Building innovative products
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The document outlines key principles for building innovative products, emphasizing genuine problems, user engagement, and rapid experimentation. It argues that innovation requires small, empowered teams who care about the issue at hand and suggests leveraging open source and analytics for effective idea generation and validation. The focus should be on continuous learning and adaptability rather than strict execution metrics.
Building innovative products
- 1. Building an Innovative Product Shishir Chandra Choudhary
- 2. What’s Innovation ? 1. Problem you care about 2. Idea Generation 3. Idea Validation 4. High Speed and Low Cost of Iteration and enough runway 5. Empowered People who love what they do and care about the problem 1.1 Closeness with User
- 3. What’s the outcome ? 6. Learning What Other’s Don’t Know (Problem and Solution) 7. Successful Idea to Scale
- 4. Detour - What Innovation is NOT Keep the innovation map we saw in mind. We will come back to it shortly.
- 5. It’s Not Eureka ! Best of First Ideas Do not Survive Impact of Reality
- 6. Neither is it careful planning You don’t know what result of your experiment would be. You don’t know the learning you would have after next experiment.
- 7. It’s not the particular technology Start with the problem you care about first. Figure out the right tech to apply. Never the other way around ! You can’t “experiment” with outcome in mind already. Also, If you don’t care about the problem, you would not survive the initial failures.
- 8. Not Enough Runway Before innovation flies, it crawls, walks and runs. Too short a runway and no idea will fly.
- 9. Not a work for large team You need small, self sufficient, fast moving team. Large team is only needed to scale the final solution.
- 10. Why Bother ? Innovation is tough, why bother ? Execution is fast. In shorter run the better executing team wins. Exploration is slow and wasteful. In long run those who explore overtake So you need both
- 12. 1. Problem You care about • Innovation is a winding path • People put more effort for things they care about • How to enable this ? We’ll see
- 13. 2. Idea Generation For idea generation you want to do following • Improve quality of ideas • Improve quantity of ideas
- 14. Idea Quality & Quantity •Be cloooose to users • Ideally - be your own target demographic • E.g. if an investment product, be user of that investment product to invest • Entire team should feel as close to users as possible • Otherwise, you solve the wrong problem or fail to learn
- 15. Idea Quality and Quantity •Explore • Experiment a lot (cheaply). Each experiment improves your next idea quality. • Have a long term process, with progress measured by learning done, not success of every step (don’t measure innovation in similar way as execution/ delivery projects)
- 16. Idea Quality and Quantity • Be aware of and leverage Open Source • Don’t reinvent the wheel, leverage open source to solve common problems well, contribute back to it as well • Be aware of what is possible with bleeding edge open source
- 17. 3. Idea Validation • Never drive blind Build analytics into your product so you know how well is your product doing? how is it being used? Did your last improvement improve retention or referral ? Did the last idea deployed become popular ? • Talk to users who used your new idea • Take your product/new ideas for test drive yourself on a new road. Often you will notice any pain more directly.
- 18. 4. Rapid Cheap Experimentation • If each experiment takes months or hundred thousand dollars to conduct , you would not experiment much • Invest in building infrastructure to enable rapid experimentation using devops and any tool to that effect
- 19. 5. Empowered People Who love their work and care about the problem • People are very important component of innovation • Hire people who just love what they do. People who do work just to pay bills never build ground breaking products • Empower them, trust them. Use agile approaches where you don’t stand behind the shoulders or try to control people. • Agile daily stands should be just 5-10 min of what each person is doing today and not a question and answer or control system. Note this requires people who love what they do. • Teams should be small (5-10) and self sufficient
- 20. Distributed Side Projects • Using Devops and Other Automation Tool Make it easy for any team to experiment in company as a cheap side project • Keep cost of side projects low • Allow anyone to start one with minor approval (not require higher management involvement) • Snowballs into lot of innovation • Every experiment succeeds (if learning is the target) • Some more financially successful • Other improve quality of ideas in future
- 22. Adopting Latest Innovation Research In House Using Open Source Models, Libraries & Platform Early on concentrate on learning from each small project, not success or inevitable failures As you figure things out, scale and execute You must do a bit of this to develop appreciation of nuances & solve problems not yet solved Identify core pain of users/ customers and focus on each of those with research too (longer runway) Small self sufficient and multi disciplinary (DS, DE, API, UI, Devops etc) teams Small self sufficient and multi disciplinary (DS, DE, API, UI, Devops etc) teams
- 23. 2. Idea Generation 3. Idea Validation 4. High Speed and Low Cost of Iteration and enough runway Get This Right Tools to speed up experimentations
- 24. Start with simple solutions Start with simple rules Once you have lot of data, introduce ML Replace any complex rules with ML
- 25. Open Data Wikipedia, Wikidata, Twitter etc Apps and API Your own UI, API etc would provide data DS Strengthens With Data Data Augmentation Use Sensible Augmentation of Available Data