This document provides an overview of data governance and how to implement it within an organization. It discusses why data governance is important, especially in a post-COVID era, and the impacts of not having it. It defines the key components of a data governance organizing framework including strategy, directives, organization, technology, measurement, and change management. It then discusses how to practically implement data governance using an agile embedded approach and considering it as a business capability. Critical success factors and 5 key takeaways are also presented.
2. AGENDA
WHY WHAT HOW
Explaining why Data Governance is
important for your business and how
it will evolve in a post covid-19 era.
01
What does Data Governance actually
mean? Going in depth into the Data
Governance Organizing Framework.
02
How can you practically implement
Data Governance within your
organization?
03
Explaining some critical success factors
you should take into account within your
Data Governance program.
CRITICAL SUCCESS
FACTORS
04
Emphasizing 5 key takeaways for you
to get going with Data Governance.
KEY TAKEAWAYS
05
4. POST COVID-19 ERA
IMPORTANCE OF DATA GOVERNANCE
The covid-19 pandemic period turned out to be
the biggest digital stress test for a majority of
organizations. Balancing privacy with
accessibility, accuracy versus speed, ensuring that
the organization's data is available as needed for
business purposes but that it also remains secure
and private under all circumstances.
Being successful in the new normal will entail a
systematic approach that emphasizes creating
and sharing value, using clear rules created
through broad agreement. Having an effective
data governance plan is key in this approach.
5. IMPACT OF NOT HAVING
DATA GOVERNANCE
DATA OF POOR QUALITY
Not properly governing data often
leads to bad data of poor quality. This
in turn will have a huge impact on the
quality, effectiveness and results
within your data value chain. Think
about the impact bad data can have
on your Artificial Intelligence,
Analytics, or decision-making
processes.
COSTS
The further ungoverned data flows
through your organization, the more
potentially expensive it gets to
address the issues it causes. Consider
the potential costs that missing,
duplicated, incorrect, non-
standardised or even incorrectly
interpreted data can entail.
NON COMPLIANCE
Not knowing if your data is compliant
with regulations puts you in great risk
of legal, financial or reputational
retributions.
6. MANAGING YOUR ASSETS
PEOPLE
People are everywhere
within an organization and
are considered to be one of
the most important assets.
DATA
Data is also everywhere in
an organization and is
increasingly seen as an
important and valuable
asset as well.
HR
MANAGEMENT
Human Resource
Management is the
organizing framework that
establishes the strategy,
objectives, and policy for
effectively and consistently
managing people.
DATA
GOVERNANCE
Just as HRM is Data
Governance the organizing
framework for effectively
and consistently managing
corporate data as an asset.
17. Business Benefits
data trapped in silos
numerous and recurring
data errors
example
established 3 data governance bodies
developed and implemented data quality “cookbooks”
supporting training programs
annual review
Business Problem
Governance Solutions
Increase in revenue of $2.4M
Cost savings realized of $4.8M
Financial Services
18. WHAT’S IN IT
FOR ME?
REDUCING COSTS
IMPROVING REVENUES
MITIGATING RISKS
20. HOW IMPLEMENTING DATA
GOVERNANCE
BIG BANG
Implementing data governance
through a sudden big bang
approach can have a disruptive
effect on your organization. You risk
being perceived as a data
governance terrorist and can be
culturally harmful.
The first change is to get the
organization data literate, because
in the end there are behaviors that
people must change.
It’s an evolution, not a revolution.
AGILE EMBEDDED
Using a more agile and iterative
approach will allow you to embed
data governance within the fabric
of the organization. If you want
data governance to stick, you need
to manage the organization’s
behavior changes. That’s why
change management is
indispensable.
Another good approach is to
perceive data governance as a
service within your organization.
A shared service of support,
awareness and decision making
so that everyone can adopt data
governance practices.
22. DATA GOVERNANCE
PROJECT PLANNING
Roll out in a thin-slice manner, using an incremental,
collaborative process to bring people, processes and IT along.
23. DATA QUALITY
PROPOSAL OF FIRST PROJECTS
DATA
STEWARDSHIP
BUSINESS GLOSSARY
& METADATA
FOUNDATIONAL
DG ACTIVITIES
MASTER DATA
MANAGEMENT
24. THE COST OF
DATA GOVERNANCE
THE NET COST OF DG IS ZERO
While the net cost of DG, over time, is zero,
there must be the understanding that
formal activity is required to ensure you
reach the zero-sum state.
Don’t forget to consider the cost of
nongovernance or continuing to use
information in a poorly managed fashion.
32. 5 KEY TAKEAWAYS
Data Governance is a
journey
Get your organization
data literate
The key is culture
Consider Data
Governance as a
business capability
Embed Data
Governance in an agile
thin-slice manner
#1 #3 #5
#4#2
33. THANKS
Does anyone have any questions?
Presentation created by Mathias Vercauteren
mathias.vercauteren@sbiconsulting.be
+32 473 833 122
www.sbiconsulting.be
34. This is where you give credit to the ones who are part of
this project.
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Notes de l'éditeur
Analogy to HR:
Employees are everywhere in the enterprise, that’s why HR considers “people” as an asset.
HR creates enterprise-wide guidelines on areas that include how to interview, hire and promote people and what benefits you can offer employees.
HR sets policies and provides support.
HR communicates tools and systems to use.
Its goal is to enable departments to make these HR practices consistent across the company. It doesn’t execute on all the HR practices itself!
Similarities with Data Governance:
Data is also everywhere in the enterprise — and is an asset, just like its employees.
Data Governance creates guidelines or policies on how data should be created, managed, shared, used and ultimately archived or deleted.
Data Governance should enable the organization, just like HR, to govern the data on their own, by providing templates, standards, tools, systems and expertise to support the data lifecycle and facilitate consistency.
Like HR, Data Governance should not execute on all the data practices itself. It’s impossible for Data Governance to create or manage all of the data in the enterprise.
Data Governance is, like HR, an enterprise-wide service, not a program or a project.
In the post covid-19 era, transformation of businesses to become more data driven and digital will will only increase at an unseen pace.
The essence of this transformation and the emphasis will be on Data Monetization. Monetizing your data assets will be of vital importance if you’d want to remain competitive and survive & thrive in the new normal (or how Peter Hinssen like’s to call it, the “Day after Tomorrow”).
Most importantly, Data Governance is the core capability to ensure monetization success.
Another core concept that will become of increasing importance is “Infonomics”. Infonomics is the title of Doug Laney’s book on how to look at data as a true asset in an accounting sense. Data Governance is key to any formal recognition of data value.
Linked to that is the concept of “Data Debt”.
Mismanagement of data creates a debt accumulation situation. The longer you keep doing dumb things with data, the more expensive or the bigger disaster you will have when you need to or want to fix it. Think of DG as the data debt repayment process.
Transforming your business isn’t just a matter of installing the latest technologies and hiring a bunch of data scientist. It isn’t just plug & play.
It’s a matter of embedding a whole new mindset in the fabric of your organization. A 21th century mindset, build for the future.
You need to leverage change management principles to develop data literacy amongst your employees and stakeholders.
To make an analogy here. This isn’t the first time this transformation occurs. Think back to the 19th century industrial factories, where people were just a simple commodity without any rights.
The development of the mindset that people where a vital asset to a company and the surge of Human Resource Management, Talent Development and Acquisition and so one illustrates the Human Driven Business Transformation. History repeats itself, but this time with a totally different asset called “data”.
Data governance is the organizing framework for establishing the strategy, objectives and policy for effectively managing corporate data.
It consists of the processes, policies, organization and technologies required to manage and ensure the availability, usability, integrity, consistency, auditability and security of our data.
A data governance program consists of the inter-workings of 7 core components
Market example of the benefits of governance for a financial servicing company.
Business problem:
Data trapped in isolated silos could not be leveraged across organizational business functions
Numerous and recurring data entry errors by company representatives, compounded by use in support of financial and regulatory reporting
Governance:
Established three new teams with enterprise-wide responsibility: data governance office, data governance council and data quality services
Developed and implemented data quality “cookbooks” and supporting custom training programs to make clear roles and responsibilities
Annual review assessing governance outcomes and projects (business + IT)
Business benefit:
Initial pilot increased revenue by $2.4M for first 2 years based upon estimated $50M increase in loan volume
Cost savings realized of $4.8M through implementation of email campaigns
Source: Gartner
Reducing costs
Boost the Digital Transformation to increase efficiency within processes and reduce costs
Ensure management decisions are taken based on right information to enable cost-efficient investments, support the new digital strategy, …
Ensure qualitative and transparent data to decrease the cost of FTE spending hours searching, fixing and manipulating incorrect data
Improving Revenues
Provide better insights by maximizing data exploitation to enable opportunities for increasing revenue, improve quarter end closing process, …
Create value for the customer considering and respecting his/her privacy to boost (digital) customer experience and support business growth
Create new sources of revenues to optimize sales conversion, reduce time to market for new products, …
Mitigating risks
Ensuring compliancy to Supervisory Authorities requirements to mitigate legal, financial (penalties) and reputation risk
Data governance is at the center of data management activities, since governance is required for consistency within and balance between the different knowledge areas (DAMA - Data Administration Management Association).
“A data governance program enables an organization to be data-driven, by putting in place the strategy and supporting principles, policies, and stewardship practices that ensure the organization recognizes and acts on opportunities to get value from its data.” (DAMA)
Foundational activities:
Data Quality Management
Metadata Management
Data Protection (Privacy, Security, Risk)
Below entails the lifecycle management.
Plan & Design
Data Architecture / Data Modeling / Design
Enable & Maintain
Big Data Storage / Data Warehousing / Master Data Management / Data Storage & Operations / Reference Data Management / Data Integration & Interoperability
Use & Enhance
Data Science & AI / Data Visualization / Data Monetization / Predictive Analytics / Master Data Usage / Business Intelligence / Document & Content Management
A “capability” means that you have the ability to do something.
A business capability is an enterprise level expression of how it's going to go about doing its business.
It is the expression or the articulation of the capacity, materials and expertise an organization needs in order to perform core functions.
Similar like Human Resource Management for people assets and Supply Chain Management for product assets, also Data Governance has specific and essential capabilities related to managing data assets. It’s the answer to WHAT needs to be done to manage data.
Costs of data quality issues
Costs of missed opportunities
Data debt
Data Governance is a journey. Companies want to embrace all of the benefits but not the work to get there. It is not overwhelming work, but it requires a few changes.
DG must be more than just a bullet point on a slide for the leadership retreat. Will organizations have the will to make the change required?
Experience has shown the first change is to get the organization data literate. There are behaviors that people must change. But the goal is to have data management as much a part of organization language as budgets and risk. There are smart people in business, and this is not hard, but the literacy aspect means there is no focus on the data issues. There are guru platitudes, but literacy goes deeper.
The key is Culture—the key to success with AI and analytics is to manage the people, then the data. Look at Costco—culture permeates the organization’s success. Data requires the same
Organizations have to adopt principles and policies that address their longstanding abuse of operational data, and they will need to wean themselves off of inappropriate use of spreadsheets and Access databases. They need to understand that governance of data usage privacy and ethics are required to allow the 21st century opportunities that abound in data to flourish. AI will hurt people if there is no data quality. Advanced analytics will continue biased models without better oversight of algorithms
Consider Data Governance as a business capability. Data governance and management are market driven—you either have these capabilities in place or your business cannot achieve maximum potential.
Embed Data Governance in an agile thin-slice manner
