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Real-World Data Governance: Setting Appropriate Business Expectations
- 1. Real-World Data Governance
Setting Appropriate Business Expectations
Monthly Webinar Series Hosted by Dataversity
Robert S. Seiner – KIK Consulting / TDAN.com
June 21, 2012 – 2:00 p.m. EST
Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
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- 2. Setting Appropriate Business Expectations
Upcoming Webinars
• Real-World Data Governance – Monthly Webinar Series
– July 19, 2012 – Meta-Data & Data Governance – 2pm EST
– August 16, 2012 – Master Data Management & Data Governance – 2pm EST
– September 20, 2012 – Business Glossaries & Data Governance – 2pm EST
– Register On-Line at Dataversity.Net
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- 3. Setting Appropriate Business Expectations
Abstract
• Organizations define Data Governance program success in different ways.
• For one organization success will be determined by the number of data
quality issues resolved or the improvements in quality of data.
• For another, success will be measured in the ability of the organization to
comply with rules and regulations, whether those rules are defined
internally or externally.
• For even another, success will be determined by the ability to provide
analytics that drive business decisions, or by the ability to manage data
development and integration projects smoothly.
• This list can go on and on.
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- 4. Setting Appropriate Business Expectations
Abstract
• Before an organization can claim Data Governance success, it is necessary
for the Data Governance Team (those people responsible for the program)
to level set with the business participants and sponsors and define
effective expectations.
• These expectations should be expanded beyond traditional business value
to include what “governing data” means to the organization and the effort
that will be required to achieve that business value. Setting and
communicating business expectations, and delivering on those
expectations, will provide an avenue to deliver success in governing data.
• Join Bob Seiner and DATAVERSITY for the sixth in a series of Data
Governance webinars titled “Real World Data Governance” where Bob will
discuss how to level-set business expectations in the real-world with the
approach and capabilities of your Data Governance program.
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- 5. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• [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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- 6. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• Articulate Expectations in Terms of:
– Existing Levels of Data Governance That Can Be Directly Applied
– Staying Non-Invasive in Your Approach to Governing Data
– The Technical Complexities of Governing Data
– The Process Complexities of Governing Data
– The Ownership Complexities of Governing Data
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- 7. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• Top Avoidable Mistakes (in no specific order) :
– Lack of Executive & Strategic Level Understanding & Support
– Lack of Program Accountability & Responsibility
– Lack of Definition of Best Practices as a Target Behavior
– Lack of Critical Analysis of Present Environment
– Inability to Select & Follow Suitable Approach
– Lack of Planning and Ability to Support Meaningful Initiatives
– Framework of Roles & Responsibilities
– Making Data Governance & Data Quality Optional
– Lack of Focus on Communications
– Improper Expectations of the Data Quality & Data Governance Solution
– Failure to Stay Iterative and Incremental in the Approach
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- 8. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• In What Areas Should We Set Expectations:
– Data Governance Basics
• Definition of Data
• Production of Data
• Usage of Data
– Risk Management
• Compliance & Regulatory Control
• Data Classification
• Security
– Disciplines
• Issue Resolution
• Quality Control & Improvement
• Proactive & Reactive Governing of Data
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- 9. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• In What Areas Should We Set Expectations:
– Roles & Responsibilities
• Executive & Strategic
• Tactical
• Support (DGT & IT)
– Communications Planning
• Audience
• Messages
• Delivery Tools
– Governance
• Process / Technology Governance
• Stewardship / Ownership
• Execution & Enforcement
• Monitoring & Reporting
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- 10. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• The Burning Questions:
– What / Where should we expect to see (as) benefits from Data Governance?
– What is the work effort that will be required to achieve the benefit?
– How will we measure the benefit of Data Governance?
– What should / shouldn’t we tell Management about Data Governance?
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- 11. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• Concepts of Non-Invasive Data Governance™ – Overview
– Data Governance Programs are often perceived as being “invasive” and “over-
and-above” the existing work culture of an organization.
– Follow the necessary steps to eliminate that perception.
– Take a “practical” and “pragmatic” approach to implementing Data Governance
and Data Stewardship that follows several key concepts.
– Use the key concepts as a starting point and basis for the “selling” and
“understanding” of your Data Governance and Data Stewardship programs.
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- 12. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• Concepts of Non-Invasive Data Governance™
– Do Not give employees new job titles and recognize that the majority of their
present work will not change.
– Data Stewards are Not hired.
Data Stewards Are identified & engaged according to their present responsibilities.
– A Data Steward is Not a position.
Becoming a Data Steward Is an accountability for the management of a subset of
enterprise data.
– The Data Stewardship process will Not create new tasks or time commitments but
instead will ensure that the appropriate Data Stewards are identified, engaged in
each data related task.
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- 13. Setting Appropriate Business Expectations
Considerations for Setting Expectations
• Concepts of Non-Invasive Data Governance™
– Data Stewards Will Not be given additional work over and above their present
responsibilities.
– Present responsibilities related to data management Will be formalized &
recorded to ensure consistent and complete involvement of the appropriate data
stewards.
– The time commitment of each Data Steward will depend on the number of
projects and data issues which impact their area of expertise.
– Data Stewards will be provided the knowledge, tools, forums and processes to
become more effective and more efficient data managers.
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- 14. Setting Appropriate Business Expectations
Messages for Management
• What We Should Tell Management About Data Governance
– We ARE already governing data (but we are doing it informally).
– We CAN formalize how we govern data by putting structure around what we are
presently doing.
– We CAN Improve.
– We DO NOT Have to Spend A Lot of Money.
– We NEED structure.
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- 15. Setting Appropriate Business Expectations
Messages for Management
• What We Should Not Tell Management About Data Governance
– Do NOT Sell Data Governance as being A HUGE CHALLENGE.
– Emphasize that Data Governance is NOT A TECHNICAL SOLUTION.
– Emphasize again that PEOPLE BEHAVIOR IS GOVERNED, Not Data.
– Emphasize that Data Governance is an EVOLUTION, NOT REVOLUTION.
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- 16. Setting Appropriate Business Expectations
Messages for Management
1. We ARE already governing data (but we are doing it informally).
– There are already people in the organization that have responsibility for data.
– We should inventory who does what with the data and provide an operating
model of roles and responsibilities that best suits our organization.
– At some level, there will need to be somebody that has an enterprise view and
responsibility for data that cuts across the silos and manage data as a shared
resource.
– This will be our biggest challenge because it is not natural for us to manage data
as a shared and enterprise resource.
– A challenge but a "do-able" challenge nonetheless.
Should Tell Management
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- 17. Setting Appropriate Business Expectations
Messages for Management
2. We CAN formalize how we govern data by putting structure around what
we are presently doing.
– There are people in our organization in operational, tactical, strategic and
support roles around data.
– We need to know who they are and put formal structure around who is
responsible, accountable, consulted and informed about the business rules and
regulations associated with the data they define, produce and use.
Should Tell Management
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- 18. Setting Appropriate Business Expectations
Messages for Management
3. We CAN Improve.
– Our Data Governance efforts can help us to improve how we manage risks
associated with compliance, classification, security, business rules ... of our data.
– People of our organization potentially put us at risk every day when they are not
assured of knowing the rules associated with the handling of data.
– Our efforts to improve the quality of data must be coordinated and cooperative
across business units using the formal structure mentioned above.
– Quality assurance requires that operational and tactical staff have the ability to
record, track and resolve known data quality issues.
– Our organization can immediately improve how we communicate about data
through recording and sharing information about who does what with data.
Should Tell Management
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- 19. Setting Appropriate Business Expectations
Messages for Management
4. We DO NOT Have to Spend A Lot of Money.
– Data Governance is not a costly endeavor.
– Depending on the approach we take, Data Governance should only cost the time
we put into it.
– Certainly Data Governance will require that an individual(s) spend the time
defining and administering the Program, but there is large misconception that
Data Governance must be over-and-above the existing work efforts of the
organization.
– We should avoid calling things "Data Governance processes" because that gives
people the impression that formal behavior around data definition, production
and usage of data is the fault of data governance rather than the glue that
assures these behaviors are handled properly.
Should Tell Management
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- 20. Setting Appropriate Business Expectations
Messages for Management
5. We NEED structure.
– We should consider the “Non-Invasive Data Governance”™ Approach.
– We must follow a proven approach to Data Governance that is not threatening
to the people of our organization that will participate in the program.
– Data Governance will require that both the business and the technology areas of
the organization take formal and shared accountability for how data is governed.
– The participants in the Data Governance Program already have "day jobs" and
we must add value, not interfere, with what they do as their daily jobs.
– The goal of "Non-Invasive Data Governance"™ is to be transparent, supportive
and collaborative.
– These concepts lie at the heart of the implementation of the "Non-Invasive Data
Governance"™ approach.
Should Tell Management
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- 21. Setting Appropriate Business Expectations
Messages for Management
6. Do NOT Sell Data Governance as being A HUGE CHALLENGE.
– If your management already thinks that Data Governance will be a big challenge,
try to calm their nerves by referring to the first five messages. Data Governance
can be implemented in a non-threatening, non-interfering, non-culture changing
… dare I say – “Non-Invasive” way that will reduce the challenge significantly.
– Data Governance doesn’t have to be implemented all at once. In fact, most
successful organizations (data governance-wise) implement their programs
incrementally – incrementally in 1) the scope of the data that is governed
(domain-wise and organizationally) and/or 2) the level of governance (formal
behavior) that is applied to that data. See #9 for further thoughts on this.
Should Not Tell Management
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- 22. Setting Appropriate Business Expectations
Messages for Management
7. Emphasize that Data Governance is NOT A TECHNICAL SOLUTION.
– There will likely be a technical component to your Data Governance program.
But then again, there might not be. Most people agree that you cannot purchase
software or hardware that will BE your Data Governance solution. And most
people will agree that simple tools can be developed (i.e., the KIK's Common
Data Matrix) internally to help organizations govern people's behaviors (see #8).
– Technology can assist in formalizing people’s behavior. Data only behaves the
way people behave. Therefore, technology may help you to govern the
behaviors of people, but it won’t – by itself – govern the data.
Should Not Tell Management
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- 23. Setting Appropriate Business Expectations
Messages for Management
8. Emphasize again that PEOPLE BEHAVIOR IS GOVERNED, Not Data.
– Data Governance is typically about formalizing the behavior of people for the
definition, production and usage of data. Formalizing people’s behavior, not
data. Data only behaves the way people behave. Therefore, technology may help
you to govern the behaviors of people, but the data does what it’s told.
– Since it is people's behavior that is governed, many organizations consider Data
Governance to be a process-driven discipline. That is partially true. Getting
people to do the right thing at the right time is a big part of governance;
however, organizations that "sell" data governance as all new "governance"
processes struggle because of the inherent (viewed) invasiveness of that
approach. Governance should formalize behavior around existing processes first,
and only add to people's workloads as a last resort.
Should Not Tell Management
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- 24. Setting Appropriate Business Expectations
Messages for Management
9. Emphasize that Data Governance is an EVOLUTION, NOT REVOLUTION.
– As was stated earlier, Data Governance will not be completed all at one time.
There are a few different ways that organizations transition themselves into a
Data Governance state.
– Some organizations focus early on specific domains or subject areas of data.
Some organizations focus on specific business areas, divisions, units,
applications, rather than implementing all across the organization at once. Some
organizations focus on a combination of the two or three, specific domains
within specific business units using specific applications. There is no single
correct way to evolve into your company. But I can almost assure you that if you
treat it as a revolution, there will be a revolt.
Should Not Tell Management
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- 25. Setting Appropriate Business Expectations
Where Should We Expect to See Benefit?
• Questions to Get the Business to Describe Where to Expect Value:
1. What data / information do you use most often to achieve your objectives?
2. What is the primary source / system used by your area to obtain the data /
information? Who do go to get information about this source / system / data /
information?
3. What processes consume the data / information?
4. Do these processes have data / information challenges? If so, what are they?
5. What is the product or customer impact? How has this been tracked or
measured?
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- 26. Setting Appropriate Business Expectations
Where Should We Expect to See Benefit?
• Questions to Get the Business to Describe Where to Expect Value:
6. Is there an associated risk – brand, compliance, legal, etc?
7. What is the operational impact (e.g. money, FTEs, manual work-around, etc) of
the challenges? Have you tracked or quantified these impacts?
8. What other impacts should be noted?
9. Have you identified potential solutions? If so, what is the status of these
solutions – Scoped, Funded, Planned, In-Flight, etc?
10. What data / information is on your “wish list” that would better enable your
area to deliver on our Core Competencies?
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- 27. Setting Appropriate Business Expectations
Where Should We Expect to See Benefit?
• Inconsistencies in the definition, production and use of specific critical pieces of
data across the company prevent the ability to:
– Compare costs across regions – Compare raw material usage across regions, plants
– Identify the best place to get alternate or substitute materials – Fully plan for and leverage material use
– Provide sophisticated ad-hoc cross-company analysis – Identify where raw materials are used globally
– Leverage capacity and material use – Identify which raw materials can be substituted for
– Manage planning for supply chain and demand globally other raw materials
– Reduce overall investment in capital improvements – Compare data across regions, plants, … for planning,
development and delivery purposes
– Target areas where cross-company comparisons will add the most value
– Identify where to build new plants to address customer
– Formally decide the best approach to build consistency in that data
needs
– Complete the process of building consistency in the data
– Clearly define global data owners or those people with
Global responsibilities
– Provide solid cost comparisons across the Company, by
plant or by region
– Define, measure and report On-Time Delivery (OTD)
– Provide consistency in how to measure and what to
measure in regards to production, shipping, requests
– Provide consistent analysis by regions, costs,
allocations,
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- 28. Setting Appropriate Business Expectations
Where Should We Expect to See Benefit?
• Data Governance provides a formal framework of roles and processes that
will enable the company to:
– Formally address accountability and ownership of that data – Formalize and implement data standards for the most
– Formally investigate and report the benefit and gain from consistency critical data across BOMs, routings, costs
in that data – Communicate efficiently and effectively regarding product
changes
– Formally investigate and report the cost associated with the benefit
– Utilize cost and production data globally to Identify and
and gain
retire products that are less profitable
– Formally identify the resources and time required to achieve the
– Prevent rework associated with product changes not
– benefit and gain formally communicated and rejected by customers
– Complete the process of building consistency in the data – Formalize responsibility for communications across the
– Control and manage raw material substitution manufacturing business areas
– Identify and plan for where raw materials are used – Standardize the approach to our product management by
– Compare material usage across plants improving the understanding of cost
– Identify alternate and substitute raw materials
– Improve metrics around data – ability to count products, materials,
customers, …
– Analyze and measure time required to load data into system globally
– Provide faster innovation and redefinition in processes, products
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- 29. Setting Appropriate Business Expectations
Where Should We Expect to See Benefit?
• Key Concepts Shared:
– Don’t let perfection get in the way of progress. – “Everything we do” around costing and benchmarks is
– Point of diminishing returns – to determine what data projects difficult and time consuming, Very painful.
should be completed. – Gain agreement on priorities and let specialists gather the
– Concerned of resources – people and time information for decision making
– Stay away from “data perfection” – address specific – Issues everywhere, in everything I do
inconsistencies that provide most value – “So important to get this done. I am supportive.”
– Secondary – focus on “political” value of consistency in – “Urgent issue and you have my support”.
product, category, customer definition – Standardizing product data for all new products will
– There are pockets of experts but no formal information about deliver consistency in a few years time due to product
who decision makers are turnover and the natural progressions.
– Need to improve overall maturity level around data and – Global has adopted the ISO standard but not the U.S. as
information only holdout.
– Record and communicate how progress is being made in data – Causes problems with all units of measure.
maturity – Product changes not communicated causing rework.
– No single person has the ability to define the standards. – Not using SAP to its fullest value because of the “do what
– Estimate the time requirements of people participating in you want” approach to data.
Governance processes – Huge disconnect to the tune of more that $1 million
– Finance’s inability to resolve issues centrally prolong issue dollars spent to ineffective communications associated
resolution process with product changes.
– Need manner to leverage customer experience – what do – Lack of understanding of costs leads to problems
”they” want w/product mgmt – introduction, delivery, retention
– Recent problems with data availability and time necessary to
translate the data for analysis
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- 30. Real-World Data Governance
Wrap Up
• Webinar Summary
– Define Setting Appropriate Business Expectations
– Considerations for Setting Expectations
– Messages for Management
– Expectations of Value Add
• Questions & Answers
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- 31. Setting Appropriate Business Expectations
Coming Up
• Real-World Data Governance – Monthly Webinar Series
– July 19, 2012 – Meta-Data & Data Governance – 2pm EST
– August 16, 2012 – Master Data Management & Data Governance – 2pm EST
– September 20, 2012 – Business Glossaries & Data Governance – 2pm EST
– Register On-Line at Dataversity.Net
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- 32. Real-World Data Governance
Contact Information
• 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
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