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Weak signals, wild cards and a leap of faith


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Overview of wildcards for leaders and managers, why they matter and how to use them in strategy.

Published in: Leadership & Management

Weak signals, wild cards and a leap of faith

  1. 1. Maree Conway Thinking Futures Weak Signals, Wild Cards and a Leap of Faith Swinburne 7th Wave Conference September 2014
  2. 2. What is a weak signal?
  3. 3. Weak signals Signals of emerging issues; an early warning of change; sometimes called seeds of the future in the present Ambiguous, incomplete information - can’t use normal forms of proof to demonstrate that the idea is good Value lies in the eye of the beholder
  4. 4. Adapted from the work of Graham Molitor and Wendy Schultz, and Everett Rogers Emerging Issues Trends Mainstream Time Number of cases; degree of public awareness Scientists, artists, radicals, mystics Newspapers, magazines, websites, journals, blogs Government Institutions Few cases, local focus Global, multiple dispersed cases, trends and megatrends Innovators Early adopters Late Adopters Late Majority Laggards Today Time from emerging issue to mainstream varies between 18-36 years TodayWeak Signals
  5. 5. Three horizons
  6. 6. Bill Sharpe Three Horizons: A way of working with change, 2013
  7. 7. Once you perceive a weak signal and understand it, a whole host of other signals may become visible. These comprise the complete ecosystem of ideas and trends that will support each other in the journey from dream to manifestation. No weak signal ever rises to dominance by itself, but is accompanied by shifts in political, economic, technological, and social thought and invention. Brian S Coffman, 1977
  8. 8. What is a wildcard?
  9. 9. A low probability, high impact event that has the potential to change the world overnight
  10. 10. John Petersen, Arlington Institute If you don’t think about a wildcard before it happens, all of the value of thinking about it is lost Accessing and understanding information is key – look for people at the edges Extraordinary events will require extraordinary approaches
  11. 11. Why care?
  12. 12. Coffman 1997
  13. 13. Examples
  14. 14.
  15. 15.
  16. 16. Some weak signals: Technology Maker movement and hyper personal manufacturing: 3D printing/4D printing – customised and on demand. Now biohacking. Internet of Things - Privacy and surveillance and issue - Lots of (big) data about you for others to use - Blurring physical and digital Robotics – drones now, in the office when? Artificial intelligence – the Singularity cometh? Wearables – using the data – how?
  17. 17. Some weak signals: Technology Haptic holographics and gamification/gaming Oculus Rift and similar immersive virtual reality headsets – virtual experiences, maybe even ‘being’ in another person’s body through mutual sensations Brain inspired computers (IBM DARPA SyNAPSE metric of a one million neuron brain-inspired processor – holistic computing intelligence)
  18. 18. Some weak signals: Users Telepathy – message sent between brains from India to France – potential to input info directly to brain? Sensors, facial recognition and wearables technologies to customise experiences for you (retail) Bank customers signing in with veins Biometrics – fingerprint scanning
  19. 19. Some weak signals: education Cognitive enhancers – improved memory and focus AI in the classroom – Japanese AI program to sit university entrance tests Mobius Slip – peer grading integrated Alison: integrated assessment with learning platform Next: AI and continuous real time digital assessment – the demise of exams as we know them? New competitors from left field – big tech players (eg Google), public libraries, Pearson, magazines, social media, Amazon?
  20. 20. Some weak signals: universities New secondary school structures and operations emerging – student centred (Templestowe College) Minerva Project – for profit, bare bones university in San Francisco – online platform. Aims to reform or replace liberal arts college sector Qualifications – digital certification, employers wanting proof of competencies Unizin – consortia to have greater control and influence over the digital learning landscape
  21. 21. Digital Business Development (Gartner) Digital Marketing: mobile, social, cloud and information – holographic displays, neurobusiness, gesture control, augmented reality Digital business: convergence of people, business and things – smart workspaces, connected homes, consumer 3D printing Autonomous: leveraging technologies that provide human-like or human replacing technologies – human augmentation, quantum computing, smart robots
  22. 22. Wildcards Teachers are replaced by adaptive learning systems Teacher-less learning models begin to appear, particularly in developing countries (like Hole in the Wall in India) Mass biometric verification data theft damages uptake of new technologies
  23. 23. That leap of faith?
  24. 24. Didn’t take a leap of faith Kodak – developed the technology but didn’t want to spend the money – Board decides to focus on existing business where they’ve invested heavily Blockbuster – offered Netflix in 2000, recognised challenges, CEO proposed changes, undermined from inside, he was sacked, new CEO leads them to bankruptcy by focusing on existing business Borders – too late to the web, missed ebooks, too many stores, over emphasis on music, industry changed around it
  25. 25. Weak signals and wildcards are not certain: we don’t know if they will really matter. We have to watch them and sometimes take a leap of faith.
  26. 26. So…what to do?
  27. 27. Go out there (via Elina Hiltunen) Human sources Textual sources Online sources
  28. 28. Add this process to your systems
  29. 29. Create some wildcards to test: Reference Impact Grid (Marcus Barber)
  30. 30. m 1 2 3 4 5 Present Concerns Future Aspirations Inspirational Practice Innovations In Play Essential Features to Maintain m
  31. 31. But…
  32. 32. Michael Parent, Google+, 2014
  33. 33. PREVALENCE TIME H3 H1 H2 Three Horizons H1 sees H2 as too risky H3 as irrelevant. H2 sees H1 as obstructive H3 as inspiring. H3 sees H1 as lunacy H2 as promising. m
  34. 34. The future will not be like the past. The future will be built by those who will take risks and action to invent the world they want. Vinod Khosla , The Case For Intelligent Failure To Invent The Future, TechCrunch, 2014
  35. 35. Thanks to my APF Colleagues Tom Abeles Bryan Alexander Marcus Barber James Breaux Dennis Draeger Robert Moran Guillermina Maria Eugenia Baena Paz Heather Schegel
  36. 36. Get in touch Maree Conway | Thinking Futures PO Box 2118, Hotham Hill, 3051 Australia Telephone: +61 (0) 3 9016 9506 Mobile: +61 (0) 425 770 181 Email: Web: Twitter: @mareeconway