see the future
DESCRIPTION
Tools and Techniques to Spot Opportunities & Threats in Emerging TechnologyTRANSCRIPT
SEE THE FUTURE
TOOLS AND TECHNIQUES TO SPOT OPPORTUNITIES
& THREATS IN EMERGING TECHNOLOGY
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
WORKSHOP AGENDA
Interactive
Can we really see the future?
• What?!• Why?
How?
• Tools• Techniques
Next Steps
• Tracking Framework• Key Players in Field
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
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
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
WHY? BENEFITS…
Environmental (weather)
Political (election outcomes)
Societal (trends, unrest)
Financial (market predictions)
Personal (career, investments, health)
Technological (impact, success, opportunity)
CASE STUDY - GOOGLE GLASS
Google Glass
• Think about some of the questions about this emerging technology
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
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
SENTIMENT ANALYSIS
Sentiment140 (sentiment140.com)
PREDICTION MARKETS
http://home.inklingmarkets.com/markets/53978
SIGNAL TRACKING #1 - GOOGLE TRENDS
Google Trends (google.com/trends)
SIGNAL TRACKING #2 – RECORDED FUTURE
Recorded Future (recordedfuture.com)
SIGNAL TRACKING #3 – NEWS ANALYSIS
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”
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
TRACKING FRAMEWORK
Define the Why / Goals /
Measures
Establish Data Sources / Tools & Techniques
MonitorAssess & Refine
Act :)
Price / affordabilityNumber of appsSentiment
Unstructured versus StructuredSentiment
Thresholds
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)
