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Decision Making in Product Design
The document outlines a lecture by Zaid Haque from Carnegie Mellon Qatar, focusing on decision-making in product design, particularly in mobility technologies like Uber. It discusses the balance between cost and user experience, the importance of quantitative data for validating design choices, and strategies for improving rider experiences. Additionally, it highlights the market potential for semi-autonomous vehicles and the competitive landscape for the company Symbiote, which aims to develop intuitive interfaces for future mobility solutions.
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Decision Making in Product Design
- 1. Zaid Haque Carnegie MellonQatar 20 March 2017
- 2. About Me Red DotAward: Bilingual Flight Info Display SystemMy Website
- 3. What about you? Whatmakes you interested in HCI and Design? Why did you choose this class? What do you want to do after graduation?
- 4. Lecture Outline -Decision makingin product design -Measuring ambiguous situations -Uber Technologies - Symbiote Systems (time permitting) An insight into design research in mobility
- 5. A little background… This lectureis 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 isliterally making decisions. But based on what? Designers often need to ‘use their gut’ to conceptualize their products.
- 9. Making large- scale decisions Alot 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 differentviews on what is important. Product Parameters
- 12. Cost Form Function Software Engineers Everyone has differentviews on what is important. Product Parameters
- 13. Cost Form Function “Designers” - closerto Artists Everyone has different views on what is important. Product Parameters
- 14. Cost FormFunction Try to balancethese out! Product Parameters
- 15. Money matters. Each decision youmake 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 wefollow the money? No. But yeah. Kind of.
- 17. Find a balance Whatcan create the biggest impact on our users with the least effort?
- 18.
- 19. But how doyou measure the impact? Only way to convince management to accept your terms is to show them numbers.
- 20. Qualitative vs. QuantitativeData 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 termfor the success of your product.
- 22. HOW CAN WE REDUCE AMBIGUITY WHEN ESTABLISHING RIDERPICKUP LOCATIONS? CHALLENGE
- 23.
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- 25. AMBIGUITY OCCURS ON TWO PARTS OFTHE USER FLOW UNPACKING
- 26.
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- 28. KEY PERFORMANCE INDICATORS 5 Star driver/riderratings Number of phone callsDistance between request and pickup locations Difference between est. and actual pickup times
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- 31. CONFIRMATION Locating the rider RIDERCONFIRMS 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 RIDERCONFIRMS 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 thedriver RIDER AND DRIVER FLASH COLOR CODED SCREENS TO QUICKLY IDENTIFY EACH OTHER. BETA TESTING IN SEATTLE
- 34.
- 36. LTE DIRECT Locating arider using other phones Rider Phone 1 Phone 2 Phone 3 https://www.qualcomm.com/invention/research/projects/lte-direct
- 37.
- 38. VALIDATION Worldwide usage ofour app Doha London San Francisco
- 39. VALIDATION 26m % of ridersby 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 ridersby 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 yourdecisions up with hard data!
- 48. Lecture Outline -Decision making inproduct 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 MellonQatar 20 March 2017 zaidhaque@gmail.com | www.zaidhaque.com
- 51.
- 52. A Lack ofTrust 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 HannahXue Noshin Nisa Strategy Technology Product
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- 56. Symbiote is developing intuitiveinterfaces for the next generation of mobility technology. symbiote
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- 61. It’s time tomove on. symbiote
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- 64. Hierarchy of needs In atransportation context Safety Comfort Satisfaction symbiote
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- 66. Acknowledge Arduino demo videoon 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.
- 68. Maintaining alertness Tasks to regainfocus 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
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- 70. Numerous Possibilities A better understandingof the rider leads to new opportunities for interaction Music Control Route Selection Driving Dynamics Ridesharing Experiences Health Monitoring Act: symbiote
- 71. Market Size Starting withsemi-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 percentagesbased 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 aremany indirect competitors, there is only one direct competitor. symbiote
- 74. Strategy An iterative approachto 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 HannahXue Noshin Nisa Strategy Technology Product symbiote
- 76.