wp_how_to_use_the_dgi_data_governance_framework - HOW TO USE THE DGI DATA GOVERNANCE FRAMEWORK TO CONFIGURE YOUR PROGRAM Prepared by Gwen Thomas of the

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Unformatted text preview: HOW TO USE THE DGI DATA GOVERNANCE FRAMEWORK TO CONFIGURE YOUR PROGRAM Prepared by Gwen Thomas of the Data Governance Institute How to Use the DGI Data Governance Framework to Configure Your Program Contents Why Data Governance? .................................................................................................................................. 3 Why the DGI Data Governance Framework Was Created .............................................................................. 4 How the Framework is Organized ................................................................................................................... 5 Using the Framework to Configure Your Program .......................................................................................... 7 Getting Started ............................................................................................................................................ 7 Components 1-­‐6: Rules and Rules of Engagement ..................................................................................... 9 1. Data Governance Missions and Visions ............................................................................................... 9 2. Goals, Governance Metrics and Success Measures, and Funding Strategies ...................................... 9 3. Data Rules and Definitions ................................................................................................................ 10 4. Decision Rights .................................................................................................................................. 12 5. Accountabilities ................................................................................................................................. 12 6. Controls ............................................................................................................................................. 12 Components 7-­‐9: People and Organizational Bodies ................................................................................ 13 7. Data Stakeholders ............................................................................................................................. 13 8. A Data Governance Office (DGO) ...................................................................................................... 14 9. Data Stewards ................................................................................................................................... 15 Component 10: Processes ......................................................................................................................... 15 Summary ....................................................................................................................................................... 16 © The Data Governance Institute Page 2 How to Use the DGI Data Governance Framework to Configure Your Program Why Data Governance? If you go back several decades in the world of IT, you’ll find that early systems were typically well governed. Not many people had “hands-­‐on-­‐keyboard” ability to change the architecture of a system or to input control files; those who were given this ability understood the rules. It was expected that they would adhere to standards, naming conventions, change control, and other aspects of governance. Data Management disciplines included Data Governance activities, even if they weren’t labeled as such. And then everything changed. Now we have an ever-­‐growing list of computing devices, with an ever-­‐ expanding list of people with “hands-­‐on-­‐keyboard” abilities to add data and to change how data is structured, stored, and linked. Those whose job titles include the words “Data Management” can no longer effectively govern data on their own. Governance requires a collaboration between many roles. During the 1990s, this need for joint control took the form of the Business/IT Collaboration Model “Business/IT Collaboration Model” – a paradigm that says Business groups and IT groups need to collaborate so that the information needs of the business can be met. Sometimes this model worked well, especially in small projects where only one business group and one technical team were represented. In more complex situations, however, this model often had poor results. Why? Technology teams were asked to produce information that was fit for use by multiple business stakeholders, but IT insisted that information requirements were the responsibility of business. No one group served as advocate for the information needs of the business. A New Paradigm Slowly, the Business/IT Collaboration Model has been The B-­‐I-­‐T Sequence supplemented by other paradigms designed to improve collaboration while ensuring accountability for meeting information stakeholders’ needs. One of these is the B-­‐I-­‐T Sequence from the Data Governance Institute (DGI). The DGI B-­‐I-­‐T Sequence states that Business needs drive Information needs, which drive Technology strategies and approaches. In other words, information technology does not exist for its own sake. IT exists to meet the information needs of the business. To succeed in this mission, technology teams must understand those information needs. They must understand how to prioritize competing requirements and how to resolve conflicts when they arise. They must understand who has the authority to speak for each stakeholder group during requirements setting and conflict resolution. They must understand the policies, standards, and rules they’re expected to adhere to as they build, maintain, and enhance systems. © The Data Governance Institute Page 3 How to Use the DGI Data Governance Framework to Configure Your Program Technology resources working with data may help enforce these policies, standards, and rules, but they typically only create the most technical of them. For all the others, they need definitive input from business resources. They need Data Governance just as strongly as the business does. One of the purposes of a Data Governance program is to serve as Data Governance advocate for the information needs of the business. It helps sort out and align overlapping accountabilities for meeting those needs. The “I” in the B-­‐I-­‐T Sequence The bulk of the work of Data Governance takes place in that area where business and technology concerns overlap to address information needs. Of course, Data Governance is not the only thing taking place in this space. Many other efforts have drivers and constraints that influence how data, information, records, documents, and other information types are managed and governed in this space. Stakeholders from these efforts may play a role in Data Governance. Or, they may already be performing processes and services (such as change control and issue resolution) that can be leveraged by Data Governance, Data Architecture, the Data Governance program. Change Control, Metadata Management, Master Data Management, Records Management, Document Management, Privacy Protection, In this case, Data Governance can help ensure that Access Management, etc. these various stakeholder groups’ needs are acknowledged and considered during data-­‐related projects. Data Governance can help align these stakeholders’ needs and provide checks-­‐and-­‐balances between those who create/collect information, those who consume/analyze it, and all these other stakeholder groups. ↑ ↑ Why the DGI Data Governance Framework Was Created In complex organizations, it’s not easy to identify – much less meet – all data stakeholders’ information needs. Some of those stakeholders are concerned with operational systems and data. Some are concerned about analysis, reporting, and decision-­‐making. Some care primarily about data quality, while others are frustrated by architectural inadequacies that keep users from linking, sorting, or filtering information. Some data stakeholders focus on controlling access to information; others want to increase abilities to © The Data Governance Institute Page 4 How to Use the DGI Data Governance Framework to Configure Your Program acquire and share data, content, documents, records, and reports. And still others focus on compliance, risk management, security, and legal issues. Each of these data stakeholder groups may have a different vocabulary to describe their needs, their drivers, and their constraints. Typically, they have trouble communicating with each other. Indeed, they may not even have the same set of requirements in mind when they call for better governance of data. Frameworks help us organize how we think and communicate about complicated or ambiguous concepts. The Data Governance Institute wanted to introduce a practical and actionable framework that could help a variety of data stakeholders from across any organization to come together with clarity of thought and purpose as they defined their organization’s Data Governance and Stewardship program and its outputs. The framework includes ten components – elements that would typically be present in any type or size of Data Governance effort. They apply to new programs and established ones, fairly informal efforts and rigorous ones, programs that are sponsored by IT staff, and those that are sponsored by the business side of the organization. These components are present in programs that involve just a handful of participants, and those that involve hundreds or even more participants. They are factors in stand-­‐alone Data Governance programs, and in efforts where Data Governance is co-­‐managed with Data Quality, Compliance, Data Architecture, or some other set of activities. As you consider your own program, then, you’ll want to consider how these universal components may be represented in your own unique culture and environment. In this paper, we’ll go through a step-­‐by-­‐step process for using these framework components to configure your own Data Governance and Stewardship program. How the Framework is Organized Some of the words used in describing Data Governance – such as “Decision Rights” – may not be familiar to us all. But the framework is organized using the familiar WHO – WHAT – WHEN – WHERE – WHY pattern. In working with the framework, you will be encouraged to clarify: • WHY your specific program should exist WHAT it will be accomplishing • WHO will be involved in your efforts, along with their specific accountabilities • HOW they will be working together to provide value to your organization • WHEN they will performing specific processes. Another way to look at your program is to consider • The RULES that your program will be creating, collecting, aligning, and formalizing (policies, requirements, standards, accountabilities, controls, data definitions, etc.) and the RULES of ENGAGEMENT that describe how different groups work together to make those rules and enforce them • The PEOPLE AND ORGANIZATIONAL BODIES involved in making and enforcing those rules, and © The Data Governance Institute Page 5 How to Use the DGI Data Governance Framework to Configure Your Program • The PROCESSES that these people follow to govern data, while creating value, managing cost and complexity, and ensuring compliance. Both of these schemas are represented the framework graphic, as well as in the list of framework components. The DGI Data Governance Framework Rules and Rules of Engagement 1. Mission and Vision 2. Goals, Governance Metrics and Success Measures, and Funding Strategies 3. Data Rules and Definitions 4. Decision Rights 5. Accountabilities 6. Controls People and Organizational Bodies 7. Data Stakeholders 8. A Data Governance Office (DGO) 9. Data Stewards Processes 10. Proactive, Reactive, and Ongoing Data Governance Processes © The Data Governance Institute Page 6 How to Use the DGI Data Governance Framework to Configure Your Program Using the Framework to Configure Your Program Designing your Data Governance and Stewardship program is not necessarily a linear progression. Instead, you’ll make decisions about each of your program components based on decisions about other components. And so, while we’ll present these steps linearly, you’ll actually look at your initial program design effort holistically. Getting Started Actually, though, “designing” your program is not the first step you should be looking at. Here are the steps in a Data Governance program lifecycle. 1. Develop a value statement The Data Governance Program Lifecycle 2. Prepare a roadmap 3. Plan and fund 4. Design the program 5. Deploy the program 6. Govern the data 7. Monitor, measure, report. Value Statements Organizational leaders rarely support the move to formal Data Governance “just because” it’s a good idea. Instead, these programs receive support because they can help address specific organizational goals. Just like any other effort that requires time, resources, and attention, Data Governance efforts should ultimately help the organization • Make money, meet its mission, and/or increase the value of assets • Manage costs and/or complexity • Support other necessary efforts, such as Security, Compliance, or Privacy As you consider your program, be sure that you’re clear about which of these concerns you’re addressing. Be prepared to track each of your program’s specific efforts to at least one of these categories. What will those specific efforts be? Here’s where Data Governance programs differ so greatly that we say there are different “flavors” of Data Governance. Some exist specifically to support Data Quality efforts, and most of their program activities involve measuring, monitoring, and improving information quality. Data Governance facilitators may spend much of their time translating requirements between business and technical staff and in reporting quality metrics to management and other data stakeholders. Data Governance may consist of a series of “routine” activities containing both business and IT-­‐run tasks. © The Data Governance Institute Page 7 How to Use the DGI Data Governance Framework to Configure Your Program Other Data Governance programs exist because their organizations find it difficult to connect sets of information in a way that support Business Intelligence, mergers and acquisitions activities, or gaining new capabilities. For these organizations, Data Governance activities may focus on bringing cross-­‐functional groups together to make complicated decisions about their data environments, how to use information, or how to prioritize data-­‐related projects. For these organizations, Data Governance leaders may spend much of their time “bringing pieces of the puzzle together”: identifying data stakeholders and their information needs, ensuring that research and analysis takes place, facilitating decision-­‐making sessions, and then following up on projects and processes that come out of those decisions. Here, Data Governance may be very political in nature. Still other organizations may understand their business needs and their data environments and the level of information quality they require to meet their goals. For these groups, the challenge is to keep individuals and teams from making “mistakes.” This flavor of Data Governance program may be primarily concerned with authority and controls. Activities may focus on policy enforcement, access control, setting standards for metadata and master data, or ensuring that new data elements don’t introduce duplicate fields. At these organizations, Data Governance participants may seem like “data cops.” Which of these flavors of Data Governance seems most like what you need? What DO you need? Specifically, what activities do you think will need to take place as part of your Data Governance efforts? Be prepared with concise value statements that describe what you want to do, and what will be the results of those actions, and what will be the ultimate impact. Consider using an A, B, C approach: If we do A, then we can expect B, which should lead to C. • If we improve our data quality in the Customer repository, then our marketing reports will have more accurate information, which should lead to more confident business decisions. • If our Data Stewardship Committee addresses this data integration problem, then we’ll have the opportunity to hear from multiple stakeholders with different perspectives, which reduces the chance that we’ll break something else when we fix this. • If our Data Governance team reviews new Product master data, then we’ll catch any non-­‐standard data before it can cause a problem, and we’ll avoid the cost of re-­‐work. The Rest of the Data Governance Lifecycle After you develop value statements for your activities, you’ll want to create a high-­‐level roadmap that takes into account known drivers and constraints for those activities. Then you’ll want to develop a high-­‐ level plan that you can use to socialize your ideas and to obtain funding commitments. Only after you hear from major stakeholders about their support for the program’s value and their willingness to contribute resources will you be ready to complete your formal program design using the components of the DGI Data Governance Framework. Of course, this doesn’t mean you can’t get a head start by making some preliminary configuration choices. You’ll actually need to do this, so you can have details to discuss with major stakeholders as you discuss your anticipated mission and value statements. But most programs discover that stakeholder input at this © The Data Governance Institute Page 8 How to Use the DGI Data Governance Framework to Configure Your Program point leads to adjustments to those preliminary choices. So while you’re painting a picture to stakeholders about what life will be like after you’ve deployed a program and are actively governing your data, be sure to listen to their expectations. Also, remember that every time you make a major change in program scope or direction, you should run through the entire Data Governance program lifecycle again, so you can be sure of achieving clarity of purpose and stakeholder buy-­‐in for the new activities. Components 1-6: Rules and Rules of Engagement 1. Data Governance Missions and Visions In some organizational cultures, it’s important to develop formal mission statements and vision statements. Other places don’t always create these documents. Regardless of your culture, you should develop a clear statement of what will be different and better if you have formal Data Governance. Use this with your value statements to paint clear before-­‐and-­‐after pictures for your data stakeholders. Remember to revisit this component every time you address a new set of data, a new repository, a new set of processes, or a new set of stakeholders. Always be prepared to deliver clear, concise, A-­‐B-­‐C statements about what you’re doing, and why. Also, remember that your program may have multiple missions and focus areas. That’s ok. Each one will be implemented in phases, but not necessarily in lockstep. 2. Goals, Governance Metrics and Success Measures, and Funding Strategies Some organizations make the mistake of only Typical universal goals of a Data Governance Program: publicizing high-­‐level program goals. Consider these goals from the Data Governance Institute website at 1. Enable better decision-making . They’re good and 2. Reduce operational friction important goals, but you’ll want to supplement them 3. Protect the needs of data stakeholders 4. Train management and staff to adopt with specific, actionable statements that describe your common approaches to data issues program scope, the results you’re looking for (from 5. Build standard, repeatable processes 6. Reduce costs and increase effectiveness your A-­‐B-­‐C value statements), and how you’ll measure through coordination of efforts your progress. Consider 7. Ensure transparency of processes • What data subject areas will you address? • What spec...
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