Designing with Human Data - Creating data-driven services with added value for people

Data is already an integral part of user-centric design processes for many products and services. This concerns all steps of digital solutions. From strategy to user experience, from visual design to content. Often, the focus is on people as sources of data. Important success factors are overvalued, control and transparency for all roles involved. Companies and people. The presentation provides a introduction into the field of data, personal data and provide methods for creative people to get involved in shaping data discussions in their projects.

Transcript

1. Creating data-driven services with 
 added value for people Designing with Human Data Thomas Otto // @thomasotto_ // thomas-otto.net
3. Thomas Otto // thomas-otto.net // 21.07.2019 3 Profile Senior User Experience Designer Research & Communication Exploring peoples behaviour & motivation Conception & Interaction Creating wireframes and prototypes Data Strategy & Consulting Exploring creative ways to use data for people and businesses
4. Thomas Otto // thomas-otto.net // 21.07.2019 4 Approach balancing and strengthening gut feeling using data to inform and inspire people leaving the comfort zone and taking different perspectives Lead through intuition , 
 informed by data , 
 driven by empathy .
5. What is Data?
6. 21.07.2019 Thomas Otto // thomas-otto.net // 6 Data Defintion Data Information =
7. 21.07.2019 Thomas Otto // thomas-otto.net // 7 Data Categories z Quantitative Data Qualitative 
 Data
8. 21.07.2019 Thomas Otto // thomas-otto.net // 8 Quantitative Data Definition • ... large amounts of structured or unstructured data • ... in the form of numerical data • ... can be divided into categories • ... can be measured • ... are mostly collected by machines • ... are evaluated by static methods Give hints that an event happened »What happened?« Server Logs 
 of login behaviour of users Facebook Likes 
 from people Conversion-Rate 
 of an eCommerce website
9. 21.07.2019 Thomas Otto // thomas-otto.net // 9 Qualitative Data Definition • ... (mostly) unstructured amounts of data • ... in the form of observations and interviews • ... are mostly collected by humans • ... are analysed through codes, summaries and topics Give hints on context of an event »How and why something happened?« Interview Protocols 
 with people Online survey 
 with open questions Remote-Usability Tests 
 with people
10. Was is Personal Data?
11. Mans of Transport Places Communication Content You
12. 21.07.2019 Thomas Otto // thomas-otto.net // 12 Data generation 2016 16,1 Zettabyte 2025 vs. 163 Zettabyte
13. Personal Data Which videos have I watched? Who are my friends? What did I have for lunch? Certificate of good conduct Identity Health data Communication Content Relationships Activity State records
14. Use & Markets of Personal Data
15. 21.07.2019 Thomas Otto // thomas-otto.net // 15 Personal data Usage Optimize your music experience and discover new music Music services use music consumption data to recommend new music, measure what music is being listened to and by whom. Manage and invest money optimally Financial services use data to recommend investments, manage money, and see who spends what on. Recommend content and play out »relevant« advertisements Social networks use data to personalize content and play advertisements that are tailored to the interests.
16. Music service Spotify collects data from smartphones... Spotify has updated its Terms & Conditions and now wants data like photos, files and contacts. There is no opt-out. https://www.theguardian.com/commentisfree/2015/aug/23/the-spotify-privacy-backlash-what-is- my-personal-data-really-worth
17. Financial service Query on details of private life Robin, a Deutsche Bank service, onboard their automated investment assistant, asks for intimate details about the household and life situation that are not relevant to the investment situation. Without this information the use of the service is not possible. https://www.maxblue.de/ddpm/#/personal-situation
18. Social Networks More than just a few preferences Facebook collects over 100 very private data points about its users. From personal details (birthplace, age, gender, sexual preferences), financial details (credit, salary, employment) to the use of third-party apps with Facebook login. https://www.washingtonpost.com/news/the-intersect/wp/2016/08/19/98-personal-data-points- that-facebook-uses-to-target-ads-to-you/?noredirect=on&utm_term=.0f7d310caef0
19. 21.07.2019 Thomas Otto // thomas-otto.net // 19 Voices of people 8,000+ global survey
 »People are concerned about how their personal data is handled« Source: »What Is the Future of Data Sharing?«
20. 21.07.2019 Thomas Otto // thomas-otto.net // 20 Negative Effects Users leave the service Through attention, users will seek alternatives to service and discourage others from doing so. Loss of profits Due to the migration of customers and image damage, sales (e.g. advertising revenues) are lost. Reputation damage for brand & company The brand and the company will hardly be able to build trust with customers and partners for a long time.
21. Human-Centred Data Strategy
22. Thomas Otto // thomas-otto.net // 21.07.2019 22 User-Centred Data Strategy Making processes transparent Create transparent processes in which all participants know which data is collected, why and how the data is further processed. Questions to answer • What data is collected? • Why is this data collected? • How is the data processed and shared? • How is the data stored and secured? Value Control Transparency
23. Thomas Otto // thomas-otto.net // 21.07.2019 23 User-Centred Data Strategy Ensure access and control Guarantee of the right of access for all parties involved to change, modify and port the data generated by them. How can we provide … • … access for users to their data • … a way for users to modify their data • … a way that users can port their data Value Control Transparency
24. Thomas Otto // thomas-otto.net // 21.07.2019 24 User-Centred Data Strategy Recognise added value Appreciation of the data generated and ensuring that there is always an equivalent and appropriate equivalent or exchange value. Every contribution made by individuals and their data forms the basis for data-based services. Therefore, they should be treated like large amounts of data from many people. Value Control Transparency
25. 21.07.2019 Thomas Otto // thomas-otto.net // 25 Current approaches EU-DSGVO Legal requirements of the European Union in force since 25 May 2018. Goal Basic protection of personal data of citizens* of the EU. Privacy-by-Design An engineering approach in which the privacy of the users is constantly present in the design of the system. Goal Ensure the privacy of the users at all stages of the design of a system. Data-Minimalism An approach in which only the most necessary data is collected and maximum transparency is achieved. Goal To collect and store only the absolute minimum of relevant data.
26. 21.07.2019 Thomas Otto // thomas-otto.net // Forerunners High-quality search results without creating profiles Search engine provider that does not create profiles and does not collect user data.
27. 21.07.2019 Thomas Otto // thomas-otto.net // Forerunners Health data in the hands of producers Menstruation app that only actively releases the data of the users.
28. 21.07.2019 Thomas Otto // thomas-otto.net // Forerunners Fitness tracking without data sale Fitness Tracker, which can also be evaluated without connection to a server.
29. Tools & Hands-On
30. Observe Reflect Make
31. Observe Reflect Make
32. 21.07.2019 Thomas Otto // thomas-otto.net // 32 Observe & Understand Who are our users (target audience)? What are goals & dependencies? Which data enrich the User Experience? Develop an understanding of the target group for which you are creating a service/product! 
 Questions • What are their values and beliefs? • What do they see and do? • What do they think and feel? Examines the use of data and examines exactly whether it is conducive to the goal of the project. Questions • Does the data contribute to the project goal? • Does the data improve the UX? • What is the purpose of usingdata? What goal should you achieve as a team or as a project? Are there dependencies? Questions • What is the goal of the project? • How is success measured? • What data is available?
33. 21.07.2019 Thomas Otto // thomas-otto.net // 33 Personal Data Cards Data type or aspect Category Examples or questions for discussion
34. 21.07.2019 Thomas Otto // thomas-otto.net // 34 Personal Data Cards Examples of personal data from the perspective of people Focus on security issues, from storage to transmission of data To raise concerns and identify challenges Ethical aspects with focus on people to make balanced decisions
35. Observe Reflect Make
36. Thomas Otto // thomas-otto.net // 21.07.2019 36 Team composition Product Team Scrum Master Friends 
 of 
 the team Exemplary team 
 setup Enterprise A large interdisciplinary specialised group Product Owner User Researcher UX 
 Designer Visual 
 Designer Frontend Developer Backend Developer Solution Architect Business Designer Data
 Analyst Data 
 Scientist Data Privacy Officer Legal QA Manager Content Strategist
37. Thomas Otto // thomas-otto.net // 21.07.2019 37 Team composition Product Team Friends 
 of 
 the team Exemplary team 
 setup small A core team of multidisciplinary roles Product Owner UX 
 Designer Visual 
 Designer Frontend Developer Backend Developer Solution Architect Data 
 Scientist Data Privacy Officer Legal
38. 21.07.2019 Thomas Otto // thomas-otto.net // 38 Don’t discuss just happy paths It is important that you get a common understanding of your work in the team as part of the project. Questions that help you to develop a common understanding are: • What do we as a team want to achieve with the data for our users? • How do we want to deal with people's data? • What do we as a team see as personal data of people? • What could happen in the worst case? Teamwork Discuss negative scenarios
39. 21.07.2019 Thomas Otto // thomas-otto.net // 39 Personal Data Canvas Long-term goals and target group Data topics: Access, use, storage Effects on people, risk management
40. Observe Reflect Make
44. Conclusion
45. Thomas Otto // thomas-otto.net // 21.07.2019 45 3 Things to keep in mind Use data Ask questions Think critically When you see the added value for your users. Reflect on your work and contribute to discussions on the subject of data. Something is not clear and you do not understand it
46. 21.07.2019 Thomas Otto // thomas-otto.net // 46 Download designhumandata.net You can find the shown material and more for free under the Creative Commons license on the website. Download, use, mix and change
47. Thank you Thomas Otto // @thomasotto_ // thomas-otto.net