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Ranconteur: Future of Data

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Data security and privacy concerns Limited access to data Lack of training Lack of sufficiently skilled people Excessive complexity in existing systems Lack of an analytics strategy Non-intuitive and/or inconvenient tools Lack of a centralised tool for capturing and analysing data Lack of proper technology Data analytics is not a key focus of the organisation Belinda Booker An award-winning business journalist specialising in events and marketing. She has written for business titles such as Meetings & Incentive Travel magazine and The Grocer. Danny Buckland An award-winning journalist and blogger who writes for national newspapers and magazines about health innovation and technology. Dan Matthews A journalist and the author of The New Rules of Business. He writes about a wide range of topics concerning business and sport. Tamlin Magee A London-based freelance journalist who specialises in technology and culture. Josh Sims A journalist and editor contributing to a wide range of publications, including Esquire Wallpaper and Spectator Life. Emma Woollacott A technology writer specialising in legal and regulatory matters. She has contributed to Forbes and the New Statesman. Sally Whittle A journalist and features writer covering business and internet technologies. She writes for outlets including Computing and InformationWeek.com. Jack Apollo George A semiotician, editor and writer, with work published in The Day and the New Statesman. Distributed in Publishing manager Sophie Freeman Although this publication is funded through advertising and sponsorship, all editorial is without bias and sponsored features are clearly labelled. For an upcoming schedule, partnership inquiries or feedback, please call +44 (0)20 8616 7400 or e-mail info@raconteur.net. Raconteur is a leading publisher of special-interest content and research. Its pub- lications and articles cover a wide range of topics, including business, finance, sustainability, healthcare, lifestyle and technology. Raconteur special reports are published exclu- sively in The Times and The Sunday Times as well as online at raconteur.net. The information contained in this publication has been obtained from sources the Proprietors believe to be correct. However, no legal liability can be accepted for any errors. No part of this publication may be reproduced with- out the prior consent of the Publisher. © Raconteur Media @raconteur /raconteur.net @raconteur_london T O P I C T I T L E T O P I C T I T L E T O P I C T I T L E It quis venia num fugit dol est la non parum qui necum quosandus est perro aut es It quis venia num fugit dol est la non parum qui necum quosandus est perro aut es It quis venia num fugit dol est la non parum qui necum quosandus est perro aut es 03 05 06 Contributors I N D E P E N D E N T P U B L I C A T I O N B Y 1 9/ 0 9/ 2 0 2 1 # 0 7 6 4 R A C O N T E U R . N E T Art director Joanna Bird Design director Tim Whitlock /future-data-2021 raconteur.net Deputy editor Francesca Cassidy Sub-editors Neil Cole Gerrard Cowan Head of production Justyna O'Connell Design and production assistant Louis Nassé Design Pip Burrows Kellie Jerrard Celina Lucey Colm McDermott Samuele Motta Nita Saroglou Jack Woolrich Sean Wyatt-Livesley Managing editor Sarah Vizard Illustration Sara Gelfgren Samuele Motta necessarily believe what they're presented with. For instance, respondents to a 2018 survey by Experian said that they consid- ered 30% of the data held by their firms to be inaccurate on average. This is not the only issue of trust that affects data democratisation, according to Kevin Hanegan, a founding partner of the Data Literacy Project and the chair of its advisory board. "The number one thing I hear from the many CEOs and CIOs I talk to is that they don't feel ready for the democratisation of data, because they don't trust employees to make the right decisions using it," he says. "There's a lot of talk of software being the solution, but technology is the least part of this. Anyone given access to data needs to be able to interpret it. Until then. it's like giving someone a black box that says 'the answer is A', to which their immediate reaction might be 'why is it A? How would I know?'. There isn't a tool to bring about this change. It won't happen overnight." The lack of trust is part of a bigger weak - ness with the democratisation concept: the fact that most people struggle to deal with statistics. A recent study in the US found that 46% of high-school graduates were unable to estimate how many times a flipped coin would probably come up heads in 1,000 tosses. "The problem, which has become clearer since the Covid crisis started, is that a lot of statistics are counterintuitive and full of surprises. That's especially the case with brains like ours, which are simply not built to be good calculators of, say, probability." So says Stian Westlake, CEO of the Royal Statistical Society, which has found a lucrative sideline as a training provider to firms in industries such as pharma and petrochemicals. He adds: "Our brains are good at seeing patterns, but struggle to see randomness when it's there. And it's often Unhidden figures It's the business buzz phrase of the moment, but is 'data democratisation' such a good idea when so many of us find it hard to deal with statistics? t was Clive Humby, the mathema- tician and data scientist behind Tesco's Clubcard, who coined the phrase "data is the new oil". It has since become something of a corporate cliché, uttered by every consultant and CEO who wants to show how deeply they understand the digital economy. For Ved Sen, head of business innovation in the UK and Ireland for Tata Consultancy Services, this maxim doesn't quite ring true. He would instead describe data as "the new plastic", because "we create a lot, we struggle to know what to do with it and it tends to turn up in the wrong places. And, for all the talk about the democratisation of data, business is not yet culturally geared up to handle this. There's a lot to do." Certainly, there are benefits to be had from democratisation: the relatively new school of thought that data should be made readily available in an organi sation rather than being kept in silos. The idea is that this provides a basis for more informed decisions throughout the enterprise while also encouraging innovation. Some of its proponents even claim that empowering employees by "digitising" a company, as Western Union calls it, could grant it a game-changing competitive edge. Yet only 27% of executives surveyed by MicroStrategy last year said they were con - fident that they'd built the right organisa- tional culture to support a data democracy. Indeed, the many hurdles to be surmoun- ted in deposing a data dictatorship – aside from the obvious ones, including simply finding the time in the case of SMEs – are only starting to become clear. Matthew O'Kane is global head of artifi- cial intelligence solutions at tech services company Cognizant. He believes that com- panies need to handle the democratisation process with kid gloves. In part, this is because of the potential interdepartmental sensitivities about data ownership, espe- cially in larger organisations. A recent multi-industry study by McKinsey found that, for teams requesting access to inter- nal data beyond their departmental remit, the response time could be measured in months in 53% of cases. O'Kane points to one retail bank's board-level diktat that ordered the central- isation of all data overnight but also gave reassurances that no material would be used without the consent of the team that originated it. Once a fully accessible centralised data store has been established, promoting it as such can be helpful, he says. For instance, AT&T rebranded its internal online mar - ketplace, Amp, as a company-wide data hub last year. This sort of "personification can create trust in the data". And trust is vital. When employees are offered greater access to data, they don't the case that [when it comes to data analysis] people don't know that they don't know." This applies even in prof- essional circles where a good understanding of data might be considered crucial. A study of 492 physicians for the Journal of the American Medical Association this year, for instance, found that their assessments of pre-test data led them to overestimate the likeli - hood of breast cancer in a patient by 976%. Small wonder, then, that a 2020 survey by data analytics company Qlik found that only 17% of lay employees considered themselves confident in handling data. More than two-thirds (67%) of respondents admitted that they felt overwhelmed by the numbers, while 19% said they had gone so far as to find other ways of completing a task without using data. The danger here is that there will be an expectation that lay employees possess the same understanding of data as its traditional keepers, the analysts. It's why O'Kane sees a growing role for artificial intelligence systems in filtering data into more comprehensible packages and also in checking all ensuing decisions. "After all", he notes, "a bank manager doesn't decide whether or not to approve your loan anymore. A computer does." This is also why education is important, according to Sen, whose company gives its employees mandatory training in certain aspects of data analysis. "Given the sheer volume of data that's out there, it's fundamental that any busi - ness seeking to democratise data should also educate its people in using that data," he argues. "Without learning how to han- dle data objectively, we all have biases and will lean into our own experiences when presented with material that challenges us. This training is not sufficient at most companies, while the smartest firms are really investing in it." But there is an argument that, even before a business addresses data literacy, it must address its data dependency: the belief that all data is valuable, even if it doesn't help to solve any known problem. "It's important for any business to rec - ognise the dynamics of complexity in data – and the fact that zooming in on really critical information can sometimes be highly predictive, better so than when using all the other data that might be added," says Florian Artinger, professor of digital business at Berlin International University of Applied Sciences. He cites the wildly fluctuating prices of airline tickets during the pandemic – a product of the data on which the industry's pricing model is based. "Making data more widely available can empower employees' expertise, but we shouldn't be lured into thinking an idea that can be backed by data is neces - sarily better than one arising from experience or intuition. After all, data can be used simply to 'cover your ass' and justify inaction or a bad move," Artinger says. "What we need first is a business culture that knows not only how but when to use democratised data – and when not to." FUTURE OF DATA R E G U L A T I O N D E C I S I O N I N T E L L I G E N C E R I S E O F T H E C D O Brexit could enable the UK to set its own data rules, but can it strike the right balance? Introducing a new analysis method that harnesses the power of machine learning Does your organisation need a chief data officer – and, if so, what kind? 06 08 10 Josh Sims I THE BARRIERS TO DATA DEMOCR ATISATION Percentage of companies that say the following factors hinder their use of data The number one thing I hear from the many CEOs and CIOs I talk to is that they don't feel ready for the democratisation of data, because they don't trust employees to make the right decisions using it D E M O C R A T I S A T I O N THE DATA SKILL S G AP What people who lack data-handling skills do when they need to make a decision based on data 43% 29% 27% 27% 25% 25% 24% 21% 21% 18% 44% Ask the IT team for help 34% Ask a business analyst for help 11% Make a gut decision 7% Use a self-service tool 4% Do their own research MicroStrategy, 2021

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