Open data landscape Open data and data-analytics Sally Howes – Executive Leader for Digital and Innovation Phil Bradburn – Data-analytics expert Tuesday 17 June

Open data landscape Open data index Chloropleth map of Open Data Index scores. Darker colours reflect higher scores, whereas grey indicates an absence of data. Based on 2013 data collected by Open Knowledge Foundation 2

Open data landscape Open data index 3

Open data landscape Contents Strategic context How SAIs can respond Creating value for: Parliament and entities that we audit our organisation our people Workshop 4

Open data landscape A rapidly changing environment Changing expectations of government/interaction with citizens Globalisation and greater connections Open data and digital transformation of government Technological change and computing capability New skills, blended skill-sets and backgrounds of workforce Open policy making Growth and strength of global audit firms Growing range of data sources and linked data External drivers and changes Changes across the world are influencing the strategic context for government and public services – and therefore audit. 5

Open data landscape Understanding a new threat and security landscape Open policy making, open data and transparency Data-science capabilities driving policy Different concepts of public service Appetite to reform and challenge status quo Transforming interaction between citizens and state Data and APIs for people to use and businesses to build on New skills and technology needed to run government Changes in public services and government Public services and government Major changes in how government operates, interacts with citizens, and in the capabilities in drawing insights from data. 6

Open data landscape 7 What does it mean for SAIs? Exploit data analytics in our assurance work Trialling innovative data-analytics throughout our assurance cycle Publishing more sophisticated data-visualisation in assurance products Reviewing audited entities use of data and data-analytics Develop our Skills and capabilities in Data-analytics Learning & Development – using formal training, learning from others and on the job Developing a skills framework for data-analytics and mapping our people against it Spreading the skills and knowledge that our people already have through tutorials Practitioners from other organisations to raise awareness of what is possible Leverage our IT Infrastructure and software Bringing together and linking up datasets in a data-service Making available the latest analytics software Using additional server capability to speed up complex analytics

Open data landscape Creating Value – for Parliament and entities that we audit Greater value - Greater insight and improved ability to draw audit conclusions Robustness - potential to exploit data (admin, transactional) in assurance work Innovation - Greater innovation, demonstrating art of the possible 8

Open data landscape Creating Value – for our Business Greater efficiency / economy – use it to drive down costs Maintaining our credibility – demonstrating leadership on data-analytics Data-led – Use data-analytics to transform our own business from the inside Expertise – developing our organisational capability and impact 9

Open data landscape What skills do we need for this new world? We need to change the profile of our people Analysis and audit Data handling I.T. and systems We need more people who have expertise in this area – bringing together data skills, analysis skills, and IT/systems knowledge 10

Open data landscape The types of people we need to get We need to look to the private sector Data scientists Multi-disciplinary knowledge Familiar with private sector Highly skilled in latest tools Leadership Strategic awareness of trends worldwide Leading edge thinking identifying innovative approaches to data Developers Attend hack events Create APIs Build apps We need to think like a start- up generating revenue from data and have the same mind-set to create innovative products 11

Open data landscape Workshop Current position: Where are you on the spectrum of change? What is the urgency for you to respond to this new world? What are you doing? What examples do you have of using big/open data? What value have you created? What were the challenges? What next? What are the implications for the skills / people you have or need to recruit? What steps should you take? 12

Open data landscape PromptsIssues to consider Implications – What does open data and digital government mean for the audit environment? Access to data? Quality issues and validation? The type of audit questions? How audit is carried out? Opportunities – What added value can SAI’s create if it maximises the use of open data – for clients, your SAI, your people? What insights can be developed for financial audit and vfm audit? Robustness of audit conclusions? Greater efficiency in conducting audit? Skills and organisation capability? Engagement with Parliament? Barriers – What are the issues, key risks, and problems to address in increasing our application of big data and analytics? Data-quality, and access to data? Skills and capability? Technology? Culture / Politics? 13

Open data landscape Definitions Business intelligence (BI) is a set of theories, methodologies, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. Big Data is a blanket term for any collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. Open data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control. Transparency – (UK) a pledge to make government more open with the objectives to strengthen public accountability, support public service improvement by generating more comparative data and increasing user choice; and stimulate wider economic growth by helping third-parties to develop products and services based on public sector information. Data-Analytics – a process of inspecting, cleaning, transforming, and modelling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. A further development of traditional analysis approaches. Digital Transformation – redesigning digital services to save money and put people’s needs first, and respond to increasing expectations of the public for quick and convenient services. 14

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