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This chapter covers the activities for defining and designing the operational, staffing, and technology resources. The chapter on data governance technology is also built into this chapter from the prior edition.

This chapter presents an overview of the process to deploy the data governance program.

This is a prologue. This chapter directly addresses top leadership on the necessity and fundamental concepts of data governance. This chapter offers the initial ideas that will form data literate leaders.

Data governance is a business program; therefore, it needs to add value to the business. However, since data governance is a program dealing in abstracts (data as an asset), it is similar to other programs where tangible results are hard to see, such as marketing or finance. The CEO will acknowledge the need for marketing and certainly the need for a finance area, but a detailed, hard-dollar justification for these areas (as for DG) is usually not sitting in a folder on a desk somewhere.

This chapter covers operating the data governance program. It covers operating technology, training, measuring, and sustaining data governance.

We will present the core managerial and business concepts required for building and operating a data governance (DG) program. The key takeaway from this chapter is that DG is not part of information technology’s job description.

This chapter addresses the most common question—“What does it look like?” It continues with a detailed examination of who should do the governing, what activities they need to perform, what is actually governed, and what data governance looks like when it occurs.

This chapter is the final chapter. It summarizes the case studies, and provides a recap of data governance critical success factors.

As we said earlier, starting the deployment of your DG program entails standard program startup activities. Therefore, we must ensure that scope and span are adequately understood, and then produce a plan that will sufficiently guide the team through DG deployment. As with any other effort related to EIM, our practice has observed that, simply stated, it is difficult to get started. This is usually due to the need for some specialized activities. Most companies have experience with projects but bog down in starting the new activity. Like any other EIM-type effort, there will be the need to execute new activities that are unique to data governance. This chapter will cover those in detail.

You cannot manage what you do not measure, and this phase gives you the ability to measure the success of managing data governance. One thing to be clear on as you read this section is the following. If you have a business case that is aligned with business needs, then this will be a very short phase. If there are no business value statements, ROI, a business case, or anything else resembling the business case for managing information as an asset, then it will be a bit longer in duration, and you must do this phase . The steps to be taken are almost identical to the steps taken to generate a business case for all other types of enterprise information-management efforts.

This chapter covers the phase of operating the DG program. It probably bears repeating that this is not the last phase of a linear process, but is instead the final step in a life cycle. It is also never ending. Like data governance itself, the Rollout and Sustain phase of the program represents the day-to-day activities.

During the past few decades, as we started to make data governance an integral part of information projects, we did not pay much attention to how the organization would operate after all the new data, tools, and neat things were turned on. After all, how hard could it be? Appoint a few stewards, give them power to enforce standards, and away we go. Reality soon hit us right between the eyes and we realized there had to be additional formal treatment of how organizations implement DG. There had to be some engineering to show people what it was they needed to do, and then they had to be appointed to do it. This had to be done in a form that allowed us to monitor it all. In other words, we had to design and staff an organization framework of sorts to actually carry out DG.

The “Vision” phase shows stakeholders and leadership what DG will look like. This means a bit more than a one-page picture, although that is important, too. This phase also includes work on the mission statement, and both vision and mission are defined in detail in the coming sections. A vision establishes a picture of where an organization would like to be at a certain point in time in the future. The mission talks about how to get there. The goal is to convey understanding and comprehension of what DG means and what the organization wants to do to get there. This vision reinforces the fact that the business of enterprise information asset management is the business.

By “stand up,” we mean define, design, deploy, and start to manage the DG program. This does not mean there is no process to get actual approval to proceed with a DG program. Many organizations struggle with the desire to carry out DG, but do not have the commitment from management to do so. However, DG is not a program to do as a stand-alone effort. After all, you need to govern something . Our process covers the business case and “selling” DG, but in the context of an organization that acknowledges something needs to be different. We also assume that the process will find a visible benefit to DG. In other words, we are showing the entire process and will not delve into a separate chapter on the debate of selling DG, or if DG has value. If you have read this far, you know that.

A data governance program really has one clear goal—to disappear. That may seem a bit enigmatic, especially since this book is about making data governance real. Nevertheless, it is true. Remember, you are deploying a new set of principles for treating a valuable asset in a much-improved manner. At the end of the day, the true mark of success is the organization treating its information as it treats its factories, supply chains, vendors, and customers. In the twenty-first century, no manager argues with standards for material handling, depreciation rules, or customer privacy. These are accepted business practices. There is no debate over whether you should have standards or controls. Yet it is easy to spread data all over an organization to the point that (a) it is excessively expensive to manage, and (b) you cannot find it, make sense of it, or agree on its meaning.

This short chapter concerns itself with some of the more mechanical and discrete elements of data governance. If you understand DG as a program, and implement it as such, sooner or later you are going to find yourself up to your hips in documents and files representing the multitude of artifacts being governed. Thus, it will be necessary to administer the governance program.

This chapter discusses the details of sustaining enterprise information management (EIM) and culture change. It suggests key factors to keep an EIM program going over the years and makes it an integral part of organization's business culture. The essence of sustaining EIM is to manage the required change. For basic change management, organizations need a dedicated team. It can be temporary or a part of HR, but it must be able to focus on EIM change. It does not have to be large—even the largest organizations should have a core team of no more than 6–8 people. It is key that the members have the necessary skills, knowledge, expertise, and, most important, influence. Most likely some training will be required as these are not typical resources that organizations have waiting in the wings. Further, communications hold the key to successful deployment of an information asset management philosophy. The EIM program will touch anyone who uses or creates data or content. The change significance is not to be taken lightly, and the communications aspects are critical. It is important for an executive to understand a few of the finer points of communications for EIM. Change management has a significant hard-dollar impact on an organization. Leaders are generally unaware of, or dismiss, the impact of poorly managed change on the bottom line.

Publisher Summary This chapter focuses on the alignment phase of the enterprise information management (EIM) process that starts and maintains the core data required to ensure alignment and measure value. Alignment refers to the direct linkage of information asset management efforts to business strategies, and the measurement of information and knowledge projects against anticipated benefits. It is also an objective of the EIM program—information and content management when called for directly fulfills aligned means that business needs. Alignment gives the ability to tie an information management project to a specific business objective, and measure results against that objective. Alignment also flows through to the architecture and road map aspects of EIM. All EIM solutions, deliverables, and policies must originate somewhere in the business driver/goal/objective framework. The activities gather and confirm business direction, and apply a formal technique to identify opportunities for data and content to improve an organization. The results of this phase will permeate all other artifacts. While the activities can be compressed or adjusted, there must be some formal exercise to align business goals and business actions that leverage information. The higher one can raise the business visibility of these work products, the better. If situations have minimal or skeptical business input, then proceed with alignment anyway, and seek out confirmation in subsequent phases of EIM.

This chapter reviews the methodology enterprise information management (EIM) program uses. It emphasizes on those tasks that are unique to EIM. The design and deployment of the EIM program is focused on one overarching goal—make the philosophy of information asset management (IAM) part and parcel of an enterprise. To do this requires a process for business alignment to ensure long-term value, and engineering and management activity to ensure the EIM people and process frameworks are matched to your organization's culture and business model. The EIM program requires many processes, techniques, and deliverables to define, convey, and implement IAM. Each of the subdisciplines has its own flavors and approaches. Planning and implementing asset management is a logistics problem of tracking what is known, delivering what is known to the right people at the right time, based on the value and cost of the information and knowledge being tapped. Organizations that can filter, ascribe, and deliver data/information at the right times to the right people are executing EIM.

This chapter presents a scheme that how phases and activities will be broken down into a specific presentation format in the discussion. Each phase will be shown in reference to where it typically occurs in the overall approach. The activities will be shown as optional, mandatory, or conditional within the phase. Business benefit and ramification recap why the business needs to participate and execute presented steps. The enterprise information management (EIM) process is designed to add value at all stages, even if the program were to be delayed at some point. Sample Output provides an example from the case studies to show what the deliverable may look like.

This chapter discusses how formalizing the management of data can increase the efficiency of enterprises. For a businessperson, the key concept is managing the asset. Managing implies setting goals, planning, directing, and supervising the execution of a plan. Managing implies governance to make sure one manages the asset in a uniform manner across the enterprise. It means being aware of compliance and risk management. The enterprise information management (EIM) program provides an effective platform for creating flexibility. The bottom line for an EIM program, which must be reinforced from time-to-time, is supporting the business with clear, documented, and effective data and information. The business user needs this as badly as anyone in information technology. One needs to treat information as an asset. That means examining other disciplines like accounting and supply chain management and implementing a new philosophy without disrupting day-to-day operations. EIM is a program that allows measuring the contribution against the costs incurred to handle and distribute the information assets.

This chapter presents the introduction to Part 2 of the book. Enterprise information management (EIM) is the program that manages enterprise information assets to support the business and improve value. EIM manages the plans, policies, principles, frameworks, technologies, organizations, people, and processes in an enterprise toward the goal of maximizing the investment in data and content. Information asset management (IAM) is the underlying philosophy for EIM. EIM implements IAM. EIM wraps people and processes and investment around the IAM concept in the form of a strategic corporate program. Only through focusing steadily on solid business cases, business alignment, and an effective practical road map will EIM succeed. The software, the dictionaries, the processes, the organization charts, the technologies, and the models are all tools to achieve what should be a well-documented and measurable business program. The remaining chapters will delve into the details of building an EIM program. It is as “how to” as one can make it. This part of this book contains sample outputs and appendices with templates. It also drives more into how to develop the products.

Publisher Summary This chapter covers why business alignment is important to Information Asset Management (IAM), and reviews the essentials of the enterprise information management (EIM) processes for alignment. Regardless of the technique or presentation, creating a clear vision of the role of data and content in achieving business direction is vital in getting EIM designed and adding value to an enterprise. Assets are used to further organization goals. Business usage must be defined if EIM will be based on IAM. The alignment activity within EIM should be revisited annually. The alignment exercise provides a pure business representation of what data can do for an enterprise. Data can be tied to direct business benefits—if the business achieves its objectives, what are the anticipated effects on balance sheets and income statements? Executing this technique at dozens of companies has given very pure and reliable indications of what is important to organizations. The objectives of EIM programs, both initial and ongoing, are rooted in the Alignment activity. The EIM program will be positioned to support the execution of the statements in these matrices. If the data or content cannot support the statements, then it may not be a vital content subject to management.

This chapter covers the organizational aspects surrounding enterprise information management (EIM), what must be considered, and how the organization structures may affect current organization charts. One needs to apply some intelligent engineering to the organizing of EIM, data governance, and affected business areas. Creativity will be key—with the structure of your guiding bodies, stewards, and accountable managers being defined by the nature of the organization. When planning for the EIM, organization reaches the point of determining accountability and identifying the caretakers, a formal exercise for the organization is highly recommended. This would take place during the Road Map and sustaining phases of the EIM program. Accountability means measurement and performance goals; incentives then come into play. So, to declare someone a steward because it seems like he is the right person and to also make him an enterprise steward even if he has a narrow functional view is risking job confusion. Unfortunately, many organizations have caretakers or stewards who have not internalized accountability, or do not even have a vested interest in a business process of any sort.

The most difficult task in any large effort like enterprise information management (EIM) is the first step. This chapter addresses the question: Where does one start? It focuses on getting EIM design and deployment started. The initiation of the EIM program should not only be a planning exercise, but it also should start to enlighten business and information technology, and result in steps toward business acceptance of information asset management (IAM). The road to IAM means looking hard at your organization's business directions. For some companies, this may not be very handy. There are substantial benefits from the first few phases: alignment to IT, education of business leaders, statement of a future vision, and documentation of critical information categories. Even if the EIM program stops, there is sufficient material to hand off to a technical team to begin subdisciplines of EIM, such as MDM, data quality, or a data warehouse.

After the enterprise information management (EIM) program is up and running, there will be need for some changes and adjustments, as will feedback from EIM team or a change management team, to ensure value, manage costs, and adjust budgets. This chapter discusses the approach to these changes down the road. Scheduling normal refreshing of the Road Map, and accompanying Sustaining Requirements, is required to maintain the EIM program energy. A normal planned visitation of the EIM strategy, without a change in business environment, means at minimum the EIM team needs to consider the Road Map from three major perspectives: Business Alignment, Sustaining Requirements, and Architecture Element changes. At regular intervals (hopefully annually) or as required, the EIM team will get the go ahead to refresh the Road Map. The EIM team should be receiving feedback and metrics on program effectiveness. Business Alignment review is very important, as budget changes and Road Map priorities may be implied. The process to do this is no different than the initial process of aligning EIM to the business, just shorter. Often, business directions become manifest in annual lists of strategic projects or approved initiatives. The EIM team needs to review these as closely as broad announcements of direction and strategy.

Publisher Summary This chapter covers the day-to-day operation of the enterprise information management (EIM) program. It operationalizes the requirements for sustaining EIM developed in the Road Map phase. This is the means by which the cultural obstacles that are barriers to Information assets are managed. It also measures and reports on the adoption of EIM and, if adjustments are required, trigger one of the other phases. There are common concerns that will be heard as formal management of information is implemented, and one needs an appropriate response such as sustaining activity, organization roll out, EIM progress metrics, and EIM project management. The Sustaining phase deals with the questions and the responses. The Sustaining phase is the longest, as it never ends. Once EIM starts, diligence is required to keep it running. Even if one starts EIM via a subdiscipline, or within a narrow portion of the organization, it will require sustaining activities to ensure ongoing value and growth.

This chapter provides the details of the metrics for measuring enterprise information management (EIM) success and progress. Specifically, it covers the meaning of the metric, its application, and how to collect the data. In addition, it explores measuring value of the information. Management and measurement go hand in hand. Managing information assets means some sort of metrics must exist. There are many more metrics possible as there are information assets to measure. There is a new realm of “information accounting” slowly developing that will remove information assets out of the realm of the abstract and fluffy accountability and place it into serious business context. The need to produce proof of EIM effectiveness will create an expectation of measurement anyway. So, there is really no intellectual excuse to avoid developing some type of proactive metrics and even a business valuation of information in an organization.

Procedures are as important to enterprise information management (EIM) as diagrams and technology. The procedures are rooted in data governance, ensuring data quality, and maintain the information life cycle. The activity in this chapter serves to provide the architecture to specify and apply the process elements of EIM. The Data Governance Architecture organizes how policies for data governance will be applied. The information value chain (IVC) Architecture focuses on the information life cycle of the enterprise. If one addresses a series of detailed processes in the Detailed Scenarios activity, then, one has a series of IVC to incorporate into the EIA. This activity is recommended if the architecture element MDM is part of EIM, or one has to essentially reengineer the entire information life cycle. The Data Quality Architecture activity uses input from the Business Data Management Architecture. Data quality is the area that establishes how the organization will address data quality issues. Lastly, the overall information life cycles are a function of various business processes and current data movement.

This chapter examines one of the key shapers and metrics of the enterprise information management (EIM) program—Information Management Maturity (IMM). It is assessed early in any effort to create an EIM program. It is also assessed frequently after the program goes into operation. The concept of information maturity is key to understanding the results of any assessment that one may execute or have executed. The maturity of the organization in the context of data and content usage, quality, alignment to the business, and other factors is crucial. Everyone, even within the same industry, will most likely have or desire a different type or flavor of maturity in terms of using data. Company A makes widgets but wants to be most innovative, so it may require more capability in the areas to enable R&D. Company B makes widgets and desires to be the most customer-intimate. Therefore, they may need to master the management of their basic reference data, like customer and sales records. Understanding the gap between needs and capabilities permits a more efficient and measurable EIM program. IMM sets the metrics for measuring the amount of convergence. IMM means institutionalizing Information Asset Management (IAM) principles.

Publisher Summary This chapter presents the business model, and supplements it with additional findings from the Business Metrics and business information requirements (BIR) activity. This assists to create the business requirement for enterprise information management (EIM). Major categories of content, expressed as metrics or BIRs, are defined. It refines how the BIRs and Metrics can support the business. Processes and resulting business actions for leveraging content are identified, and models built or modified to reflect the EIM perspective. Data groups and elements were matched to the requirements to ensure completeness and understanding of the scope of what EIM will manage. Optionally, one can go deeper into the process and design new workflows and even improve the business case. If one wants, these activities provide a means to start to organize the navigation and definition of enterprise DNA, or metadata, via a first pass at enterprise taxonomies.

Setting enterprise information management (EIM) into real scenarios provides context for understanding the potential value and impact of EIM of organization. This chapter presents basic information about the components of EIM, considers what they might look like, and introduces two case studies. The case studies will help lock in relevant concepts, as well as provide an overview of how the programs were developed, what some of their artifacts contain, and what outcomes were achieved. It also provides examples of what the various work products from the case studies look like. The executive audience samples emphasizing business drivers, visual aids, and comparisons to best practices are also presented. A business leader sponsoring, initiating, or leading an EIM program needs to make sure business alignment permeates all of the work. Starting with an understanding of business plans, the earlier examples emphasized the alignment of the business. The EIM program is launched with credibility. In addition, the EIM effort is sustainable; it is easy to revisit documented directions and make adjustments as business conditions change.

Enabling the business, managing costs, and supporting staff are all important business vision concepts. The enterprise information management (EIM) program needs to do the same things, and be structured accordingly. This chapter describes EIM as a business component. If a business user or customer or other constituent question the source or relevance of the data or content being presented, they will hesitate to take effective action. They will create or acquire their own, or come to their own conclusions. This is information mismanagement. However, society and pervasive technology are forcing organizations into taking some formal stance on their information assets. A reasonable first step is to begin to incorporate data quality and formal information management into all projects that create or rely on data to enable business actions and decisions. There are basic required components and functions that must be designed into the organization. These components and functions are not very different than the basic building blocks of any other strategic area within an organization.

Publisher Summary This chapter provides a review to the Part 2 of the book. It discusses the positive aspects provided by an enterprise information management (EIM) program. At some time, the EIM program will be challenged. Even if there is no challenge to the business viability of EIM, the various building blocks may give the impression of EIM being too encompassing but there are logical connections between EIM and all of the building blocks that contribute to EIM. Information asset management addresses all the categories of content an enterprise can use. The process in Part 2 sets up a process to design and maintain the asset management program. Besides addressing inhibitors to prior success with information projects, the EIM program strives to improve the business, as measured by the balance sheet or income statement. Part 2 focuses on the program and the business benefits.

This chapter discusses the method to develop a valuation for information and help complete a business case. The only real barrier to the enterprise information management (EIM) business case is where the return on the information asset management (IAM) investment or benefits are applied, not where they are created. Further, this chapter delves into the valuation of information assets. The perspective of the business case is to influence the income statement via looking for our cash flow or income from EIM. EIM is a business program and must be treated as such. It can be positioned to financially justify implementing IAM; EIM economics can reveal financial justification, or at least measurable targets. The real issue is not whether there is value in managing information. The real issue is the association of the benefits of exploiting and leveraging information to the actual program that enables the leverage: EIM.

Businesspeople meet and assess the effectiveness of the marketing program, the sales campaign, or the cost-reduction imperative. Businesses revisit their programs frequently. The enterprise information management (EIM) should be no different. This chapter discusses what needs measuring, what to revisit, and what needs to happen if the business environment changes. Many of the metrics presented in this discussion are familiar, but add the dimension of information. In addition, there are new metrics to be considered. Essentially, the organization must be willing to invest in collecting the data and producing the metrics. EIM is about managing assets. One cannot manage what one does not measure. Finally, all but the smallest companies should consider the value of their information in the light of the value of the entire organization. This means applying some of the concepts of intangible asset accounting. Although not official, this exercise forces the EIM area to examine the relevancy of information to the enterprise, and determine risks as well as value.

This chapter describes two detailed situational activities: community/social network architecture, enterprise taxonomy. They would apply if the organization will be incorporating content management, document management, workflow, collaboration, or social networking into the enterprise information management (EIM) program. If EIM encompasses web site content, e-mails, manuals, and any other media that may be used by the organization, the EIM team needs to consider addressing these areas as part of the EIM program. One may just acknowledge their existence, and perhaps assess potential risk. The same goes for any type of content where collaboration or sharing of the content appears in business processes, or is being poorly managed, like SharePoint databases. Lastly, manual, safety protocols, and other documents where process or safety is involved need to be considered. There are business benefits with managing these assets as part of EIM. Like any other element, there may not be an immediate need to roll out applications or consolidate content, but the asset management aspect of EIM means the financial aspects should be documented. Leadership needs to make a conscious decision on when and how to address this content.

Publisher Summary This chapter discusses the vision phase that reinforces the reason for following enterprise information management (EIM). A vision of future is developed to convey a business perspective of the role of EIM. This is reinforced with the business case for EIM. Often, the EIM team will need to execute a preliminary version of activities, such as starting to define business information requirements and assembling the conceptual model of the business. The abstract model from the Vision is not the only model one needs. Given that to develop a program to manage information, one needs to start to define how the organization relates to and uses the managed data and content, and how the data and content needs to be logically managed. This means one starts the development of the EIM data, or information model, and some kind of process model. At the end of the Vision phase, the EIM program has established or affirmed the reason for existence. Subsequent phases start to shape the actual program and further define the assets to be managed.