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Data Maria Izquierdo, @izdo_maria Martin Jordan, @martin_jordan SERVICE LAB LONDON, 19 OCTOBER 2016 Services &

Data & Services / Service Lab London

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Page 1: Data & Services / Service Lab London

Data

Maria Izquierdo, @izdo_maria Martin Jordan, @martin_jordan

SERVICE LAB LONDON, 19 OCTOBER 2016

Services&

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@izdo_maria @martin_jordan

Who we are

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Maria Izquierdo — @izdo_maria Service Designer, Government Digital Service (GDS)

Martin Jordan — @martin_jordan Service Designer, Government Digital Service (GDS)

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@izdo_maria @martin_jordan

Disclaimer: We are not speaking on behalf of GDS today, but as professionals with a genuine interest in data

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Stand up, please!

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@izdo_maria @martin_jordan

Sit down if you have never dealt with data in a digital product or service in some way

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@izdo_maria @martin_jordan

Sit down if you have never had a discussion about the collection of data in a digital product or service

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Service

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“A service is something that helps someone to do something”—Louise Downe Head of Design of the UK Government

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“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

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Data

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“Data: Facts and statistics collected together for reference or analysis”—Oxford Dictionary

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“Data: commonly, organised information, collected for specific purpose”—Black’s Law Dictionary 1990

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DATA

INFORMATION

KNOWLEDGE

WISDOM

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LEVEL OF CARE INCREASES

Sensitive Personal Pseudonymous Anonymous

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Personal data• name • date of birth • address • telephone number

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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

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@izdo_maria @martin_jordan

Data in services

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@izdo_maria @martin_jordan

There can be no service without data

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@izdo_maria @martin_jordan

You cannot not design data in a service

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@izdo_maria @martin_jordan

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Gmail Calendar NotificationNow

Account

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@izdo_maria @martin_jordan

Data in services has implications for its users, but also for non-users

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Service needs Business needs User needs

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Service needs—improving offering Business needs—generating revenue User needs—fulfilling tasks

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“There is no such thing as a free service. So who gets paid by whom before what?”—Horace Dediu Industry analyst

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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

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When things go wrong

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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

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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

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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

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Privacy paradox

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“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

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1975Source: Paramount Pictures

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2015

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Ethical aspects—ignoring moral principles Privacy concerns—disclosing private matters Security risks—endangering people

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What the heck?

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Designers, ethics over aesthetics!

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You are the advocate for your users

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User needsBusiness needs

Service needs

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User needs Business needs

Service needs

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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?

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When things go well

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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/

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@izdo_maria @martin_jordan

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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/

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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.

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Principles for design for data by Sarah Gold / Project IF

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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

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Let’s apply Sarah’s principles to services in the private sector:

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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

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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

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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

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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

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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

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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

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Exercise

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Exercise!

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Form a group of five—with maximum diversity, i.e. not your colleagues or friends who you arrived with

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Grab a sheet, pick a service category, answer the questions

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Messaging service Photo-sharing service Micro-blogging serviceX

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What data is being collected? Why? What does it enable in the service? What are potential risks?

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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

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Tell us!

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Take-aways

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If you aren’t acting as the users’ advocate, no one else will

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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

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• 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.

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It ain’t proper service design, if you aren’t designing for data in the service

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Thanks very much Questions? Comments? Concerns?

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GDS

Government Digital Service is hiringservice designers

@GDSteam #govdesign

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GDS

Join us and work on things that matter

@GDSteam #govdesign

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Happening soon…

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Not your average conference

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Inspiring key talks

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Confirmed so far…

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Hands-on workshops

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Open session you decide on…

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… and lead

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That’s why we call it a co-conference —because you co-create it

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Plus, more fun than at a usual conference

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And really great food

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Taking place 18–19 November in Berlin

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Save 10% until midnight

using the code ‘SXC16xServiceLabLDN’

sxc16.eventbrite.com