Editing Public policy (section)

== Policy design ==
Policy design entails conscious and deliberate effort to define policy aims and map them instrumentally.<ref name=":4">{{Cite book|date=2010-12-17|title=Designing Public Policies|url=http://dx.doi.org/10.4324/9780203838631|doi=10.4324/9780203838631|isbn=978-0-203-83863-1|last1=Howlett|first1=Michael}}</ref> Policy design proposes critical analysis of policy instruments and their implementation. Uncertainties policy designers face include (in brief):
* Technical difficulties: mechanism, design, constituency, environment of public policies
* Cost issues: resources, materials, products, etc.
* Political problems: selection process of solutions and decision making. Policies require tedious and rigorous research on advice for its feasibility, legitimacy and choice.
* Compliance: Understanding the target market and discovering data for those dependent, disadvantaged or deviant on policy change.
* Effectiveness: There is a possibility of spillovers, complementariness and inconsistencies.

Nevertheless, policy design is elemental for the succession of public policy, with it comes intricate and multi-level approaches but it is necessary for good, careful policy design to be considered before implementing the policy.<ref name=":4" />

=== Data-driven policy ===
Data-driven policy is a policy designed by a government based on existing data, evidence, rational analysis and use of information technology to crystallize problems and highlight effective solutions.<ref>{{Cite journal|url=https://issues.org/esty-2/|title=The Promise of Data-Driven Policymaking|journal=Issues in Science and Technology|last1=Esty|first1=Daniel|last2=Rushing|first2=Reece|volume=23|number=4|date=Summer 2007|language=en-US|access-date=2020-01-08|archive-date=2022-01-21|archive-url=https://web.archive.org/web/20220121083716/https://issues.org/esty-2/|url-status=live}}</ref> Data-driven policy making aims to make use of data and collaborate with citizens to co-create policy.<ref>{{Cite book|last1=van Veenstra|first1=Anne Fleur|date=2017|pages=100–111|publisher=Springer International Publishing|isbn=978-3-319-64321-2|last2=Kotterink|first2=Bas|title=Electronic Participation |chapter=Data-Driven Policy Making: The Policy Lab Approach |series=Lecture Notes in Computer Science|volume=10429|doi=10.1007/978-3-319-64322-9_9|chapter-url=https://hal.inria.fr/hal-01703333/file/453549_1_En_9_Chapter.pdf|access-date=2020-01-12|archive-date=2022-01-18|archive-url=https://web.archive.org/web/20220118182809/https://hal.inria.fr/hal-01703333/file/453549_1_En_9_Chapter.pdf|url-status=live}}</ref> Policy makers can now make use of new data sources and technological developments like [[Artificial intelligence in healthcare|Artificial Intelligence]] to gain new insights and make policy decisions which contribute to societal development.

In the 2020s, policymakers will use data for policies and public service design, while responding to citizen engagement demands. The [[Anticipatory governance|Anticipatory Governance]] model is particularly important when considering the sheer amount of data available. In terms of using new technology to collect, analyze, and disseminate data, governments are only just beginning to utilize data science for policy implementation.<ref>{{Cite journal |last1=Maffei |first1=Stefano |last2=Leoni |first2=Francesco |last3=Villari |first3=Beatrice |date=2020-04-02 |title=Data-driven anticipatory governance. Emerging scenarios in data for policy practices |journal=Policy Design and Practice |volume=3 |issue=2 |pages=123–134 |doi=10.1080/25741292.2020.1763896|s2cid=219423835 |doi-access=free |hdl=11311/1140914 |hdl-access=free }}</ref> With new technologies implemented in government administration, a more complete visualization of current problems will emerge, allowing for more precision in targeted policy-making.<ref>{{Cite web |last1=Esty |first1=Daniel |last2=Rushing |first2=Reece |date=1970-01-01 |title=The Promise of Data-Driven Policymaking |url=https://issues.org/esty-2/ |access-date=2022-03-29 |website=Issues in Science and Technology |language=en-US |archive-date=2022-01-21 |archive-url=https://web.archive.org/web/20220121083716/https://issues.org/esty-2/ |url-status=live }}</ref> Data science involves the transformation, analysis, visualization, and presentation of data, and potentially improve the quality of life and society by providing a more informational environment for public debate and political decision-making. Some examples of utilizing data science in public policy making are resource optimization, improving current public services, and fraud and error mitigation.<ref>{{Cite journal |date=2020 |title=Research in Data Science and Applied to Public Administration |url=https://www.fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf |journal= |publisher=Fundação para a Ciência e a Tecnologi |access-date=2022-05-09 |archive-date=2022-03-19 |archive-url=https://web.archive.org/web/20220319223356/https://fct.pt/media/docs/Brochura_ResearchinDataScienceandAIappliedtoPA.pdf |url-status=live }}</ref>

Data sets rarely merge between government agencies or within agencies or countries' governments. This is beginning to change with the [[COVID-19 pandemic]] spreading globally in early 2020.<ref>{{Cite web |title=Covid-19: How unprecedented data sharing has led to faster-than-ever outbreak research {{!}} Research and Innovation |url=https://ec.europa.eu/research-and-innovation/en/horizon-magazine/covid-19-how-unprecedented-data-sharing-has-led-faster-ever-outbreak-research |access-date=2022-05-06 |website=ec.europa.eu |date=23 March 2020 |language=en |archive-date=2022-05-09 |archive-url=https://web.archive.org/web/20220509025339/https://ec.europa.eu/research-and-innovation/en/horizon-magazine/covid-19-how-unprecedented-data-sharing-has-led-faster-ever-outbreak-research |url-status=live }}</ref> Forecasting and creating data models to prevent the propagation of the virus has become a vital approach for policy makers in governments around the world.<ref>{{Cite journal |last1=Hasan |first1=A. |last2=Putri |first2=E. R. M. |last3=Susanto |first3=H. |last4=Nuraini |first4=N. |date=2021-01-20 |title=Data-driven modeling and forecasting of COVID-19 outbreak for public policy making |journal=ISA Transactions |volume=124 |pages=135–143 |language=en |doi=10.1016/j.isatra.2021.01.028 |issn=0019-0578 |pmc=7816594 |pmid=33487397}}</ref>

=== User-centered policy design ===
User-centered policies are policies that are designed and implemented with the end-users, or those who are impacted by the policy, as co-designers.<ref name=":2">{{Cite journal|last=Ranney|first=Frances|date=11 March 2009|title=Beyond Foucault: Toward a user-centered approach to sexual harassment policy|doi=10.1080/10572250009364683|journal=Technical Communication Quarterly|volume=9|issue=1|pages=9–28|s2cid=143856976}}</ref><ref>{{Cite journal|last=Moilanen|first=Stephen|title=When to Use User-Centered Design for Public Policy|journal=Stanford Social Innovation Review|url=https://ssir.org/articles/entry/when_to_use_user_centered_design_for_public_policy|date=May 15, 2019|access-date=2020-11-06|language=en-us|archive-date=2022-01-26|archive-url=https://web.archive.org/web/20220126072241/https://ssir.org/articles/entry/when_to_use_user_centered_design_for_public_policy|url-status=live}}</ref> Policymakers using this design process utilize users' knowledge of their lived experiences.<ref name=":2" /> This can allow for policymakers focus on including both comprehensiveness and comprehension within policies to aid in clarity for end-users, such as workers or organizations.<ref name=":2" />

=== Small system dynamics model ===
The small system dynamics model is a method of condensing and simplifying the understanding of complex issues related to overall productivity.<ref>{{Cite journal|last1=Ghaffarzadegan|first1=Navid|last2=Lyneis|first2=John|last3=Richardson|first3=George P.|date=2011|title=How small system dynamics models can help the public policy process|journal=System Dynamics Review|language=en|volume=27|issue=1|pages=22–44|doi=10.1002/sdr.442|issn=1099-1727|citeseerx=10.1.1.407.8702}}</ref>

===Evidence-based policy===

[[Evidence-based policy]] is associated with [[Adrian Smith (statistician)|Adrian Smith]] because in his 1996 presidential address to the [[Royal Statistical Society]], Smith questioned the current process of policy making and urged for a more "evidence-based approach" commenting that it has "valuable lessons to offer".<ref>Boaz, Ashby, Young (2002). [http://www.kcl.ac.uk/content/1/c6/03/45/85/wp2.pdf "Systematic Reviews: What have they got to offer evidence based policy and practice?"] {{Webarchive|url=https://web.archive.org/web/20200814083940/http://www.kcl.ac.uk/content/1/c6/03/45/85/wp2.pdf |date=2020-08-14 }} ESRC UK Centre for Evidence Based Policy and Practice. Retrieved 7 May 2016</ref>

Some policy scholars now avoid using the term ''evidence-based'' policy, using others such as ''evidence informed''. This language shift allows continued thinking about the underlying desire to ''improve'' evidence use in terms of its rigor or quality, while avoiding some of the key limitations or reductionist ideas at times seen with the evidence-based language. Still, the language of evidence-based policy is widely used and, as such, can be interpreted to reflect a desire for evidence to be used well or appropriately in one way or another – such as by ensuring systematic consideration of rigorous and high quality policy relevant evidence, or by avoiding biased and erroneous applications of evidence for political ends.<ref name="Routledge">{{cite book|last1=Parkhurst|first1=Justin|title=The Politics of Evidence: from Evidence Based Policy to the Good Governance of Evidence|date=2017|publisher=Routledge|location=London|isbn=978-1-138-93940-0|doi=10.4324/9781315675008|url=http://eprints.lse.ac.uk/68604/1/Parkhurst_The%20Politics%20of%20Evidence.pdf|access-date=2020-08-28|archive-date=2022-01-24|archive-url=https://web.archive.org/web/20220124022913/https://eprints.lse.ac.uk/68604/1/Parkhurst_The%20Politics%20of%20Evidence.pdf|url-status=live}}{{page needed|date=April 2018}}</ref>

The development and analysis of evidence based / evidence informed policy are supported by multidisciplinary [[public policy research]] and [[policy analysis]].

==== In the U.S. ====
Unlike the UK, the U.S. has a largely devolved government, with power at local, state and federal level. Due to these various levels of governance, it can often be difficult to coordinate passing bills and legislation, and there is often disagreement. Despite this, the system allows citizens to be relatively involved in inputting legislation. Furthermore, each level of government is set up in a similar way with similar rules, and all pump money into creating what is hoped to be effective legislation. Policy creation in America is often seen as unique to other countries.<ref>{{Cite book|title=American public policy : promise and performance|last=Peters |first=B. Guy|date=30 September 2015|isbn=978-1-4833-9150-2|edition=Tenth|location=Los Angeles|oclc=908375236}}</ref>