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
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Decision Making in Product Design
- 1. Zaid Haque Carnegie Mellon Qatar 20 March 2017
- 2. About Me Red Dot Award: Bilingual Flight Info Display SystemMy Website
- 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. Lecture Outline -Decision making in product design -Measuring ambiguous situations -Uber Technologies - Symbiote Systems (time permitting) An insight into design research in mobility
- 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
- 8. My job is literally making decisions. But based on what? Designers often need to ‘use their gut’ to conceptualize their products.
- 9. 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?
- 10. Cost FormFunction Product Parameters Money, Manpower, effort, etc. Aesthetics, Beauty Performance, Features
- 11. Cost FormFunction Corporate Managers Everyone has different views on what is important. Product Parameters
- 12. Cost Form Function Software Engineers Everyone has different views on what is important. Product Parameters
- 13. Cost Form Function “Designers” - closer to Artists Everyone has different views on what is important. Product Parameters
- 14. Cost FormFunction Try to balance these out! Product Parameters
- 15. 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.
- 16. So do we follow the money? No. But yeah. Kind of.
- 17. Find a balance What can create the biggest impact on our users with the least effort?
- 19. But how do you measure the impact? Only way to convince management to accept your terms is to show them numbers.
- 20. 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. ??? ???
- 21. Key Performance Indicators Business-savvy term for the success of your product.
- 22. HOW CAN WE REDUCE AMBIGUITY WHEN ESTABLISHING RIDER PICKUP LOCATIONS? CHALLENGE
- 23. UNPACKING
- 25. AMBIGUITY OCCURS ON TWO PARTS OF THE USER FLOW UNPACKING
- 28. KEY PERFORMANCE INDICATORS 5 Star driver/rider ratings Number of phone callsDistance between request and pickup locations Difference between est. and actual pickup times
- 31. 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#
- 32. 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#
- 33. COLOR CODES Identifying the driver RIDER AND DRIVER FLASH COLOR CODED SCREENS TO QUICKLY IDENTIFY EACH OTHER. BETA TESTING IN SEATTLE
- 34. COLOR CODES Identifying the driver
- 36. LTE DIRECT Locating a rider using other phones Rider Phone 1 Phone 2 Phone 3 https://www.qualcomm.com/invention/research/projects/lte-direct
- 37. ARCHITECTURE
- 38. VALIDATION Worldwide usage of our app Doha London San Francisco
- 39. 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
- 40. 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
- 41. Qualitative Analysis? It’s still useful, but can you make it quantitative?
- 47. Always remember Back your decisions up with hard data!
- 48. 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
- 49. Zaid Haque Carnegie Mellon Qatar 20 March 2017 zaidhaque@gmail.com | www.zaidhaque.com
- 52. 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.
- 54. Zaid Haque Hannah Xue Noshin Nisa Strategy Technology Product
- 55. symbiote
- 56. Symbiote is developing intuitive interfaces for the next generation of mobility technology. symbiote
- 58. Keyboards
- 59. Mice
- 60. Touchscreens
- 61. It’s time to move on. symbiote
- 64. Hierarchy of needs In a transportation context Safety Comfort Satisfaction symbiote
- 66. 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
- 67. symbiote
- 68. 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
- 70. 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
- 71. 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
- 72. 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
- 73. Competitive Landscape Although there are many indirect competitors, there is only one direct competitor. symbiote
- 74. 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
- 75. Zaid Haque Hannah Xue Noshin Nisa Strategy Technology Product symbiote
- 76. symbiote