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The Age of Analytics: Unveiling the Power of Big Data

Explore the origins of operational research, the opportunities of big data, sources and utilization of data in smart cities, implications in public and private sectors, and the significance of data in national systems.

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The Age of Analytics: Unveiling the Power of Big Data

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  1. The Age of AnalyticsOperational Research Society, April 30th 2014 Sir Mark WalportChief Scientific Adviser to HM Government

  2. WW2 origins of operational research: learning to think counter-intuitively • Add armour to the parts of bombers that come back damaged by flak, or the undamaged parts? • Better to protect the parts that stay undamaged. If the plane gets hit there, it never comes back for inspection. The Age of Analytics, April 30th 2014

  3. Patrick Blackett • Answers like this were developed by Patrick Blackett (1897-1974) and team. • Blackett was a key founder of the Operational Research Society in 1947. • His career nearly ended in 1925, when a young Robert Oppenheimer attempted to give him a poisoned apple. The Age of Analytics, April 30th 2014

  4. The opportunities presented by big data The Age of Analytics, April 30th 2014

  5. What is big data? • Rule of thumb definition is a dataset that can’t be mapped on an Excel spreadsheet. • More technically, the four Vs: velocity, variety, volume and veracity, are the key characteristics of big data. The Age of Analytics, April 30th 2014

  6. Sources of data in a smart city • Real-time Object sensors Pollution sensors People Social media Admin data Housing Health Education Taxes The Age of Analytics, April 30th 2014

  7. How a smart city can use data • Optimising flows of people and resources Providing personalised services Planning for future requirements The Age of Analytics, April 30th 2014

  8. Data can help us get about Open data - Citymapper Crowdsourced data - Streetbump Anonymised crowdsourced data – Google Traffic Driverless cars The Age of Analytics, April 30th 2014

  9. Data opens up a world of possibilities for our entertainment, education and efficiency Finding things out Telling other people things Listening and watching things Navigating the real world Navigating fictional worlds Buying and selling stuff Playing games Storing stuff Recording our lives and those of friends/families Socialising with others Stealing things Plotting and causing harm The Age of Analytics, April 30th 2014

  10. Private sector analytics: loyalty cards and Experian • Companies make it easier and cheaper for consumers to get the goods they want, in return for access to data about their spending habits. • That data can be used on an individual level, e.g. to target advertising, or to develop more sophisticated insights into how people shop. The Age of Analytics, April 30th 2014

  11. How does government use data? Planning Voting Taxes Law enforcement The Age of Analytics, April 30th 2014

  12. Harnessing ICT: A national diabetes system for Scotland Total Scottish Population 5.2M People with diabetes : 251,132 (4.9%) People with Type 1 DM : ~27,000 (0.5%) All patients nationally are registered onto a single register; the SCI-DC register SCI-DC used in all 38 hospitals Nightly capture of data from all 1043 primary care practices across Scotland Courtesy of Andrew Morris The Age of Analytics, April 30th 2014

  13. Scottish Diabetes Survey – over 90% capture of key variables since 2007Recording of Key Biomedical Markers Percentage of Patients Data recorded within the previous 15 months Courtesy of Andrew Morris http://www.diabetesinscotland.org.uk/Publications/SDS%202010.pdf The Age of Analytics, April 30th 2014

  14. Tax data to home in on fraud • HMRC uses sophisticated software to collect and analyse many sources of information about the finances of corporations and individuals, to identify cases that warrant investigation. • Connect, running since 2010, combines over 1 billion records and has yielded over £2bn in tax. The Age of Analytics, April 30th 2014

  15. National security The Age of Analytics, April 30th 2014

  16. What about privacy and security? The Age of Analytics, April 30th 2014

  17. Information technology has created new ways of locating or finding us Image: iPhone tracking data The consequence of all of this is that we are giving a lot of information out that others can then use…. The Age of Analytics, April 30th 2014

  18. Lots of other people are interested in our data. Who knows the most about us? Government Corporations ONS Google HMRC Experian NHS Loyalty Cards The Age of Analytics, April 30th 2014

  19. Dangers of releasing data into the wild • Released anonymised search data for research purposes. • Journalists were able to pick up clues to name and location, then triangulate with embarrassing search queries. • Programme was halted, its initiators sacked. • Released anonymised film rental data and set a $1m prize, hoping to improve recommendation algorithms. • People’s viewing taste beyond usual blockbusters is highly individual. • Triangulating with IMDB data, bloggers identified individual users and were able to reveal their full list of rentals, not just those they had “rated”. The Age of Analytics, April 30th 2014

  20. Privacy controls are not binary but fall on spectra Obfuscation Anonymised to the point of losing valuable content Openly identifiable Access / Environment Locked in a steel-lined room Free on the internet (Everyone) (Accredited researcher) Governance and accountability Highly legislated Little legislation The Age of Analytics, April 30th 2014

  21. The myth of consent - do we really read and understand the full terms and conditions? • In 2008, researchers calculated it would take 76 working days to read all the privacy policies you encounter in a year. If everyone in the US did so, it would cost the country more than the GDP of Florida. • In 2010 GameStation.com - a UK-based games retailer - added a clause to their T&Cs, “to grant Us a non transferable option to claim, for now and for ever more, your immortal soul”. • A publicity stunt, but revealed 88% of customers in the time period had not read the T&Cs. Michael Pacher: St. Augustine and the Devil, 1471-75 The Age of Analytics, April 30th 2014

  22. Can we blame people? Source: Which, via Bobby Duffy IPSOS-MORI The Age of Analytics, April 30th 2014

  23. Social intelligence on personalisation vs. privacy • Personalisation vs. Privacy was a major IPSOS MORI international poll, 16,000 interviews, results released early 2014. • Up to 90% of people are concerned about how their (online) information is used. • People are more outraged by companies being cavalier with their data than they are by companies exploiting foreign workers, damaging the environment, overcharging for their products or paying huge bonuses. The Age of Analytics, April 30th 2014

  24. Governance: data protection legislation • Harm can be done by sharing and not sharing data • DPA law provides exemptions for research. The proposed EU Data Protection Regulation, which would replace the DPA, remains a concern. The Parliament’s draft text would make some current medical research illegal. • HMG and the UK academic community are united in lobbying for a final text that does not overly restrict important research. The Age of Analytics, April 30th 2014

  25. The challenge of communicating the benefits: care.data • In the USA, preventable medical errors are the third leading cause of death (440,000 per year – Journal of Patient Safety, 2013). Data analytics can identify and address the underlying causes. • Countries all around the world are currently wrestling with the same issue of how to share medical data while protecting privacy. • We need to be more open with people on how their data may and may not be used, and communicate the benefits. On care.data… “This information helps us identify the causes of cancer and heart disease; it helps us to spot side-effects from beneficial treatments, and switch patients to the safest drugs; it helps us spot failing hospitals, or rubbish surgeons; and it helps us spot the areas of greatest need in the NHS. Numbers in medicine are not an abstract academic game: they are made of flesh and blood, and they show us how to prevent unnecessary pain, suffering and death.” Ben Goldacre, Guardian 21 February The Age of Analytics, April 30th 2014

  26. How do we build capability? The Age of Analytics, April 30th 2014

  27. Mathematics teacher recruitment shortfall/surplus Skills pipeline Source: DfE The Age of Analytics, April 30th 2014

  28. The Turing Institute • The Mission • To undertake research and knowledge sharing in the key disciplines of mathematics, computer and data science • To develop networks between leaders • To enable industry and academia to work together on research with practical applications • To provide advice to policy makers on the wider implications of research • To provide strategic oversight and leadership • The vision • Promote the development and use of advanced mathematics, computer science and algorithms for human benefit • Conduct first class research and development • It will be a world leading institute that will provide a fitting memorial to Alan Turing The Age of Analytics, April 30th 2014

  29. We need to ensure analysts have space within their jobs to innovate • Operation • The day job. • Doing the same thing repeatedly, with minimal failure. • Change is risky. • Success is easy to measure. • Return is immediate. • Innovation • Few people do this only. • Finding better ways to do things. • Failures and false starts are to be expected. • Fuzzy, conflicting goals. • Hard to measure. • Return comes in the future. The Age of Analytics, April 30th 2014

  30. Enabling legislation • An open consultation on data sharing, led by Francis Maude. • Aiming for an agreed approach between parties and involving privacy groups, for a White Paper at the end of the year. • Laying the ground for a Data Sharing Bill after the 2015 election. The Age of Analytics, April 30th 2014

  31. What is needed from the OR Society? • Research to stay at the cutting edge. • Augment analytical skills with coding skills. • Plug into the world of big data: volume, velocity, variety and veracity. The Age of Analytics, April 30th 2014

  32. We all need to work together Industry Universities The Age of Analytics, April 30th 2014

  33. There is no going back – the world has been shaped by the digital revolution There are new tools for understanding ourselves and the world Huge opportunities for the data science and operational research profession, to be right at the centre of policymaking There are unforeseen benefits and harms: need a sophisticated level of debate Final messages The Age of Analytics, April 30th 2014

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