{"id":10704,"date":"2016-07-13T17:16:03","date_gmt":"2016-07-13T15:16:03","guid":{"rendered":"https:\/\/www.etalab.gouv.fr\/?p=10704"},"modified":"2019-06-18T10:35:33","modified_gmt":"2019-06-18T08:35:33","slug":"frances-chief-data-officer-report-on-data-governance","status":"publish","type":"post","link":"https:\/\/preprod.etalab.gouv.fr\/frances-chief-data-officer-report-on-data-governance","title":{"rendered":"France’s Chief Data Officer report on data governance"},"content":{"rendered":"\n
The decree of 16 September 2014 creates, under the Prime minister\u2019s authority, a Chief Data Officer<\/strong>\n (CDO), attached to the Secretariat general for government modernisation\n (SGMAP). The CDO coordinates the administrations action with regards to\n the inventory, governance, production, circulation and data use. The \nChief Data Officer Henri Verdier<\/strong> also deliver each year to the Prime Minister a public report<\/a> on the inventory, governance, production, circulation and use of data by administrations.<\/p>\n\n\n\n Predicting and preventing car thefts, optimizing waiting times for \nemergencies, better targeting of customs controls, identifying energy \ndeficient buildings, identifying companies that will soon be recruiting \nand informing the relevant job seekers, addressing the shortage of \nteachers in school, optimizing traffic lights to decongest and clean \nup\u00e9the city centers, revising the price calculation formula for \nmedicinal drugs, negotiating electricity purchases by anticipating and \ncontrolling consumption peaks, negotiating better public procurements, \npredicting the micro-economic effects of a tax reform, forecasting \nmedical investment needs through the analysis of scientific literature\u2026\u00e9 all these uses of predictive analysis are within reach of public authorities<\/strong>. They hold enormous potential for efficiency, expenditure control and policy accuracy.<\/p>\n\n\n\n Predictive analysis<\/strong> is only one example of a set of new practices : data-driven strategies<\/strong>, which for example allow :<\/p>\n\n\n\n These promises carried by data sciences are at the core of the digital transformation<\/strong> of big companies and large cities worldwide and are one of the levers for the modernisation of public action. This implies integrating new skill sets in government teams<\/strong>:\n data scientists, statisticians with innovative profiles, computer \ngeeks, keen on new data-processing methods, and concerned with the \nconcrete impact and translation of their mathematical results. It \nrequires high-quality data \u2018 that France does indeed produce and handle \nfollowing a long-standing tradition, thanks to its high standard \nstatistics and its commitment to the quality of public service. It also \nrequires an enhanced culture of \u00e9?data-driven strategies\u00e9?<\/strong>,\n an ambition to carry this type of change and the patience to \ncontinuously test and verify whether small changes can produce major \nimprovements.<\/p>\n\n\n\n The correct implementation of these methods, however, requires a prior effective data governance<\/strong>,\n i.e. global management of data produced or held by government to ensure\n the quality, freshness, interoperability and availability in the \ncorrect formats, facilitating swift use and dissemination amongst public\n servants \u2018from central and local governments \u2018so that they receive the \ninformation necessary to the performance of their tasks in compliance \nwith important statutory secrets that protect fundamental freedoms and \nthe nation\u2019s fundamental interests. It also requires organisation that \nallows the State control and sovereignty over its data, processes and \nsystems, and provides citizens the transparency they are entitled to \nclaim.<\/p>\n\n\n\n This first report<\/a><\/strong>,\n based on a year of investigation, exchange and experimentation with \nnumerous public officials and many administrations intends to provide a framework<\/strong>\n of analysis, detect promises and illusions of data-driven science, \npresent initial results, report the initial difficulties encountered and\n suggest first orientations, including a collaborative mapping of the \ndata available in the State, open to all administrations who wish to \nparticipate and benefit from it. api.gouv.fr<\/strong><\/a> and FranceConnect<\/strong><\/a> are concrete examples of the strategic framework of State as a platform.<\/p>\n\n\n\n