There has been a great deal of confusion around the term information governance (IG), and how it is distinct from other similar industry terms such as information technology (IT) governance and data governance.
Publisher’s note: This is an excerpt from the author’s book Information Governance: Concepts, Strategies and Best Practices (Wiley CIO).
Some books, articles, and blogs have compounded the confusion by offering a limited definition of IG, or sometimes offering a definition of IG that is just plain incorrect, often confusing it with data governance. Even so-called “experts” confuse the terms!
So, in this chapter we will spell out the differences and include examples in hopes of clarifying what the meaning of each is, and how they are related.
All three terms are a subset of corporate governance, and in the above sequence, become increasingly granular in their approach. Data governance can be seen as part of IT governance, which is also a part of a broader program of information governance.
We will now delve into more detailed definitions, and a comparison of the three.
Data governance expert Robert S. Seiner, author of the book Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success (Technics Publications), and also the publisher of The Data Administration Newsletter (TDAN.com) for over 20 years, pioneered the concept of “non-invasive data governance.” In his approach, Seiner focuses on what can get done toward improving data governance without major disruptions to the business, or redesigning business processes. He offers his definition of data governance: “the execution and enforcement of authority over the definition, production and usage of data.” He goes on to say, “My definition intentionally has some grit and some teeth—I fully stand behind having strong definition especially if it catches people’s attention and opens the door for greater discussion. At the end of the day, true governance over data or information requires executed and enforced authority.”
But his clients sometimes like to tone it down, softening the definition. Seiner notes, “Some of my clients ponder that the definition is too aggressive. These clients do not like the words ‘execution and enforcement’ so they tame it down to something less aggressive like ‘formalized behavior for the management of data.’ That is my definition of data stewardship.” Publisher’s note: Replace “behavior” with “accountability” and that is spot on.
“Data governance is the execution and enforcement of authority over the definition, production and usage of data.”– Robert S. Seiner
Data governance involves processes and controls to ensure that data at the most basic level—raw data that the organization is gathering and inputting—is true and accurate, and unique (not redundant). It involves data cleansing (or data scrubbing) to strip out corrupted, inaccurate, or extraneous data and de-duplication, to eliminate redundant occurrences of data. It also usually involves implementing Master Data Management (MDM, which is discussed in more detail in Chapter 10 on IG for IT).
Data governance focuses on data quality “from the ground up” at the lowest or root level, so that subsequent reports, analyses, and conclusions are based on clean, reliable, trusted data (or records) in database tables. Data governance is the most fundamental level at which to implement information governance. Data governance efforts seek to assure that formal management controls—systems, processes, and policies—are implemented to govern critical data assets to improve data quality and to avoid negative downstream effects of poor data. DG efforts also hold data stewards accountable for information quality and accuracy.
Data governance uses techniques like data cleansing and de-duplication to improve data and reduce redundancies.
Data governance is a newer, hybrid quality control discipline that includes elements of data quality, data management, IG policy development, business process improvement (BPI), and compliance and risk management.
Data Governance Strategy Tips
Everyone in an organization wants good quality data to work with. But it isn’t so easy to implement a data governance program. First of all, data is at such a low level that executives and board members are typically unaware of the details of the “smoky back room” of data collection, cleansing, normalization, and input. So, it is difficult to gain an executive sponsor and funding to initiate the effort. And if a data governance program does move forward, there are challenges in getting business users to adhere to new policies. This is a crucial point since much of the data is being generated by business units. But there are some general guidelines that can help improve a data governance program’s chances for success:
- Identify a measurable impact. You must be able to demonstrate the business value of a data governance program, or it will not get the executive sponsorship and funding it needs to move forward. A readiness assessment should capture the current state of data quality and whether or not an enterprise or business unit level effort is warranted. Other key issues include: Can the organization save hard costs by implementing data governance? Can it reach more customers, or increase revenue generated from existing customers? 
- Assign accountability for data quality to business units, not IT. Typically, IT has had responsibility for data quality, yet it is mostly not under their control, since most of the data is being generated out in the business units. So, a pointed effort must be made to push responsibility and ownership for data to the business units that create and use the data.
- Recognize the uniqueness of data as an asset. Unlike other assets like people, factories, equipment, and even cash, data is largely unseen, out of sight, and intangible. It changes daily. It spreads throughout business units. It is copied and deleted. Data growth can spiral out of control, obscuring the data that has true business value. So, data has to be treated differently and its unique qualities must be considered.
- Forget the past, implement a “going forward” strategy. It is a significantly greater task to try to improve data governance across the enterprise for existing data. Remember, you may be trying to fix decades of bad behavior, mismanagement, and lack of governance. Taking an “incremental approach with an eye to the future” provides for a clean starting point and can substantially reduce the pain required to implement. So, a “from this point on” strategy where new data governance policies for handling data are implemented beginning on a certain date is a proven best practice.
- Manage the change. Educate, educate, educate. People must be trained to understand why the data governance program is being implemented and how it will benefit the business. The new policies represent a cultural change and supportive program messages and training are required to make the shift.
Good data governance ensures that downstream negative effects of poor data are avoided, and that subsequent reports, analyses and conclusions are based on reliable, trusted data.
IT governance is the primary way that stakeholders can ensure that investments in IT create business value and contribute toward meeting business objectives. This strategic alignment of IT with the business is challenging, yet essential. IT governance programs go further and aim to “improve IT performance, deliver optimum business value and ensure regulatory compliance.”
Although the CIO typically has line responsibility for implementing IT governance, the CEO and board of directors must receive reports and updates to discharge their responsibilities for IT governance and to see that the program is functioning well and providing business benefits.
Typically, in past decades, board members did not get involved in overseeing IT governance. But today it is a critical and unavoidable responsibility. According to the IT Governance Institute’s Board Briefing on IT Governance, “IT governance is the responsibility of the board of directors and executive management. It is an integral part of enterprise governance and consists of the leadership and organizational structures and processes that ensure that the organization’s IT sustains and extends the organization’s strategies and objectives.”
IT governance seeks to align business objectives with IT strategy to deliver business value.
The focus is on the actual software development and maintenance activities of the IT department or function. IT governance efforts focus on making IT efficient and effective. That means minimizing costs by following proven software development methodologies and best practices, principles of data governance and information quality, and project management best practices, while aligning IT efforts with the business objectives of the organization.
IT Governance Frameworks
There are several IT governance frameworks that can be used as a guide to implementing an IT governance program. (They are introduced below in a cursory, way, as a detailed discussion of them is best suited for other books focused solely on IT governance).
Although frameworks and guidance like COBIT® and ITIL have been widely adopted, there is no absolute standard IT governance framework. The combination that works best for your organization depends on business factors, corporate culture, IT maturity and staffing capability. The level of implementation of these frameworks will also vary by organization.
COBIT (Control Objectives for Information and Technology) is a process-based IT governance framework that represents a consensus of experts worldwide. It was codeveloped by the IT Governance Institute and ISACA and first released in 1996, as a set of control objectives to assist auditors. COBIT 5 was released in 2012, and the current version is COBIT 2019.
COBIT is a high-level framework and de facto standard to guide software development efforts. It holds IT departments accountable for contributing to business objectives. COBIT has been harmonized with other standards and best practices contained in ITIL (IT Infrastructure Library), COSO (Committee of Sponsoring Organizations of the Treadway Commission), ISO 27001/2, PMBOK (Project Management Book of Knowledge), and other “accepted practices” in IT development and operations. COBIT addresses business risks, control requirements, compliance, and technical issues.
COBIT offers IT controls which:
- Cut IT risks while gaining business value from IT under an umbrella of a globally accepted framework
- Assists in meeting regulatory compliance requirements
- Utilizes a structured approach for improved reporting and management decision-making
- Provide solutions to control assessments and project implementations to improve IT and information asset control
COBIT consists of detailed descriptions of processes required in IT and also tools to measure progress toward maturity of the IT governance program. It is industry agnostic and can be applied across all vertical industry sectors, and it continues to be revised and refined.
COBIT is broken out into three basic organizational levels and their responsibilities: (1) board of directors and executive management, (2) IT and business management, and, (3) line level governance, security and control knowledge workers.
The COBIT model draws upon the traditional “plan, build, run, monitor” paradigm of traditional IT management, only with variations in semantics. There are four IT domains in the COBIT framework, which contain 34 IT processes and 210 control objectives that map to the four IT processes: (1) plan and organize, (2) acquire and implement, (3) deliver and support, and, (4) monitor and evaluate. Specific goals and metrics are assigned, and responsibilities and accountabilities are delineated.
Val IT is a newer value-oriented framework that is compatible with and complementary to COBIT. Its principles and best practices focus are on leveraging IT investments to gain maximum value. 40 key Val IT essential management practices (analogous to COBIT’s control objectives) support three main processes: value governance, portfolio management, and investment management. Val IT and COBIT “provide a full framework and supporting tool set” to help managers develop policies to manage business risks and deliver business value while addressing technical issues and meeting control objectives in a structured, methodic way.
COBIT is process-oriented and has been widely adopted as an IT governance framework. Val IT is value-oriented and compatible with and complementary to COBIT yet focuses on value delivery.
ITIL (Information Technology Infrastructure Library) is a set of process-oriented best practices and guidance originally developed in the UK to standardize delivery of IT service management. ITIL is applicable to both the private and public sectors and is the “most widely accepted approach to IT service management in the world.”  Again, as with other IT governance frameworks, ITIL provides essential guidance for delivering business value through IT, and it “provides guidance to organizations on how to use IT as a tool to facilitate business change, transformation, and growth.”
ITIL best practices form the foundation for ISO/IEC 20000 (previously BS15000), the International Service Management Standard for organizational certification and compliance. ITIL 2011 is the latest revision (as of this printing), and it consists of five core published volumes that map the IT service cycle in a systematic way:
- ITIL Service Strategy
- ITIL Service Design
- ITIL Service Transition
- TIL Service Operation
- ITIL Continual Service Improvement
ITIL is the “most widely accepted approach to IT service management in the world.” 
ISO/IEC 38500:2015 is an international standard that provides high-level principles and guidance for senior executives and directors, and those advising them, for the effective and efficient use of IT. Based primarily on AS 8015, the Australian IT governance standard, it “applies to the governance of management processes” that are performed at the IT service level, but the guidance assists executives in monitoring IT and ethically discharging their duties with respect to legal and regulatory compliance of IT activities.
The ISO 38500 standard comprises three main sections:
- Scope, Application and Objectives
- Framework for Good Corporate Governance of IT
- Guidance for Corporate Governance of IT
It is largely derived from AS 8015, the guiding principles of which were to:
- Establish responsibilities
- Plan to best support the organization
- Acquire validly
- Ensure performance when required
- Ensure conformance with rules
- Ensure respect for human factors
The standard also has relationships with other major ISO standards, and embraces the same methods and approaches. It is certain to have a major impact upon the IT governance landscape.”
ISO 38500 is an international standard that provides high level principles and guidance for senior executives and directors responsible for IT governance.
Corporate governance is the highest level of governance in an organization and a key aspect of it is information governance (IG). According to the Sedona Conference, IG programs are about minimizing information risks and costs and maximizing information value. This is a compact way to convey the key aims of IG programs, and it is what should be emphasized when the merits of an IG program are being discussed. The definition of IG can be distilled further to a more succinct “elevator pitch” definition of IG, which is“security, control, and optimization”of information. (See Chapter 1 for more detailed definitions.)
IG processes are higher level than the details of IT governance, and much higher level than data governance, but both of the aforementioned can be (and should be) a part of an overall IG program. In fact, often IG programs are launched from successful (and funded) data governance programs.
IG program are driven from the top-down but implemented from the bottom-up.
The IG approach to governance focuses not on detailed IT or data capture and quality processes, but rather on controlling the information that is generated by IT, office systems, and external systems, that is, the output of IT. IG efforts seek to manage and control information assets to lower risk, ensure compliance with regulations, and to improve information quality and accessibility while implementing information security measures to protect and preserve information that has business value.
IG programs focus on breaking down traditional functional group “siloed” approaches, to maximize the value of information. Mature IG programs employ the principles of infonomics, to measure and monetize information. But these programs rely on robust, effective data governance programs to provide good, clean data so that calculations and analytics that are applied yield true and accurate results.
Information governance is how an organization maintains security, complies with regulations, and laws, and meets ethical standards when managing information.
Impact of a Successful IG Program
When making the business case for IG, and articulating its benefits, it is useful to focus on its central impact. If there is a business case to apply infonomics and gain new value from information, the benefits may be quite clear in terms of monetizing information or leveraging it in a barter transaction. However, putting cost-benefit numbers to IG programs is often difficult, unless you also consider the worst-case scenario of loss or misuse of corporate or agency records. How much is losing the next big lawsuit worth? How much are confidential merger and acquisition (M&A) documents worth? How much are customer records worth? How much could a GDPR or HIPAA fine be, and what is the risk?
Frequently, executives and managers do not understand the value of IG until there is a crisis, an expensive legal battle is lost, a heavy fine imposed for noncompliance, or executives go to jail.
There are some key outputs from implementing an IG program. A successful IG program should enable organizations to:
- Improve collaboration between business units. IG programs require cross-functional collaboration,so that IG team leaders can foster an environment of information sharing and leverage across the entire enterprise.
- Use common terms across the enterprise. This means that departments must agree on how they are going to classify document types, which relies on a cross-functional effort. With common enterprise terms, searches for information are more productive and complete. This begins with developing a standardized corporate taxonomy, which defines the terms (and substitute terms in a custom corporate thesaurus), document types, and their relationships in a hierarchy.
- Map information creation and usage. This effort can be buttressed with the use of technology tools such as data mapping, and data loss prevention (DLP), which can also be used to discover the flow of information within and outside of the enterprise. You must first determine who is accessing which information when, and where it is going. Then, these information flows can be monitored and analyzed. The goal is to stop the erosion or misuse of information assets, and to stem data breaches with monitoring and security technology.
- Comply with data protection regulations. Once a data map is created, organizations are better able to govern data, and to comply with requirements like digital subject access requests (dSAR) under GDPR.
- Obtain “information confidence.” That is, the assurance that information has integrity, validity, accuracy, and quality; this means being able to prove that the information is reliable, and its access, use, and storage meets compliance and legal demands.
- Harvest and leverage information. Using techniques and tools like business intelligence and advanced analytics (descriptive, diagnostic, predictive, prescriptive), new insights may be gained that provide an enterprise with a sustainable competitive advantage over the long term, since managers will have more and better information as a basis for business decisions.
- Monetize information. Applying infonomics principles and specific formulas can allow an organization to find real, tangible value in their information, which had not been capitalized upon before.
Summing Up the Differences
IG consists of the overarching polices and processes to optimize and leverage information, while controlling its access, keeping it secure, and meeting legal and privacy obligations, in alignment with stated organizational business objectives.
IT governance consists of following established frameworks and best practices to gain the most leverage and benefit out of IT investments and support accomplishment of business objectives.
Data governance is the execution and enforcement of authority over the definition, production, and usage of data, and consists of the processes, methods, and techniques to ensure that data at the root level is of high quality, reliable, and unique (not duplicated), so that downstream uses in reports and databases are more trusted and accurate.
- IG, IT governance, and data governance are all a subset of corporate governance.
- Data governance is the “execution and enforcement of authority over the definition, production and usage of data,” according to expert Bob Seiner.
- Data governance uses techniques like data cleansing and de-duplication to improve data and reduce redundancies.
- Good data governance ensures that downstream negative effects of poor data are avoided, and that subsequent reports, analyses, and conclusions are based on reliable, trusted data.
- IT governance seeks to align business objectives with IT strategy to deliver business value.
- COBIT2019 is process-oriented and has been widely adopted as an IT governance framework. Val IT is value-oriented and compatible and complementary with COBIT yet focuses on value delivery.
- ITIL is the “most widely accepted approach to IT service management in the world.”
- ISO 38500 is an international standard that provides high-level principles and guidance for senior executives and directors responsible for IT governance.
- Information governance is how an organization maintains security, complies with regulations, and laws, and meets ethical standards when managing information.
- According to the Sedona Conference, IG is about minimizing information risks and costs and maximizing information value.
- IG, in short, is “security, control, and optimization of information.”
- IG programs allow organizations to improve collaboration between business units; use common terms across the enterprise; map information creation and usage; comply with data protection regulations; obtain information confidence; harvest and leverage information; and monetize information, using infonomics principles and techniques.
 “Talking Data Governance with Thought Leader Bob Seiner,” Information Governance World, Fall issue, 2018, 58.
 “New Trends and Best Practices for Data Governance Success,” SearchDataManagement.com eBook, http://viewer.media.bitpipe.com/1216309501_94/1288990195_946/Talend_sDM_SO_32247_EBook_1104.pdf (accessed March 11, 2013).
M. N. Kooper, R. Maes, and E. E. O. Roos Lindgreen, “On the Governance of Information: Introducing a New Concept of Governance to Support the Management of Information,” International Journal of Information Management 31 (2011), 195–20, www.scribd.com/doc/63866742/On-the-Governance-of-Information.
 Nick Robinson, “The Many Faces of IT Governance: Crafting an IT Governance Architecture,” ISACA Journal 1(2007), www.isaca.org/Journal/Past-Issues/2007/Volume-1/Pages/The-Many-Faces-of-IT-Governance-Crafting-an-IT-Governance-Architecture.aspx.
 Bryn Phillips, IT Governance for CEOs and Members of the Board (CreateSpace Independent Publishing Platform, 2012), 18.
 Ibid., 26.
 “Control Objectives for Information and Related Technology (COBIT®) Internationally Accepted Gold Standard for IT Controls & Governance,” IBM Global Business Services—Public Sector, www-304.ibm.com/industries/publicsector/fileserve?contentid=187551 (accessed March 11, 2013).
 Bryn Phillips, 26.
 “Control Objectives for Information and Related Technology (COBIT®) Internationally Accepted Gold Standard for IT Controls & Governance,” IBM Global Business Services—Public Sector, http://www-304.ibm.com/industries/publicsector/fileserve?contentid=187551 (accessed March 11, 2013).
 www.itil-officialsite.com/AboutITIL/WhatisITIL.aspx (accessed March 12, 2013).
 www.naa.gov.au/records-management/agency/digital/digital-continuity/plan/information-governance.aspx (accessed March 12, 2013).
 Arvind Krishna, “Three Steps to Trusting Your Data in 2011,” CTO Edge, March 9, 2011, www.ctoedge.com/content/three-steps-trusting-your-data-2011.
 Robert S. Seiner, e-mail to author, July 24, 2018.