context for Data Architecture Lisa Black – Lead Data Architect Data Design Connie Dowler – Data Base Administer Data Design Implementation Lisa, Connie with customers Ted – practical benifits DOE Federal Lead Ted Griffin Benefits and Lessons

Methodology Methodology: Dr. Steven Spewak: Enterprise Architecture Planning: Developing a Blueprint for Data, Applications and Technology Initiated in 1997, continually updated and improved

Seven Components of Information Architecture Customer Team Business Model Operating Plan Strategic Application Architecture Principles Technology Architecture Example of Principles: - IM services and systems are an integral part of CH future business strategy. - Standards will be adopted when they lead to a stable and maintainable environment. Data Architecture Existing Systems

Results of the Initial Strategic Plan Initial Strategic Plan called for two main applications Many more applications existed in the whole, but major effort was in the main applications. Two JAD groups organized to initiate those applications Managers and Directors organized, trained in JAD/RAD, etc.

How We Proceeded Problem analysis Business modeling Logical data modeling Normalization Data integrity issues Elicitation with managers to Identify problem areas within business practices Modeling an AS-is business process using IDEF0 methodology Re-engineering efforts Creation of a logical data model using the business model Use of normalization to reduce the redundancy Data integrity by sharing data between organizations Referential integrity with lookups, mouse clicks versus typing

Business Representatives Change the Course Revised Plan Foundation Projects Defined common data components Functionality chunking Strategic Information Planning Group Strategic Planning and Architecture group Made up of managers, and directors to assist in identifying the business process and problem areas Identified that with all business processes there is a core foundation data that runs through all areas Institutions – that are given awards Organizations – groups with the Government that monitor the award Persons – persons within the Institutions, and organizations Program Areas – Research Areas, Budget and Reporting Codes, Crosscuts, Micro Codes Projects/Work Elements – level of funding Identified these areas Execution work management Budget Management Human Resource management Support services RAD/JAD process chunked out business process areas to be completed in 6 week time frame Solicitation Proposals Award Procurement Request

Foundation Projects Organization Institution Person Project (replaced later by Work Element) Program Area

Change in the Way IM Was Done Organization Administrators Working Together Cooperation Communicating Compromising Prioritizing Progressing in this RAD?JAD process identified a need for the Organization administrator, the real user of the system. Reality set in in that the managers and directors had identified roles and responsibilities that were probably not the best suited for real life business With the 7 different organizations coming together where they had always been separate

State Institution Country InstitutionType InstitutionDetails InstitutionTypeClassification

Foundation Provided Data Repository Real work could begin Back to the original applications Integrated Financial Management Project Integrated Research Project and Procurement Project Revise the projects Execution Work Management (IMSC) Worksheet Exchange

Data Conversion Free form data fields from legacy system All records imported into IMSC Identify and reduce duplicate records in IMSC

Information Management in the Office of SC (IMSC) Central Repository provided by Foundation Projects Additional data integrated into repository Work toward single application for all users / organizations Each org had their own thought Thoughts were actually the same, just different levels of detail, and different definitions (project means different things to different offices)

What We Did to the Users Data Integrity – Users must look for data before they add new data Referential Integrity – Pick lists provided, editing isn’t allowed (on the fly) Duplicate Squash – Eliminate duplicate records within IMSC

Issue 1: The System Doesn’t Work! Due to the implementation of Referential Integrity, users attempted to put bad B&R code into the system. System rejected the code and a helpdesk issue was recorded Users perspective: “I can’t do my job.” Overall perspective: “Great, we finally have good data.”

Issue 2: We Can’t Use This! Data now has integrity. Prior systems provided ability to overload fields so that queries and reports couldn’t be done on the database. Searches had to be done on unstructured data. User perspective: “This isn’t right, we define a word as something else.” Overall perspective: “Finally, a system for all to use.”

Issue 3: Less Complex, More Flexible With the above restrictions, and the ability to aggregate the data, reporting and queries on the data provide the same answers to all users. Separate queries don’t have to be written for each organization. Smaller number of canned reports Easier to Query and get Big Picture reports

Unsuccessful Efforts All have in common: Focus is not on service, consequently service did not improve Total Quality Management Process Improvement Team Matrix Management Partnering Covey Management by Objectives Just-in-Time Service Reorganization Re-engineering Strategic Planning / Planning

IM Organization Goals Focus is on service Customers perform their jobs better

Effective IM Service Effective Service Result: Best Process: Supports customer business activities Supports customer priorities Involves the customer Result: Focus is on service Customers do their jobs better Best Process: Information Architecture

Benefits of SC HQ After Information Architecture Process: IM Strategic Plan based on business activities Budget based on IM Strategic Plan IM Operating Plan based on IM Strategic Plan & Budget All IM implemented supports business activities Technology implemented to support system development IM Team organization dependent on IA / strategic planning All decisions based on customer developed principles

SC HQ After Information Architecture Customer Involvement Business folks engaged Customer Information Advisory Group (CIAG) IM Board Executive Steering Committee (ESC) Development process requires customer involvement Business folks decide what IM to implement Business folks defend budget

SC HQ After Information Architecture Requirements: Are tied to business activities Are better identified Can be traced from identification to product rollout Are satisfied following one process

SC HQ After Information Architecture Customer Service Policies developed and followed One standard image provided COTS evaluated and selected more easily Moving towards one data store Service consistent Interoperability Service more responsive Corporate systems take priority (reduction in systems performing same function) Communications Performance measures implemented

SC HQ After Information Architecture Budget / Cost The provision of IM more cost effective FY 99, 00, & 01 budgets reflect significant increase Costly interfaces avoided Benefits and impacts of IM more easily assessed Result: Making maximum effective use of available IM funding to provide IM products and service that best enable customers to perform their jobs

Information Architecture Why we like it Focus is on service IM Team better able to provide effective service Customers better able to perform their jobs Working on the right issues

Keys to a Successful Implementation General Prior to Project Initiation (IM Organization) During the Project After Implementation

General Focus must be on customer service and collaboration to enable them to do their jobs better IM organization takes ownership

Prior to Project Initiation Obtain top management support Produce a well designed project plan focusing on IM team and customer jointly producing first seven IA components and transition plan Conduct top management and customer presentations on IA (project plan and process) to describe benefits and manage expectations Established customer groups (with time expectations) to work project plan and create customer infrastructure Manage logistics Obtain Federal/contractor support experienced in IA implementation

During Project Physically locate IM team (including support) and customer group together Continue education on IA process with customer groups and how the current project step fits in Produce each component with the intent of being good not perfect Provide oral status reports to top management at agreed-to-intervals Perform good project management

After Implementation Institutionalize process Maintain communications Business customers take ownership Develop budget request based on strategic plan Have customers request budget IM team and customer jointly develop annual operating plan Become IM consultants and facilitate customer decisions Maintain communications Maintain customer infrastructure

What Are Ongoing Challenges? Maintaining collaboration Ensuring customer understanding of IA process Providing the right communications Managing customer involvement, accountability, and expectations Elimination of us vs. them

Contacts Mr. Ted Griffin, SC-65 Strategic Planning & Architecture Federal Lead, Department of Energy (301) 903-4602 Ted.Griffin@Science.doe.gov Lisa Black, Lead Data Architect, Stanley Associates (301) 903-1310 Lisa.Black@science.doe.gov Connie Dowler, Data Base Administrator, Stanley Associates (301) 903-1018 Connie Dowler@science.doe.gov Pat Flannery, DOE Project Manager, Stanley Associates (301) 903-9002 Pat.Flannery@science.doe.gov Todd Forsythe, Strategic Planning & Architecture, Stanley Associates (301) 928-1244 Todd.Forsythe@science.doe.gov