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Carl Ryden (Founder, PrecisionLender) - Build Iron Man Suits Not Terminators

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This video for this talk from Business of Software Conference Europe 2018 will be published here soon: http://businessofsoftware.org/2016/07/all-talks-from-business-of-software-conferences-in-one-place-saas-software-talks/

Carl founded his second business in 2009 with one goal: to let computers do what computers do best, so humans are free to do what they do best. This approach eventually led to Andi®, the AI platform developed by PrecisionLender, which is used within the PrecisionLender application to offer commercial bankers actionable insights at the exact moment they need it.

When PrecisionLender developed Andi, they thought about Intelligence Augmentation, rather than AI. They focused on UX, customer jobs-to- be-done, and the incredible power of personification to build their most successful product. Carl will share how he came to realise as he grew PrecisionLender that a relentless focus on people, employees, and customers was the key to profitable growth. And he’s watched as the company itself has grown to over 100 people with staff turnover of just 3%.

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Carl Ryden (Founder, PrecisionLender) - Build Iron Man Suits Not Terminators

  1. 1. Build Iron Man Suits Not Terminators Carl Ryden CEO/Co-founder PrecisionLender @caryden
  2. 2. This guy…
  3. 3. “If in your office, you, as an intellectual worker, were supplied with a computer display backed up by a computer that was alive for you all day, and was instantly responsive to every action you have—how much value could you derive from that?”
  4. 4. oN-Line System
  5. 5. “I don’t know what Silicon Valley will do when it runs out of Doug’s ideas.” -Alan Kay
  6. 6. Intelligence Augmentation (IA)
  7. 7. Digital Transformation
  8. 8. Our Journey to Andi
  9. 9. Where we started
  10. 10. Andy and the Magic Dots
  11. 11. …every PrecisionLender user …now has their own pricing analyst
  12. 12. Her name is Andi. She is new on job, but she learns very quickly. She works 24x7. She never sleeps. She sees every deal within your bank. She learns what is working and what is not. She helps you to price each new opportunity, offering suggestions on structure and how to compete. She monitors your relationships and alerts you to threats and opportunities. ..and a completely extensible “Andi Skills Framework” for adding, deploying and managing new skills
  13. 13. What have we learned? (so far)
  14. 14. Context is King • Narrow the context • User Interface & User Experience matter immensely
  15. 15. Not All Data is Created Equal • Labelled behavioral data is most valuable. • Most of the existing data is not this. • Build this data organically to drive results.
  16. 16. Nobody actually wants Artificial Intelligence. They just want Intelligence • Simple, heuristic-driven insights: • Drive early value • Establish delivery pathways • Establish success metrics/set the bar • Amplify the human in the loop • Build Iron Man suits not Terminators.
  17. 17. The impact of the personification of “Andi” has amazed me. • It is relatable and human. • It extracts the “job to be done” instead of “put a button here.” • It humanizes the machine instead of mechanizing the human.
  18. 18. There is an intelligence augmentation value chain • To win, you must implement the entire value chain. • Most die at the “last mile” of AI: Translating insight into action.
  19. 19. Ajay Agrawal’s Anatomy of a Task Human Judgement ActionPrediction OutcomeData Feedback Data
  20. 20. Gordon Ritter’s Coaching Networks
  21. 21. SoR, SoI, SoE…oh my Systems of Record (SoR) Systems of Intelligence (SoI) Systems of Engagement (SoE) What is it? Captures data around what happened, when it happened and who was involved. Uses machine learning algorithms to transform facts from systems of record into “beliefs” about the business/ world (predictions are just beliefs about the future). Rides “shotgun” with the end user while they “do what they do” and translates facts and beliefs into discrete, measurable actions to coach or nudge the user to a better outcome. Deals in: Facts Beliefs/ Predictions Actions Examples: CRM, ERP, SCP, etc. Data Robot, Tensorflow, etc. PrecisionLender, Hemingwayapp, Chorus.ai
  22. 22. Many ways of saying the same thing… Systems of Record (SoR) Systems of Intelligence (SoI) Systems of Engagement (SoE) Perception Cognition Action Greylock’s Jerry Chen Microsoft’s Satya Nadella: Gathering Comparing Coaching Emergence’s Gordon Ritter: Data Prediction Action U of Toronto’s Ajay Agrawal:
  23. 23. Centaur or Freestyle Chess When you create a Human + AI team, the hard part isn’t the “AI”. It isn’t even the “Human”. It’s the “+”.
  24. 24. Again, many ways of saying the same thing… Cognitive Expert Advisors Citizen AI Gartner Accenture Coaching Networks Emergence’s Gordon Ritter: Cognitive CollaborationDeloitte
  25. 25. Applied Insights - Coaching Contextual Contemporaneous Constructive Individualized Actionable Attributable
  26. 26. “If in your office, you, as an intellectual worker, were supplied with a computer display backed up by a computer that was alive for you all day, and was instantly responsive to every action you have—how much value could you derive from that?”

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