Competency 7 of 8 - Data
“A digital-era public service leader understands how to use data to inform decisions, design and run services, and create public value inside and outside government."
Background to this competency
Public servants have collected and used data since before the word 'statistics' was invented. The disciplines of economics, statistics, and public accounting has grown up hand-in-hand with the growth of modern bureaucratic states, pursuing the ideal of 'evidence based policy making'.
The dependence of public service on numeracy can be seen in the nature of core educational topics taught to public servants. Few people now gain positions of leadership without at least a minimum of tuition in the fundamentals of statistics or economics.
Given such a preponderance of numerical skills in current public affairs education, it might seem curious that we name data as a new competency that merits a focus. Isn't this an area already 'covered' by the typical MPA or MPP programmes, or the new wave of specialised data science programmes?
These courses have made great strides to match the pace of developments in technology and data. Indeed there has been an explosion of new modules and teaching on data science, data ethics, web analytics, AI and data. However the challenge is to ensure that public leaders can make good choices about which of these skills need deploying in which circumstances.
This means adapting teaching to public servants to adjust to the following major changes:
The types of data savvy specialists have increased and now include, for example, web analytics experts, and urban sensing experts.
There are new sources of data that modern public servants have to know about, beyond the traditional realm of official statistics.
These new data streams are more voluminous, and more often problematic in terms of quality than traditional official data.
Given all these changes are ongoing and rapidly changing, it is important to support educators in adapting their skillset to the new era.
Meaning of this competency
Public servants now need to be able to:
Differentiate the types of problems that will require data scientists, versus statisticians or economists.
Identify what skills will be required to acquire and clean data, and when these skills will be essential.
Understand how the architecture and governance of new digital systems will make data more or less easy to use, share and maintain.
Explain how the gap between 'policy data' and 'operations data' is collapsing.
Anticipate and mitigate problems related to the sharing of data within governments.
All the above will create security, privacy and ethical implications that are critical, but for clarity we have separated into another competency, No. 2.
Ultimately, this competency means that public service leaders need to be able to use data 'for real', not 'in laboratory conditions'.
Why was this competency developed and agreed?
Our list of eight Digital-Era Competencies is designed to sit alongside current, existing competencies often taught in schools of public administration or public policy. All eight of our competencies therefore represent capabilities that are either not being taught to current and future public servants or that require some updating to succeed in the digital era.
We were concerned that the high numeracy requirements for many MPP, MPA and Data Sciences courses might conceal the fact that the type of numeracy required of public servants has changed considerably in the last two decades.
Whereas a previous generation of public servants thought of data primarily as something they had to be able to perform analyses upon, the next generation sees it as a stock and flow of resource that is powerful but which comes with enormous technical, ethical and legal problems. They need skills that relate to technical architecture, HR and strategy, not just direct analysis.
Reading Suggestion
The Quartz Guide to Bad Data - Christopher Groskopf
Mergel, I., Kleibrink, A., & Sörvik, J. (2018). Open data outcomes: US cities between product and process innovation. Government Information Quarterly, 35(4), 622-632.
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