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501 Talks Tech: Design Thinking Workshop by Dupla Studios

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501 Talks Tech: Design Thinking Workshop by Dupla Studios

  1. 1. Design Thinking Your Creative Toolkit to Solving Real-World Problems Kevin Decker, Head of Research and Strategy Dupla Studios Melissa Quintanilha, Head of Design
  2. 2. What is Design Thinking Case Study 1: Automotive Infotainment Case Study 2: Democracy Lab Break Practice: Interviewing skills Practice: Making sense of user data AGENDA
  3. 3. Design Thinking is an innovation methodology WHAT IS DESIGN THINKING? - for products, for services, for anything
  4. 4. WHAT IS DESIGN THINKING? Design Thinking is a culture of mindsets
  5. 5. The Design Thinking Process
  6. 6. Getting the right design Getting the design right
  7. 7. Case Study 1: 
 Automotive infotainment
  8. 8. Get into the field and empathize 1 DISCOVER Make your observations with your target profile/persona, at the front lines of the problem. Explore the problem from the classic reporting vectors; Who, What, Where, When, and Why One important point: Your observations have to be something you personally observed or heard. A behavior or a quote. It’s ok to note other problems that you identify as an expert, but you want to solve your customers’ pain points. Avoid jumping to solutions Don’t assume to know what people need before you’ve identified the common problems. Contextual Interviews and how to handle them The beginner’s guide to contextual interviewing RESOURCES
  9. 9. FIELD OBSERVATIONS • Most people are distracted by things they bring into the car, cell phone, coffee, food, makeup, electric razors etc. • Existing in-car infotainment systems are overly complex with multiple screens, confusing navigation, and unfamiliar interaction models, (e.g. BMW dial/knob control) • Overly complex systems take more cognitive resources and attention than simple systems. • Most modern infotainment systems use touch as the primary input making people remove their hands from the wheel (most allow for voice activation for phones). CASE STUDY: AUTOMOTIVE INFOTAINMENT 1 DISCOVER
  10. 10. Make sense of the data Extract themes from your field observations. Themes are clusters of observations that are associated. Group themes into insights. Insights are your analysis of how the themes relate to your research problem/ questions. Your insights become your product requirements. Translating insights into requirements is done by asking how the insight describes the solution. Scenarios are created which are stories of how customers use the solution. Organizing the scenarios together in chronological order becomes the user journey. Affinity Diagrams: Learn how to cluster and bundle ideas and facts A Beginner’s Guide to User Journey Mapping RESOURCES 2 DEFINE
  11. 11. • People are required to look away from the road for too long in current solutions. • People need a simple navigation schema to maximize their attention to driving. • People should not have to remove their hands from the vehicle controls in order to interact with the system. DESIGN INSIGHTS CASE STUDY: AUTOMOTIVE INFOTAINMENT • All screens need to be understood at a glance (a look lasting under a few seconds). • Interaction should be accomplished without touch. • Information prioritization puts highest important information closest to the steering wheel, HUD. Less important on the console or screen. PRODUCT REQUIREMENTS USER SCENARIOS AND STORYBOARDS 2 DEFINE
  12. 12. 1. Defer judgement 2. Encourage wild ideas 3. Build on the ideas of others (“Yes, and…” mentality) 4. Stay focused on the topic 5. Go for quantity 6. Brainstorm with the data in sight EXPLORE OPTIONS Operationally define your success 1. What does success look like? 2. How would you know you were a success? 3. What behaviors would characterize the ideal? DEFINE SUCCESS Ideate and Prototype 3 DEVELOP Brainstorming RESOURCES Prototype most promising ideas. PROTOTYPE
  13. 13. • Screen layouts enable understanding in less than a few seconds • All interactions are voice first • Primary information appears in the HUD, Secondary information is surfaced behind the steering wheel and tertiary information lives on the in dashboard/ console. SUCCESS CRITERIA CASE STUDY: AUTOMOTIVE INFOTAINMENT 3 DEVELOP
  14. 14. 1. Create prototypes with the idea that the prototype may be thrown away. (don’t fall in love with it) 2. Show customer (get feedback early and often) 3. Catalog failures/Keep successes 4. Iterate 5. Wash, rinse, and repeat until design meets success criteria BIAS TO ACTION: CREATE, MAKE, DISCARD Delighting your customers means combining the pain points you observed, as an expert, with the pain points your customers explicitly revealed to you into a single solution. REFINE AND FINISH Iterate and Perfect 4 DELIVER
  16. 16. Delighting your customers is a process, not luck
  17. 17. Case Study 2
  18. 18. FIELD OBSERVATIONS •Project owners often work in isolation •Volunteers tend to me more hobbyist than professionals •Projects are hard to discover •Hard to get volunteers if project is not open source. •Volunteers have limited time to devote, so they want to have impact with the time they have. •Difficult to maintain volunteer commitment. •Cost of onboarding volunteers exceeds benefits •Finding the right talent with current tools a challenge. CASE STUDY: DEMOCRACY LAB
  19. 19. DESIGN CONSTRAINTS •Volunteers need to find jobs that they already have skills to do. •Non-profits need to retain their volunteers to be successful. •Regular communication is key. •Access anywhere so that volunteers can see information at their convenience so they are not working in isolation. •Projects need to have resources attached to them to onboard new volunteers as simply as possible. DESIGN INSIGHTS •Volunteers need to feel their work has impact. •Non-profits need specific skills but do not know how to advertise them. •Skilled volunteers develop loyalty when they feel responsibility for calling or purpose. •Projects tend to have poor onboarding which leaves new volunteers unsure of ability to help. •Communications between the non-profits and volunteers is random and comes in fits and spurts. CASE STUDY: DEMOCRACY LAB
  20. 20. SUCCESS METRICS •Increase in volunteer sustainability in non-profit engagements •Increase in volunteer satisfaction •Increase in volunteer acquisition by non-profits using Democracy Lab compared to those who do not. CASE STUDY: DEMOCRACY LAB
  21. 21. Success metrics The solution is a Web application where volunteers can input their skills and interests and the site will output opportunities and requirements for each effort. CASE STUDY: DEMOCRACY LAB
  22. 22. “The design thinking process we learned from Dupla Studios was essential to the subsequent success we experienced researching, designing and developing our open source platform. We learned the critical importance of talking to users, how to distill users' observations into insights, and how to make those insights actionable. These lessons now inform every decision we make.” Mark Frischmuth, CEO Democracy Lab
  23. 23. WORKSHOP Understanding your users
  24. 24. 15 MINUTES Break
  25. 25. Even imperfect data trumps opinion DISCOVER Better to do something than nothing
  26. 26. FIELD OBSERVATIONS Data are bits of information that you can gather. There are three valuable pieces of data that you can access. •Primary data – 1st hand information you collect. •Secondary data – data supplied by a third party, anecdote about themselves •Tertiary – data from someone about someone else's experience. Any data trumps opinion 1 DISCOVER
  27. 27. Some popular research methods ranked from least to most expensive Pros Cons Costs Periodicals Easy to find and use Quality, interpretation of results Low Surveys Easy to set up, large sample size, analysis tools included Access by target audience, data entry, actionable results difficult Low 1:1 interviews Easy to perform, flexible time frame, deep dive on subject matter Invasive, interviewer ability, small sample size, analysis is messy and time consuming Low Focus groups Quick to perform, modest cost Very challenging method to execute, data is similar to interviews Modest Participatory design Immediate feedback, deep dive, Small sample size, time intensive, ability to respond to feedback Mid-high Longitudinal Studies Data comes in over time, deep dive, large sets of data Costly in both time and money, small sample sizes, attenuation. High Understanding the people you are designing for
  28. 28. Every method relies on one key ingredient… CURIOUS MIND Asking good questions
  29. 29. • Ask open-ended questions • Ask about actual behavior, not intention • Ask about illustrative stories Good vs Bad questions DO DON’T • Ask leading questions • Ask compound questions • Point out specific issues
  30. 30. Good vs Bad questions • Q: "So you feel that grilling outdoors fosters family togetherness?“ • A: "Sure." • Q: "Is there anyone in your family who doesn't enjoy grilling?" • A: "My father." • Q: "But you feel it's a bonding ritual all the same?" • A: "Yeah, kinda." • Q: "How does grilling work in the text of your life? Would charcoal have interfered with the process of social bonding?" • A: "I'm not sure, really. We just prefer gas."
  31. 31. Good vs Bad questions Bad questions Good questions Do you like free weights? Answer can be given with a single word answer, does not allow for alternatives What kind of equipment do you like to use at the gym? Invites longer answers, allows for a larger variety of answers Would you say that Cardio classes are a better workout than lifting weights? A lot of people think weights are dangerous, you agree right? Implies a “correct” answer What type of exercise gives you the best workout? Allows for all types of answers When at the gym do you like free weights, or weight machines or resistance bands, or cross fit? Compound questions can be confusing. Which strength training method do you like to do? Lets interviewee inform you of their behavior.
  32. 32. • Easy to perform • Flexible time frame • Deep dive on subject matter Method: Interviews PROS CONS • Invasive • Interviewer ability • Small sample size • Analysis is messy and time consuming
  33. 33. • Create a discussion guide • Pre-define a recording method – bring a back up plan • Limit the number of attendees – is it an interview or inquisition? • Know your topic boundaries – stay on task • One interviewer per interviewee • Use appropriate note taking method Interviewing Best Practices Prepare Respect participants • Be on time/start on time • ALWAYS ask permission for recording (even note taking) • Explain reason for interview • Explain confidentiality • Make it a conversation • Take notes but don’t be a stenographer • Never judge responses • Keep your timetable
  34. 34. • Participants = People • Put yourself in the other person’s shoes • Listen at least twice as much as you speak • Don’t feel the need to fill silence • Never interrupt! • Don’t judge what you hear Interviewing Best Practices
  35. 35. Data Gathering Techniques PRACTICE
  36. 36. • Break into groups of 3 • 3 minutes 
 Write a discussion guide to learn everything you can about your group mates • 1 minute
 Assign each person in the group a role (Interviewer, Interviewee, Observer) • 5 minutes 
 Interview your group mates. • 2 minutes 
 Have observer critique interview with specific examples • Rotate roles until everyone has had a chance in each role PRACTICE (30 mins)
  37. 37. • Tell me a little about yourself - where are you from, where do you live now? • What do you do for a living? For fun? • Tell me about a typical day. • What is your least / most favorite thing that happens in a typical day? • If you could wave a magic wand and have an app to make the least / most favorite thing better, what would you want to have happen? Example Discussion Guide
  38. 38. Making sense of user data
  39. 39. Assembling your observations 1 It has to be something you saw your heard. A behavior or a quote. GUIDELINE 2 It can’t be a solution yet. Don’t assume to know what people need before you’ve identified the common problems. GUIDELINE MAKING SENSE OF USER DATA problem definition research question gather observations glean insights develop design constraints
  40. 40. Populating your affinity diagram MAKING SENSE OF USER DATA USE SHARPIE ONLY WRITE ONE DATA POINT PER POST-IT WRITE LARGE AND LOUD USE ONE COLOR OF POST-IT PER INTERVIEWEE problem definition research question gather observations glean insights develop design constraints
  41. 41. Developing groups and themes MAKING SENSE OF USER DATA Look at your research and create an affinity diagram looking for groups of behaviors, attitudes, or attributions. FIND YOUR GROUPS What do the groupings mean? Not looking for a description, but rather investigating why those things are affiliated. Write down the relationship between the things in the group. FIND YOUR THEMES problem definition research question gather observations glean insights develop design constraints
  42. 42. Extracting insights from user data MAKING SENSE OF USER DATA Identify which of these insights has direct bearing on the design challenge that you want to resolve, discard the rest (archive if possible). AND EXTRACT THE MOST IMPORTANT ONES Think about and document the relationship between your themes AND your problem, domain, or design challenge. FIND YOUR INSIGHTS Theme + Problem = Insight problem definition research question gather observations glean insights develop design constraints
  43. 43. Insights become design constraints MAKING SENSE OF USER DATA Refine your insights into design constraints depending upon what type of solution you are attempting to resolve. Design constraints are no more or less than the translation of how your themes define the boundaries of your solution. REFINE YOUR INSIGHTS problem definition research question gather observations glean insights develop design constraints Reframe your insights into constraints for the design of your solution (also known as design requirements).
  44. 44. Thank You. Kevin Decker, Head of Research and Strategy ( Dupla Studios Melissa Quintanilha, Head of Design (