Public-sector Productivity

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. 

Course Objectives

The main objectives of this course are:

  • Explain the principles and practices of public-sector innovation labs.
  • Learn about the different kinds of public-sector innovation labs and how their structure and relation to government affect their performance.
  • Understand the rationale behind the use of innovation labs and the types of public and social problems they can help address.

Course Modules

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

Important Notes:

  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 multicountry 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, although they will not have an opportunity to attend the follow-up face-to-face multicountry APO projects.
  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.


Course Duration in Hours: 10 hours
Skill Level: Beginner
Upcoming Course: No
New Course: Yes

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.

Course Objectives

The main objectives of this course are:

  • Introduce the concept, principles, and guidelines of RMS.
  • Understand the applications of RMS and their institutionalization.
  • Learn about successful RMS implementation in the public sector in terms of regulatory quality
  • tools, practices, strategies, and institutions.

Course Modules

This e-learning course will cover the following modules:
Module 1: Improving regulatory quality through RMS: Context and concepts
Module 2: Tools for better policy and regulation
Module 3: Institutionalization of RMS in policymaking and setting regulations
Module 4: Purpose, people, and politics of RMS
Module5: Effective regulation, good practices, and sustainable success

Important Notes:

  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 multicountry 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, although they will not have an opportunity to attend the follow-up face-to-face multicountry APO projects.
  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.

Course Duration in Hours: 10 hours
Skill Level: Beginner
Upcoming Course: No
New Course: Yes

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.

Course Objectives

The main objectives of this course are:

  • Understand the theories and concepts of behavioral public administration to enhance public-sector performance and productivity.
  • Learn about best practices of behavioral public administration through its use and applications.
  • Impart knowledge of the integration of behavioral approaches in public-sector administration.

Course Modules

This e-learning course will cover the following modules:
Module 1: Theory and concept of behavioral public administration
Module 2: Uses and benefits of behavioral public administration in public services and policymaking
Module 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, and governance

Important Notes:

  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 multicountry 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, although they will not have an opportunity to attend the follow-up face-to-face multicountry APO projects.
  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.

Course Duration in Hours: 14 hours
Skill Level: Beginner
Upcoming Course: No
New Course: Yes
Decision making in the public sector is complex, often involving many stakeholders and lots of uncertainty. In this course, you will learn to make more effective use of one of the greatest resources available to us in the modern world: science. Drawing on insights from philosophy of science and methodology, this course aims to develop your ability to think scientifically and to draw on the findings of others when needed.

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.

Course Objectives

The main objectives of this course are:

  • Understand the importance of scientific literacy for the public sector.
  • Identify key policy areas where scientific and technological knowledge is critical in formulating effective public action.
  • Enhance the capability of participants in using scientific knowledge in developing innovation-and science-related policy.

This e-learning course will cover the following modules:

Module 1: Science and the Human Mind
This module introduces the scientific way of thinking and contrasts this with our more natural thinking style.

Module 2: The Scientific Method
This 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 research.

Module 3: Making Use of Science
This 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: Superforecasting
This 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.

Important Notes:

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.



Course Duration in Hours: 25
Skill Level: Beginner
Upcoming Course: No
New Course: Yes

Course Description

“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:

  1. Effective Analysis in an Era of Advanced Data Analytics
  2. Data Visualization and Story-telling
  3. Fundamentals of Causal Inference
  4. Experimental Survey Methods for Policy Evaluation

 Problem Set 1:

  1. Fundamentals of Machine Learning
  2. Applying Machine Learning in a Causal Inference Setting
  3. Data Integrity and Handling Missing Data
  4. Multi-Level Regression and Post-Stratification

Problem Set 2:

Final Test (multiple choice)

Course Objectives:

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:

  • Recognize appropriate statistical uses for different types of data
  • Understand how to translate data into effective visualizations
  • Distinguish between correlation and causation, identification and prediction
  • Understand the benefits and limitations of machine learning
  • Resolve common data issues using advanced statistical techniques

Important Notes:

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.

Course Duration in Hours: 32 hours
Skill Level: Beginner
Upcoming Course: No
New Course: No

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

Final examination

Methodology:

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.


Course Duration in Hours: 20 hours
Skill Level: Beginner
Upcoming Course: No
New Course: No

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. 

The course will cover the following modules:

Module 1: Purpose and use of data analytics in the public sector
Module 2: Fundamentals of data analytics in the public sector: sampling and measurement
Module 3: Analysis and visualization of data I: descriptive statistics
Quiz 1
Module 4: Analysis and visualization of data II: probability distributions
Module 5: Analysis and visualization of data III: linear regression and correlation
Quiz 2
Module 6: Application of data analytics to the public sector problem solving_final_revision
Final examination

Important Notes:

A minimum score of 70% on the final examination is required to qualify for the APO e-certificate.


Course Duration in Hours: 20 hours
Skill Level: Beginner
Upcoming Course: No
New Course: No