RWDG Slides: Master Data Governance in Action

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Copyright © 2020 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
#RWDG @RSeiner
Real-World Data Governance
Master Data Governance in Action
Monthly Webinar Series Hosted by DATAVERSITY
Robert S. Seiner – KIK Consulting / TDAN.com
November 19, 2020 – 11:00 a.m. PT / 2:00 p.m. ET

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#RWDG @RSeiner
Introduction
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#RWDG @RSeiner
• In the webinar I will share:
– What Makes It Master Data Governance
– Aligning Roles and Responsibilities with MDM
– Qualities of “Governed Data”
– Governing to a “Master” Version of the Truth
– Implementing Master Data Governance Domain by Domain
Abstract

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• Let’s Define Data Governance
• And Now Let’s Define Master Data
• Types of Data Governance
• Is There Such Thing as Master Data Governance?
• Does It Even Matter?
What Makes It Master Data Governance

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• Let’s Define Data Governance
– Data Governance is the execution and enforcement of authority over
the definition, production and usage of data and data-related assets.
(Seiner)

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• Other Definitions of Data Governance:
– The exercise of authority and control (planning, monitoring, and
enforcement) over the management of data assets. (DAMA)
– A system of decision rights and accountabilities for information-related
processes, executed according to agreed-upon models which describe
who can take what actions with what information, and when, under
what circumstances, using what methods.” (Data Governance Institute)
– Harmonization of people, process and technology to manage data.
– Orchestration of people, process and technology to manage data.

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– Master data is data about the business entities that provide context for
business transactions. (DAMA)
– Master Data are the business objects that contain the most valuable,
agreed upon information, shared across an organization.
(Dreibelbis, A.; Hechler, E.; Milman, I.; et al.)

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– Master data should be distinguished from Reference Data.
– While both provide context for business transactions, reference data is
concerned with classification and categorization, while master data is
concerned with business entities.
– Reference Data is often considered coded data that is either internally
or externally managed.
– Master data is, by its nature, almost always non-transactional.
– Commonly defined Master Data includes Parties, Products, Financial
Structures, and Locational Concepts. (Wikipedia)

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• Types of Data Governance
– There is one type of data governance. (Seiner)
– You can call it what you want … but there is only one. (Seiner)
– Depends on the data you are governing:
• Information Governance
• Master Data Governance
• Big Data Governance
• Metadata Governance
• Unstructured Data Governance
• Data Governance 2.0, 3.0 (4.0?), Next Generation Data Governance

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• Is there such a thing as Master Data Governance?
– Definition
– Roles
– Stewardship
– Metadata
– Process
– Metrics
– Tools
– Communications
EXECUTIVE
STRATEGIC
TACTICAL
OPERATIONAL
SUPPORT
Copyright © 2020 – Robert S. Seiner and KIK Consulting & Educational Services, LLC
Levels
Components
ROLES
COMMUNICATIONS
TOOLS
METRICS
PROCESSES
NON-INVASIVE DATA GOVERNANCE™ FRAMEWORK
DATA
LEVELS
EXECUTIVE – SENIOR LEADERSHIP TEAM
STRATEGIC – BUSINESS & TECHNOLOGY MGMT
TACTICAL – SUBJECT MATTER EXPERTISE
OPERATIONAL – DAILY JOB FUNCTION
SUPPORT – FUNCTIONAL MANAGEMENT
COMPONENTS
DATA – ASSETS BEING GOVERNED
ROLES – FORMAL ACCOUNTABILITY
PROCESSES – APPLICATION / ENFORCEMENT
COMMUNICATIONS – EDUC, TRN, AWARENESS
METRICS – MEASUREMENTS and KPIs
TOOLS – ARTIFACTS PURCHASED / DEVELOPED
Discussed in the
RWDG webinar in
May 2019

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• Does it even matter?
– I answer that question “No!” It does not matter.
– Name it in the way that makes you and your organization comfortable.
– You can refer to the governance of Master Data as MDG.
– Remember that all components are necessary.
– Be aware of the issues that can be caused by more than one DG.

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• Data Governance Roles and Responsibilities
• Master Data Roles and Responsibilities
• Similarities Between the Two
• Difference Between the Two
• Why It Matters
Aligning Roles and Responsibilities with MDM

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• Data Governance Roles and Responsibilities
– Executive Level – Management / Steering Committees
– Strategic Level – Council – Data / Data Governance / Data Strategy
– Tactical Level – Data Domain Stewards / Subject Matter Experts
– Operational Level – Data Stewards
– Support Level – Data Governance Partners / Working Teams
– Administrative Level – Program Administrator / Lead / Manager

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Discussed in the
RWDG webinar in
August 2020

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• Master Data Roles and Responsibilities
– Tactical Level – Master Data Domain Stewards / Subject Matter Experts
– Support Level – Information Technology, IT Partners
• It is not considered industry best practice to have a separate set of roles
and responsibilities for Master Data.

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• Similarities Between the Two
– Executive Level – Management / Steering Committees (same)
– Strategic Level – Council – Data / Data Governance / Data Strategy (same)
– Tactical Level – (Master) Data Domain Stewards / Subject Matter Experts
– Operational Level – Data Stewards (same)
– Support Level – Data Governance Partners / IT Partners
– Administrative Level – Program Administrator / Lead / Manager (same)

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• Difference Between the Two
– Tactical Level – Master Data Domain Stewards / Subject Matter Experts
– Support Level – Data Governance Partners / IT Partners / Working Teams
• If it is necessary, draw a distinction between a Master Data Domain Steward
and other Data Domain Stewards. This is not a recommendation.

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• Why It Matters
– Want your program to answer more questions than you raise.
– Focus first on a single set of roles and responsibilities.
– Define Master Data subject areas.
– Determine who the Owners (bleh!) of the Master Data are.
– Determine the authorities for the Master Data.

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• Difference Between Governed and Ungoverned Data
• Dimensions of Data Quality
• Measuring the Impact of Governed Data
• Measuring the Impact of Ungoverned Data
• Effectively Communicating the Impact
Qualities of “Governed Data”

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• Difference Between Governed and Ungoverned Data
– Governed
• Formally owned
• Formally defined
• Metadata available
• Quality assured
• Certified
• Confidence
– Ungoverned
• Not formally owned
• Definition not collected
• Metadata not available
• Quality is what it is
• Uncertified
• Uncertainty

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– Completeness: Are all the pertinent fields filled?
– Validity: Do all the values conform?
– Accuracy: Does the data reflect a real-world person or object?
– Consistency: Does the data align with understood patterns?
– Uniqueness: Are there duplicate instances?
– Timeliness: Is it up-to-date?
Amber Lee Dennis (Dataversity) – November 2019

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– Completeness
– Consistency
– Conformity
– Accuracy
– Integrity
– Timeliness
Smartbridge.com – Data Done Right: 6 Dimensions of Data Quality

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– Ability to Measure Quality Per Quality Dimensions
– Time to Prepare Data for Analysis
– Time to Request and Gain Access to Data
– Ability to Address Data Opportunities (requires further definition)
– Reduction in Data Incidents (requires further definition)

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– Usage of Data Analytics
• Data collected by Salespeople that lead to closed sales
• Data collected by Engineers that lead to improved product info
• Data collected by the organization leading to improved performance
• Data integrated by the organization to make decisions
– Data they knew could be integrated
– Data they had not recognized could be integrated
• ……………………… (fill in the blank) ……………………………..

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– Inability to Standardize Data
– Inability to Measure Data Quality
– Time to Manipulate Data for Analysis
– Inability to Address Data Opportunities
– Inability to Log Data Incidents

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– Inability to Use of Data Analytics to Analyze …
• Salespeople data that lead to closed sales
• Engineer data that lead to improved product info
• Performance based on master data analysis
• Or Integrate data to make decisions
– Data they knew could be integrated
– Data they had not recognized could be integrated
• ……………………… (fill in the blank) ……………………………..

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• Effectively Communicating the Impact
– Work with someone (if available) from Corporate Communications to
shape the messaging to maximize consumption.
– Utilize communications tools to maximize socialization and acceptance.
– Questions to Convince Stakeholders Importance of Governed Data
• What can’t you do because you don’t have the data, or do not have
confidence in the data enough, to do it?
• What could you do if you had the data, and the confidence in the
data, to do it?

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• How a Master Version is Valuable
• Getting to a Single Point of Truth
• More Than One Version of the Truth
• Impact of Data Governance on Master Data
• Measuring the Investment in Master Data and Data Governance
Governing to a “Master” Version of the Truth

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– Single Point of Truth – “The Golden Record”
– Data that is “Fit for Purpose”
– Data that is “Certified”
– Valuable Because it is Standardized, Accurate, Stewarded, Consistent
– The data that people can rely on because it has been governed.

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– Single Point of Truth – “The Golden Record”
– Data that is “Fit for Purpose”
– Data that is “Certified”
– Valuable Because it is Standardized, Accurate, Stewarded, Consistent
– The data that people can rely on because it has been governed.
Can data be Master Data if it is ungoverned?
Should the word “governed” be included
in the definition of Master Data?

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• Getting to a Single Point of Truth
– Define Master Data Domains (Subject Areas)
• These may already be defined.
– Utilize Governance Roles & Responsibilities
– Define Ownership (bleh!) and Stewardship of the Data
– Create Working Teams to Focus on Domains
– Naturally Recognize Master Data Domain Stewards
– Define (Repeatable) Processes for Standardizing Data Domains
– Define Standards for Domain Data

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• More Than One Version of the Truth
– The answer to the question that is asked/analysis performed …
• Depends on who you ask.
• Depends on what data they use.
• Depends on availability of, and access to, the data.
• Depends on their understanding of the data.
• Depends on the analyst/requestor/receiver confidence in the data.
– Data Governance provides information to improve outcomes.

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• Impact of Data Governance on (Master) Data
– Improves (master) data accountability.
– Improves (master) data definition.
– Improves (master) data production.
– Improves (master) data usage.
– Improves (master) data confidence.
– Improves (master) data value.

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• Measuring the Investment in Master Data and Data Governance
– Master Data
• People
• Process
• Technology
– Data Governance
• People
• Process
• Technology
ROI must be in terms of Business Outcomes.

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• Definition of a Data Domain
• Other Names for Data Domains
• Incremental Delivery of Master Data
• Incremental Delivery of Data Governance
• Upside and Downside of Incremental Delivery
Implementing Master Data Governance Domain by Domain

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• Definition of a Data Domain
– Clarify what YOUR organization means by Data Domain.
– Data Subject Area = Data Domain for purposes of this discussion.
– Break the domains into sub-domains, sub-sub-domains -> CDEs
– Common Data Domains
• Customer
• Product
• Vendor
• Part
.
• Employee
• Location
• Material
• Party ???

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• Other Names for Data Domains
– Subject Areas
– Categories
– Business Areas / Lines of Business
– Business Functions / Operating Areas
– Themes, Dominions, …
– Master Data ……………………………….

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• Incremental Delivery of Master Data
– Start with a slice of the pie
– Eat the elephant one bite at a time
– Learn from experience
– Improve with every iteration
– Achieve a “Master” version
• Principal version
• Controlled version
• Guru version

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• Incremental Delivery of Data Governance
– Validated roles & responsibilities through MDM
– Recognized participants into Roles through MDM
– Vetted, validated and repeatable Processes through MDM
– Improvements in confidence in the Data through MDM
– Improvements in all the other core components of DG framework
• Communications
• Metrics
• Tools
EXECUTIVE
STRATEGIC
TACTICAL
OPERATIONAL
SUPPORT
Copyright © 2020 – Robert S. Seiner and KIK Consulting & Educational Services, LLC
Levels
Components
ROLES
COMMUNICATIONS
TOOLS
METRICS
PROCESSES
NON-INVASIVE DATA GOVERNANCE™ FRAMEWORK
DATA
LEVELS
EXECUTIVE – SENIOR LEADERSHIP TEAM
STRATEGIC – BUSINESS & TECHNOLOGY MGMT
TACTICAL – SUBJECT MATTER EXPERTISE
OPERATIONAL – DAILY JOB FUNCTION
SUPPORT – FUNCTIONAL MANAGEMENT
COMPONENTS
DATA – ASSETS BEING GOVERNED
ROLES – FORMAL ACCOUNTABILITY
PROCESSES – APPLICATION / ENFORCEMENT
COMMUNICATIONS – EDUC, TRN, AWARENESS
METRICS – MEASUREMENTS and KPIs
TOOLS – ARTIFACTS PURCHASED / DEVELOPED

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– Downside
• Proof of value requires patience
• Takes an extended period of time
• Requires management commitment
• Agile is not always effective for Master Data

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– Upside
• Improve Master Data efficiency
• Improve Master Data effectiveness
• Build repeatable processes
• Build up subject matter expertise
• Build confidence in Master Data

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#RWDG @RSeiner
• In the webinar I shared:
– What Makes It Master Data Governance
– Aligning Roles and Responsibilities with MDM
– Qualities of “Governed Data”
– Governing to a “Master” Version of the Truth
– Implementing Master Data Governance Domain by Domain
Summary

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#RWDG @RSeiner
Questions and Answers
Q & A

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#RWDG @RSeiner
• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
412.220.9643 rseiner@tdan.com @RSeiner
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RWDG Slides: Master Data Governance in Action

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