This document discusses building products for maximum impact. It begins by explaining the importance of understanding customer problems, experimenting to test hypotheses, and aligning work with customer needs. It then provides an example of a product that was considered successful internally but that customers disagreed with. The company focused too much on features without understanding the underlying customer problem. The document stresses the value of experimentation and notes that failed experiments provide learning opportunities if the goal is to take enough risks. It concludes by discussing the need to align organizational structures with customer needs.

1. Building Products for Maximum Impact
A story about a product
we called a success, but customers disagreed
SPEAKER: Vasily Starostenko
vstarostenko@gmail.com

2. Great Being With You Today,
IT Arena!

3. SPEAKER: VASILY STAROSTENKO
I help Founders and Companies:
● 💡Understand their customers’ problems
● 💊 Experiment and place big bets
● 🚀Align their work with customer needs
Education: Physics, Math, Economics, Business
EmployeeStocks.com

4. How You Build for Maximum Impact
I help Founders and Companies, building great products,
grow faster by delivering better experience to their customers.
1. 💡 Understand: Avoid Feature Fetish by Starting with a Problem Statement
2. 💊 Experiment: “Always Have a Hypothesis,” But Don’t be Blinded by Science
3. 🚀 Align: Put Your Money Where Your Mouth Is

5. Just like self driving technology is
competing with human drivers, cars
used to compete with horses

6. Agenda
● How cars competed with horses and won
● How self driving cars compete with human driven cars
● What we value in transportation and what it takes to win
● Safety and miles driven by self driving cars and all cars

7. One exciting thing has happened 100 years ago

8. Cars stormed into our lives and replaced horses

9. Today we are living through another exciting moment

10. Self driving cars are coming, but when?

11. Self Driving Technology
Impact
Miles Driven, share of total
Safety, per mile driven

12. Miles Driven

13. Tesla: over a billion autonomously driven miles
Independent estimate by https://hcai.mit.edu/tesla-autopilot-miles/

14. A little, compared to 3 trillion miles in US per year

15. A lot, compared to 8 million Waymo autonomous miles

16. Safety
1.3 million people die in road crashes each year
Up to 50 million are injured or disabled

17. Autopilot predicts and prevents crashes
https://youtu.be/RjGe0GiiFzw
https://youtu.be/--xITOqlBCM

18. Autopilot: How Safe Is It Today?
A. As safe as human
B. 3x as safe as a human
C. 10x as safe as a human
D. 100x as safe as a human

19. Tesla Autopilot: ~3x as Safe as a Human
US National Safety Council reports 1.25 deaths
per 100 million vehicle miles in 2016.
Transportation safety in the United States - Wikipedia
For Tesla, there is one fatality, including known
pedestrian fatalities, every 320 million miles in
vehicles equipped with Autopilot hardware.

20. Autopilot: When Is It Ready for Prime Time?
A. As safe as human
B. 3x as safe as a human
C. 10x as safe as a human
D. 100x as safe as a human

21. Can It Be Perfect?
Tesla Autopilot will never be perfect but
could be 10x safer than humans, says
Elon Musk
It’s important to emphasize we’ll never be
perfect. Nothing in the real world is perfect.
But I do think that long term, it can reduce
accidents by a factor of 10. So there are 10
fewer fatalities and tragedies and serious
injuries. And that’s a really huge difference.

22. When are we going to start perceiving
self driving technology as safe?

23. Autopilot is Safe, but Needs to Be Perceived Safe

24. A story about a product
we called a success,
but customers disagreed
Understand Customer Problem:
Avoid Feature Fetish by Starting with a Problem Statement

25. Uber Rider: Get from A to B on time & cheap

26. Uber Driver: Go Offline or Not?

27. We Asked: Are You Sure?

28. Then We Asked “Are You Really Sure?”

29. “Don’t Go Offline”: Success, but ultimately a Failure
● Drivers participating in experiment stayed online much longer than drivers who
did not
● Product was advanced to include ‘hooks’ and psychological tricks, which even
further improved success metrics
● Only much later we realized many drivers were annoyed, a sentiment never
displayed in our datasets
● Customer support records were the best way to see a footprint of this
annoyance coupled with live conversations
● As a result, the “Do Not Go Offline” experience was rolled back, we made it
easy for drivers again to go offline

30. Thank You!
Please share your feedback

31. Experiment
Experiment: “Always Have a Hypothesis,” But Don’t be Blinded by Science

32. To Build a Rocket Ship, You Gotta Move Fast

33. Moving Fast: Rocket Ship or Steam Room
Takeoff Energy Heat Energy

34. Rocket Ship: Power of Compounding
One thing rocket ships have in common,
they get lots of things right
One way to get things right is through
experimenting and shipping a winner
Impact of multiple experiments
compounds:
When we ship two experiments, each
delivering 10% lift
10% + 10% = 21% > 20%
1.1 x 1.1 = 1.21 -> 21%
Run 100 experiments 5% lift each
5% x 100 = 13,000%
1.05^100 = 131.50 -> + 13,000%

35. Value of Failed Experiments
Is Failed Experiment Valuable?
Yes, because we are still learning what
does not work
Yes, because it provides evidence we
are taking risks
If we only ship successful experiments,
we are not taking enough risk
If we are not taking enough risk, we are
not getting enough return

36. Tough Call - Is Success a Success, Really?

37. Thank You!
Please share your feedback

38. Align Org Chart to Customer Needs
Align: Put Your Money Where Your Mouth Is

39. Org Chart: Should You Have a Growth Team?
CEO
Growth Core Product
Supply Growth Demand Growth Driver Experience Rider Experience

40. Org Chart Aligned with Customer Needs
CEO
Driver Team Rider Team
Driver Need 1 Driver Need 2 Rider Need 1 Rider Need 2