The ability of a government to deliver policies and effective services for its citizens depends on the quality of its public servants. Governments are also significant employers in APO members. The World Bank’s Bureaucracy Lab (2018) reported that 39% of formal employment in East Asia and the Pacific was in the public sector. This means that human resources (HR) practices in the public sector directly affect many workers in the region.
Governments face challenges in designing HR practices to improve employee recruitment, performance, and retention. These challenges are amplified by globalization, increasing knowledge work, accelerating technological advances, and rising competition, which make it vital for government agencies to hire and manage new forms of human capital. The COVID-19 pandemic compelled governments to consider new ways of working including remote work and HR management under novel arrangements. HR strategy has therefore become central to supporting public-sector productivity and effective governance. A comprehensive HR strategy should address recruitment, performance management, and staff development.
This course will itroduce emerging HR practices in the public sector. It will lay out the principles and components of HR management for public-sector professionals and support decision-making to improve employee recruitment, performance, and retention in modern public service.
The main objectives of this course are:
This e-learning course will cover the following modules: Module 1: Overview of HR management and strategy in the public sector Implications of
HR strategies to deal with changes that have occurred in the public sector as a result of new public management.Module 2: Strategic workforce planning: Recruitment, selection, and placement The key role of workforce planning and
recruitment as the foundation of strategic HR management.Module 3: Approaches to managing performance and motivation in the public sectorThe complex relationship among public service motivation, commitment, and performance is examined.Module
4: Strategic HR training, development, and public-sector careersDifferent approaches to training, skills, and talent management in the public sector and the role of training and development in HR strategy are reviewed.Module 5: Organization
design and reform in the public sector: Job classification, pay, and rewards Administrative reform, centralization and decentralization, and how they relate to basic issues and principles of job analysis, classification, and pay determination are discussed in detail.
innovation radically improves operational parameters such as efficiency,
productivity, quality, and flexibility, especially in manufacturing. Digital
transformation has also brought advances to public service.
OECD Digital Economy Outlook 2020 highlighted the growing importance of digital
technologies in daily life and showed that governments are increasingly relying
on digital strategies in their policy agendas. Digital transformation can
potentially alter existing boundaries and support new methods of delivering
public services more productively through the adoption of the IoT, big data,
The recent pandemic has accelerated digital transformation in many public-sector
organizations. By building on this progress, the public sector could transform
how it works and improve life for citizens. In this process, it is important to
consider key digital tools and effective skills and policies needed to support
continued public-sector digital innovation.
objectives of this course are to:
This e-learning course will cover the
following modules:Module 1: Digital innovation in
public-sector organizationsModule 2: Benefits, challenges, and
determinants of public-sector digital innovationModule 3: Digital innovation strategies for
public managersModule 4: Basic concepts of AI, deep
learning, and big data applications in the public sectorModule
5: Case studies of digital projects in public-sector organizations
Public-sector organizations have been transforming
for higher efficiency and broader scope, particularly to cope with
complexity and uncertainty in the external environment affecting the delivery
of services to citizens. Strategic
management is an approach to integrate strategy formulation and implementation,
which can help public-sector organizations to focus on their strengths to
achieve goals and create greater public value.
One feature of strategic management in the public
sector is the use of appropriate performance measures to track progress in
implementing initiatives and achieving goals and objectives. Incorporating
goals and objectives related to strategic management plans in individual
performance appraisal processes and rewarding contributions to achieving those
goals are critical factors in strategic management.
main objectives of this course are to:
e-learning course will cover the following modules:
Module 1: Strategic management applications in the public sector.Module 2: Strategy formulation, governance, and performance of the public sector. Module 3: Techniques of strategic management in the public sector. Module 4: Cases
of strategic management application in public-sector organizations. Module 5: Future of strategic management in the public sector.
Governments have turned to public-sector innovation labs to develop new approaches to designing policies and public services. Worldwide, more than 100 government innovation units have sprung up to find solutions to pressing social challenges (Deloitte
2020). Among APO members, some of the notable ones include the Public Service Division’s Innovation Lab in Singapore, the Innovation Bureau in the Republic of Korea, and the Thailand Policy Lab that was launched in collaboration with the UNDP.
Innovation labs provide platforms and protocols for engaging civil society, technologists, the private sector, and government to solve social and public challenges with experimental methods. They can take various forms from small, distributed teams to
a physical office, and employ diverse methodologies. These include design thinking, behavioral insights, randomized controlled trials, and advanced data analytics. The labs share some common features. First, they are focused on people-centered policymaking.
This means that innovation labs involve co-designing proposals with citizens and bringing in diverse stakeholders to develop empathy and ensure successful design and implementation. Second, they employ design-thinking approaches, i.e., processes of
iterative, user-centric problem solving originating from tech and product design. Third, they promote cross-departmental collaboration, enabling different government agencies to work together and share learning.
This e-learning course will cover the following modules:Module 1: Introduction to innovation labs Module 2: Setting up the team and conditions Module 3: Prototypes and pilot projects Module
4: Tools and techniques Module 5: Sustaining a lab
Regulatory management systems (RMS) refer to the meta structures that oversee the development and review of regulations. They comprise four core components: regulatory policies; regulatory tools; regulatory institutions; and regulatory procedures. According
to the APO publication Regulatory Management Framework to Enhance Productivity (2019), RMS serve to assess policies, analyze regulatory performance, and identify success factors and priority areas for reform. Regulatory management
systems (RMS) refer to the meta structures that oversee the development and review of regulations. They comprise four core components: regulatory policies; regulatory tools; regulatory institutions; and regulatory procedures. According to the APO
publication Regulatory Management Framework to Enhance Productivity (2019), RMS serve to assess policies, analyze regulatory performance, and identify success factors and priority areas for reform.
The OECD’s Regulatory Policy Outlook (2021) reported that all countries strived to achieve effectiveness and efficiency in their regulatory systems. In the context of regulations, effectiveness refers to the extent to which they contribute to stated objectives,
while efficiency means the balance between costs and benefits associated with their use. In short, a regulation should achieve an identified objective at minimum cost, or alternatively confer greater net benefits than any other available policy tool
to achieve the same objective. In the pursuit of good governance, APO members are introducing management policies and strengthening institutions to make regulatory systems effective.
This e-learning course will cover the following modules:Module 1: Improving regulatory quality through RMS: Context and conceptsModule 2: Tools for better policy and regulationModule 3: Institutionalization of RMS in policymaking
and setting regulationsModule 4: Purpose, people, and politics of RMSModule5: Effective regulation, good practices, and sustainable success
Behavioral public administration is a subfield that deals with the integration of theories and methods from psychology in the study of public administration. It has three main components: 1) uses individuals and groups of citizens, employees, and
managers within the public sector as units of analysis; 2) emphasizes the behavior and attitudes of these groups; and 3) integrates insights from psychology and the behavioral sciences in the study of public administration. As governments face increasing
challenges in addressing the growing complexity of society including citizens’ rising expectations regarding the quality, availability, and effectiveness of government services, public-sector performance and productivity must continually be upgraded.
Behavioral public administration is a developing theory that provides complementary approaches to policy design and implementation. While behavioral economics describe individual decision-making with alternative objectives to traditional utility maximization,
behavioral public administration shifts the reliance on traditional causal models toward actual behavior as governments improve their governance and administrative ability.This course aims to contribute to the enhancement of public-sector performance and productivity through better administrative leadership and improved public management and administration. The course
will offer practical explanations of the basic concepts and principles of behavioral public administration and present best practices of its applications in the public sector.
This e-learning course will cover the following modules:Module 1: Theory and concept of behavioral public administrationModule 2: Uses and benefits of behavioral public administration in public services and policymakingModule 3: Behavioral
approaches to public administration: Discussions on future developments of advanced behavioral public policy Module 4: Applications of behavioral public administration Module 5: Behavioral approaches to public policy, regulation,
Module 1 introduces the scientific way of thinking and contrasts this with our more natural thinking style.
Module 2 goes into scientific methods, giving you an overview of how research is done and providing the principles behind the most important methods, including experimental, archival, and qualitative research.
Module 3 offers practical advice for how you can make use of science. This is not self-evident, as the way scientific results appear in the media can be misleading. We look at the different way you, as a consumer of science, can access the findings of
the producers of science. In
Module 4, we dive deeply into the world of forecasting, discussing a book that offers a practical guide based on solid scientific research. This is both an example of a well-executed research project and a lesson in scientific thinking.
Module 5 ties everything together by looking at the theme of decision making, which is a very effective place to introduce science into your daily work.
This e-learning course will cover the following
Module 1: Science and the Human MindThis module introduces the scientific way of thinking and contrasts this with our more natural thinking style.
Module 2: The Scientific MethodThis module goes into scientific methods, giving you an overview of how research is done and providing the principles behind the most important methods, including experimental, archival, and qualitative
Module 3: Making Use of ScienceThis module offers practical advice for how you can make use of science. This is not self-evident, as the way scientific results appear in the media can be misleading. We look at the different way
you, as a consumer of science, can access the findings of the producers of science.
Module 4: SuperforecastingThis module dives deeply into the world of forecasting, discussing a book that offers a practical guide based on solid scientific research. This is both an example of a well-executed research project
and a lesson in scientific thinking.
Module 5: Rational Decision Making
This module ties everything together by looking at the theme of decision making, which is a very effective place to introduce science into your daily work.
1) Participants who register to take this course and pass the final examination with a score of 70% or higher will be eligible to receive the APO certificate. Please note that the final examination can be taken only once. Therefore, the most appropriate
time to take the examination should be chosen carefully. The self-assessment quizzes are for personal evaluation only and are not related to the final examination results.
2) Participants who perform well in this course and receive the APO certificate will be given preference, on a merit basis, for selection to attend follow-up face-to-face multi-country APO projects on similar topics, when nominated by their NPOs and
if slots are available.
3) Notes 1 and 2 are applicable only to participants from APO member countries. Participants from nonmember countries are welcome to take the course for self-improvement, though they will not get an opportunity to attend the follow-up face-to-face
multicountry APO project.
4) Each module is in a prerecorded video format in which the expert delivers presentations by explaining each slide. Participants can access the video by clicking on the link provided under the title of each module.
“Advanced” research strategies are, by virtue of their name, often complicated and require full courses of their own. Just look at the range and specificity of courses available via online learning platforms, the volumes of tutorials on building complex machine learning models, or appropriately estimating causal effects. Too often, however, analysts (and their clients) can place huge emphasis on the apparent benefits of this complexity without pausing to consider a method’s appropriateness, or limitations inherent to the data itself that may scupper valid analysis.
This course is designed to focus on the fundamentals of advanced data analytics, and in doing so to draw attention to the various theoretical, inferential, and computational issues that ultimately constrain any quantitative project. Most importantly, this course will equip you with the skills necessary to know when and why certain procedures are useful, and how to ensure the validity and appropriateness of your analysis. Along the way, we will cover a range of exciting and cutting-edge techniques across several key areas of analysis, including causal inference, machine learning, and experimentation.
This course should refine your ability to conduct advanced analysis of data across a variety of contexts, and I hope it sparks further interest in the various methods you will encounter along the way. Of course, there is only so much material eight modules can cover and, where applicable, I have highlighted extra readings you may wish to pursue beyond the confines of this course.
This course is comprised of eight, self-guided modules, two problem sets, and a final test:
Problem Set 1:
Problem Set 2:
Final Test (multiple choice)
This course aims to improve your ability to analyze data by focusing on advanced topics in data science and statistics. By the end of this course, you should be able to:
1) Participants who register to take this course and pass the final examination with a score of 70% or higher will be eligible to receive the APO certificate. Please note that the final examination can be taken only once. Therefore, you decide when you choose to take the examination. Please note that the self-assessment quizzes are for your own evaluation and have no connection with the final examination results.
2) Participants who perform well in this course and receive the APO certificate will be given preference, on a merit basis, for selection to attend the follow-up face-to-face multicountry APO project, provided their nominations are received through the concerned NPOs and slots are available.
3) Notes 1 and 2 are applicable only to participants from APO member countries. Those from nonmember countries are welcome to take the course for self-improvement, although they are not eligible to attend follow-up face-to-face multicountry APO projects.
Public-sector productivity is an important part of the economic performance of a country. Yet measuring productivity in the sector, especially of public services, is not a simple task. It requires an appropriate framework and robust calculations of various basic inputs. As the government’s function is not to maximize profits but people’s welfare, performance measures in the public sector must therefore be addressed differently. In the long run, productivity measures for the public sector are vital in understanding the success of governments in using their resources to improve living standards and community well-being, giving warning signs to take policy action to improve productivity performance, providing feedback on the effectiveness of productivity-related measures taken, alerting policymakers to adverse productivity consequences that may result from actions taken in other areas, etc.
While determining the productivity of a specific service has proved to be challenging, the APO must increasingly recognize the important role of the public sector and examine how it can produce results of higher value to society. Hence, it must continue efforts to equip member country governments to apply the theories, concepts, and tools to improve the motivation and skill levels of public officials, strengthen management systems, enhance performance in the changing environment, and better understand productivity within their public agencies. This course will therefore provide a fundamental understanding of public-sector productivity by introducing some basic measurement techniques and applying them using examples provided in the course.
The course will cover the following modules:
Module 1: Why does measurement of public-sector productivity matter?
Module 2: The basics of productivity measurement
Module 3: Outputs and outcomes in the public sector
Module 4: How to measure output
Module 5: How to measure input
Module 6: Formulating productivity measures
Module 7: Dealing with quality
Module 8: How to interpret productivity trends
Module study, additional study material for participants, short quizzes for self-assessment, and a final examination to qualify for the APO e-certificate for eligible participants.
In recent years, we have seen the increased use of basic data analytics and how they revolutionize and revitalize not only businesses but also the public sector. They have played a vital, transformational role in improving the quality of public-sector decision- and policy making, strengthening political accountability, and delivering reforms in terms of advancing public services, monitoring budgets, and cutting waste, among other ways to enhance efficiency and effectiveness. Governmental organizations can now operate in a more data-driven, information-led manner, which was not possible previously. At the same time, this development also involves challenges since the responsible, secure use of public data must be ensured.
Aligned with the transformation initiative of the APO, this course will introduce the background to why data analytics are important in public-sector organizations by examining key concepts and trends of the big data environment and their applicability. As a capacity-building effort, this course will show how public-sector organizations can apply data analytics, process the results, and make data-based decisions for better performance and increased productivity.
Module 1: Purpose and use of data analytics in the public sectorModule 2: Fundamentals of data analytics in the public sector: sampling and measurementModule 3: Analysis and visualization of data I: descriptive statisticsQuiz 1Module 4: Analysis and visualization of data II: probability distributionsModule 5: Analysis and visualization of data III: linear regression and correlationQuiz 2Module 6: Application of data analytics to the public sector problem solving_final_revisionFinal examination
A minimum score of 70% on the final examination is required to qualify for the APO e-certificate.