See the Future
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Tools and Techniques to Spot Opportunities & Threats in Emerging Technology
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See the Future
- 1. SEE THE FUTURE TOOLS AND TECHNIQUES TO SPOT OPPORTUNITIES & THREATS IN EMERGING TECHNOLOGY
- 2. MY BACKGROUND 12 years in technology Application Developer • MTV Networks, JP Morgan, Microsoft Instructor at the General Assembly Based out of New York City Interest in… • Data Science • Disruptive Technologies
- 3. WORKSHOP AGENDA Interactive Can we really see the future? • What?! • Why? How? • Tools • Techniques Next Steps • Tracking Framework • Key Players in Field
- 4. CAN WE REALLY “SEE THE FUTURE”? Obviously no such thing as a crystal ball Although we’re getting close(r) Driven by a two key trends • Data growth • Increasing array of tools & techniques Derive signal (insights) from the noise (data) • Insights = Predictions & Forecasts • Data = Growing Exponentially
- 5. DATA, DATA, DATA… 2.5 quintillion bytes of data per day, IBM • Equal to 2220.45 petabytes 90% of data created was in the last 2 years Sources • Social, News, Images, Sensors, Financial, Geographic, Sports, Meteorological, etc That’s a lot of noise! • Somewhere in there is (future) signal though
- 6. WHY BOTHER? Because we increasingly can / value if you can find the signal • "Google Search Terms Can Predict Stock Market” • Warwick Business School, Boston University Habit • Professionally and Personally More specifically, uncover the following… • Strengths • Weaknesses • Opportunities • Threats
- 7. WHY? BENEFITS… Environmental (weather) Political (election outcomes) Societal (trends, unrest) Financial (market predictions) Personal (career, investments, health) Technological (impact, success, opportunity)
- 8. CASE STUDY - GOOGLE GLASS Google Glass • Think about some of the questions about this emerging technology
- 9. CASE STUDY - GOOGLE GLASS Types of questions we might ask… • Will Google Glass be a success? • How will it impact my business? • Should we develop app(s) for it? • When will it launch? • What else will it disrupt? Unstructured data (sentiment driven) • No app store, sales, price • LOTS of hype
- 10. HOW? TOOLS & TECHNIQUES Sentiment Analysis • Opinion mining Prediction Markets • Leverage the “wisdom of the crowd” Signal Tracking • Discover insights Machine Learning • Learn and analyze data
- 13. SIGNAL TRACKING #1 - GOOGLE TRENDS Google Trends (google.com/trends)
- 14. SIGNAL TRACKING #2 – RECORDED FUTURE Recorded Future (recordedfuture.com)
- 15. SIGNAL TRACKING #3 – NEWS ANALYSIS
- 16. CASE STUDY – SUMMARY Insights • Google Glass tends to polarize opinion • Although sentiment is generally positive • Prospective buyers are price sensitive • Anticipated launch in Q4 2013 • Interest from Asian markets • Developer interest (apps being created) Implications • Quite niche product (initially) • Needs right price / refined form factors • Worth exploring space, as well as other “wearables”
- 17. ADDITIONAL TECHNIQUES “Datafication” • Taking aspects of life and turning them into data • Seating positioning in a car (AIIT, Tokyo) • IBM patent for “touch sensitive floor covering” Explore Models • Hype Cycles • S-Curves Watchlists • SV Angel's "Megatrends” • Kickstarter (great bell-weather…Pebble Watch) • Betali.st
- 18. TRACKING FRAMEWORK Define the Why / Goals / Measures Establish Data Sources / Tools & Techniques Monitor Assess & Refine Act :) Price / affordability Number of apps Sentiment Unstructured versus Structured Sentiment Thresholds
- 19. WHO? Chris Anderson(s) (@chr1sa and @TEDchris) Ray Kurzweil (@raykurzweil2035) Peter Diamandis (@PeterDiamandis) Clayton Christensen (@claychristensen) Esther Dyson (@edyson) Nate Silver (@fivethirtyeight) Elon Musk (@elonmusk) Guy Kawasaki (@GuyKawasaki)
- 20. THANK YOU :) Get in touch… • kevin@bluer.com • @kevinbluer
Notas do Editor
- Quick show of hands…DeveloperDesignerSocial Media / Marketing / Other
- What do we mean by “seeing the future”?Why would we want to do this?How? Tools and techniques to help you spot opportunities + threat / get laptops readyRemind people that I’ll send out the slides
- Refer this back to the first trend…Eric Schmidt quote – In two days we create all the data that we created from the beginning of time up until 2003.Nomi – Sensors into stores to track foot traffic / optimizations
- NateSilver (statistician, blogger, writer)…election outcome prediction23andMe…DNA sequencing, predict likelihood of illness / disease
- Has anyone not heard of Google Glass? :)
- Note that we’ll go through each one…Stress this isn’t a definitive listMachine Learning -> Analyze a training data set - > Make prediction
- Opinion MiningHighlight the Google Glass “case study”
- Under the umbrella of wisdom of the crowd
- Notes#1Ability to forecast#2 Regional interest – particularly from Asia#3 Related items – top one is price (so obviously this is something that people are sensitive to and will likely impact success)Note that trends can go the other way too…e.g. Microsoft :)
- Under “implications”, also overlaid more personal thoughts…Potential for broader success over time (with the right price / seamless integration)