Data & Services / Service Lab London

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To design effective user-focused services, we need to use data. We need to understand how people are using the service, what works for them and what doesn’t. There can be no service without data.

But as designers, we have to focus on user needs. That means we need to address users’ data needs as well as their service needs. We must design good services based on good data that don’t infringe on people’s privacy.

This means we have to look at questions like: what data is my service collecting? How and when is this data being used? Who has access to this data and who owns it? And how do we keep it secure?

As service designers working with data on a daily basis, we want to raise awareness of the value of data to services. And we want to discuss fundamental questions around what happens to that data.

This talk was held at Service Lab London on 19 October 2016 by Maria Izquierdo and Martin Jordan.

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Data & Services / Service Lab London

  1. 1. Data Maria Izquierdo, @izdo_maria Martin Jordan, @martin_jordan SERVICE LAB LONDON, 19 OCTOBER 2016 Services &
  2. 2. @izdo_maria @martin_jordan Who we are
  3. 3. @izdo_maria @martin_jordan Maria Izquierdo — @izdo_maria Service Designer, Government Digital Service (GDS) Martin Jordan — @martin_jordan Service Designer, Government Digital Service (GDS)
  4. 4. @izdo_maria @martin_jordan Disclaimer: We are not speaking on behalf of GDS today, but as professionals with a genuine interest in data
  5. 5. @izdo_maria @martin_jordan Stand up, please!
  6. 6. @izdo_maria @martin_jordan Sit down if you have never dealt with data in a digital product or service in some way
  7. 7. @izdo_maria @martin_jordan Sit down if you have never had a discussion about the collection of data in a digital product or service
  8. 8. @izdo_maria @martin_jordan Service
  9. 9. @izdo_maria @martin_jordan “A service is something that helps someone
 to do something” —Louise Downe Head of Design of the UK Government
  10. 10. @izdo_maria @martin_jordan “Service is the application of specialised competences through deeds, processes and performances for the benefit of another entity” —Stephen L. Vargo Professor of Marketing, University of Hawai'i at Manoa
  11. 11. @izdo_maria @martin_jordan Data
  12. 12. @izdo_maria @martin_jordan “Data:
 Facts and statistics collected together
 for reference or analysis” —Oxford Dictionary
  13. 13. @izdo_maria @martin_jordan “Data:
 commonly, organised information,
 collected for specific purpose” —Black’s Law Dictionary 1990
  14. 14. @izdo_maria @martin_jordan DATA INFORMATION KNOWLEDGE WISDOM
  15. 15. @izdo_maria @martin_jordan LEVEL OF CARE INCREASES Sensitive Personal Pseudonymous Anonymous
  16. 16. @izdo_maria @martin_jordan Personal data • name • date of birth • address • telephone number
  17. 17. @izdo_maria @martin_jordan Personal data — Sensitive personal data • name • date of birth • address • telephone number • physical or mental health conditions • offences or alleged offences • religious beliefs • sexual life
  18. 18. @izdo_maria @martin_jordan Data in services
  19. 19. @izdo_maria @martin_jordan There can be no service without data
  20. 20. @izdo_maria @martin_jordan You cannot not design data in a service
  21. 21. @izdo_maria @martin_jordan
  22. 22. @izdo_maria @martin_jordan Gmail Calendar NotificationNow Account
  23. 23. @izdo_maria @martin_jordan Data in services has implications for its users, but also for non-users
  24. 24. @izdo_maria @martin_jordan Service needs Business needs User needs
  25. 25. @izdo_maria @martin_jordan Service needs—improving offering Business needs—generating revenue User needs—fulfilling tasks
  26. 26. @izdo_maria @martin_jordan “There is no such thing as a free service.
 So who gets paid by whom before what?” —Horace Dediu Industry analyst
  27. 27. @izdo_maria @martin_jordan Source: http://www.bbc.co.uk/news/business-37476335 92% do not understand how personal information is used 57% do not trust organisations to use data responsibly 51% say their data misused 16% always read terms and conditions
  28. 28. @izdo_maria @martin_jordan When things go wrong
  29. 29. @izdo_maria @martin_jordan Target—is able to calculate a pregnancy prediction score based on 25 products and send coupons timed to very specific stages of someone’s pregnancy, thereby, in one instance, knowing about a teenage girl’s pregnancy before their parents did Ethical aspect Source: http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/#50b7f32734c6
  30. 30. @izdo_maria @martin_jordan DriveNow—created precise movement profile of a carsharing customer including route taken, speed of vehicle, outdoor temperature and position of mobile phone during booking; providing evidence in manslaughter trial, but violating its own T&Cs Privacy concerns Source: http://www.manager-magazin.de/unternehmen/autoindustrie/bmw-autobauer-liefert-gericht-kundendaten-fuer-bewegungsprofil-a-1104050.html
  31. 31. @izdo_maria @martin_jordan SmartTVs—recording spoken words including personal or other sensitive information and transmitting the captured data to a third party through use of their Voice Recognition software; constantly spying in people’s living rooms Security risks Source: http://www.bbc.co.uk/news/technology-31296188
  32. 32. @izdo_maria @martin_jordan Privacy paradox
  33. 33. @izdo_maria @martin_jordan “We say we want privacy online, but our actions say otherwise […] people who indicate serious privacy concern nevertheless reveal intimate details of their lives for trivial rewards” —Leslie K. John Associate professor, Harvard Business School Source: https://hbr.org/2015/10/we-say-we-want-privacy-online-but-our-actions-say-otherwise
  34. 34. @izdo_maria @martin_jordan 1975 Source: Paramount Pictures
  35. 35. @izdo_maria @martin_jordan 2015
  36. 36. @izdo_maria @martin_jordan Ethical aspects—ignoring moral principles Privacy concerns—disclosing private matters Security risks—endangering people
  37. 37. @izdo_maria @martin_jordan What the heck?
  38. 38. @izdo_maria @martin_jordan Designers, ethics over aesthetics!
  39. 39. @izdo_maria @martin_jordan You are the advocate for your users
  40. 40. @izdo_maria @martin_jordan User needs Business needs Service needs
  41. 41. @izdo_maria @martin_jordan User needs Business needs Service needs
  42. 42. @izdo_maria @martin_jordan Ask: What data is the service collecting? And why? How and when is this data being used? Who has access to this data and who owns it? And how do we keep it secure?
  43. 43. @izdo_maria @martin_jordan When things go well
  44. 44. @izdo_maria @martin_jordan
  45. 45. @izdo_maria @martin_jordan BBC—“Our privacy promise covers how we treat your data and put you in control of what happens to it. It’s based around three main areas […] transparency, choice, trust” Embracing transparency and simple language Source: http://www.bbc.co.uk/privacy/
  46. 46. @izdo_maria @martin_jordan
  47. 47. @izdo_maria @martin_jordan
  48. 48. @izdo_maria @martin_jordan Co-op Paperfree—“We’re committing to a data relationship that’s unambiguously clear and transparent. We will always be clear and precise with you, our members about what we are going to do with your data. You will be in control of the data we hold on you.” Taking sensitive data seriously Source: https://digital.blogs.coop/2016/05/21/co-op-agm-2016/
  49. 49. @izdo_maria @martin_jordan
  50. 50. @izdo_maria @martin_jordan Source: http://www.helloclue.com/privacy.html / http://blog.helloclue.com/post/135713474876/why-data-will-revolutionize-global-female-health Providing options and guaranteeing privacy Clue—“You can use Clue without creating an account and if you do you will not share your data. If you wish to use Clue Connect, however, you do need an account and once you create an account your data will be hosted on Clue’s servers.
  51. 51. @izdo_maria @martin_jordan Principles for design for data by Sarah Gold / Project IF
  52. 52. @izdo_maria @martin_jordan Source: Sarah Gold, Projects by IF / https://projectsbyif.com/ideas/design-for-data 1 Keep other services in mind 2 Collect minimum viable data 3 Be transparent 4 Get consent 5 Put users in control of their data 6 Separate the data
  53. 53. @izdo_maria @martin_jordan Let’s apply Sarah’s principles to services in the private sector:
  54. 54. @izdo_maria @martin_jordan Source: Sarah Gold, Projects by IF / https://projectsbyif.com/ideas/design-for-data 1 Keep other services in mind • Don’t lock users into your service • Consider what value the data could create when used in other services too • Think about API usage
  55. 55. @izdo_maria @martin_jordan 2 Collect minimum viable data • Ask for the data you really need, not more • Question what you really need to know e.g. date of birth / confirmation of 18+ • Think about data breaches, hacks, requests from regimes
  56. 56. @izdo_maria @martin_jordan 3 Be transparent • Explain to your users what data you keep for what reason and who owns it • State what data you collect, use and store • Share this big data with the world
  57. 57. @izdo_maria @martin_jordan 4 Get consent • Use simple language so people understand what they are agreeing to • Don’t bury details in 60-page privacy statement when you ask for consent • Allow them to revoke consent
  58. 58. @izdo_maria @martin_jordan 5 Put users in control of their data • Give users a choice to share data or not • Don’t force account creation • Allow full deletion of account and data
  59. 59. @izdo_maria @martin_jordan 6 Separate the data • Decouple services and data • Unlink personal and sensitive personal data wherever possible—pseudonymise • Separate data on people from data on things
  60. 60. @izdo_maria @martin_jordan Exercise
  61. 61. @izdo_maria @martin_jordan Exercise!
  62. 62. @izdo_maria @martin_jordan Form a group of five
 —with maximum diversity, i.e. not your colleagues or friends who you arrived with
  63. 63. @izdo_maria @martin_jordan Grab a sheet, pick a service category, answer the questions
  64. 64. @izdo_maria @martin_jordan Messaging service Photo-sharing service Micro-blogging serviceX
  65. 65. @izdo_maria @martin_jordan What data is being collected? Why? What does it enable in the service? What are potential risks?
  66. 66. @izdo_maria @martin_jordan What data is being collected? Location of user, every 3 minutes Why? To give user contextual recommendations What does it enable in the service? Understanding if user is new to area or not What are potential risks? Generating detailed movement profiles
  67. 67. @izdo_maria @martin_jordan Tell us!
  68. 68. @izdo_maria @martin_jordan Take-aways
  69. 69. @izdo_maria @martin_jordan If you aren’t acting as the users’ advocate, no one else will
  70. 70. @izdo_maria @martin_jordan Step up your game, designers, don’t only design services that easy are to use but also trustworthy, understandable, accountable* *Inspiration: Richard Pope / http://www.memespring.co.uk/talks/oscon2016/oscon.pdf
  71. 71. @izdo_maria @martin_jordan • Join discussions with your team members • Apply Sarah’s principles for design for data • Ask why, ask why again and then once more • Design for worst case scenarios • Consider data accumulation over time • Tweak your tools, add data swim lanes etc.
  72. 72. @izdo_maria @martin_jordan It ain’t proper service design, if you aren’t designing for data in the service
  73. 73. @izdo_maria @martin_jordan Thanks very much Questions? Comments? Concerns?
  74. 74. GDS Government Digital Service is hiring service designers @GDSteam #govdesign
  75. 75. GDS Join us and work on things that matter @GDSteam #govdesign
  76. 76. Happening soon…
  77. 77. Not your average conference
  78. 78. Inspiring key talks
  79. 79. Confirmed so far…
  80. 80. Hands-on workshops
  81. 81. Open session you decide on…
  82. 82. … and lead
  83. 83. That’s why we call it a co-conference —because you co-create it
  84. 84. Plus, more fun than at a usual conference
  85. 85. And really great food
  86. 86. Taking place 18–19 November in Berlin
  87. 87. Save 10% until midnight using the code ‘SXC16xServiceLabLDN’ sxc16.eventbrite.com

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