This Data Management Capability Assessment Model (DCAM®) is being provided to the Recipient as a Member of the EDM Association, Inc. (“EDM Association”). The Model and all related materials are the sole property of EDM Association, and all rights, titles, and interests therein are vested in EDM Association. The Model, or any portion thereof, may not be copied by any Recipient and may not be distributed to, or made available for the use by any party other than Recipient, unless, in each case, Recipient has obtained the prior written authorization of EDM Association. Except as provided above, the Model, or any portion thereof, may not be used in any way by Recipient, its officers, employees, or agents or by any other party without the prior written consent of EDM Association. The Model may only be used by Recipient for external purposes or external assessments if it has entered into a separate licensing agreement with EDM Association governing the terms for such use. By reviewing or using the model, or any portion thereof, the Recipient (and each person reviewing or using the Model) agrees to the terms set forth above. Any copying or use of the Model except as set forth above is strictly prohibited. DCAM® is a registered trademark of the EDM Association, Inc., and may not be used or copied without the prior written authorization of the EDM Association, Inc. Open Preface

The Data Management Capability Assessment Model is a structured resource that defines and describes the capabilities needed to establish and sustain a successful data management initiative in any organization. The Enterprise Data Management Council developed this Model, drawing upon the real-world experiences and valuable lessons learned by many of the world's top organizations. The result is the synthesis of a broad range of Data Management best practices from across the full spectrum of interconnected business processes. The DCAM addresses the strategies, organization-wide structures, technology, and operational practices needed to drive Data Management successfully. To manage data in today's organizations, we must start by recognizing that proper Data Management is about managing data as meaning. This relatively new concept is not well understood by many organizations. Managing data, according to its meaning, is the process of defining each piece of data by what it represents or describes in the real world. This process results in a direct, readily comprehensible label for that data. By adding descriptive metadata, the precise nuanced connection between each piece of data and the real world is established. Data exists everywhere within an organization and must be managed consistently within a well-defined control framework. The DCAM defines the framework and capabilities required to make Data Management a critical part of an organization's everyday operational fabric. The challenges of effectively managing data are significant. In most organizations, there are numerous legacy data repositories and an overabundance of functions to unravel. There are social and political barriers to overcome. There are real technical challenges and execution gaps to address. Data ownership and accountability are hard to establish. Historically, funding often has been project-based, making Data Management an intermittent priority. Data's now critical place in the organization requires a commitment to robust, ongoing funding. Organizations have an additional challenge to build the strong executive support needed to ensure that the organization stays the course in the face of short-term measurement criteria, operational disruption, and conflicting stakeholder priorities. We understand this reality because we have the experiences and the scars to show for it. Data is foundational. It is the lifeblood of the organization. The bad-data tax is a significant expenditure for many organizations though it may remain hidden in accepted inefficiencies and stunted results. Unraveling data silos through the creation of harmonized data is a prerequisite for eliminating redundancy, reducing reconciliation, and automating business processes across the organization. Managing this kind of fully interconnected data is essential if we are to gain insight from analytics, feed our models with confidence, enhance our service to clients and capitalize on new, but often fleeting, business opportunities. DCAM provides the guidance needed to assess the current state of any organization's Data Management and define the objectives and framework for the target-state of the Data Management initiative. The DCAM is organized into seven core components and one optional component:

Core:

• 1.0 Data Strategy, Data Management Strategy & Business Case
• 2.0 Data Management Program & Funding
• 3.0 Architecture – Business, Data & Technology
• 4.0 Business Data Knowledge
• 5.0 Data Quality Management
• 6.0 Governance - Data & Data Management Program
• 7.0 Data Management Operations, Risk & Control

The core components are organized into 28 capabilities and 80 sub-capabilities.

Optional:

• 8.0 Analytics Management

This optional component covers Analytics Management and is relevant where the scope of the Data Management program or the Chief Data Officer's responsibilities cover the Analytics functions of the organization. This component is organized into 6 capabilities and 21 sub-capabilities. A note on the optionality of Component 8.0, Analytics Management is a critical function that must be present in all organizations to deliver analytics in alignment with business goals and objectives. However, when using DCAM for assessment purposes, this component is considered optional. As noted earlier, the decision to include this component in the assessment scope is at the discretion of the organization being evaluated. The EDM Association extends its sincere gratitude to the many members who contributed to the development of the original DCAM in 2014, as well as to its subsequent updates, including the current 3.1 Version. DCAM continues to gain momentum and widespread adoption across the data management industry and around the world. To date, DCAM training has been delivered to over 6,000 professionals globally. The DCAM Framework, originally developed for the financial services sector, and in recent years, has been adopted across a wide range of industries, from manufacturing to government. To maintain the relevance and leadership of the model, the EDM Association is committed to a disciplined product management approach, ensuring the Framework is reviewed and updated regularly. We remain committed to ensuring that DCAM meets the evolving needs of the data management community. Contributions and insights from our members, particularly those working closely with the model, have always been, and will continue to be, vital to its ongoing success.

Open Acknowledgement

The EDM Association (EDMA) is committed to leveraging the knowledge of the data management practitioners across our membership. For Version 3.1, a global team of representatives from organizations and consultancies was assembled to participate in a Work Group to develop the latest updates to the Framework. A thank you is extended to the groups listed below for their role in advising on the enhancements to DCAM.

EDMC Executive Director & Advisors

• John Bottega - EDM Association
• Predrag Dizdarevic - Element 22
• Mark McQueen - Ortecha

Work Group Co-Leads

• David Kowalski, MIDAS Advisory Services
• Robert Wentz, EDM Association

Sub-Group Leads

• Paul Carey, Bank of NY
• Malcolm Clarke, Ortecha
• Ben Clinch, Ortecha
• Brady Cole, Equifax
• Neil Coulson, Transurban
• James Genever, Data Consultant
• Nirusha Perera, Scotia Bank
• Marilena Stavrides, Cortico-X
• Nanette Vogler, Raymond James
• Richard White, McKinsey & Company

Work Group Members

• James Arnold, CVS Health
• Stefan Buxton, HSBC
• Rod Culbreth, II Data Solutions
• Martin Doyle, Data Quality Global
• Paul Finney, RBC
• Lata Garlapati, American Dental Association
• Jacqueline Hayes, TTEC
• Todd Henley, Northwest Bank
• Neal Linson, InCite Logix
• Kelly McIsaac, TD Bank
• Paricia Melat, Cardinal Health
• Scott Peachey, Bread Financial
• Emarie Pope, Sandhill Consultants
• Nadine Schramm, Citibank
• Roman Sinagl, Sandoz
• Cindy Sullivan, Ortecha
• Kyler Way, KPMG US
• John Wills, Prentice Gate Advisors
• Mike Zuschin, Cleveland FRB
• Jonathan Adams, Data Reach
• Paul Bell, Entain Group
• Brenda Carmichael, Franklin Templeton
• Michael Fallon, Genpact
• Mike Frey, First Interstate Bank
• Tim Hachmeister, Golden 1
• Justin Heller, Synchrony Bank
• Fahad Khan, Hewlett Packard
• Marilu Lopez, Segda
• Matt McQueen, Ortecha
• Mark Mullins, United Community Bank
• Robert Peterkins, Risk Data Group
• Mariane Santana, Co-operators
• Tel Seera, Northern Trust
• John Stark, State of Indiana
• John Varga, Deutsche Bank
• Kristy Weaver, New Belgium Brewing
• Jeff Wolkove, EDM Resource Group