Real-World Data Governance: Data Governance Policy - Components and Content

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Copyright © 2012 Robert S. Seiner– KIK Consulting & Educational Services /TDAN.com
Non-Invasive Data Governance™
is a trademark of Robert S.Seiner & KIK Consulting
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Copyright © 2014 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
is a trademark of Robert S. Seiner & KIK Consulting
#RWDG @RSeiner
Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Real-World Data Governance
Data Governance Policy:
Components and Content
Monthly Webinar Series Hosted by Dataversity
Robert S. Seiner – KIK Consulting / TDAN.com
June 19, 2014 – 2:00 p.m. EST

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• Real-World Data Governance – Monthly Webinar Series
– Third Thursday of Each Month – 2pm EST
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Real-WorldData Governance
Upcoming Webinars

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Data Governance Policy
Session Abstract
• This webinar will focus on the following:
– Is a Policy Necessary to Guide Appropriate& Formal Behavior?
– Data Governance Definition / What Does It Mean to Govern
– Policy Components
– Policy Content
– Policy Principles & Dimensions
– Tools Associated with Principles
– Defining "Enterprise"in Termsof Data Governance Policy
– Gaining Approval of an Data Governance Policy

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Considerations
• First … Let’s consider these questions:
– Does our Organization Require a Policy?
– Are there Similar Policies that we can use as a Model?
– Who is the Audience for the Policy?
– Who will have the Responsibilityfor Approving the Policy?
– Who will have the Responsibilityfor Enforcing the Policy?
– How will we Communicate the Policy?

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“The Graphic”
Copyright © 2012 – Robert S.Seiner – KIK Consulting & Educational Services, LLC
Used by Permission Only

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Definitions

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• Policy
– A plan of action adopted or pursued by an individual, government,
party, business, etc.
– A course of action, guiding principle, or procedure considered
expedient, prudent, or advantageous.
FreeDictionary.Com
Policy Definitions

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• Data Governance
– Data Governance is the Execution and Enforcement of Authority
Over the Management of Data and Data-Related Resources.
Robert S. Seiner
• Data Stewardship
– Data Stewardship is the Formalization of Accountability Over the
Management of Data and Data-Related Resources.
Robert S. Seiner
Recent ClientDefinitions
Formalization of behavior around the definition, production
and usage of data to manage risk and improve quality and
usability of selecteddata.
Formalization and guidance for behavior over the definition,
production and use of information and information related
assets.
Policy Definitions

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• Non-Invasive Data Governance™
– The practice of:
• applying formal accountability & behavior
• through non-invasive roles & responsibilities
• to existing and / or new processes
• to assure that the definition, production & usage of data
• assures regulatory compliance, security, privacy, protection & quality.
– Non-Invasive describes how governance is appliedto assure
non-threatening management of valuable data assets.
– The goal is to be transparent, supportive, collaborative.
Policy Definitions

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What It Means to “Govern Data”
• [to] gov·ern [data]
v. gov·erned, gov·ern·ing, gov·erns
– To make and administer the public policy and affairs [of data]
– To exercise sovereign authority [in data]
– To control the speed or magnitude [of data]
– To regulate [data]
– To control the actions or behavior [of data]
– To keep under control [data]; to restrain [data]
– To exercise a deciding or determining influence [on data]
– To exercise political authority [over data]
– To have or exercise a determining influence [over data]
FreeDictionary.com [Bob Seiner]

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Components

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• Components of a Data Governance Policy
– Introduction
– Policy Statement
– Data Governance Principles
– Data Governance Dimensions
– Data Governance Glossary
– Data Governance Roles & Responsibilities
Policy Structure

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• Introduction
– Purpose
• The Data Governance Policy is designed to manage the creation,
transformation, and usage of data and related information owned
by or in the care of Company.
• This policy will direct the development of common data definitions,
standards, requirements and processes; enforce lines of authority;
and assure that the Data Governance Policy Principles defined in
this document and the associated frameworkis fully implemented.
Policy Structure

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• Introduction
– Scope
• This policy applies to all employees, contractors, temporary
employees, consultants, and authorized agents of the Company.
Throughout this policy, the word "users" will be used to collectively
refer to all such individuals. Adhering to the Data Governance
Policy is the corporate responsibilityof everyone.
• This policy applies to all data that is managed as an internal asset to
Company. Data that is defined, produced and managed by the
parent company, including Human Resource data, is not in scope
for the Data Governance Program.
Policy Structure

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• Introduction
– Violations
• Data and informationis a critical component of Company business.
• All usersmust maintain the quality and integrity of these resources.
• Violations of this policy may be considered serious breaches of
trust, which can result in disciplinary action up to and including
termination of employment or contract and prosecution in
accordance with applicable federal, state, and local laws.
Policy Structure

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• Data Governance Policy
– How Data Governance Is Implemented
• Data Governance Principles
– How Data Governance Is Defined
• Data Governance Dimensions
– How Data Governance Is Measured
Policy Structure

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• Data Governance Policy – How Data Governance Is Implemented
– It is the policy of Company to require that all data defined, produced
and used by or in the care of Company be governed as a corporate asset
through defined data governance standardsand procedures.
– It is the policy of Company that Data Governance will be applied
consistently to Enterprise Strategic Data, Master Data and Transactional
Data. For definitions of these terms please refer to the Glossary section
of this Policy document.
Policy Structure

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• Data Governance Policy – How Data Governance Is Implemented
– This Data Governance Policy is broken into four Data Governance
Principles that are measured by the Data Governance Dimensions as
represented on “The Graphic”.
Policy Structure

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“The Graphic”

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Content

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• Data Governance Principles– How Data Governance Is Defined
• Principle 1: From “MY” Data to “OUR” Data
– Data is a valuable strategic asset to Company and shall be managed accordingly.
Rationale:
– Data is a valuable corporate resource; it has real, measurable value. In simple
terms, data drives decision making. Accurate, timely data is the critical
foundation for effective decision making and customer service at Company.
Implications:
– Data must be carefully managed to ensure it is clearly defined, properly
accessed, and appropriately controlled. Company management and staff must
be able to rely upon its accuracy and be able to obtain it when and where it is
needed.
Data Governance Principles

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• Principle 2: Data is Everyone’s Responsibility
– Data shall be shared, secured, and accessed as appropriate and allowed.
Rationale:
– Most data has value to the organization beyond the uses of any one specific
application. Company requires that data be shared and integrated at the
Enterprise level, consistent with information security and privacy policies (see
relevant policies).
– Data must be well defined to be sharable. Enterprise shareable data must be
defined consistently across the Enterprise, with understood definitions available
to all users.
– Wide access to data leads to efficiency and effectiveness in decision-making and
provides timely response to information requests and service delivery.

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Implications:
– Shared data will result in improved decisions. It is less costly to maintain a single
source of timely accurate data than to continue to maintain several sources of
data that are not unique. Data will be better aligned with cross-business
requirements, syntactic and semantic differences between databases will be
minimized and applications will be more portable. Additionally, Data
Management can change the data environment based on changing requirements
or conditions with a minimal impact to the applications.
– Data must be protected from unauthorized use and disclosure. Processes,
procedures and automated methods will be used to ensure the security of Data.

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Implications:
– Access to data should be performed through appropriately defined interfaces to
ensure the proper understanding and use of the data.
– To enable data sharing, the Data Governance Team with the cooperation of the
Data Domain Stewards and the Business Areas must develop, abide by, and
communicate a common set of definitions, policies, and standards. Common
data definitions are the foundation for systems interfaces and data exchanges.
A common vocabulary will increase the value of the definitions.

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• Principle 3: Avoid Risk and Compliance Issues
– Data shall have clearly defined accountability and shall be defined and managed
consistently according to relevant regulations.
• Rationale:
– Current legislation and regulations require the safeguarding, security and privacy
of personally identifiable information.
– Open data sharing, managed accessibility and the release of data and
information must be balanced against the need to restrict the availability of
restricted, proprietary or sensitive information.
– Data Owners, in the role of Data Domain Stewards, are accountable for data
quality, definition, security, privacy, standardization, appropriate use of data in
their domain.

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• Principle 3: Avoid Risk and Compliance Issues
– Data shall have clearly defined accountability and shall be defined and managed
consistently according to relevant regulations.
• Implications:
– To improve the quality and value of data, and to avoid risk and compliance
issues, accountability and rules for the definition, production and use of the data
must be recorded, managed and communicated.
– The Data Governance Team must be responsible for recording and
communicating information about individual’s accountabilities across the
company.
– The Data Governance Team must work with the business areas to assure that the
relevant regulations are documented and communicated to impacted Areas.

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• Principle 4: Right the First Time, Every Time
– The quality of Data will be recorded, measured and reported to assure that data
will be trusted for business processes and decision making.
• Rationale:
– The quality standards for data must be well defined to be able to identify record,
measure and report the quality of the data.
– The quality standards will focus on measuring business process and decision
making improvements from complete, relevant and unique data.
– Enterprise critical data must be tested against the standards consistently across
the Enterprise, with understood standards available to all definers, producers
and users.
– Data Owners, in the role of Domain Stewards, are accountable for data standard
definitions and appropriate use of the standards for data in their domain.

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• Principle 4: Right the First Time, Every Time
– The quality of Data will be recorded, measured and reported to assure that data
will be trusted for business processes and decision making.
• Implications:
– To improve data quality, the Data Governance Team with the cooperation of the
Data Domain Stewards and the Business Areas must develop, abide by, and
communicate a common set of standards.
– Common data standards are the foundation for quality systems interfaces and
data use. A common place to record data standards will increase ability to
improve the quality of the data.

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• Data Governance Dimensions– How Data Governance Is Measured
• The following Data Governance Dimensions have been defined as a way to
measure the governance of data.
– Accessibility – Data accessibility will be defined and managed in
accordance with appropriate Business Rules for access and local and
Federal Rules and Regulations.
– Accuracy – Data should correctly reflect the real world object or an
event being described to enable informeddecision-makingat all levels.
– Completeness – All expected, mandatory attributes of data should be
provided.
– Consistency – Data across the Company should be in synch.
Data Governance Dimensions

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• Data Governance Dimensions– How Data Governance Is Measured
• The following Data Governance Dimensions have been defined as a way to
measure the governance of data.
– Relevance (Non-Obsolete) – Data managed as an asset must be relevant
to the business and retired when obsolete.
– Timeliness – Data should be up-to-date, produced in a timely manner
and appropriate for the task at hand to support informationneeds.
– Uniqueness– Duplicate data should be avoided (or managed).
Data Governance Dimensions

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Tools Associated with Principles

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• Messages for Management:
– We are already governing data (but we are doing it informally).
– We can formalizehow we govern data by putting
structure around what we are presently doing.
– We CAN Improve:
• How We Manage Data Risk& Secure/Protect Data
• Data Quality & Provide Quality Assurance
• Coordination, Cooperation, CommunicationAround Data
Principle 1 Tool: Data as an Asset

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• Messages for Management:
– We DO NOT Have to Spend A Lot of Money.
In fact … Data Governance only costs the time we put into it.
– We need structure.
We should consider a Non-Invasive approach.

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• What We Should Not Tell Management:
– Do NOT Sell Data Governance as being A HUGE CHALLENGE.
– Emphasizethat Data Governance is NOT A TECHNICAL SOLUTION.
– Emphasizeagain that PEOPLE BEHAVIOR IS GOVERNED, Not Data.
– Emphasizethat Data Governance is an EVOLUTION, NOT REVOLUTION.

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Operational Level
Operational Data Stewards (existing)
Data Definers, Producers, Users
These people are presently defining,
producing and using data as part of their
jobs. Recording of the Operational Data
Stewards will be an important enabler of
improved communications, coordination
and cooperation among stewards.
Tactical Level
Data Domain Stewards
Per assigned Subject Areas
Data Steward Coordinators
One per Business Unit
Strategic Level
Data Governance Council
Data Governance Sponsors Group
or Group of similar participation. One person, plus
alternate, for each Business Unit represented & IT.
Consider financial services & human resources.
Executive Level
Data Steering Committee
Senior-most level knowledge of the program.
Leverage existing business structure as possible.
If no structure exists, utilize an IT Steering Committee
or an executive founded board or council.
Operational Level - Business Unit Specific
Strategic -
Enterprise
Tactical Level - Cross Business Unit
Executive
“Non-Invasive Data Governance”™ Operating Model
of Roles & Responsibilities
Escalation
/ApprovalPath
Copyright © 2009 - Robert S. Seiner - KIK Consulting & Educational Services, LLC - All Rights Reserved
Data
Governance
Program
Team
(DGPT)
IT
SubjectResource
Experts
Data Governance Program Team
Data Governance Team Manager
Responsible for Administering the Program,
facilitating use of the Data Governance Council,
communicating program components and value to the Organization.
Advisory assistance from other levels.
IT Subject Resource Experts
System/Data Resource Experts
IT Staff including Application
Development, Data Design,
Security, and other Data
Resource Management.
Com
m
unication
KIK Consulting & Educational Services, LLC
EXI
STS
EXIS
TS
EXI
STS
NE
W
LEVE
RAGENE
W
Principle 2 Tool: Clearly Defined Accountability

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Principle 2 Tool: Clearly Defined Accountability

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Principle 3 Tool: Follow Rules

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Principle 4 Tool: Consistent Application

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“The Graphic”

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• Data Governance Policy Statement – Revisited
– It is the policy of Company to require that all data defined, produced
and used by or in the care of Company be governed as a corporate asset
through defined data governance standardsand procedures.
– It is the policy of Company that Data Governance will be applied
consistently to Enterprise Strategic Data, Master Data and Transactional
Data. For definitions of these terms please refer to the Glossary section
of this Policy document.
• Is Company the Entire Company – A Part of the Company – A Business Unit?
Enterprise Policy

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• Data Governance Policy Approval Steps
Enterprise Policy
Data Governance
Executive Steering
Committee
Data Governance
Council
Data Governance
Program Team
FeedbackLoop

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• Data Governance Policy Approval Steps
– This review, feedback and update loop repeats until the Data Governance
Council gives final approval to the component.
– The DGT presents the Council-approved component to the Executive Steering
Committee for approval.
– The Steering Committee reviews the program component and provides feedback
to the DGT. The DGT, working with Data Governance Council representatives,
incorporates the feedback into the component.
– This review, feedback and update loop repeats until the Executive Steering
Committee gives final approval to the component of the Data Governance
Program.
Enterprise Policy

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Wrap Up
& Discussion
• Final Summary:
 Is a Policy Necessary to Guide Appropriate & Formal Behavior?
 Data Governance Definition / What Does It Mean to Govern
 Policy Components
 Policy Content
 Policy Principles & Dimensions
 Tools Associated with Principles
 Defining "Enterprise" in Terms of Data Governance Policy
 Gaining Approval of an Data Governance Policy

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• Real-World Data Governance – Monthly Webinar Series – 2pm EST
– July 17, 2014 – Metadata to Empower Data Stewards *
– Register On-Line at DATAVERSITY.Net * with guest
Upcoming Webinars

4646
#RWDG @RSeiner
• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643,412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com
@RSeiner
#RWDG
Contact Information

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