The future of golf club management · 2016-05-17 · The future of golf club management David Wood @dw2 Chair, London Futurists Principal, Delta Wisdom londonfuturists.com deltawisdom.com
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The future of golf club
management
David Wood @dw2
Principal, Delta Wisdom Chair, London Futurists londonfuturists.com deltawisdom.com
Breakout
@dw2 Page 2
Long-lived organisations work on three timescales in parallel
1-12 Months
Fulfilling Commitments
1-3 Years
Search for Growth
Incremental new business Operational excellence Creating a new future
3-10+ Years
Anticipating Disruption
Today’s skills Tomorrow’s skills
@dw2 Page 3
Disruption via convergence
Are impacted & enhanced
Are impacted & superseded
?
See the steamrollers coming Be agile and strong enough to turn the steamrollers to your advantage
@dw2 Page 4
Group discussion 1
Highlight other examples of companies that have failed to spot (or handle) incoming “steamrollers”
Also consider examples of companies that turned incoming steamrollers to their advantage
@dw2 Page 5
Kindle books vs. physical books
www.theverge.com/2012/9/6/3298533/amazon-kindle-event-september-6th-video-watch
E-books leapfrog physical books at Amazon
in less than 3 years
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
@dw2 Page 6
Progress by selective combination
Smart combination of multiple tech improvements • Cheap digital storage • Low energy screens, pleasant to look at • High-speed “Whisper net” wireless distribution • Customisable (Linux/Android) software platform • Huge catalog of books available to purchase
+ Innovative business model
Improvements in computers: Performance
Applicability (digitisation)
+ Focus on addressing a small number of user requirements
@dw2 Page 7
What you’ll prioritise, and what you’ll not prioritise
Strengths
Weaknesses
Opportunities
Threats
Sources of upside
Sources of downside
Internal (company)
External (environment)
Forthcoming Opportunities
Forthcoming Threats
Future (scenarios)
Strategy = choice
Strategy = preparation SWOT
@dw2 Page 8
Group discussion 2
What are the “opportunities” and “threats” that would feature in a SWOT for your company?
Consider both “environment” and “future” as the sources of the opportunities and threats
@dw2 Page 9
Physical + Virtual
Mobile -> Wearable -> -> Insideable ->…
Cyborgs
3 AI + Human Intelligence
Human + Machine Software + Biology
Synthetic biology
Genetic engineering
4
2 1
4 great convergences
VR -> AR (Augmented Reality)
MOOCs, cryptocurrency…
@dw2 Page 10 http://intelligenceexplosion.com/en/2011/superstition-in-retreat/
“Only humans can play master chess”
“Only a human musician can compose in the style of Bach”
@dw2 Page 11
Convergence: AI & human intelligence
http://www.csmonitor.com/Innovation/Tech/2010/0617/How-a-computer-program-became-classical-music-s-hot-new-composer
http://www.allmusic.com/album/bach-by-design-computer-composed-music-mw0001354257/credits
@dw2 Page 12 http://intelligenceexplosion.com/en/2011/superstition-in-retreat/
“Only humans can drive cars”
@dw2 Page 13 http://www.amazon.com/The-New-Division-Labor-Computers/dp/0691119724
“The new division of labor”
Computerisation should have little effect on the percentage of the work force engaged in these tasks…
Non-routine manual tasks: physical tasks that cannot be well-described as following a set of If-Then-Else rules, because they require optical recognition and
fine motion control that have proven extremely difficult for computers to carry out…
Examples include driving a truck…
Frank Levy and Richard J. Murnane, 2004
@dw2 Page 14 http://en.wikipedia.org/wiki/DARPA_Grand_Challenge
Completed <5% of the course
Sandstorm: Winner of 2004 DARPA Grand Challenge
150 miles in the Mojave
Desert region of the US
2005 Challenge:
Five vehicles completed whole
course
@dw2 Page 15 http://telematicswire.net/self-drving-cars-after-google-its-baidu-carmakers-and-technology-
companies-competing-together/
Taxi drivers
Truck drivers
Insurance salespeople
@dw2 Page 16 https://www.youtube.com/watch?v=M7nLQpWiy1o
@dw2 Page 17
“A group of young people playing Frisbee”
https://medium.com/backchannel/google-search-will-be-your-next-brain-5207c26e4523
@dw2 Page 18
“A person riding a motorcycle on a dirt road”
https://medium.com/backchannel/google-search-will-be-your-next-brain-5207c26e4523
@dw2 Page 19 https://medium.com/backchannel/google-search-will-be-your-next-brain-5207c26e4523
“A herd of elephants walking across a dry grass field”
@dw2 Page 20 http://googleresearch.blogspot.co.uk/2014/11/a-picture-is-worth-thousand-coherent.html
“A dog is jumping to catch a Frisbee”
@dw2 Page 21
Image-Net database: 14M+ images
http://image-net.org/
• 1000 classes of object • Large Scale Visual Recognition Challenge • Held every year since 2010…
@dw2 Page 22
Large Scale Visual Recognition Challenge
http://bits.blogs.nytimes.com/2014/08/18/computer-eyesight-gets-a-lot-more-accurate/
• Classifications by the winning software in 2014 had only 6.6% errors
• Compares to 11.7% errors in 2013 • Four-fold improvement since 2010 • Compares to 5.1% errors by humans • Feb 2015: Team from Microsoft Beijing • Led by Jian Sun • 4.94% error rate
http://blogs.technet.com/b/inside_microsoft_research/archive/2015/02/10/microsoft-researchers-algorithm-sets-imagenet-
challenge-milestone.aspx
Computer vision is the key to robots being able to do lots more “human” tasks
@dw2 Page 23
The three ages of machines 1. Machines replaced human muscular effort
– They produced motion
– They manipulated energy
2. Then machines replaced human calculation effort – They produced numerical results
– They manipulated information (using algorithms)
3. Machines are now replacing human creative effort – They produce algorithms (using information)
– They manipulate “learning data” to reveal cause-effect patterns
– Goals are given, but the machines work out the best methods
@dw2 Page 24
“Google is ‘re-thinking’ all of its products to include machine learning”
“Machine learning and artificial intelligence got a lot of love on Google’s 2015 Q3 earnings call”
“During CEO Sundar Pichai’s prepared remarks, he went out of his way to point out that investments in machine learning and AI were a continued priority for the company moving forward” Sundar Pichai, Google CEO
http://www.businessinsider.com/google-on-machine-learning-2015-10
@dw2 Page 25
https://www.youtube.com/watch?v=V1eYniJ0Rnk
@dw2 Page 26 http://intelligenceexplosion.com/en/2011/superstition-in-retreat/
“Only humans can understand natural language”
@dw2 Page 27
Convergence: AI & human intelligence
http://www.ibm.com/smarterplanet/us/en/ibmwatson/what-is-watson.html
http://singularityhub.com/2011/03/09/paging-dr-watson-ai-jeopardy-champion-could-become-physicians-assistant/
“I for one welcome our new computer overlords”
@dw2 Page 28
Technological unemployment
http://venturebeat.com/2013/12/05/khosla-explains-his-robots-replacing-doctors-comment-and-goes-on-the-hunt-for-data-scientists/
“By 2025, 80% of the functions doctors do will be done much
better and much more cheaply by machines & algorithms”
– Vinod Khosla
“80% of doctors will be replaced by technology”
@dw2 Page 29 http://dilbert.com/strips/comic/2011-12-16/
Technological unemployment
Admin staff
@dw2 Page 30
Group discussion 3
Which employee tasks within your companies are most likely to be replaced by automation in 5 years?
How can you “race with the machines” rather than “racing against the machines”?
@dw2 Page 31
Group discussion 4
Which changes to current operational practice will make it more likely you are ready to
create a successful new future?
@dw2 Page 32
https://www.youtube.com/watch?v=Ft2fLuz9mF0
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