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Better Startups Through Science -  MIT Accelerator 2014
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Better Startups Through Science - MIT Accelerator 2014

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Exploring how small experiments can build better businesses faster. ...

Exploring how small experiments can build better businesses faster.
- Science, and how it applies
- "Bad" & "Good" science
- Experiments and 'Little Bets'
- Applications in startups
- Where to go next
Presented at MIT Founders' Skills Accelerator program at The Martin Trust Center for MIT Entrepreneurship in July 2014.

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  • How many are not from MIT <br /> <br /> How many are undergrad <br /> How many in Engineering? <br /> How many in Business? <br /> How any have been involved in a startup?
  • The key elements in the following slides should factor into the conversation about each of the real questions
  • <br /> <br /> * Experiment <br /> <br /> * Learn by doing. Fail quickly to learn fast. Develop experiments and prototypes to gather insights, identify problems, and build up to creative ideas, like Beethoven did in order to discover new musical styles and forms. <br /> <br /> * Play <br /> <br /> * A playful, improvisational, and humorous atmosphere quiets our inhibitions when ideas are incubating or newly hatched, and prevents creative ideas from being snuffed out or prematurely judged. <br /> <br /> * Immerse <br /> <br /> * Take time to get out into the world to gather fresh ideas and insights, in order to understand deeper human motivations and desires, and absorb how things work from the ground up. <br /> <br /> * Define <br /> <br /> * Use insights gathered throughout the process to define specific problems and needs before solving them, just as the Google founders did when they realized that their library search algorithm could address a much larger problem. <br /> <br /> * Reorient <br /> <br /> * Be flexible in pursuit of larger goals and aspirations, making good use of small wins to make necessary pivots and chart the course to completion. <br /> <br /> * Iterate <br /> <br /> * Repeat, refine, and test frequently armed with better insights, information, and assumptions as time goes on, as Chris Rock does to perfect his act. <br />

Better Startups Through Science -  MIT Accelerator 2014 Better Startups Through Science - MIT Accelerator 2014 Presentation Transcript

  • BETTER STARTUPS THROUGH SCIENCE GFSA 2014 M a r t i n Tr u s t C e n t e r f o r M I T E n t r e p r e n e u r s h i p
  • WHO
  • sci·ence • /ˈsīəns/ • noun the intellectual and practical activity encompassing the systematic study of the structure and behavior of the physical and natural world through observation and experiment.
  • WHAT ARE WE DOING HERE? explore how small experiments build better businesses faster
  • AGENDA o Why Science? o Bad science, good science o Experiments and ‘Little Bets’ o Applications in startups o Where to go next
  • STARTUPS DO TWO THINGS BUILD STUFF SELL STUFF
  • SCIENTIFIC METHOD 1. Question 2. Hypothesis 3. Prediction 4. Testing 5. Analysis 6. Conclusion
  • QUESTION
  • HYPOTHESIS
  • PREDICTION
  • TESTING
  • ANALYSIS
  • CONCLUSION
  • AGENDA o Why Science? o Bad science, good science o Experiments and ‘Little Bets’ o Applications in startups o Where to go next
  • BAD SCIENCE & GOOD SCIENCE
  • • Humans are hardwired to learn specifics when they should be focused on generalities • We concentrate on things we already know and fail to take into consideration what we don’t know • How we fool ourselves into thinking we know more than we actually do http://amzn.com/081297381X
  • TRAPS Confirmation bias The tendency of people to favor information that confirms their beliefs or hypotheses. People display this bias when they gather or remember information selectively, or when they interpret it in a biased way Narrative fallacy We’re unable to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship upon them.
  • WHAT IF THIS GOOD IDEA IS ACTUALLY A BAD IDEA?
  • in·val·i·date • /inˈvaliˌdāt/ • verb make (an argument, statement, or theory) unsound or erroneous.
  • TESTABLE HYPOTHESES • What is testable? • Invalidation • DATA / KPI / Failure
  • AGENDA o Why Science? o Bad science, good science o Experiments and ‘Little Bets’ o Applications in startups o Where to go next
  • EXPERIMENTS AND LITTLE BETS
  • • Rather than start with a big idea or plan a whole project in advance, make a methodical series of little bets • Leverage principles from psychology & design thinking • Lots of little failures and small but significant wins • How to navigate uncertain situations http://amzn.com/1439170436
  • FUNDAMENTALS • Experiment • Play • Immerse • Define • Reorient • Iterate
  • BIG BETS VS. LITTLE BETS
  • LEARNING VS. VERIFYING
  • FAILURE AND SPEED
  • PROBLEMS AND CONSTRAINTS
  • INQUISITIVENESS
  • DISPLACED INSIGHTS
  • FIRST ADOPTERS LEAD THE WAY
  • AGENDA o Why Science? o Bad science, good science o Experiments and ‘Little Bets’ o Applications in startups o Where to go next
  • YOUR RISKIEST ASSUMPTION
  • PRODUCT
  • CUSTOMER ACQUISITION
  • NETWORK EFFECT
  • MARKET POSITIONING
  • PRICING
  • GROWTH
  • GOOD EXPERIMENTS ARE… • Fast • Inexpensive • Conclusive
  • AGENDA o Why Science? o Bad science, good science o Experiments and ‘Little Bets’ o Applications in startups o Where to go next
  • WHAT’S NEXT FOR YOU?
  • READ
  • EXPLORE
  • STAY CONNECTED twitter: @rcolinkennedy meet: ohours.org/rcolinkennedy more: rcolinkennedy.com
  • THANKS