Resource Person:

Resource Person:
Dr. JAYSON D. VELASCO
Data Driven Teacher III/ Subject Group Head, SHS
Department of Education, DDSNHS

Governance 2016- Senior High School Teacher

Dupax del Sur NHS
Competency 2013- Instructor, Isabela State University
Echague Campus, IICT Department
Guide 2013- Data Documentator- World Vision North
Luzon Cluster.
2011- Faculty, Saint Mary’s University
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 Being Competent
“A competent person has definitive
understanding, skills and character needed to
perform
at a given level of
performance
standard,
the decision and work associated to the mandated
function and outcome of a defined strategy and
operation of the organization.
 Being Competent

It is indicated by the person’s

ability to transfer and apply
knowledge, skills and attitude

to new situations, and to the

requirement of collaborative results.
 Competency Model

A competency model is about

shareable body of knowledge
believed to define and differentiate
the essential indicators of the
required understanding, action and
attitude behind the successful
delivery of the service objectives.
Competency Model

(Center for Creative

Leadership
Morgan McCall
Michael M. Lombardo
Robert A. Eichinger)
Performance Standards

“Standards are the distilled

wisdom of people with expertise
in their subject matter and who
know the needs of the
organizations they represent –
people such as manufacturers,
sellers, buyers, customers, trade
associations, users or
regulators.”
Performance Standards
“Standards are document,
established by consensus and
approved by a recognized body,
which provides for common and
repeated use, rules, guidelines or
characteristics for activities or their
results, aimed at the achievement
of the optimum degree of order in a
given context.” (PMI)
Performance Methodology
It is a combination of logically related
practices, processes, rules and procedures
that determine how best to communicate
and to contextually do the details of the
collaborative work related to planning,
designing, implementing and improving the
data driven approach behind the exercise of
“decision rights” called governance.
Performance Methodology
It secures the presence and agreement
about the common language, common
processes, common rules, and common
documentation in the delivery and
support of the data driven governance
program and project as defined and
agreed with the stakeholders.
Performance Methodology
A good performance methodology
provides the framework, processes,
guidelines and techniques to achieve
the performance objectives of data
driven governance that are agreed by
the stakeholders, development team,
and service users.
Performance Methodology
A good methodology makes the
“possible” of succeeding the data driven
governance outcome and therefore
provides value to the stakeholders and
customers of the organization.
Training Questions of Understanding

1. What are the key result areas and performance

indicators of governance in an organization
or government agency?

2. What is the motivation, design,

methodology, and technology of data
driven approach in governance?
 Training Questions of Understanding
3. What are the key result areas and performance
indicators of data management, data
governance, data quality, and data
privacy that support data driven governance
4. system
How dowith effectiveness,
digital efficiency and
transformative
security?
technologies enable the achievement,
improvement and continuity of data driven
governance objectives?
 Training Questions of Understanding

5. How data driven governance is a necessary

component in the quality management
system, ease of doing business and data
privacy of a government agency? (E.O.
605-2007., R.A.11032, and R.A.10173)
 Data Driven Approach
Data Driven to Governance
Governance Regulatory and Standards Context
Competency Guide of Data Driven Governance

Data Management Framework of

Data Driven Governance

Data Quality Framework of Data

Driven Governance

Digital Transformative Technologies

of Data Driven Governance
 Data Driven
Approach
Data Driven
The leadership and management of
quality performance creates and
achieves their strategy, tactical and
operational decisions
based on real-time and/or re-use stored
data that are digitally gathered,
transmitted, integrated, analyzed, and
interpreted in order to achieve the
 Data Driven
Approach
Data Driven
It is a business term that refers to
the utilization of connected data
from varied sources and format to
inform or enhance policies,
processes, decision, option,
control, intervention, action, and
the revenue model.
 Data Driven
Approach
Data-Driven Decision Making
It is an organized and a standard
practice of collecting data, analyzing
data , and creating understanding,
options and decisions based on the
insights derived from the
communicated and secured
information.
 Data Driven
Approach
Data-Driven Decision Making
A data-driven decision making
process prevents or eliminates
decisions based on hard selling or
marketing, influence peddling, gut
feeling, instinct, tradition, theory,
or personality.
 Data Driven
Approach
Data-Driven Decision Making

Data-driven decisions constructs

options with objectivity that can be
easily evaluated according to their
impact on established performance
metrics of governance.
 Data Driven Approach
Implementation
1. Data-driven agrees and creates the principle, policy,
people, process, procedure, product, and provider
that enables the valid, verifiable,
acceptable and actionable
management of data, analytical
tools and technology
to deliver and support
evidence-based performance of governance
 Data Driven Approach
Implementation
2. Data-driven creates and maintains
quality performance management system
that is backed by quality
standards assured models of
process, data, application and
technology for an evidence-
based exercise of decision
rights.
 Data Driven Approach
Implementation
3. Data driven maintains inventory of all the
informationthat
assets
are associated to the capture,
transmission, processing, storage,
integration, utilization, sharing, analytic,
security
that areand archiving
related to the of data,
continuously
improved business and information and
technology reference architecture of the
organization.
Data Driven Approach
Implementation
4. Data driven performs
assessment of data risks by
identifying, analyzing,
evaluating and treating the
threats coming from failed
data quality requirements
and undermined
information security.
Data Driven Approach
Implementation
5. Data driven develops data-
drive-culture in the
organization’s management
practice.of organizational
The C-level
management is the “champion”
in the actual use of data and
analytics in all aspect of
decision making.
Data Driven Approach Success
Factors
1. Ability to create, gather, integrate and
secure digital data
2. Ability to deduce intelligence and insights
from digitally stored and networked data and
information.
3. Ability to decide and formulate actions
based upon the results of the data analytics.
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 Governance with Data Driven
Approach
Question of Understanding
“What are the rules and standards of
governance and data driven approach
that must be elicited, elaborated,
analysed and applied to the
implementation of valid, verifiable,
acceptable and actionable data driven
governance program or project?”
 Governance in Government Context
Governance Defined
“It is the manner in
which power is exercised
in the management of a
country’s economic and
social resources for
development.”
(World Bank)
Governance in Government Context
Governance Elements
1.Process by which governments are selected,
monitored and replaced
2.Capacity of the government to effectively
formulate and implement sound policies
3.Respect of citizens and the state for the
institutions that govern economic and social
interactions among them.
(World Bank)
Governance in Government Context
Worldwide Governance Indicators
1. Voice and Accountability:
Perceptions of the extent to which a country’s
citizens are able to participate in selecting
their government, as well as freedom of
expression, freedom of association, and a free
media
(World Bank)
Governance in Government Context
Worldwide Governance Indicators
2. Government Effectiveness:
Perceptions of the quality of public services,
the quality of the civil service and the degree
of its independence from political pressures,
the quality of policy formulation and
implementation, and the credibility of the
government’s commitment to such policies
(World Bank)
Governance in Government Context
Worldwide Governance Indicators
3. Rule of Law: reflects perceptions of the
extent to which agents have confidence in
and abide by the rules of society, and in
particular the quality of contract enforcement,
property rights, the police, and the courts, as
well as the likelihood of crime and violence
Governance in Government Context
Worldwide Governance Indicators
4. Regulatory Quality:
Perceptions of the ability of the government
to formulate and implement sound policies
and regulations that permit and promote
private sector development
(World Bank)
Governance in Government Context
Worldwide Governance Indicators
5. Control of Corruption:
Perceptions of the extent to which public
power is exercised for private gain, including
both petty and grand forms of corruption, as
well as “capture” of the state by elites and
private interests
(World Bank)
Governance in Government Context
Worldwide Governance Indicators
6. Political Stability and Absence of Violence/
Terrorism:
Perceptions of the likelihood of political
instability and/or politically-motivated violence,
including terrorism
(World Bank)
 Governance with Data Driven Approach
Governance Outcomes
Governance Outcome Performance Indicators
1. Effective The organization is true to its
performance. purpose, performs as required,
realizes value for stakeholders
and remains in compliance with
its policies and stakeholder
expectations
(ISO 37000 -6)
 Governance with Data Driven Approach
Governance Outcomes
Governance Outcome Performance Indicators
2. Responsible The organization makes use of
stewardship resources in a responsible manner,
effectively balancing negative and
positive impacts, considering its
global context and ensuring its
long-term sustainability;
(ISO 37000 -6)
 Governance with Data Driven Approach
Governance Outcomes
Governance Performance Indicators
Outcome
3. Ethical behavior The organization demonstrates:
accountability, accurately and timely
reporting on its performance and
stewardship of resources; fairness in its
treatment of and engagement with
stakeholders; integrity and transparency in
fulfilling its obligations and commitments;
(ISO 37000 -6) and competence and probity in the manner
 Governance with Data Driven Approach
Governance Outcomes Regulatory Complianc
Governance Outcome Regulatory Compliance
1. Effective Performance 1.E.O. 605 – 2007 QMS
2.R.A. 11032 – EODB
 Governance with Data Driven Approach
Governance Outcomes Regulatory Complianc
Governance Outcome Regulatory Compliance
2. Responsible Stewardship 1.R.A. 9184
2.COA Rules and
Regulation
 Governance with Data Driven Approach
Governance Outcomes Regulatory Complianc
Governance Outcome Regulatory Compliance
3. Ethical behaviour 1.R.A. 3019- Anti Graft
2.R.A. 6713 – Ethical
Standards
 Governance and Data Driven Approach
Governance Data Driven Principles
“The governing body should
recognize data as valuable
resource for decision making
by the organization and
others.”
(ISO 37000 – 7.8.1)
 Governance and Data Driven Approach
Governance and Data Driven Practice
Principle Description
Practice
1. Use The governing body uses data from many sources to
make decision for the organization.
appropriate data
Decision making has the required quality of information
for decision
Exercise the right and responsibility to determine and
making receive the information it requires, including the
appropriate data collection methods, preparation and
timely delivery of information
(ISO 37000 – 7)
Have diverse inputs into a rigorous, open and
transparent decision-making process to better
 Governance and Data Driven Approach
Governance and Data Driven Practice
Principle Practice Description
2. Recognize data Understand its use and potential use by the organization
and others (e.g. suppliers, customers,,regulators and
as a strategic other stakeholders as well as competitors and those who
resource misuse the data)
Acknowledge the complexities and evolutionary nature
of data and establish governance policies and direction
that aligns with the organization’s needs and the degree
of change
(ISO 37000 – 7) Ensure that the information requirements of the
organization are sufficiently supported by its current
 Governance and Data Driven Approach
Governance and Data Driven Practice
Principle Practice Description
3. Ensure In the midst of new technology it the responsibility
of governing bodies to ensure that valuable
responsible data opportunities are leveraged, while sensitive data is
treatment protected and secured.
Have sufficient oversight associated with the use of
data and its supporting technology to ensureit
(ISO 37000 – 7) remains within its established risk appetite.
 Governance and Data Driven Approach
Governance Quality Management Principle
Principle Performance Indicators
Principle 6: 1. Determine, measure and monitor key indicators to
demonstrate the organization’s performance.
Evidence- 2. Make all data needed available to the relevant people. Ensure
based decision that data and information are sufficiently accurate, reliable
making and secure.
3. Analyze and evaluate data and information using suitable
methods.
4. Ensure people are competent to analyse and evaluate data
as needed.
5. Make decisions and take actions based on evidence, balanced
(ISO 9000) with experience and intuition.
 Governance and Data Driven Approach
Governance Quality in Project Principle
Principle Performance Indicators
Project 1. Effective decisions are based on the analysis of data and
information
Evidence- 2. Information about the project’s progress and performance
based decision should be recorded
making 3. Performance and progress evaluations should be carried out
periodically in order to assess the project status
4. The project organization should analyze the information
from performance and progress evaluations to make
effective decisions regarding the project and for revising the
(ISO 10006 -5.2.7)
project management plan .
 Governance and Data Driven Approach
Governance Digital Development Principle
Principle Performance Indicators
Be Data Driven 1. Design programs so that impact can be measured
continuously and incrementally, focusing on
outcomes, not just outputs.
2. Make use of existing data, including open data sets
and data from interoperable systems.
3. Use rigorous data collection methods. Consider and
address potential biases and gaps in the data collected,
perform data quality checks, and maintain strong
documentation behind collected data.

digitalprinciples.org
 Governance and Data Driven Approach
Governance Digital Development Principle
Principle Performance Indicators
Be Data Driven 4. Close knowledge gaps by contributing data to the
development community and using data and
interoperability standards.
5. Use quality real-time or timely data to support
rapid decision making, improve programming for
users and inform strategy.
6. Present data in formats that are easy to
interpret and act on, such as data visualizations.
 Governance and Data Driven Approach
Governance Digital Development Principle
Principle Performance Indicators

Be Data 7. Create a data use culture by prioritizing capacity

building and data use efforts across all stakeholder
Driven groups, including the groups whose data are being
collected.
8. Be holistic about data collection and analysis. Collect
data from multiple sources, and use a mix of data
collection and analysis methods. Analyze your data
collaboratively with stakeholders.
9. Identify and use open data and interoperability
standards.
digitalprinciples.org 10. Collect and use data responsibly according to
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Data Management Knowledge Areas
 Data Reference &
Security Master Data
Management Management Data
Database Warehousing
Operations & Business
Management Intelligence
Management

Document &
Data
Content
Development
Management

Data
Meta Data
Architecture
Management
Management

Data Handling DATA Data Quality

Ethics GOVERNANCE Management

Data Management Body of Knowledge (DAMABOK)

Data Quality Knowledge Areas
Inherent Data Quality
ISO 25012
1. Accuracy

2. Completeness

3. Consistency 4. Credibility

5.
Currentness
System Dependent Data Quality
ISO 25012
1. Accessibility

2. Compliance 5. Precision

3. Confidentiality 6. Traceability

4. Efficiency 7. Understandability

8. Availability

9. Portability

10. Recoverability
ISO 8000-150
Data
Quality
Management
Framework
Data Security and Privacy Knowledge Areas
 R.A.
3. DATA PRIVACY RIGHTS 10173 – DATA PRIVACY ACT 4. PRIVACY
1. INFORM REGULATED
2. OBJECTDATA SUBJECT 1. PERSONAL
3. ACCESS 1. Personal Information
DATA 1. Business DATA PROCESSING
1. Collection
4. RECTIFY 2. Sensitive Personal Information Process
2. Retention
5. ERASE 3. Privileged Information Events
6. BLOCK 2. Information 3. Use
7. PORTABLE 2. DATA System 4. Sharing
8. COMPLAIN
9. DAMAGE CLAIM
PROTECTION Functions 5. Disposal
Regulatory
ACCOUNTABILIT
-National
Y Privacy 5. Indicators of Data Privacy
6. DATA PRIVACY VIOLATION Commission
1. Unauthorized processing Protection and Controls
2. Negligence in access Compliance 1. Data Privacy Principles
3. Improper disposal -Personal Information Controller 2. Criteria Lawful Processing
4. Unauthorized purpose
-Personal Information Processor 3. Condition SPI Processing
5. Unauthorized access
4. Security Measures
6.
7.
Intentional breach
Concealed breach
Oversight 5. ISO 29100 Privacy Framework
8. Malicious disclosure -Data Protection Officer 6. ISO 29151 Privacy Controls
7. ISO 27001 IS Security Control
9.
10.
Unauthorized disclosure
Combination of unwanted act
7. RISKS ASSESSMENT -Compliance Officer on Privacy 8. ISO 27701 IS Privacy Management

IMPACT THREATS VULNERABILITIES

Violation Penalty Unlawful acts on collection, use, retention, disclosure, disposal; Lack of control policy, means to assess and
Lost reputation and trust misrepresentation; denial of service; theft, human negligence/error, validate-verify, weak decision rights, poor
Financial liability data loss, competency
PRIVACY AND SECURITY MANAGEMENT: CONTROL MEASURES:
Compliance Organization, Policy Development, Risks Management, Security Organization, Physical & Technical Measures of
Operation, Incident Response Team, Breach Reporting, and Complaint Handling Personal Information Protection
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Training Activity
Governance Outcome and Value of Data
Governance Outcome Data Related Risks
1.

3.
3
Governance Outcome and Regulatory Compliance
Performance Areas Practice Standards
1. Quality Management 1. Internation Standards Organization
2. Professional Organization
2. Business Process 3. Competency Framework Product
Management
3. Program Management
4. Project Management
5. Financial Management
6. Asset Management
7. Human Resource
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 Searched Link to Knowledge Source

1. Governance in Organization
https://www.wfeo.org/wp-content/uploads/members/Webinars/ISO-TC309-Draft%20ISO%2037000_Governance
%20of%20Organisations%20for%20comment%20June%202020_WFEO.pdf

2. Data Management
https://www.scribd.com/document/433871646/DAMA-International-DAMA-DMBOK-2nd-Edition-Data-Manage
ment-Body-of-Knowledge-Technics-Publications-2017-pdf

3. Data Quality
https://iso25000.com/index.php/en/iso-25000-standards/iso-25012

4. Data Governance
https://www.dpadvantage.co.uk/wp-content/uploads/2018/03/DPA-White-Paper-ISO-8000-Part-150-1-1.pdf

5. Data Privacy
https://standards.iso.org/ittf/PubliclyAvailableStandards/c045123_ISO_IEC_29100_2011
.zip