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Data-driven UX: What it really takes and how to get there

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Data-driven UX: What it really takes and how to get there

  1. 1. Data-driven UX What it takes and how do we get there? Emmanuelle Boloix, Ph.D.
  2. 2. Who am I? https://www.linkedin.com/in/eboloix/
  3. 3. • Design thinking workshops • Creativity workshop • Stakeholder interviews • Quick user feedback • Context mapping • Communication mapping • Participatory design • Surveys… Define Ideate Prototype DeliverUnderstand • Usability testing • User interviews • Surveys • User experience questionnaires • SUS • SUPR-Q • NPS… • User interviews • Stakeholder interviews • Contextual inquiries • Observations • Surveys • Card sorting • Eye tracking • Heuristic evaluations… User-Centered Design
  4. 4. Data-driven UX: Measuring UX at every phase of the UCD process “The good thing about data? It speaks for itself.” Define Ideate Prototype DeliverUnderstand • Measure and understand the various parts of the ecosystem • Cross-reference and validate insights • Protect the researchers against their own biases • Inform decision • Strategize the roadmap • Benchmark solution UX • Monitor UX health • Identify areas and group of adoption risk • Predict user adoption • Measure user adoption Define Ideate Prototype DeliverUnderstand
  5. 5. Distribution tower Responsible for planning and delivering materials and personnel to the crews on the wellsite Objective: Rethink the distribution tower to unlock potentialities
  6. 6. Define Ideate Prototype DeliverUnderstand
  7. 7. From user interviews and observations to data • 5 user roles identified • Users have a capital support role for field operation: if they fail, operations cannot run • Major issues experienced by users are: • Communication failures • Poor handover between teams • Software systems unfit to user needs • Creation of shadow systems Understand
  8. 8. Logging data is a key part of the process toward data-driven UX It allows: • Coding insights and discover invisible patterns • Preserve the integrity of the qualitative data against researcher biases (empathy bias, memory bias, confirmation bias…) Understand
  9. 9. Demo
  10. 10. What do the numbers tell us? • Communication seem to fail for most user roles, and particularly for the user role 5  What is happening exactly? • Handover is a major issue to user roles 1 and 5  Why? How? • Current systems seem to fail all user roles, and all user roles have created their own shadow systems 0 1 2 3 4 5 6 7 8 9 COMMUNICATION HANDOVER SYSTEM FAILURE SHADOW SYSTEM NUMBEROFISSUES User role 1 User role 2 User role 3 User role 4 User role 5 Understand
  11. 11. What does that tell us about the solution? Systems are unfit for purpose for all users • Exploration of shadow system reveals that current modules for personnel planning and materials planning are unfit for purpose and need to be redesigned Communication and handover • Communication and handover between user roles are a big issue and raised more questions Define Ideate
  12. 12. Define Ideate Prototype DeliverUnderstand
  13. 13. Creativity workshops and surveys can help answering additional questions Define IdeateUnderstand
  14. 14. From maps to data
  15. 15. 0 2 4 6 8 10 12 14 User role 2 User role 4 User role 5 User role 3 User role 1 Number of topic exchanged between user role 5 and their main contacts Communication mapping survey User role 5 only pushes information to contact 1 User role 1 is dependent on user role 5 on a lot of topics 0% 20% 40% 60% 80% 100% User role 2 User role 4 User role 3 User role 5 User role 1 Communication direction between user role 5 and their main contacts To From Define Ideate
  16. 16. What does that tell us about the solution? Communication and handover • Reorganize seating so that user role 1 and user role 5 are now sitting next to each other: force communication and increase quality of information handover Systems and shadow systems • Exploration of shadow system reveals that current modules for personnel planning and materials planning are unfit for purpose and need to be redesigned Define Ideate
  17. 17. How can data help the stakeholders strategize the roadmap? 0% 20% 40% 60% 80% 100% User roles affected Number of users Materials planning Personnel planning Define Ideate
  18. 18. Define Ideate Prototype DeliverUnderstand
  19. 19. Usability testing Prototype Deliver
  20. 20. What type of issues for users? 0% 2% 4% 6% 8% 10% 12% 14% 16% History Materials planning Personnel planning Data History Materials planning Personnel planning Data History Materials planning Personnel planning LIKE Unmet need Usability Percentageofissues Prototype Deliver
  21. 21. Tracking UX issues and fixes Prototype Deliver
  22. 22. Usability testing issues tracking 0 5 10 15 20 25 30 35 40 FURTHER VERSION IN QUEUE NEED BUSINESS DECISION TRAINING Unmet need Usability Prototype Deliver
  23. 23. Tracking issues across solution releases Release 1 Release 2 Release 3
  24. 24. Tracking usability testing fixes across time Evolution of “unmet needs” issues Evolution of “usability issues” 0 5 10 15 20 25 30 35 40 FURTHER RELEASE IN QUEUE NEED BUSINESS DECISION TRAINING RELEASE 1 RELEASE 2 RELEASE 3 0 5 10 15 20 25 30 35 40 FURTHER RELEASE IN QUEUE NEED BUSINESS DECISION TRAINING RELEASE 1 RELEASE 2 RELEASE 3
  25. 25. Benchmarking and predicting user adoption Legacy system Release 1 Release 2 Release 3
  26. 26. 0 20 40 60 80 100 User group 1 User group 2 Legacy system Release 1 Benchmarking UX and predict adoption Track the UX health of your solution across groups Track the UX health of your solution over time 0 20 40 60 80 100 Legacy system Release 1 Release 2 Release 3 *
  27. 27. Every data you analyze is a piece of the puzzle
  28. 28. The major obstacles to data-driven UX Limited access to users Team/stakeholders need feedback right away Limited amount of time: UX Unicorn working on several project Strong insights from few interviews Insufficient training in data analysis
  29. 29. Thank you

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