PHASE
1
Build a Collaborative Data Governance Engine
Plan
Enable Shared Insights With an Effective Data Governance Engine
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Phase 1 outline
Call 1-888-670-8889 or email GuidedImplementations@InfoTech.com for more information.
Complete these steps on your own, or call us to complete a guided implementation. A guided implementation is a series of
2-3 advisory calls that help you execute each phase of a project. They are included in most advisory memberships.
Guided Implementation 1: Build a Collaborative Data Governance Engine Plan
Proposed Time to Completion (in weeks): 2-4 weeks
Step 1.1: Unite Under the Data
Governance Business Rationale
Start with an analyst kick-off
call:
•
•
•
Identify the value data governance
will provide for the organization.
Assess the organizational
requirements.
Discuss the flow of data, data
pains, and drivers.
Then complete these
activities…
•
•
•
Discuss the flow of data, data
pains, and drivers.
Identify the organization’s data
needs through business interviews.
Create a business data glossary.
With these tools & templates:
Business Data Glossary Template
Step 1.2: Assess Maturity of the Existing Data Governance
Program
Step 1.3: Structure the Shared Data
Governance Program
Review findings with analyst:
•
•
•
Understand how Info-Tech’s approach to data
governance is supported by industry best practices.
Gain a deeper understanding of data governance using
Info-Tech’s practical and tactical framework.
Insight into the current state of your organization’s data
governance using our framework and research.
Finalize phase deliverable:
•
•
•
Then complete these activities…
•
•
•
Discover Info-Tech’s data management and data
governance frameworks.
Determine IT’s expectations and current understanding
of data governance.
Assess the maturity of your organization’s current data
governance practice.
With these tools & templates:
Identify the project vision, purpose, and
goals of the project.
Acknowledge the risks of the project and
create an appropriate mitigation strategy.
Identify project team members from IT and
the business.
Then complete these activities…
• Determine the vision, purpose, and goals.
• Identify risks.
• Create a data governance team.
• Create a RACI chart to assign
responsibility.
• Create a project plan.
• Identify data governance metrics.
With these tools & templates:
Data Governance Initiative Planning and Roadmap Tool
Data Governance Program Charter
Phase 1 Results & Insights:
• A scoped and planned data governance project.
• Stakeholder buy-in and a clear understanding of the value of data within the context of your organization.
• An approved and launched data governance project.
Info-Tech Research Group
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Step 1: Unite under the data governance business rationale
1
Unite Under the
Data Governance
Business Rationale
2
Assess Maturity of the
Existing Data
Governance Program
3
Structure the Shared
Data Governance
Program
This step will walk you through the following activities:
This step involves the
following participants:
1.1.1
Learn the benefits of a data governance program from an IT and business perspective.
• Business Stakeholders
1.1.2
Understand the business drivers for a data governance program.
• IT Representatives
1.1.2a
Capture the high-level and data-related long-term strategies of the organization.
1.1.2b
Identify stakeholders and conduct interviews with individual business units.
1.1.2c
Generate the data flow diagram and business data glossary for key business units.
1.1.2d
Identify the three key drivers for each business unit.
Outcomes of this step
 A firm understanding of the value of a data governance program and how it can help the organization efficiently manage
its data to gain a greater competitive advantage and achieve operational excellence.
 A data flow diagram and business data glossary that is populated with the crucial data of the business and contains
correctly defined and owned data.
Info-Tech Research Group
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1.1.1
Data governance enables the business and IT to climb
the data value chain together
After starting the data governance engine with the organization’s fuel – its data, information, and needs – the real
power from the engine emerges when the program is implemented. Using Info-Tech’s methodology and extensive
resources will help you get the power that you need out of your data governance engine. Together, this will help drive
your organization up the data value chain to gain knowledge and shared insight from the business.
Info-Tech Methodology of Implementation
Shared Insight
Policies and
Procedures
Shared insight is the goal of using data.
Mix knowledge with collaboration
between business units and IT to enable
innovation and trend-setting by the
organization.
• Communicate the
policies continuously.
Data
Governance
Engine
• Continuously
update policies and
ensure they are
socialized.
People
• Outline clear roles
and responsibilities
for data working
groups (data owners,
data stewards),
steering committee,
and data governance
council.
Communication Plan
• Create clear and
concise policies.
Knowledge
Information
Data
Business
Knowledge is the result of
overlaying multiple sets of
information.
Information is data in a usable
format. Can be a trend in the data
or a summary in report form.
IT
Data can be in many formats
but is most commonly in
structured table form.
The Data Value Chain
• Train individuals.
Info-Tech Research Group
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1.1.1
Achieve the greatest returns from your data investments with
an effective data governance strategy
Data governance is a strategic and long-term program and way of thinking that will enable your organization to manage its
data.
This is accomplished by implementing the people, processes, policies, and technologies needed to ensure that accurate
and consistent data and data policies are enforced across varying lines of business within your organization.
A data governance program will help your organization:
•
Increase confidence and consistency in reporting and
decision making.
•
Identify the decision-making power for policies and
procedures that will affect enterprise data.
•
Align data initiatives with corporate strategies to promote
consistent organizational goals.
•
Effectively manage and maintain data resources, ensuring
the integrity of organizational data.
•
Decrease the risk of data misuse through the implementation
of appropriate policies and procedures.
•
Increase adherence to regulatory requirements and improve
the overall security of organizational data.
It has been estimated that 5-15% of
our revenue is lost due to poor data.
- Data Owner,
Financial Services
There’s definitely some inconsistencies in
process that we’re seeing across the
organization…[that require us] to adopt a best
practice standard and work to implement
across all areas and applications where we see
those inconsistencies [in data].
- VP, Information Technology, Health
Care Organization
Data is one of the organization’s largest and most valuable assets and it continues to grow. For
organizations to utilize their data effectively and benefit from it, they must govern their data.
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To operate efficiently, the right data needs to be available at
the right time
CASE STUDY
Industry
Source
Engineering
Info-Tech Research
Group Interview
Challenge
Solution
Results
• There are roughly 13,000 projects
per year. Technicians are sent on
site daily to complete projects.
• Skilled people have been hired but
if they do not have the right data at
the right time, they will be
ineffective.
• By establishing an effective data
governance program, Braun
Intertec was able to take on a
variety of data initiatives to
enhance the product, change user
behavior, and improve content
management.
• There is an ample amount of
information that the technician
needs to know – they need to
know where they are going, the
safety requirements, the scope of
the project, and the tools that are
needed.
• Goal: Improve availability of data.
• The primary deliverable is a report
that provides a results summary
that can be easily interpreted.
• The information needs to be
streamlined, effective, and
consistent.
• Braun Intertec needs to be able to
survive a downturn in the
environment, establish itself in
new geographies, and become
scalable and portable.
• Data governance will ensure
unstructured data locations and
permanent storage are managed
for everyone.
• To improve the availability of data,
Braun Intertec created a
comprehensive roadmap for the
2015 fiscal year.
Info-Tech Research Group
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Understand how a lack of data governance can cripple the
modern enterprise
1.1.1
A data governance program may be right for you if you are experiencing any of the following pains:
As a Business:
As a CIO and the IT Department:
•
There is uncertainty as to whether the data is
complying with laws and regulations.
•
•
The business has trouble executing its main
business processes due to bad data.
The business continues to complain to IT that
the organizational data is inadequate for its
operations.
•
Employees get different answers from what are
supposed to be the same data sets.
CIO and IT department feel that they need to
step in to alleviate pains caused from bad data.
•
There is a genuine inability to make good
business decisions because our data is of
such low quality.
IT has spent countless person-hours sifting
through data to resolve issues, wasting time
and money.
•
The business insists that IT is responsible and
IT takes measures to rectify the issue, but
clean-up efforts are futile: regardless of the
tools we employ, the data gets dirty again,
almost immediately.
•
•
•
The business is experiencing severe
dissatisfaction from customers, partners,
and suppliers alike due to our bad data and it
is eroding our reputation.
•
The business is leaking money as a result of
duplicate mailings, time wasted finding new
customer information, etc.
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Stop overlooking the importance of data governance;
strategic business initiatives depend on it for success
1.1.1
Most organizations overlook the sheer importance of a data governance program and the value it can provide to different
facets of the business. Data governance can no longer be absent when discussions are taking place around strategic, dataintensive enterprise initiatives such as mergers and acquisitions, business partner integration, security and privacy, and
planning and budgeting.
Mergers and Acquisitions
Although a merger or acquisition may seem irrelevant to IT,
almost 25% of the cost of the venture can be attributed to data
integration. The data governance team can provide insight into
realistic costs, risks, and challenges of data integration.
Security and Privacy
Discussions and projects concerning security and privacy should
always involve data governance. Today, the average cost of a
company’s response to a data breach is close to $100 per record
compromised. To ensure data policies and procedures are
aligned with business needs, there needs to be continuous
collaboration between the data governance team and the
business.
Planning and Budgeting
It is crucial that data governance is involved to ensure
organizations aren’t guilty of planning first and budgeting second.
Source: Pradel Consulting Whitepaper
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Learn how your data is being affected by availability, trust,
compliance, and security
AVAILABILITY
With the increase of internal applications, there is a need for the
creation of policies and assignment of roles for managing
the availability of data.
• High availability of data to the appropriate users is critical.
• Disaster recovery plans are required to meet operational
SLAs.
• Mobile users demand access to data anytime, from anywhere.
• Timeliness and availability of current and historical data for
reporting.
• Adequate backup and storage of data is required.
1.1.1
TRUST
Ensure data maintains a high level of integrity within the
organization and can be used to drive decision making.
• The amount of data created is increasing rapidly.
• Data exists in multiple systems, with some data being
incomplete and some being duplicate.
• The amount of data sources is increasing. Data is being
collected from multiple social media sites.
• The amount of unstructured data is increasing.
• Availability of data validation rules and references are the
basis for data quality inspection and monitoring.
The biggest problem with our ERP implementation was not the quality of data but the availability of data. [Our
employees] are working for the same company but looking at the data differently. There needs to be a way to determine
access rights and train employees on how to interpret the data.
- John Cahill, IT Demand Manager, Braun Intertec
COMPLIANCE
An increase in external regulations is pushing organizations to
adopt internal policies that align with external laws and
regulations.
• HIPAA, FIPPA, SOX, the Data Protection Act, and privacy
rules surrounding PII.
• Data stored in the cloud may cross jurisdictional boundaries –
know where it is and which local regulations apply.
• Mobile device compliance and regulatory obligations.
• As computing becomes increasingly global, organizations
need to be aware of off-shore regulations in any country where
their data is stored and used.
SECURITY
The need for more secure data is driving the adoption of security
policies that are able to adapt to changing security requirements
and control access to sensitive data.
• Mobile devices are now accessing corporate data through
unsecure networks.
• Data is being housed on mobile devices or on cloud-based
file-sharing sites such as Dropbox.
• Data is getting corrupted, lost, or compromised while in transit
between cloud and on premise.
• Data is increasingly subject to new data privacy laws,
archiving, and disclosure rules.
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1.1.1
Realize the implications of increasing regulatory pressure
Increasing regulatory pressure has been a key driving force
pushing companies towards adopting data governance.
Case Study: Target
The banking industry estimates that the annual cost of credit
card breaches exceeds $2 billion. (Source: PCI Data Security in the
Source: Bloomberg Business Week
Title: Missed Alarms and 40 Million
Stolen Credit Card Numbers: How
Target Blew It
Parking Industry, Digital Payment Technologies)
Examples of regulatory pressure:
• BIC and IBAN are mandatory for businesses making/receiving
cross-border payments, and demand greater data validation.
•
In late 2013, hackers managed to steal customer
credit card information at all 1,797 Target
locations. This amounted to 40 million credit card
numbers, 70 million addresses and numbers, and
additional personal information.
•
Target incurred billions of dollars in expenses as
a result of the data breach. Customers and
banks, outraged by the scandal, filed nearly 100
lawsuits for negligence and compensatory
damages.
•
In an attempt to rectify the issue and regain
customer trust, Target spent $61 million. The
holiday shopping period following the breach
suffered a drastic profit decline: approximately
46% from the fourth quarter the following year.
•
If Target’s security team hadn’t overlooked the
early signs of data breach, the credit card fiasco
could have been avoided and Target’s reputation
could have been saved.
• FATCA and AML demand a higher degree of data cleansing
and a customer screening.
• Basel lll and Dodd-Frank require capture and usage of
accurate data.
• PCI requires a greater level of security over credit card
information.
• CASL requires organizations to take greater action with network
security programs, anti-virus software, and employee education
and awareness.
• Data Protection Policy sets forth rules to govern the
compilation, disclosure, and use of personal information.
• GLBA places expectations on financial institutions to define
specific standards for protecting customer personal information.
• HIPAA requires a degree of confidentiality and maintenance for
electronic health information.
Info-Tech Research Group
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Extensive changes to the business environment have placed
pressure on the business to adopt data governance
Big Data
Rapid
Technological
Evolution
1.1.1
As companies continue to grow and generate progressively large volumes of data, their ability to staff and manage
this digital universe continues to fall behind the perpetual increase of data being stored. It is becoming costly and
inefficient for a company to find specific information in their cosmos of unstructured data.
With new technological advancements being introduced to the market every day, many companies pursue these
technological trends in an attempt to increase efficiency in their business practices. However, with these
technologies (mobile devices, cloud computing, SaaS models, and on-demand computing) comes several new
ways to store information and subsequently organize data. Organizing this data seems to be an afterthought for
most companies. They would benefit from developing a strategy for these specific issues ahead of time.
Security
Many industries are disposed to cyber attacks (financial, medical, government, etc.). The success of cyber attacks
is generally due to the overload of new technology mixing with older systems without proper integration and
governance. Instilling security policies is a good first step; however, it is extremely hard to maintain without proper
data governance.
Competitive
Pressures
It is a clear competitive advantage for companies to hold a proactive business model. Effective data governance is
an organizational strategy that is a key element in holding this competitive advantage over those companies that
have yet to invest in their long-term strategies.
Social Media
With social media, you cannot have politics of non-transparency anymore. The customer is
demanding transparency. Customers will not buy from a company who is not transparent.
- Dr. Walid el Abed, Founder and CEO, Global Data Excellence
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1.1.1
Know where the technology market is headed to
appropriately plan for your organization’s program
Data
governance
is on the
rise
1. There will be a shift in organizational business cultures. Those
that have data-driven individuals on staff will have the most success
with a data governance initiative.
2. The technology that surrounds data has become more
complex with a greater ability to manipulate and display
information. As a result, stricter compliance strategies will be
needed for business users who are not willing to commit to a data
governance initiative.
3. Vendors will begin releasing competitive products that enforce
compliance to data governance policies. These products will
also focus on measuring the success of data governance programs.
Data
Integration
Social Media
Big Data
Cloud
4. Unstructured big data leaves organizations dazed and
confused. Pulling information from social media sites can be risky,
but it is often a necessity for accurate reporting. A data governance
initiative will help clean this data and allow for verifiable results.
5. With SaaS solutions varying in popularity, some of the
organizational data may be hanging in the cloud. Having a strategy
to manage this data is integral to keeping it clean.
Master
Data
Business
Intelligence
Tailoring your data governance plan to incorporate cloud, big data, and changing privacy laws will
prepare your organization for success.
Info-Tech Research Group
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1.1.2
Kick-start your data governance program by understanding
why the business needs it – the fuel for the DG engine
Data governance and data empowerment is ultimately meant to support the goals and objectives
of the organization. If you don’t know why business units need data governance, the project will be
focused on improving data quality without a larger purpose. This will not only be unsustainable but
also a waste of time for the organization.
Remember: The Data Value Chain
Data
Information
Knowledge
Shared
Insight
The data value chain will break if this mode of thinking is not pervasive throughout the organization.
Before trying to force data governance into an unreceptive environment, you have to make sure that the business is on board, naturally
thinking in this manner, and actively evangelizing the ability of proper data governance to enable shared insight.
The following activities (on the next few slides) will bring you through the most important steps of the data governance program:
•
Work with the business to unite under WHY the business needs data governance and help the business understand these reasons.
•
Collaborate with the business to figure out HOW data governance will help drive the long-term goals and strategies of the organization
to get the right information to the right people at the right time.
•
Combine your ideas and efforts to establish WHAT you can do to accomplish the above.
Info-Tech Research Group
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Build your Business Data Glossary to determine what key
business data will be governed
1.1.2
In an ideal world, you would have all the resources that you need to govern all of the organization’s
data. This is rarely the case, if ever. Instead, target a realistic data scope to govern that will fit within
your resourcing. To do this, figure out which is the most important data to the business.
The next set of activities will bring you through the following process:
Business
Unit
Interviews
Risk/Value
Assessment
Data Flow
Diagram
Business
Data
Glossary
Governance
on Data in
the BDG
These activities will help you accomplish the following outcomes:
1.
Identify the key data that should fall under the scope of the data governance program, based on
targeted input from the business units that need improved data usability and access.
2.
Generate a data flow diagram that will document the relationships between essential aspects of key
organizational data such as where it is stored, who uses it, and for what purpose.
3.
Create a Business Data Glossary (BDG) to document the data that will be governed and their
essential attributes such as ownership and uses.
4.
Identify purposeful, business-driven pilot program initiatives that will help you start the data
governance program, show quick value of the program, and popularize/socialize the program to other
business units that may be skeptical of the value.
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Capture the high level and data-related long-term strategies
of the organization
1.1.2a
~2 hours
Format: Roundtable Discussion
Instructions
1. Gather senior management representatives from key business units in a meeting room.
2. Have an open discussion about the long-term strategies of the organization and how data
can enable them to be accomplished.
3. Use the following questions as a guide for the discussion:
1. What are the organization’s strategic imperatives over the next 3-5 years?
•
What are your strategic goals?
•
What are key growth/focus areas and key performance indicators (KPIs)?
•
How can data support these plans?
2. What are the critical business functions/ practices at the organization?
•
Is the organization changing? Is it moving into new markets?
3. What are the primary regulatory and organizational requirements?
•
Are regulations and requirements changing?
INPUT
• Sample questions
targeting the datarelated strategies of
the organization
OUTPUT
• How data enables the
long-term strategies
of the organization
Materials
• Note-taking materials
• Whiteboard, flip chart,
markers
Participants
• Business
representatives
(Directors of business
units)
• IT representatives
(CIO, CDO)
Info-Tech Research Group
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Identify data-enthusiastic stakeholders and conduct
deep-dive interviews with these individual business units
1.1.2b
3 hours per interview, 2-3 interviews
Once you understand the high-level goals of the organization and how data can enable the
achievement of these goals, identify 2-3 business units that demonstrate enthusiasm for
or a positive outlook on improving how organizational data can help them in their role and as
a unit.
Conducting a deep-dive interview process with these key stakeholders will help further identify
high-level goals for the data governance program within each business unit. This process will
help to secure their support throughout the implementation process by giving them a sense of
ownership.
Key Interview Questions:
1.
2.
3.
4.
What are your primary activities? What do you do?
What challenges do you have when completing your activities?
How is poor data impacting your job?
If [your selected domain]’s data is improved, what business issues would this help solve?
Request background information and documentation from stakeholders regarding the
following:
•
What current data management policies and processes exist (that you know of)?
•
Who are the data owners and end users?
•
Where are the data sources within the department stored?
•
Who has access to these data sources?
•
Are there existing or ongoing data issues within those data sources?
INPUT
• Sample questions
targeting the activities,
challenges, and
opportunities of each
business unit
OUTPUT
• Key challenges,
activities, and
opportunities of the
business unit
• Insight into the root
causes of data-related
pains
Participants
• Business representatives
(Directors of business
units)
Info-Tech Research Group
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Conduct a risk/value quadrant assessment to identify the
key data of each business unit that will be governed
1.1.2b
30 minutes
INPUT
Instructions
1. While facilitating the business unit deep-dive interview, identify the key data assets for the
business unit and determine those that will fall under the scope of the data governance
program.
2. Based on your answers to the following questions, place the identified data assets on the
quadrant according to where they lie along the risk and value axes:
Value
Second
Value driven
Do this first!
Both Value
and Risk
driven
•
•
•
•
•
What do you do?
Challenges?
Activities/Systems?
Value?
What is the risk associated
with this data asset if
mishandled, stolen, or lost?
Risk
Kipple (not
worth
considering)
Second
Risk driven
• Business unit answers
to questions targeting
key data
OUTPUT
• Identified key data to focus
on and populate the
business data glossary
Materials
• Note-taking materials
• Whiteboard or flip
chart, markers, sticky
notes
Info-Tech Insight
The top right quadrant of the risk/value assessment can also be thought of
as a compilation of the master data in your organization. These are likely
to be part of your master data management solution.
3. Data assets in the top right (value and risk driven), top left (value driven), and bottom right (risk driven)
quadrants should be governed. These will be focused on to complete the next series of exercises, including generating
the data flow diagram for these data elements, as well as creating the business data glossary with these key elements.
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Data isn’t static; it moves in and out of systems and is used
for various purposes by multiple user groups
Understanding where data lives can be challenging as it
is often in motion and rarely resides in one place. There
are multiple benefits that come from taking the time to
create a data flow diagram.
A data flow diagram is crucial to start the
requirements gathering process:
• Mapping out the flow of data can help provide clarity on
where the data lives and how it moves through the
enterprise systems.
• It will help to identify opportunities to clean and
manage the data:
• Having a visual of where and when data moves helps to
understand who is using data and how it is being
manipulated at different points.
• A data flow diagram will allow you to elicit how data is used
in a different use case.
Used by
Business
Data
• By knowing where data lives, you can easily identify
the business stakeholders to interview.
o i.e. where you need data owners and data
stewards and a logical way to assign these
roles.
• It will help you understand the level of security
required and compliance implications.
Housed in
Business
Unit
1.1.2c
Used for
Systems
Usage of
the Data
A data flow diagram can provide value by allowing an organization to adopt a proactive approach to a
data governance strategy. Save time by knowing where the entry points are and where to look for data
flaws.
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Generate a data flow diagram for each key business unit to
visualize how all key data flows through the organization
1.1.2c
~30 minutes per business unit
Info-Tech’s Four Column Model of Data Flow
Instructions
While you facilitate the business unit interviews, capture the four key components of the business
unit’s data and map how they interact with each other. As you already know the “Business Unit”
column, start with the “Usage of the Data” column and identify the “Systems” the data is housed in.
This information, along with the data in the risk and value driven quadrants of the value/risk
quadrant assessment, can then be used to populate the Business Data Glossary column, which
will be used to generate the Business Data Glossary.
Business Data
Glossary
Business
Unit
Mkt-Product
Marketing
Fin-Product
Shi-Product
Finance
Systems
• Business unit
interview
OUTPUT
• Visual guide to how
key data flows
through the
organization
XYZ ERP
Reporting
ABC CRM
Shipping
DEF
Inventory
Management
Research
BI
Platform
Legal
Usage of the
Data
INPUT
Other - like
a desktop
spreadsheet
Billing
Campaign
Contracting
Materials
• Note-taking materials
• Whiteboard or flip
chart, markers
Participants
• Business
representatives
(Directors of business
units)
Info-Tech Research Group
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Create a business data glossary to maximize the
understanding of the organization’s key data
The business data glossary is a collection of the organization’s key data assets.
Elements of a Business Data Glossary
Purpose of having a comprehensive business data glossary:
1.
Data element name
2.
Definition
3.
Abbreviations and acronyms
4.
Source system
1. Manages the business terms, their definitions, and associated
knowledge including who owns the data and how the data should be
used and when. This can help to increase the accuracy of reports
because there is no ambiguity in the data definitions between business
units.
5.
Source detail
2. Better access to knowledge of the business terms.
6.
Possible values
7.
Data steward
8.
Data sensitivity
3. Aligns the terminology of the business with the technology and
organization assets. It allows the people who interact with the data to
quickly identify the applications, processes, and stewardship associated
with it.
9.
Usage of the data
4. Enhances the accuracy and efficiency of searches for organization data
definitions and attributes, enabling better access to the data.
The existence of a business data glossary does not mean that all of the
organization’s data problems will be solved, but when coupled with effective
active governance, the business data glossary will help to enable better data
access and accuracy.
Info-Tech Research Group
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Use the stakeholder interviews and data flow diagrams to
populate the Business Data Glossary
1.1.2c
Business Data Glossary
After completing Info-Tech’s four column model
of data flow for each business unit, leverage
the “Business Data Glossary” column to
populate the organization’s Business Data
Glossary. For each entry, use the Business
Data Glossary template to document key
aspects of the data, such as:
 Definition
 Data Sensitivity
 Source System
 Data Availability
 Possible Values
 Batch or Live
 Data Steward
 Retention
Data
Element
INFO-TECH DELIVERABLE
Mkt-Product
Fin-Product
Shi-Product
Populate the
Business Data
Glossary
based on your
data flow
diagrams
Use your data flow to define your data
Using the data flow model to populate the organization’s
Business Data Glossary ensures that the crucial data
that has key business use by key business systems
and users is appropriately owned and defined. It also
establishes rules that lead to proper data management
and quality, to be enforced by the data owners.
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Identify the 3 key drivers for 2-3 business units to prime the
data governance engine with pilot projects
1.1.2d
~1 hour per business unit
Instructions
INPUT
For each of the 2-3 business units that contributed their data activities, challenges, and
flow diagrams, identify 3 drivers in the following categories:
• Business unit
interview
1 The biggest opportunity that improved data can bring for them.
2 Their largest data-related pain, frustration, or pet peeve.
OUTPUT
3 An easy data-related win that will showcase results quickly.
If the business unit is having trouble identifying these drivers, prompt them with common
pain areas such as trust in the data, availability of the data, compliance, and security.
• Key pilot initiatives for
the data governance
program
Info-Tech Insight
Benefits
These harvested drivers will reveal some pilot
projects that can be addressed practically and
strategically to demonstrate the true value of
having a pervasive and enabling data governance
structure in the organization. Once you are able
to show the value of data governance to 1-2
influential business leaders, the rest will follow.
The interview process can be a large time commitment for busy
executives. However, you must convey the importance of this series of
crucial activities and the benefits that will be generated through this
investment of time.
Involving senior management in the program might be your most
significant success factor. They are needed to evangelize the
importance of data governance and promote the understanding of
data governance initiatives throughout the organization. Focus on the
business benefits (e.g. reduced costs, higher revenues) associated
with purging low-quality data.
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Step 2: Assess the maturity of the existing data governance
program
1
Unite Under the
Data Governance
Business Rationale
2
Assess the Maturity of
the Existing Data
Governance Program
This step will walk you through the following activities:
1.2.1
1.2.2a
1.2.2b
Discover Info-Tech’s data management and data governance frameworks
Determine IT’s expectations and current understanding of data governance
Assess the maturity of your organization’s current data governance practice
3
Structure the Shared
Data Governance
Program
This step involves the
following participants:
• IT Representatives
• Data Governance Program
Team
Outcomes of this step
 Understand how Info-Tech’s approach to data governance is supported by research using industry best practices.
 Gain a deeper understanding of data governance using Info-Tech’s practical and tactical framework around data
governance as a component of your organization’s overall data management practice.
 Insight into the current state of your organization’s data governance using our framework and research.
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Data Governance is the top
enabler of Info-Tech’s Data
Management Framework
1.2.1
Successful data governance requires a
comprehensive approach
For data governance to be successfully planned,
Please note the components of
implemented, and maintained, it must take into account
the model are not meant to reflect
effective capabilities in the critical processes and suba flow diagram, but to instead
practices of data management (see Layer 1: Data
reflect a taxonomy of capabilities
Management Enablers). It is also a critical factor in
and components needed for
successful data endeavors (see Layer 2: Information
effective Data Management.
Dimensions). For more information on Info-Tech’s Data
Management Framework, see the description of its approach and
layers in the appendix.
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Data governance is the central component of the DMBOK2
Data Management Framework
1.2.1
This research is created with reference to the Data Asset Management Association’s Book of Knowledge,
Version 2 (DAMA DMBOK2).
The DAMA DMBOK2 Data Management
Framework
Data management is the planning,
execution, and oversight of policies,
practices, and projects that acquire, control,
protect, deliver, and enhance the value of
data and information assets (DAMA, 2009).
In other words, getting the right information,
to the right people, at the right time.
The research in this blueprint will focus on data
governance, the central idea of data
management without which the surrounding
data management initiatives would have no
structure.
Data governance directly complements all ten
data management initiatives.
Source: DAMA International
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1.2.1
Use industry best practices and methods to implement an
effective data governance program
A successful data governance program calls for a balance between planning and
control activities.
DAMA Data Management Body of Knowledge Version 2
provides a comprehensive data management framework
that touches on the 11 data disciplines.
DAMA DMBOK2 positions data governance at the core of all
data disciplines to clearly depict the influence data
governance has on the surrounding disciplines.
In each discipline of data management, DAMA DMBOK2
identifies a list of activities that are segregated in one of four
groups: planning, control, operations, and development.
Data governance is comprised of planning and control
activities.
Info-Tech Insight
It is vital that a proportionate amount of
activities are implemented from planning
and control to create balance. Planning
activities will only prove to be effective if
there are mechanisms in place to control
them.
Planning
Control
Vision
Supervise
Roles &
Structure
Manage &
Resolve
Policies,
Procedures &
Standards
Monitor
Projects &
Services
Oversee &
Communicate
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Build your organization’s data governance engine depending
on its needs
1.2.1
Now that we know more about the fuel going into the data governance engine, let’s focus on the engine itself.
While data governance informs all of the
DMBOK2 elements, we are going to
focus on the four most crucial elements.
The Info-Tech Data
Governance Engine
Organization
Fuel In
Data
Architecture
Data
These four main pistons of the engine are
moved by the fuel coming in, enabled by data
governance:
Data
Quality
Master and
Reference
Data
Management
Information
Policies and
Procedures
(PnP)
Business
Needs
Data Security
and Audit
•
PnP
•
Data Quality
•
MDM
•
Data Architecture
Info-Tech Insight
Data Risk
Management
Data
Integration
Data
Modeling
Data
Warehousing
& BI
Documents
and Content
Metadata
Data Storage
& Ops
Depending on your organization’s needs,
some of these components may change
size. For example, if you are in an industry
that has sensitive data, data security may
be a main piston. This is similar to how
engine components change depending on
your need out of the engine: if you need
fuel efficiency, your engine will be different
than if you want to build a race car.
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Use Info-Tech’s resources to target the parts of the data
governance engine where the organization is lacking
1.2.1
Main Components of the Info-Tech Data Governance Engine
Data architecture depends on effective
data governance. Use our blueprint,
Modernize Data Architecture for
Measurable Business Results to get
more out of your architecture.
Data
Architecture
When you start your data
governance program, you will
quickly realize that you need an
effective MDM strategy for
managing your critical data
assets. Use our blueprint, Develop
a Master Data Management
Strategy and Roadmap to Better
Monetize Data to get started with
MDM.
Master and
Reference
Data
Management
Data
Quality
Policies and
Procedures
(PnP)
The key to maintaining high data
quality is a proactive approach to
data governance that requires
you to establish and update
strategies for preventing,
detecting, and correcting errors.
Find out more on how to
improve data quality with InfoTech’s blueprint, Conquer Data
Quality Challenges in 4 Steps.
Great policies and procedures are key
considerations of an effective data
governance program. Leverage Info-Tech’s
extensive library of policy templates and
our exciting web-based policy and
procedure management tool here:
Click on the above image to find out more
about myPolicies
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Set expectations for data governance within the IT group by
interviewing key IT representatives
1.2.2a
~2 hours
Format: Roundtable Discussion
Please introduce yourself and share your answers to the following
questions:
1. What is your role in the organization?
2. Why are you here?
3. What does data governance mean to you?
Prompts
1. Share your current experiences with data governance and data management at the
organization.
2. What other governance practices are in place at the organization?
• IT governance?
• Formalized change management?
3. What barriers exist that may constrain the effectiveness of data management and
data governance goals at the organization?
4. How would you like to see the organization and IT work together in implementing
data governance? Frame the discussion around what the business wants out of data
governance, gathered from the previous exercises.
5. What IT frameworks do you use at the organization?
OUTPUT
• Expectations and pain
points from the IT side
of data governance
Materials
• Note-taking materials
• Flip charts,
whiteboard, and
markers
Participants
• CIO, CISO, CDO
• Managers of IT
groups
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Before assessing your organization’s current state of data
governance, take a minute to understand the CMMI program
1.2.2b
To assess data governance functions, Info-Tech uses the Capability Maturity Model
Integration (CMMI) program for rating governance capabilities in each of the function areas
on a scale of 1 to 5.
5
Continuous organizational focus on innovation and improvement
4
Process and projects managed based on measures
3
Processes defined, with performance managed
2
Projects managed, based on defined
plans
1
Process unpredictable,
reactively managed
Optimized
Organizational strategy
Quantitatively Managed
Processes and activities managed
based on measures
Defined
Work done according to processes
Managed
Activities are managed
Initial
Project success depends on individual performance
Source: Cynertia Consulting, 2015
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Use Info-Tech’s Data Governance Initiative Planning and
Roadmap Tool to assess your current maturity
1.2.2b
Data Governance Initiative Planning and Roadmap Tool
The time is now.
Whether you are just getting started with data
governance or have been trying to get it going for
years, now is the best time to start improving
how you do it to get the most out of your data.
The first step in any improvement is knowing where
you currently stand. Use Tab 1 of Info-Tech’s Data
Governance Initiative Planning and Roadmap Tool to
get a handle on where your organization currently
stands in its data governance practice.
When does an organization know when they are
ready for data governance? When they are ready to
stop sitting on their hands, roll up their sleeves, set
it up, and get it going. People are waiting for these
stewards to just materialize in front of them. They
are ready when they say, let’s just do it.
– Stan Christiaens, Co-Founder and COO, Collibra
INFO-TECH DELIVERABLE
Once you know what you are doing well and
what could be improved, you are ready to
begin maturing your data governance
practices by creating practical and tactical
initiatives backed by the business.
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1.2.2b
By increasing your data governance maturity, the organization
will move from chaotic to predictive
Chaotic
Reactive
Before Data
Governance
• No standards
• No common approach
to data integration and
sharing
Year 1
• Processes defined
• Data cleansing
approach to data
quality
Stable
Proactive
Year 2
• KPIs visible
• Business rules in
repository
• Common platform
for data integration
Source: Global Data Excellence, Data Excellence Maturity Model
As you move from reactive to stable, don’t rest and assume
that you can let data governance keep going by itself.
Rapidly changing consumer requirements, regulatory
requirements, or other pains will catch up to your
organization and you will fall behind again. By moving to
the proactive and predictive end of the maturity scale, you
can stay ahead of the curve.
Predictive
Year 3
• Business rules/
stewardship in place
• Education and
training
• Increased
transparency from data
sharing
Year 4
• Governance fully in
place and embedded
in the culture
• Full transparency and
information sharing
• Trusted and intelligent
enterprise
If you know what the impact will be of changing rules and
apply your changes to governance before they happen (this is
the predictive model), you can realize your value target. It
depends on if you are seeking excellence. If you are not seeking
excellence, you can be stable…but for how long?
- Dr. Walid el Abed, CEO and Founder, Global Data Excellence
Data governance is not a one-and-done project. It is a dynamic program that must be improved upon
continuously depending on changing business needs, as well as business and IT feedback.
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British Airways implemented data governance strategies to
improve data accuracy for BI and reporting
CASE STUDY
Industry Airline
Source Trillium Software
Success Stories
Challenge
Solution
Results
• As one of the largest premium
airlines, British Airways must be able
to capture and use data on millions of
passengers for its operations
including ticketing, check-in, and seat
allocation.
• To standardize and improve data
quality, British Airways recognized
the need for an enterprise-wide
data governance program.
• As a result of the data
governance program, and in
conjunction with data quality
initiatives, recognition of the
importance of data accuracy and
quality increased.
• As a result of the large volume of
data, the airline has difficulty
maintaining data quality and access
to the information.
• In addition, it is difficult to have
effective business intelligence for
decision making and marketing when
data quality can be low at any time,
and accuracy and timeliness of the
data is questioned.
• This can affect customer relations
and ultimately tarnish the airline’s
reputation.
1.2.2b
• To do this, the airline set up a
cross-functional data governance
team to represent and lead data
governance for each business
unit.
• Data stewards were also
appointed who understood both
the technical and business
aspects of data governance.
• The governance teams introduced
standards to combat the different
rules being used by each unit.
• The airline established more trust
in the data and began generating
more accurate reports.
• This moved British Airways from
a chaotic governance
environment to a stable
environment. With further
governance work, they are well
on their way to becoming
predictive.
• The airline is already seeing the
benefits of the program through
better customer service and
decreased risk.
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Step 3: Structure the shared data governance program
1
Unite Under the
Data Governance
Business Rationale
2
Assess Maturity of the
Existing Data
Governance Program
3
Structure the Shared
Data Governance
Program
This step will walk you through the following activities:
This step involves the following participants:
1.3.1
1.3.2
1.3.3
1.3.4
1.3.5
1.3.6
• Business Stakeholders
• IT Representatives
• Data Governance Program Team
Identify project vision, mission, purpose, and goals
Identify risk and mitigation strategy
Build a cross-functional project team and create a RACI chart
Construct a project timeline
Track key business and IT metrics
Receive sign-off from the business to proceed
Outcomes of this step
• An all-encompassing data governance vision that incorporates business goals and IT strategies and objectives
• A completed project charter for the data governance project that includes:
 A clear list of goals and objectives
 Risks and mitigation steps
 A RACI chart delineating accountability for the data governance project
 A timeline specifying key milestones
 Project metrics to determine the value and success of the data governance project
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A data governance program cannot be an IT-only endeavor –
the business owns the data and must be involved
1.3.1
While data governance involves collaboration between IT and the business,
the process must ultimately be owned by the business.
 The goal of data governance is to find workable definitions
and business rules that address the individual needs of
stakeholder groups, while creating an authoritative source of
enterprise data. Where necessary, it will be the final voice
when changes to data processes and data definitions are
required.
 Data governance ensures that the correct group of people
that handles the data are involved in the decisions
surrounding data usage, data quality, business processes, and
change implementation.
 A data governance program coordinates people (data
owners) across different lines of business in the organization
who have a vested interest in maintaining current data
systems and processes, but understand the need for
organization-wide policies to maintain consistent data.
Data governance [needs to be] done
in a way that is sustainable and… is
easy for the business to maintain
because IT doesn’t own the data.
[The business people] own the data.
- George Neill, Organic Valley
Ensure your organization is launching data governance with the right initiatives in place for the people,
processes, and technologies surrounding your data. Make sure you involve all appropriate
stakeholders.
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Develop a project charter that outlines the essential elements
of project management to commit the business
1.3.1
One of the key first steps in launching a successful data governance program is securing executive
buy-in. Use a project charter to sell the importance of data governance to senior executives. This will
help get the backing required to get a data governance project started.
Project Charter Purpose
A project charter serves several important functions. It
organizes the project so that you can make efficient and
effective resource allocation decisions. It also
communicates important details about the project
purpose, scope definition, and the project parameters.
Table of Contents
1.
Create a vision statement
2.
Craft a mission statement
3.
Identify the purpose
4.
Document goals and objectives
5.
Identify risks and create an appropriate
mitigation strategy
6.
Build a cross-functional project team
7.
Identify stakeholders and build a RACI
8.
Develop a timeline for the project
9.
Identify metrics
Instructions
To use Info-Tech’s Data Governance Program Charter
Template, simply modify or delete all information in grey
text and convert the remaining text to black before
printing or sending. The following slides will walk you
through instructions on modifying this document for a
data governance project.
10. Review and approval
Getting buy-in can be difficult to achieve immediately, but once the business is on board, obstacles
are removed and the project runs smoothly. Having the management team interested and engaged will
assist in securing the budget and the political support required to launch a data governance initiative.
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1.3.1
Identify the data governance program vision, mission,
purpose, and goals
1-2 hours
Before you start “walking” data governance, you need the entire organization to “talk” data
governance. This is the purpose of the charter: to clearly state and socialize with the business the
vision, mission, purpose, and goals of the program.
• Business input and
drivers
Talk
Vision
INPUT
3-5 year view
Mission
What
Values
How
OUTPUT
• Clear vision, mission,
purpose, and goals of
the program
Materials
Walk
Strategies/Goals
Focus
Objectives
Measure 6-18 months
Tactical Plans
0-6 Months
• Data Governance
Program Charter
Template
Participants
• IT Representatives
• Business Leaders
Don’t develop these crucial statements and goals in isolation. At the very minimum, consult the business interviews
to identify the drivers of the data governance program. Ideally, you would collaborate with the business to come up
with and update the statements during multiple rounds of review.
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1.3.1
Use these vision statement starting ideas to craft your own
Having a vision at the front and center of your data governance program helps to
communicate the critical importance of data governance. A clear vision also establishes a
unified business-IT understanding of the 3-5 year high-level plan and the objectives of data
governance in the organization.
Some starting points include:
•
Business-IT collaboration
•
The organization is dedicated to creating a data governance program with shared
responsibilities between the business and IT that will foster a standard approach to
identifying, using, and understanding data across all areas.
•
The organization is dedicated to creating a data governance program that consists of an
enabling structure that helps the organization get the right information, to the right
people, at the right time.
•
To accurately interpret and analyze data from different systems with confidence that data
attributes and definitions conform to enterprise standards established through data
governance policies and procedures.
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1.3.1
Use these mission statement starting ideas to craft your own
Having a mission statement for your data governance program outlines the “what’s” of data
governance: what it will accomplish, what it does for the business, and what it will do to
improve the organization’s strategic use of its data.
Some starting examples include:
•
Establish an enterprise-wide data governance framework to facilitate improved services,
planning, and policy implementation across the enterprise.
•
Identify the decision-making power for policies and procedures that will affect business
data.
•
Align data initiatives with corporate strategies to promote consistent organizational
goals.
•
Effectively manage and maintain data resources, ensuring the integrity, reliability,
availability, and compliance of organizational data and information.
•
Decrease the risk of data misuse through the implementation of policies and procedures.
•
Increase adherence to regulatory requirements and improve the overall security of
organizational data.
•
Provide ongoing structure to ensure adherence to data governance.
•
Turn data into information that supports the organization’s…
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1.3.2
Identify risks and create an appropriate mitigation strategy
20 minutes
INPUT
Brainstorm
Brainstorm the likely pitfalls of data governance: Who is likely to push back?
What capabilities will be difficult to revise? For each risk, identify possible
mitigation steps. Include the output in the project charter.
• Business interviews
• IT brainstorming
OUTPUT
Risk
Budget constraints and a lack
of stakeholder participation.
End-user refusal to adhere to
new policies, procedures, and
standards.
Inadequate budget for
additional staffing resources.
Mitigation Steps
Highlighting positive benefits in a business
case will help overcome the challenges
associated with launching the data
governance program.
Create mechanisms to ensure adherence,
such as monitoring and supervision.
• Risks and strategies
to mitigate those risks
Materials
• Data Governance
Program Charter
Template
Participants
Rely on internal transfers or role-sharing
rather than external hiring.
• IT Representatives
• Data Governance
Program Team
Info-Tech Research Group
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Assemble the right team for starting the data governance
program, and then delegate appropriate levels of support
1.3.3
30 minutes
OUTPUT
Instructions
• Outlined
responsibilities for the
Data Governance
Program Team
1. Identify the key stakeholders that should be involved in the data governance project.
Remember that you should have a cross-functional team that encompasses both IT
(various units) and the business.
2. Determine whether each stakeholder should be Responsible, Accountable, Consulted, or
Informed with respect to each overarching project step.
Participants
• IT Representatives
• Data Governance
Program Team
3. Confirm and communicate the results to relevant stakeholders and obtain their approval.
4. Move the contents of this chart into the project charter.
Stakeholders
Project Step
Complete the Project Charter
Identify Business Requirements
Assess Solution Initiatives
Prioritize Initiatives and Create Roadmap
Create Communication Plan
Implement and Roll Out Data Governance
Stakeholder
1
R
A
C
I
I
C
Stakeholder
2
A
C
C
C
A
R
…
…
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Build a RACI chart to delineate stakeholder involvement for
different phases and levels of support
1.3.3
30 minutes
Use a RACI chart to specify who is Responsible, Accountable, Consulted, and Informed about a task. The chart below is a
sample.
CDO
Data
Stewards
Data
Owners
Subject
Matter
Experts
Assess Readiness for a
Data Governance Project
A
R
C
C
C
I
I
Structure the Data
Governance Project
C
C
A
R
I
I
I
Identify Business
Requirements
A
R
C
C
I
C
C
Assess Solution Initiatives
A
R
I
C
I
I
I
Create Data Governance
Roadmap
C
C
A
R
I
I
I
Complete Communication
Plan
A
C
I
R
I
C
C
Execute Data Governance
Rollout
C
C
A
R
C
I
I
IT
Director
Business
Analysts
Database
Administrators
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Develop your timeline for the data governance project in
order to specify concrete project milestones
1.3.4
2 hours
Remember to consider dependencies when creating the schedule and identify appropriate subtasks.
Key Activities
Assess Stage Gate
Finalize Project
Charter
Identify Business
Requirements
Assess Solution
Initiatives,
Planning Initiatives,
Control Initiatives
Prioritize Solutions
Complete
Roadmap
Create
Communication
Plan for Rollout
Implement and Roll
Out Data
Governance
Start Date
End Date
Target
Status
Resource(s)
INPUT
• Business interviews
• IT brainstorming
OUTPUT
• A tentative, high-level
schedule for your
data governance
program
Materials
• Data Governance
Program Charter
Template
Participants
• IT Representatives
• Data Governance
Program Team
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Implement metrics and avoid common challenges associated
with the launch of data governance programs
55%
Of IT projects are delivered
successfully annually…
8X
1.3.5
High performers are eight times more likely to
measure the successes of their programs using
metrics.
The lack of challenge score evaluates whether
the following exist as a challenge within an
organization that has launched a data governance
program:
1
Determining key metrics to measure data
governance success.
2
Lack of consistent data definitions and data
structures across lines of business.
3
Staff resistance to following new
governance guidelines and processes.
4
Lack of staff resources willing to take
accountability for data governance
processes.
5
High regulatory standards of some data
sets.
The above are considered challenges because
they were faced by 79% of organizations when
launching a data governance program.
Lack of Challenge Score
Source: Accenture, “Mind the Gap,” 2010
47
Best practices reduce challenges associated
with launching a data governance program
27
20
16
8
Implemented
key metrics
2
Secured
Developed a Established Developed a Established
active
formal
ownership
dedicated data steward
roles
support of communication
and
data
plan
organization’s
accountability management
for data sets
team
senior
management
Source: Info-Tech Research
Group, N=44
Establishing data steward roles is important, but it does not mitigate the
challenges associated with launching a data governance initiative. Determining
your organization’s key metrics and using them will reduce the number of
challenges associated with launching a data governance program.
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1.3.5
Increase the value of your DG program by outlining specific
budget requirements and metrics to provide proof of success
Every organization’s data governance objectives are different, and so the metrics that an
organization chooses to measure its data governance success should be dependent on its specific
business goals and outcomes.
There are two broad groupings of governance metrics that can
be used:
1 Quantitative – those metrics that measure hard benefits
such as resource allocation savings or reduction in
operational costs.
2 Qualitative – metrics that measure soft benefits such as
improved customer satisfaction or employee loyalty.
Sample governance metrics may include:
• Number of duplicate entries/data quality issues
• Number of data breaches/non-compliance issues
• Percent of returned mail due to incorrect addresses
• Level of accuracy for data field entries
• Percent of time data conforms to governance policies
• Percent of operational costs reduced post data governance
launch
• Time spent on data entry
• Time spent on data cleansing
Measured Value
• Cost savings through the reduction of time spent on data
entry, data cleansing, and data searching.
Organizations undergoing a data governance
program have annual budgets of between
$200K
and
$500K
allocated for
the program.
Rand, 2013
Use these figures as benchmarks for
implementing your data governance
program.
Info-Tech Insight
Relating data governance success metrics to overall business
benefits keeps executive management and executive
sponsors engaged because they are seeing actionable
results. Review metrics on an ongoing basis with those data
owners/stewards who are accountable, the data governance
steering committee, and the executive sponsors.
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Enumerate the costs and the metrics you’ll use to define
success or failure for the data governance project
1.3.5
30 minutes
Instructions
1. Establish metrics for both the business and IT that will be used
to determine if the data governance program is effective.
2. Set targets for each metric.
INPUT
• Business interviews
• IT brainstorming
3. Collect current data to calculate the metrics and establish a
baseline (see next section for data collection practices).
4. Assign an owner for tracking each metric as well as someone
to be accountable for performance.
Metric
Target
% of operational costs reduced
post data governance launch
Level of accuracy for data field
entries
Number of data breaches/noncompliance issues
The more specific your metrics are, the better. Not only will
you know exactly where you are struggling and where you are
succeeding, but meeting more goals will provide inspiration
for the team overseeing data governance.
Materials
• Project Charter
• Whiteboard
• Markers
OUTPUT
• Specific metrics to
measure success of
the program
Participants
• IT Representatives
Accountability for
Tracking
Accountability for
Performance
[Name]
[Name]
[Name]
[Name]
[Name]
[Name]
82%
Of metrics currently used are too
general and can be summarized in
one line: Total IT spending and budget
adherence (Accenture, “Mind the Gap,” 2010)
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Complete the program charter and receive final sign-off to
proceed with the initiative
1.3.6
1 hour
Reinforce understanding of the need for data governance with senior
executives and key stakeholders.
•
Before proceeding with the data governance project, validate
the program charter and metrics with senior sponsors or
stakeholders and receive their consent to proceed.
•
Schedule a 30-60 minute meeting with the senior stakeholders
and conduct a live review of the program charter.
•
Obtaining the necessary stakeholder approval face-to-face
ensures that there are no miscommunications or
misunderstandings around the scope of the work that needs to
be done to reach a successful project outcome.
•
Obtaining approval should be an iterative process; if senior
management has concerns over certain aspects of the plan,
revise and review again.
•
Final sign-off should only take place when consensus has been
reached.
Use Info-Tech’s
Data Governance
Program Charter
Template to get
executive
commitment.
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If you want additional support, have our analysts guide
you through this phase as part of an Info-Tech workshop
Book a workshop with our Info-Tech analysts:
• To accelerate this project, engage your IT team in an Info-Tech workshop with an Info-Tech analyst
team.
• Info-Tech analysts will join you and your team onsite at your location or welcome you to Info-Tech’s
historic Toronto office to participate in an innovative onsite workshop.
• Contact your account manager (www.infotech.com/account), or email Workshops@InfoTech.com for
more information.
The following are sample activities that will be conducted by Info-Tech analysts with your team:
1.1.2a
Interviews with key business units to sell the importance of data
governance, as well as to collaborate with them to understand how
better data governance can help them.
1.1.2c
Conduct deep-dive interviews with 2-3 business units and generate a
business data glossary that will define your key data assets and
assign ownership to them.
An analyst will work with the data governance project team and key business units to
brainstorm the long and short-term data-related strategies for the business and how
improved data governance can help.
An analyst will help the project team coordinate and facilitate deep-dive interviews with
data-enthusiastic business units and establish their uses of the data, what the SoRs are,
and the definitions of the data that will populate the data glossary.
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If you want additional support, have our analysts guide
you through this phase as part of an Info-Tech workshop
Book a workshop with our Info-Tech analysts:
Set expectations within the data governance program team.
1.2.2a
In order to be truly collaborative with the business, IT representatives need to set their
expectations, goals, and pains around data governance as well. This will then allow an
analyst to facilitate brainstorming of alignment strategies and marry the business and IT.
Craft mission and vision statements for the organization.
1.3.1
1.3.6
Using the business unit interviews and IT expectations, an analyst will help the program
team generate a vision and mission statement that will set the stage for the data
governance program and will be key to unifying the organization in tackling data
governance improvement.
Generate a data governance program charter to help secure business
commitment to the program and establish key planning elements of
the program.
For the data governance program to be successful, you need to document key metrics,
timelines, costs, risks, and more at the beginning of the project. Our charter will help you
document these key aspects, as well as get the final sign-off from the business to go
ahead with the project.
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