Unit 5
How Ines Mergel teaches Unit 5
What is this page?
This is a detailed breakdown of how Professor Ines Mergel from the University of Konstanz teaches a class that covers the contents of Unit 5 of the open access syllabus developed by Teaching Public Service in the Digital Age.
The official designation of the course Professor Mergel is teaching here is "MA Seminar: Digital Governance".
We believe it is helpful to see how professors in different contexts teach the same concepts, so to see how Harvard Kennedy School's David Eaves teaches the same unit, see here.
Who is this page for?
This page has been developed for use by university faculty who are teaching Master's levels students in Public Policy and Public Administration. It has been published to help them design their own approaches to teaching the digital era skills covered in Unit 5 of our syllabus.
Class Overview
From the New Public Management era onwards, data in government has increasingly important for evidence-based decision making. It helps public servants to understand behavioral changes around them, so that they can make better decisions. Understanding which data sources are available, how to access data from deep organizational silos, and how to clean and integrate different data sets is an integral part of the work of public managers.
This Class' Learning Objectives
By the end of this class students should be able to:
Identify how data is generally used in government and for what of purposes
Identify the types of problems data can be used to solve
Recount some of the main ways & reasons that data is not successfully deployed
Explore the responsibilities in managing data
How this class relates to the Digital Era Competencies
💡 This class has a specific focus on Competency 7 - Data See all eight competencies here.
Assigned Reading
Bassa, A. (2018). Managing a Data Science Team. Harvard Business Review.
Mergel, I., Kleibrink, A., & Sörvik, J. (2018). [Open data outcomes: US cities between product and process innovation](https://www.sciencedirect.com/science/article/pii/S0740624X18300017#!). Government Information Quarterly, 35(4), 622-632.
The Economist (2017). Regulating the internet giants - The world’s most valuable resource is no longer oil, but data.
Detailed Class Breakdown
Class plan: 90 minutes
The sections below describe the dynamics of each part of the class:
Segment 1 - Exercise - 25'
As warm-up exercise and to introduce students to the topic, this class section starts with an exercise: the students are moved into groups (or breakout rooms) and are asked to discuss the following question:
"What types of data are public administrations collecting for what types of archetypical purposes?"
Debriefing part 1 of this group work can then focus on the following data types. During these discussions students are asked to focus on the high level categories of purpose that all data usage fits (and are discouraged from simply naming many uses of data). The purpose is to get students to see how a near infinite number of specific data uses actually fit under a modest number of purposes. The main examples the instructor is trying to tease out of students are:
Administrative data (government data collected during regular service delivery)
Actively collected data (survey data, tax forms, census data)
Passively collected data (traffic monitoring, CCTV, weather data)
Structured or unstructured data
Debriefing part 2 should then focus on the archetypical purposes of data collection in public administrations:
As a tool to inform policy design and to set strategies
To monitor compliance with laws and programs
To understand citizen needs and behavioural changes
To monitor performance
To identify and prevent new problems
To directly power a public service (for example, biometric passport gates)
To enable policy and program evaluation
to meet the needs of parties outside of government
Segment 2 - Short lecture on data purposes during the policy cycle - 20'
The second segment then includes a short lecture in which Professor Mergel first summarizes the discussion of the first exercise and the moves into an overview of how data is used in the different phases of the policy cycle:
A diagram showing the policy cycle - a circle of arrows showing the phases 'Identifying policy needs', 'Clarifying policy needs', 'Formulating policy needs', Designing digital public servcices to implement policy' and 'Evaluating policy outcomes'. The circle then repeats.
For each of the phases in the policy cycle the students are challenged to discuss which assumptions might underly the initial data collection design, the subsequent modelling of the data analysis, how the data is then linked and interpreted, and how this might impact public administrations' decision making about programs and policies.
Subsequently, the students review which biases might potentially lead to harmful use of data and are asked to think about examples.
Segment 3 - Open Data and its outcomes - 15'
One of the most common forms of data that students will interact with - even as outsiders to public administrations - is open data. This is a specific form of data that is made available for public display and consumption, and for government's own internal use across agencies. However, it remains oftentimes unclear what it takes to move data onto an open data platform, how open data can be used by (mostly) professionals, and what the outcomes are of this process. The questions listed here highlight some of the difficulties related to the approach:
the organizational and cultural change that is necessary to internally negotiate the release of valuable data sets not only to the public, but more importantly to government itself
the limited use of large amounts of data to non-professionals and the main reuse by data professionals (such as journalists, other government units, researchers, etc.)
the (still) unknown outcomes of open data
The segment ends with an overview of potential open data outcomes (based on Mergel et al. 2018)
Source: Mergel et al. 2018: Internal and external process and product outcomes
Segment 4 - Exercise 2 on key challenges to use data effectively in government - 15´
The different topics mentioned in this class are then pulled together in a final class discussion where students have to discuss in the large group what they believe are the key challenges to the effective use of data in government. The results can be collected on a White Board or a shared document.
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Acknowledgements
David Eaves would like to note that this material was made possible by numerous practitioners and other faculty who have generously shared stories, pedagogy and their practices. David is also grateful to the students of DPI 662 at the Harvard Kennedy School for enriching the course and providing consent to have the material and questions shared. Finally, an enormous thank you must be given to Beatriz Vasconcellos, who helped assemble and organize the content on this page.