APPROACH TO EIM. Bonnie O Neil, Gambro-BCT Mike Fleckenstein, PPC



Similar documents
Make the maturity model part of the effort to educate senior management, so they understand the phases of the EIM journey.

Enterprise Information Management Capability Maturity Survey for Higher Education Institutions

Enterprise Data Governance

OPTIMUS SBR. Optimizing Results with Business Intelligence Governance CHOICE TOOLS. PRECISION AIM. BOLD ATTITUDE.

Whitepaper Data Governance Roadmap for IT Executives Valeh Nazemoff

The following is intended to outline our general product direction. It is intended for informational purposes only, and may not be incorporated into

Enterprise Information Management

US Department of Education Federal Student Aid Integration Leadership Support Contractor January 25, 2007

Enterprise Data Governance

Explore the Possibilities

EIM Strategy & Data Governance

CDCR EA Data Warehouse / Strategy Overview. February 12, 2010

The Business Case for Information Management An Oracle Thought Leadership White Paper December 2008

Data Governance: A Business Value-Driven Approach

Presented By: Leah R. Smith, PMP. Ju ly, 2 011

Data Governance 8 Steps to Success

Business intelligence (BI) How to build successful BI strategy

Big Data and Big Data Governance

Data Governance: A Business Value-Driven Approach

BI STRATEGY FRAMEWORK

An RCG White Paper The Data Governance Maturity Model

University of Michigan Medical School Data Governance Council Charter

Vermont Enterprise Architecture Framework (VEAF) Identity & Access Management (IAM) Abridged Strategy Level 0

Knowledge Management and Enterprise Information Management Are Both Disciplines for Exploiting Information Assets

Master Data Management. Zahra Mansoori

Bringing Strategy to Life Using an Intelligent Data Platform to Become Data Ready. Informatica Government Summit April 23, 2015

SAP Thought Leadership Business Intelligence IMPLEMENTING BUSINESS INTELLIGENCE STANDARDS SAVE MONEY AND IMPROVE BUSINESS INSIGHT

Operationalizing Data Governance through Data Policy Management

The DGI Data Governance Framework

Deploying Governed Data Discovery to Centralized and Decentralized Teams. Why Tableau and QlikView fall short

Unveiling the Business Value of Master Data Management

Enabling Data Quality

Building a Data Quality Scorecard for Operational Data Governance

Business Intelligence Maturity Model. Wayne Eckerson Director of Research The Data Warehousing Institute

Enterprise Data Quality Dashboards and Alerts: Holistic Data Quality. Jay Zaidi Fannie Mae

Gwen Thomas, The Data Governance Institute. Abstract

Governance Is an Essential Building Block for Enterprise Information Management

Information Governance Workshop. David Zanotta, Ph.D. Vice President, Global Data Management & Governance - PMO

Data Governance Primer. A PPDM Workshop. March 2015

5 Best Practices for SAP Master Data Governance

STRATEGIC INTELLIGENCE WITH BI COMPETENCY CENTER. Student Rodica Maria BOGZA, Ph.D. The Bucharest Academy of Economic Studies

Enterprise Information Management and Business Intelligence Initiatives at the Federal Reserve. XXXIV Meeting on Central Bank Systematization

Importance of Data Governance. Vincent Deeney Solutions Architect iway Software

Summit 2015 Orlando London Frankfurt Madrid Mexico City

Research. Mastering Master Data Management

Three Fundamental Techniques To Maximize the Value of Your Enterprise Data

Management Update: The Cornerstones of Business Intelligence Excellence

DATA QUALITY MATURITY

Turning Data into Knowledge: Creating and Implementing a Meta Data Strategy

By Makesh Kannaiyan 8/27/2011 1

California Enterprise Architecture Framework

Request for Information Page 1 of 9 Data Management Applications & Services

The Role of the BI Competency Center in Maximizing Organizational Performance

A McKnight Associates, Inc. White Paper: Effective Data Warehouse Organizational Roles and Responsibilities

Business Intelligence and Analytics: Leveraging Information for Value Creation and Competitive Advantage

CrossPoint for Managed Collaboration and Data Quality Analytics

Information Management & Data Governance

Using SAP Master Data Technologies to Enable Key Business Capabilities in Johnson & Johnson Consumer

Introduction to Business Intelligence

THOMAS RAVN PRACTICE DIRECTOR An Effective Approach to Master Data Management. March 4 th 2010, Reykjavik

Submitted to: Service Definition Document for BI / MI Data Services

Begin Your BI Journey

HOW TO USE THE DGI DATA GOVERNANCE FRAMEWORK TO CONFIGURE YOUR PROGRAM

White Paper

Learning to drive your Ferrari

04 Executive Summary. 08 What is a BI Strategy. 10 BI Strategy Overview. 24 Getting Started. 28 How SAP Can Help. 33 More Information

Session 0905 ASUG SBOUC Align your Business and IT with a Solid BI Strategy. Deepa Sankar Pat Saporito

Challenges in Metadata Integration: BMO Financial Group Case Study

Creating a Business Intelligence Competency Center to Accelerate Healthcare Performance Improvement

IBM Information Management

Building a strong data management capability with TOGAF and ArchiMate. Bas van Gils b.vangils@bizzdesign.com

Solutions. Master Data Governance Model and the Mechanism

Using Master Data in Business Intelligence

Implementing Oracle BI Applications during an ERP Upgrade

SAP Manufacturing Intelligence By John Kong 26 June 2015

Data Governance Implementation

POLAR IT SERVICES. Business Intelligence Project Methodology

Deliver the information business users need

Master data deployment and management in a global ERP implementation

Master Data Management in Practice. Achieving True Customer MDM. Wiley Corporate F&A

Busting 7 Myths about Master Data Management

Why You Still Need to Master Your Data Before You Master Your Business (Intelligence) Business Imperatives Addressed By Reliable, Integrated View

Best Practices for Deploying Managed Self-Service Analytics and Why Tableau and QlikView Fall Short

TDWI strives to provide course books that are content-rich and that serve as useful reference documents after a class has ended.

Expanding Data Governance Into EIM Governance The Data Governance Institute page 1

Washington State s Use of the IBM Data Governance Unified Process Best Practices

DATA GOVERNANCE AT UPMC. A Summary of UPMC s Data Governance Program Foundation, Roles, and Services

SAP BusinessObjects Information Steward

Make information work to your advantage. Help reduce operating costs, respond to competitive pressures, and improve collaboration.

Enterprise Business Intelligence Solutions

Managing Data as a Strategic Asset: How is that Accomplished? Tuesday, April 28, 2015

Technical Management Strategic Capabilities Statement. Business Solutions for the Future

From Capability-Based Planning to Competitive Advantage Assembling Your Business Transformation Value Network

Building a Comprehensive Strategy for Enterprise Data Management An Executive Overview

Implementing a Data Governance Initiative

How To Develop An Enterprise Architecture

Transcription:

USING A FRAMEWORK APPROACH TO EIM Bonnie O Neil, Gambro-BCT Mike Fleckenstein, PPC

AGENDA The purpose of an EIM Framework Overview of Gartner's Framework Elements of an EIM strategy t Implementation of EIM How to use a Framework for EIM

INITIAL BACKGROUND Client requested that we use Gartner s Framework It is thorough and well thought-outout It covers the main areas of concern In your environment, you may want to emphasize different things, so you can tweak the framework accordingly

EIM A LA GARTNER Enterprise information management (EIM) is an integrative discipline for structuring, describing and governing information assets regardless of organizational and technological boundaries to improve operational efficiency, promote transparency and enable business insight. -From Gartner Group, BI Summit, 2007

PURPOSE OF A FRAMEWORK Present, usually in diagram form, all components and how they interrelate Helpful in a major, complex effort that has many components, to assist iterative development Verify that no component is left out of the final implementation ti Analogous to a roadmap

GARTNER S EIM BUILDING BLOCKS Vision Strategy Vision: How is information perceived and valued in the organization? A bi-product or shareable resource? Strategy: How currently managed? Ad-hoc, departmental, or enterprise-wide? Governance: Are there defined decision rights and controls for managing information as an asset? Who s involved? Governance Organization Organization: What information-centric roles exist? Where located? Process Information Infrastructure Metrics Process: Are there practices (such as stewardship and data quality) across life cycle? Information Infrastructure: How well do the technologies support current and future needs? Metrics: How much is spent managing ginformation? How much is redundant? What is financial impact of poor quality data on the business? From Gartner Group, BI Summit, 2007

METADATA REQUIRED FOR BUILDING BLOCKS Vision i Strategy Governance Organization Process Information Infrastructure Metrics Vision: Vision of EIM; Track the value of information Strategy: How data is managed Governance: Data Stewards, Council, Policies, Checkpoints Organization: Information roles and who fills them Process: Policies & Procedures of data management Infrastructure: What is in place and how well it serves the business Metrics: Measurements to determine data quality and cost of poor quality

METADATA SUBJECT AREAS Vision/ Strategy Mission Statement Governance Organization Process Charter Policy Process Data Warehouse Metadata Repository Infrastructure Data Marts Metrics Transaction Systems

ASSESS READINESS AND OPPORTUNITIES FOR EIM THROUGH ADOPTION MODEL 9 Characteristics EIM Building Blocks Vision Strategy Governance Organization Process Information Infrastructure Leve Le el 5: Optimi evel 4: Man Level 3: P Level 2 Lev Le vel 1: Aware evel 0: Una e ware ized naged Proactive 2: Reactive Levels Metrics From Gartner Group, BI Summit, 2007

IMPLEMENTATION GUIDELINES Many of the areas overlap Not a perfect cube Keep this in mind when you implement

GARTNER S EIM MATURITY MODEL: LEVEL 0 Level 0: Unaware most organizations assume significant enterprise-wide risk. They see information as a system byproduct. Information quality is poor. Data cannot be trusted. Most are unaware that information is a problem. Note: All CMM for EIM Levels come from Gartner Group, BI Summit 2007

LEVEL 1: AWARE Level 1: Aware most organizations are somewhat aware of the issues of information management. Here information is a source of power and managed in silos. IT tries to normalize information through consolidation efforts such as data warehousing.

LEVEL 2: REACTIVE Level 2: Reactive a core base of leaders reacts to the need for consistent, accurate and faster information.

LEVEL 3: PROACTIVE Level 3: Proactive Information assets are perceived as necessary for improved business performance.

LEVEL 4: MANAGED Level 4: Managed Information is perceived as a critical component of the business. Here, significant portions of the EIM building blocks are in place. For example, senior management recognizes information as a strategic asset. It embraces the EIM strategy.

LEVEL 5: OPTIMIZED Level 5: Optimized Here, organizations are at the apex of an EIM program and see information as a competitive differentiator and source of operational efficiency. At this level, organizations should put barriers in place against complacency, because information excellence can easily devolve in response to changes in business dynamics.

IMPORTANT INITIATIVES UNDER EIM Data Quality Master Data Management Data Warehouse/Business Intelligence Data Sharing/Service Level Agreements (SLA)

USING THE FRAMEWORK FOR EACH EIM INITIATIVE Vision Data Quality Strategy MDM Governance Organization Process Information Infrastructure Metrics Data Sharing Data Warehouse

EIM FUNCTIONS AND ORGANIZATION

EIM ORGANIZATION IMPLEMENTS INFORMATION ARCHITECTURE POLICIES, STANDARDS & GUIDELINES Text in Red = Recommended Starting Points Information Life Cycle Business Information Management Chief Information Officer Enterprise Data Management Senior Director David Newman Enterprise Information Management Group Data & Content Management Common Organizational Models: 1. Centralized approach (pictured here) 2. Decentralized approach (matrix model) Run Information Value Management Plan Build Use Data & Content Design Quality Management Migration and Sourcing Systems Support Information Access Services Metadata Management Major Focus: Implement Information Architecture Content taxonomies Project-level modeling Data quality program Records Management Major Focus: Enterprise data warehousing Master data stores Information Infrastructure Performance monitoring and tuning From Gartner Group, BI Summit, 2007 Major Focus: Metadata management Governance and methodology Training g& Communications Information access

IMPLEMENTING EIM

GROW THE EIM TEAM Start out with a Data Architect As EIM grows, add people responsible for the areas shown on the last slide

DATA GOVERNANCE ORGANIZATION First Tier Set the strategy, mission, business motivation High Level in the organization Data Governance Council Second Tier General Management and Oversight Data Stewards Third Tier Data analysts performing metrics

HOW DATA GOVERNANCE FUNCTIONS

WORKING EIM IN TO EXISTING ORGANIZATIONAL PROCESSES

START SMALL WITH INTEGRATION Think big, start small, iterate and evolve modeling paradigm & principles i The Integration model approach allows iterative development The model can be integration model Finance extension Distribution ecommerce Partners Supply Chain Sales Marketing HR evolved over time Based on the principles, extensions get simpler with each extra iteration Finally, new subjects are incorporated completely within the model

PHASING IN EIM

CREATING AN EIM ROADMAP Every Program is a series of discrete projects Start with Vision, Goals and Objectives Include As-Is and To-Be Must understand where you are now and how far you have to go Creation of a Program includes: People Process Best Practices & Standards Technology/Tools

SUMMARY An EIM Framework provides an inventory of important components that should not be overlooked Gartner's Framework is a great place to start to launch your EIM Program Implementation of EIM includes the start-up tasks such as a Charter/Mission and Governance as well as initiatives such as MDM or Data Quality EIM should be incrementally implemented EIM elements should be woven into existing processes (such as SDLC) as much as possible

FOR MORE INFORMATION, SEE THE FOLLOWING GARTNER REPORTS Website: www.gartner.com; all documents on the website are available for purchase Newman, David. The New Information Architecture: Enterprise Architecture and Enterprise Information Management, BI Summit 2007, Chicago. Newman, David. Business Drivers and Issues in EIM, July 25, 2005 Newman, David. Toolkit Case Study: Making EIM Sustainable at Anglo Platinum, July 10, 2007 Newman, David. and Logan, Debra. Toolkit: Best Practices in Defining an Organizational Structure for Enterprise Information Management, Dec 8, 2006 Logan, Debra and Newman, David. From IM to EIM: An Adoption Model, May 18, 2006. Newman, David. and Logan, Debra. Achieving Agility: How Enterprise Information Management Overcomes Information Silos, April 19, 2006. Handler, Robert A. and Newman, David. Use Enterprise Information Architecture t Techniques to Move Information Management, Sep 2, 2005