- Organizations are faced with challenges associated with changing data landscapes, evolving business models, industry disruptions, regulatory and compliance obligations, as well as changing and maturing user landscapes and demands for data.
- Although the need for a data governance program is often evident, organizations often miss the mark.
- Your data governance efforts should be directly aligned to delivering measurable business value by supporting key strategic initiatives, value streams, and underlying business capabilities.
Our Advice
Critical Insight
- Your organization’s value streams and their associated business capabilities require effectively governed data. Without this, you may experience elevated operational costs, missed opportunities, eroded stakeholder satisfaction, and exposure to increased business risk.
- Ensure your data governance program delivers measurable business value by aligning the associated data governance initiatives with the business architecture.
- Data governance must continuously align with the organization’s enterprise governance function. It should not be perceived as a pet project of IT, but rather as an enterprise-wide, business-driven initiative.
Impact and Result
Info-Tech’s approach to establishing and sustaining effective data governance is anchored in the strong alignment of organizational value streams and their business capabilities with key data governance dimensions and initiatives. Info-Tech's approach will help you:
- Align your data governance with enterprise governance, business strategy, and the organizational value streams to ensure the program delivers measurable business value.
- Understand your current data governance capabilities and build out a future state that is right-sized and relevant.
- Define data governance leadership, accountability, and responsibility.
- Ensure data governance is supported by an operating model that effectively manages change and communication and fosters a culture of data excellence.
Member Testimonials
After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.
9.3/10
Overall Impact
$108,021
Average $ Saved
38
Average Days Saved
Client
Experience
Impact
$ Saved
Days Saved
University of Cincinnati
Guided Implementation
10/10
$137K
20
Loeb & Loeb, LLP
Guided Implementation
4/10
N/A
N/A
The meeting with Usman was helpful from the perspective of gaining consensus of our approach. However, we didn't gain anything net new from the cal... Read More
Lifeway Christian Resources
Guided Implementation
9/10
$34,250
23
Waterloo Region District School Board
Workshop
10/10
N/A
N/A
* note - unable to determine time/financial impact at this time Fantastic facilitation - excellent engagement with our team - applicable templat... Read More
Natco Home Group
Guided Implementation
10/10
N/A
N/A
Great discussion with Usman Lakhani regarding data conference and also data classification. Not sure of the hours and dollars impacted yet, but I ... Read More
Winnipeg Airports Authority Inc.
Workshop
10/10
$200K
20
Paul was an amazing facilitator, it was clear that he understands and is passionate about data & data governance. The take-away materials are very ... Read More
Central California Alliance for Health
Guided Implementation
10/10
$274K
100
Crystal's knowledge and experience were clear. She was able to galvanize the teams and to clarify what data governance is all about and why we nee... Read More
Central California Alliance for Health
Workshop
10/10
$137K
120
Crystal was great. She was able to cover a large amount of material in a limited amount of time. Crystal was able to level set the entire team a... Read More
Feed The Children, Inc.
Workshop
10/10
N/A
N/A
Paul did a great job of facilitating the workshop and keeping all participants engaged on a topic that the collective group had very little knowled... Read More
Goodwill Industries of Middle Tennessee, Inc.
Guided Implementation
8/10
$12,330
20
Milwaukee County Department of Administrative Services – Information Management Division (DAS-IMSD)
Workshop
10/10
$68,562
120
Igor was able to adapt to our specific needs without compromising the effectiveness of the workshop. This workshop has supported our team in moving... Read More
Gillette Children's Specialty Healthcare
Workshop
10/10
$548K
50
The best was having a partner marching through this process to see how it all connects together. four days was a lot. But there was a lot of ground... Read More
California Department of Social Services
Workshop
10/10
$137K
65
Paul did a fantastic job facilitating our conversation and helping us identify our vision, missions, and roadmap for moving forward with our data g... Read More
General Conference of Seventh-day Adventists
Guided Implementation
10/10
N/A
N/A
The tools and explanations were very helpful. We appreciated the conversations where you listened and adapted and advised based on our specific needs.
Oregon Parks And Recreation Department
Guided Implementation
9/10
$2,740
5
The President and Fellows of Harvard College, a Massachusetts nonprofit corporation, acting by and through Harvard Business School
Workshop
9/10
$411K
100
From pre-planning, until the last day of the workshop, it felt as if InfoTech was a true partner with us. Paul was terrific at letting the ener... Read More
BC Energy Regulator
Workshop
9/10
N/A
20
It was excellent to have the facilitated process with the right people in the room to develop a shared understanding of different aspects of the da... Read More
California Department of Housing & Community Development
Workshop
7/10
$26,030
10
Dataprise Inc.
Guided Implementation
9/10
$10,960
60
The best was the expert helped narrow down what I need to do in the short term and gave me a starting point. The worst I guess is I still have que... Read More
Allegheny College
Guided Implementation
9/10
$2,740
5
Angola LNG
Guided Implementation
10/10
$2,603
20
Infotech Tools really save time and improve productivity during the project. There are no worst parts based on my experience.
Uber Technologies, Inc.
Guided Implementation
8/10
$1.37M
20
Smile Train
Workshop
10/10
$68,500
60
I must say it was an exceptionally positive and enlightening experience. The workshop was not only well-organized but also tailored to meet the spe... Read More
Data Recognition Corporation
Guided Implementation
10/10
$34,250
10
Ampath Trust
Guided Implementation
10/10
$34,250
60
State of New Mexico - New Mexico Department of Public Safety
Guided Implementation
10/10
N/A
120
I appreciated Crystal's expertise in Data Governance and the discovery discussion. Very helpful.
Caribbean Public Health Agency
Guided Implementation
9/10
$2,742
1
The consultant provided valuable expertise, objectivity, and specialised knowledge that would assist us in establishing our data governance practic... Read More
Delta Dental Plan Of Colorado
Guided Implementation
10/10
$102K
20
Crystal was very good at explaining topics and giving us directioni
Milwaukee County Department of Administrative Services – Information Management Division (DAS-IMSD)
Guided Implementation
10/10
$12,330
32
Langara College
Guided Implementation
10/10
N/A
20
Workshop: Establish Data Governance
Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Establish Business Context and Value
The Purpose
- Identify key business data assets that need to be governed.
- Create a unifying vision for the data governance program.
Key Benefits Achieved
- Understand the value of data governance and how it can help the organization better leverage its data.
- Gain knowledge of how data governance can benefit both IT and the business.
Activities
Outputs
Establish business context, value, and scope of data governance at the organization
Introduction to Info-Tech’s data governance framework
Discuss vision and mission for data governance
Understand your business architecture, including your business capability map and value streams
Build use cases aligned to core business capabilities
- Sample use cases (tied to the business capability map) and a repeatable use case framework
- Vision and mission for data governance
Module 2: Understand Current Data Governance Capabilities and Plot Target-State Levels
The Purpose
- Assess which data contains value and/or risk and determine metrics that will determine how valuable the data is to the organization.
- Assess where the organization currently stands in data governance initiatives.
- Determine gaps between the current and future states of the data governance program.
Key Benefits Achieved
- Gain a holistic understanding of organizational data and how it flows through business units and systems.
- Identify which data should fall under the governance umbrella.
- Determine a practical starting point for the program.
Activities
Outputs
Understand your current data governance capabilities and maturity
- Current state of data governance maturity
Set target-state data governance capabilities
- Definition of target state
Module 3: Build Data Domain to Data Governance Role Mapping
The Purpose
- Determine strategic initiatives and create a roadmap outlining key steps required to get the organization to start enabling data-driven insights.
- Determine timing of the initiatives.
Key Benefits Achieved
- Establish clear direction for the data governance program.
- Step-by-step outline of how to create effective data governance, with true business-IT collaboration.
Activities
Outputs
Evaluate and prioritize performance gaps
Develop and consolidate data governance target-state initiatives
- Target-state data governance initiatives
Define the role of data governance: data domain to data governance role mapping
- Data domain to data governance role mapping
Module 4: Formulate a Plan to Get to Your Target State
The Purpose
- Consolidate the roadmap and other strategies to determine the plan of action from Day One.
- Create the required policies, procedures, and positions for data governance to be sustainable and effective.
Key Benefits Achieved
- Prioritized initiatives with dependencies mapped out.
- A clearly communicated plan for data governance that will have full business backing.
Activities
Outputs
Identify and prioritize next steps
- Initialized roadmap
Define roles and responsibilities and complete a high-level RACI
- Initialized RACI
Wrap-up and discuss next steps and post-workshop support
Establish Data Governance
Deliver measurable business value.
Executive Brief
Analyst Perspective
Establish a data governance program that brings value to your organization.
Data governance does not sit as an island on its own in the organization – it must align with and be driven by your enterprise governance. As you build out data governance in your organization, it’s important to keep in mind that this program is meant to be an enabling framework of oversight and accountabilities for managing, handling, and protecting your company’s data assets. It should never be perceived as bureaucratic or inhibiting to your data users. It should deliver agreed-upon models that are conducive to your organization’s operating culture, offering clarity on who can do what with the data and via what means. Data governance is the key enabler for bringing high-quality, trusted, secure, and discoverable data to the right users across your organization. Promote and drive the responsible and ethical use of data while helping to build and foster an organizational culture of data excellence.
Crystal Singh
Director, Research & Advisory, Data & Analytics Practice
Info-Tech Research Group
Executive Summary
Your Challenge
The amount of data within organizations is growing at an exponential rate, creating a need to adopt a formal approach to governing data. However, many organizations remain uninformed on how to effectively govern their data. Comprehensive data governance should define leadership, accountability, and responsibility related to data use and handling and be supported by a well-oiled operating model and relevant policies and procedures. This will help ensure the right data gets to the right people at the right time, using the right mechanisms.
Common Obstacles
Organizations are faced with challenges associated with changing data landscapes, evolving business models, industry disruptions, regulatory and compliance obligations, and changing and maturing user landscape and demand for data. Although the need for a data governance program is often evident, organizations miss the mark when their data governance efforts are not directly aligned to delivering measurable business value. Initiatives should support key strategic initiatives, as well as value streams and their underlying business capabilities.
Info-Tech’s Approach
Info-Tech’s approach to establishing and sustaining effective data governance is anchored in the strong alignment of organizational value streams and their business capabilities with key data governance dimensions and initiatives. Organizations should:
- Align their data governance with enterprise governance, business strategy and value streams to ensure the program delivers measurable business value.
- Understand their current data governance capabilities so as to build out a future state that is right-sized and relevant.
- Define data leadership, accountability, and responsibility. Support these with an operating model that effectively manages change and communication and fosters a culture of data excellence.
Info-Tech Insight
Your organization’s value streams and the associated business capabilities require effectively governed data. Without this, you face elevated operating costs, missed opportunities, eroded stakeholder satisfaction, and increased business risk.
Your challenge
This research is designed to help organizations build and sustain an effective data governance program.
- Your organization has recognized the need to treat data as a corporate asset for generating business value and/or managing and mitigating risk.
- This has brought data governance to the forefront and highlighted the need to build a performance-driven enterprise program for delivering quality, trusted, and readily consumable data to users.
- An effective data governance program is one that defines leadership, accountability, and responsibility related to data use and handling. It’s supported by a well-oiled operating model and relevant policies and procedures, all of which help build and foster a culture of data excellence where the right users get access to the right data at the right time via the right mechanisms.
As you embark on establishing data governance in your organization, it’s vital to ensure from the get-go that you define the drivers and business context for the program. Data governance should never be attempted without direction on how the program will yield measurable business value.
“Data processing and cleanup can consume more than half of an analytics team’s time, including that of highly paid data scientists, which limits scalability and frustrates employees.” – Petzold, et al., 2020
“The productivity of employees across the organization can suffer.” – Petzold, et al., 2020
Respondents to McKinsey’s 2019 Global Data Transformation Survey reported that an average of 30% of their total enterprise time was spent on non-value-added tasks because of poor data quality and availability. – Petzold, et al., 2020
Common obstacles
Some of the barriers that make data governance difficult to address for many organizations include:
- Gaps in communicating the strategic value of data and data governance to the organization. This is vital for securing senior leadership buy-in and support, which, in turn, is crucial for sustained success of the data governance program.
- Misinterpretation or a lack of understanding about data governance, including what it means for the organization and the individual data user.
- A perception that data governance is inhibiting or an added layer of bureaucracy or complication rather than an enabling and empowering framework for stakeholders in their use and handling of data.
- Embarking on data governance without firmly substantiating and understanding the organizational drivers for doing so. How is data governance going to support the organization’s value streams and their various business capabilities?
- Neglecting to define and measure success and performance. Just as in any other enterprise initiative, you have to be able to demonstrate an ROI for time, resources and funding. These metrics must demonstrate the measurable business value that data governance brings to the organization.
- Failure to align data governance with enterprise governance.
78% of companies (and 92% of top-tier companies) have a corporate initiative to become more data-driven. – Alation, 2020
But despite these ambitions, there appears to be a “data culture disconnect” – 58% of leaders overestimate the current data culture of their enterprises, giving a grade higher than the one produced by the study. – Fregoni, 2020
The strategic value of data
Power intelligent and transformative organizational performance through leveraging data.
Respond to industry disruptors
Optimize the way you serve your stakeholders and customers
Develop products and services to meet ever-evolving needs
Manage operations and mitigate risk
Harness the value of your data
The journey to being data-driven
The journey to declaring that you are a data-driven organization requires a pit stop at data enablement.
The Data Economy
Data Disengaged
You have a low appetite for data and rarely use data for decision making.
Data Enabled
Technology, data architecture, and people and processes are optimized and supported by data governance.
Data Driven
You are differentiating and competing on data and analytics; described as a “data first” organization. You’re collaborating through data. Data is an asset.
Data governance is essential for any organization that makes decisions about how it uses its data.
Data governance is an enabling framework of decision rights, responsibilities, and accountabilities for data assets across the enterprise.
Data governance is:
- Executed according to agreed-upon models that describe who can take what actions with what information, when, and using what methods (Olavsrud, 2021).
- True business-IT collaboration that will lead to increased consistency and confidence in data to support decision making. This, in turn, helps fuel innovation and growth.
If done correctly, data governance is not:
- An annoying, finger-waving roadblock in the way of getting things done.
- Meant to solve all data-related business or IT problems in an organization.
- An inhibitor or impediment to using and sharing data.
Info-Tech’s Data Governance Framework
Create impactful data governance by embedding it within enterprise governance
Organizational drivers for data governance
Data governance personas:
Conformance: Establishing data governance to meet regulations and compliance requirements.
Performance: Establishing data governance to fuel data-driven decision making for driving business value and managing and mitigating business risk.
Data Governance is not a one-person show
- Data governance needs a leader and a home. Define who is going to be leading, driving, and steering data governance in your organization.
- Senior executive leaders play a crucial role in championing and bringing visibility to the value of data and data governance. This is vital for building and fostering a culture of data excellence.
- Effective data governance comes with business and IT alignment, collaboration, and formally defined roles around data leadership, ownership, and stewardship.
Traditional data governance organizational structure
A traditional structure includes committees and roles that span across strategic, tactical, and operational duties. There is no one-size-fits-all data governance structure. However, most organizations follow a similar pattern when establishing committees, councils, and cross-functional groups. Most organizations strive to identify roles and responsibilities at a strategic and operational level. Several factors will influence the structure of the program, such as the focus of the data governance project and the maturity and size of the organization.
A healthy data culture is key to amplifying the power of your data.
“Albert Einstein is said to have remarked, ‘The world cannot be changed without changing our thinking.’ What is clear is that the greatest barrier to data success today is business culture, not lagging technology. “– Randy Bean, 2020
What does it look like?
- Everybody knows the data.
- Everybody trusts the data.
- Everybody talks about the data.
“It is not enough for companies to embrace modern data architectures, agile methodologies, and integrated business-data teams, or to establish centers of excellence to accelerate data initiatives, when only about 1 in 4 executives reported that their organization has successfully forged a data culture.”– Randy Bean, 2020
Data literacy is an essential part of a data-driven culture
- In a data-driven culture, decisions are made based on data evidence, not on gut instinct.
- Data often has untapped potential. A data-driven culture builds tools and skills, builds users’ trust in the condition and sources of data, and raises the data skills and understanding among their people on the front lines.
- Building a data culture takes an ongoing investment of time, effort, and money. This investment will not achieve the transformation you want without data literacy at the grassroots level.
Data-driven culture = “data matters to our company”
Despite investments in data initiative, organizations are carrying high levels of data debt
Data debt is “the accumulated cost that is associated with the sub-optimal governance of data assets in an enterprise, like technical debt.”
Data debt is a problem for 78% of organizations.
40% of organizations say individuals within the business do not trust data insights.
66% of organizations say a backlog of data debt is impacting new data management initiatives.
33% of organizations are not able to get value from a new system or technology investment.
30% of organizations are unable to become data-driven.
Source: Experian, 2020
Absent or sub-optimal data governance leads to data debt
Only 3% of companies’ data meets basic quality standards. (Source: Nagle, et al., 2017)
Organizations suspect 28% of their customer and prospect data is inaccurate in some way. (Source: Experian, 2020)
Only 51% of organizations consider the current state of their CRM or ERP data to be clean, allowing them to fully leverage it. (Source: Experian, 2020)
35% of organizations say they’re not able to see a ROI for data management initiatives. (Source: Experian, 2020)
Embrace the technology
Make the available data governance tools and technology work for you:
- Data catalog
- Business data glossary
- Data lineage
- Metadata management
While data governance tools and technologies are no panacea, leverage their automated and AI-enabled capabilities to augment your data governance program.
Measure success to demonstrate tangible business value
Put data governance into the context of the business:
- Tie the value of data governance and its initiatives back to the business capabilities that are enabled.
- Leverage the KPIs of those business capabilities to demonstrate tangible and measurable value. Use terms and language that will resonate with senior leadership.
Don’t let measurement be an afterthought:
Start substantiating early on how you are going to measure success as your data governance program evolves.
Build a right-sized roadmap
Formulate an actionable roadmap that is right-sized to deliver value in your organization.
Key considerations:
- When building your data governance roadmap, ensure you do so through an enterprise lens. Be cognizant of other initiatives that might be coming down the pipeline that may require you to align your data governance milestones accordingly.
- Apart from doing your planning with consideration for other big projects or launches that might be in-flight and require the time and attention of your data governance partners, also be mindful of the more routine yet still demanding initiatives.
- When doing your roadmapping, consider factors like the organization’s fiscal cycle, typical or potential year-end demands, and monthly/quarterly reporting periods and audits. Initiatives such as these are likely to monopolize the time and focus of personnel key to delivering on your data governance milestones.
Sample milestones:
Data Governance Leadership & Org Structure Definition
Define the home for data governance and other key roles around ownership and stewardship, as approved by senior leadership.
Data Governance Charter and Policies
Create a charter for your program and build/refresh associated policies.
Data Culture Survey
Understand the organization’s current data culture, perception of data, value of data, and knowledge gaps.
Use Case Build and Prioritization
Build a use case that is tied to business capabilities. Prioritize accordingly.
Business Data Glossary
Build and/or refresh the business’ glossary for addressing data definitions and standardization issues.
Tools & Technology
Explore the tools and technology offering in the data governance space that would serve as an enabler to the program. (e.g. RFI, RFP).