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Decision Making in Product Design

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Lecture I gave on Decision Making and Research in Product Design, for a Faculty Position Interview at Carnegie Mellon University.

Outline:
- Decision Making in Product Design
- Measuring Ambiguous Situations
- Case Study: Uber Technologies
- Case Study: Symbiote Systems

Published in: Design
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Decision Making in Product Design

  1. 1. Zaid Haque Carnegie Mellon Qatar 20 March 2017
  2. 2. About Me Red Dot Award: Bilingual Flight Info Display SystemMy Website
  3. 3. What about you? What makes you interested in HCI and Design? Why did you choose this class? What do you want to do after graduation?
  4. 4. Lecture Outline -Decision making in product design -Measuring ambiguous situations -Uber Technologies - Symbiote Systems (time permitting) An insight into design research in mobility
  5. 5. A little background… This lecture is brought to you by a design researcher and strategist symbiote Uber Technologies, Inc. Design Researcher Product Team Symbiote Systems Co-founder Strategy/Product
  6. 6. My job is literally making decisions. But based on what? Designers often need to ‘use their gut’ to conceptualize their products.
  7. 7. Making large- scale decisions A lot of times as designers and engineers we need to make decisions on potentially ambiguous situations. 
 How do we decide which path to follow?
  8. 8. Cost FormFunction Product Parameters Money, Manpower, effort, etc. Aesthetics, Beauty Performance, Features
  9. 9. Cost FormFunction Corporate Managers Everyone has different views on what is important. Product Parameters
  10. 10. Cost Form Function Software Engineers Everyone has different views on what is important. Product Parameters
  11. 11. Cost Form Function “Designers” - closer to Artists Everyone has different views on what is important. Product Parameters
  12. 12. Cost FormFunction Try to balance these out! Product Parameters
  13. 13. Money matters. Each decision you make as a designer/engineer costs the company money. You’ll need to convince them what you are doing will help their business.
  14. 14. So do we follow the money? No. But yeah. Kind of.
  15. 15. Find a balance What can create the biggest impact on our users with the least effort?
  16. 16. Complexity/Cost Impact quick wins low-hanging fruit ratholes big ticket items
  17. 17. But how do you measure the impact? Only way to convince management to accept your terms is to show them numbers.
  18. 18. Qualitative vs. Quantitative Data Our customers are giving positive reviews. Our rating on the App Store is 4.7 stars. We provide taxis quicker than our competitors. We can get a driver to a customer within 3 mins. ??? ???
  19. 19. Key Performance Indicators Business-savvy term for the success of your product.
  20. 20. HOW CAN WE REDUCE AMBIGUITY WHEN ESTABLISHING RIDER PICKUP LOCATIONS? CHALLENGE
  21. 21. UNPACKING
  22. 22. MULTIPLE TYPES OF RIDER PICK-UPS UNPACKING
  23. 23. AMBIGUITY OCCURS ON TWO PARTS OF THE USER FLOW UNPACKING
  24. 24. SYSTEM DIAGRAM/ WEDGES
  25. 25. SYSTEM DIAGRAM/ WEDGES
  26. 26. KEY PERFORMANCE INDICATORS 5 Star driver/rider ratings Number of phone callsDistance between request and pickup locations Difference between est. and actual pickup times
  27. 27. KEY PERFORMANCE INDICATORS
  28. 28. JOURNEY START FINISH iBEACONS BLUETOOTH LTE DIRECT SUGGESTIONS COMMENTS COLOR CODING CONFIRMATION STREET VIEW
  29. 29. CONFIRMATION Locating the rider RIDER CONFIRMS THEIR LOCATION; GPS COORDINATES AND VENUE NAME SENT TO DRIVER. Rider app Driver app https://atc-mengproject.herokuapp.com/nearby_locations#
  30. 30. CONFIRMATION Locating the rider RIDER CONFIRMS THEIR LOCATION; GPS COORDINATES AND VENUE NAME SENT TO DRIVER. Rider app Driver app https://atc-mengproject.herokuapp.com/nearby_locations#
  31. 31. COLOR CODES Identifying the driver RIDER AND DRIVER FLASH COLOR CODED SCREENS TO QUICKLY IDENTIFY EACH OTHER. BETA TESTING IN SEATTLE
  32. 32. COLOR CODES Identifying the driver
  33. 33. LTE DIRECT Locating a rider using other phones Rider Phone 1 Phone 2 Phone 3 https://www.qualcomm.com/invention/research/projects/lte-direct
  34. 34. ARCHITECTURE
  35. 35. VALIDATION Worldwide usage of our app Doha London San Francisco
  36. 36. VALIDATION 26m % of riders by walking distance 0 4.5 9 13.5 18 5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 AVERAGE WALKING DISTANCE FOR RIDERS Calculated using Uber’s Ride Data in Manhattan
  37. 37. VALIDATION % of riders by walking distance 0 12.5 25 37.5 50 5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 10.5mAVERAGE WALKING DISTANCE FOR RIDERS Calculated using our app
  38. 38. Qualitative Analysis? It’s still useful, but can you make it quantitative?
  39. 39. Always remember Back your decisions up with hard data!
  40. 40. Lecture Outline -Decision making in product design - Balance between cost and experience - Ambiguous situations - Can you assign a number to it? - Improving the Uber experience through research An insight into design research in mobility
  41. 41. Zaid Haque Carnegie Mellon Qatar 20 March 2017 zaidhaque@gmail.com | www.zaidhaque.com
  42. 42. Autonomy is the future.
  43. 43. A Lack of Trust and Understanding Prevents us from moving faster. Blanco, Myra, et al. Human NFactors Evaluation of Level 2 and Level 3 Automated Driving Concepts. No. DOT HS 812 182. 2015.
  44. 44. Zaid Haque Hannah Xue Noshin Nisa Strategy Technology Product
  45. 45. symbiote
  46. 46. Symbiote is developing intuitive interfaces for the next generation of mobility technology. symbiote
  47. 47. Building an interface symbiote
  48. 48. Keyboards
  49. 49. Mice
  50. 50. Touchscreens
  51. 51. It’s time to move on. symbiote
  52. 52. Building an interface symbiote
  53. 53. Phase I Phase II Safety Comfort Satisfaction symbiote
  54. 54. Hierarchy of needs In a transportation context Safety Comfort Satisfaction symbiote
  55. 55. Perceive symbiote
  56. 56. Acknowledge Arduino demo video on http://symbiote.link/product Jung, Malte F., et al. "Displayed uncertainty improves driving experience and behavior: The case of range anxiety in an electric car." Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2015. symbiote
  57. 57. symbiote
  58. 58. Maintaining alertness Tasks to regain focus during autonomy Jung, Malte F., et al. "Displayed uncertainty improves driving experience and behavior: The case of range anxiety in an electric car." Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2015. Act I: symbiote
  59. 59. Changing Driving Dynamics ZCT symbiote Act II: symbiote +
  60. 60. Numerous Possibilities A better understanding of the rider leads to new opportunities for interaction Music Control Route Selection Driving Dynamics Ridesharing Experiences Health Monitoring Act: symbiote
  61. 61. Market Size Starting with semi-autonomous cars, with an intent to expand to other transportation industries. ~$250B in yearly revenue $126B Air Transport $40B Road Transport $30B Other Transport $50B Autonomous Vehicles (2020) Data Source: Statista http://statista.com symbiote
  62. 62. TAM Taking different percentages based on the value of autonomy and trust in different contexts. ~$1.8B Total Addressable Market $126M Air Transport $400M Road Transport $30M Other Transport $1.25B Autonomous Vehicles (2020) Data Source: Statista http://statista.com symbiote
  63. 63. Competitive Landscape Although there are many indirect competitors, there is only one direct competitor. symbiote
  64. 64. Strategy An iterative approach to gaining customers Sell to Owners of Luxury Vehicles (validation) Partnerships with Car Manufacturers Standardizing Safety Technologies (e.g. ABS, SRS) Partnerships with Passenger Transportation Phase I Phase II 1 2 4 3 symbiote
  65. 65. Zaid Haque Hannah Xue Noshin Nisa Strategy Technology Product symbiote
  66. 66. symbiote

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