Watson toa san fran high tech event v 2
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The document is a presentation on Watson Tradeoff Analytics from September 17, 2015. It discusses how making complex choices can be difficult for humans due to cognitive biases and limitations. It presents Watson as enabling more evidence-based decisions through its capabilities in natural language processing, machine learning, and ability to analyze both structured and unstructured data. Specific use cases discussed include purchase selection, human resources decisions, inventory balancing, and more.
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Watson toa san fran high tech event v 2
- 1. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam Watson T&T: Use Cases WATSON TRADEOFF ANALYTICS SEPTEMBER 17, 2015 CRISTENE GONZALEZ-‐WERTZ LEADER, INDUSTRY VALUE SOLUTIONS, WATSON GROUP
- 2. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam Making choices among many things can difficult. OSen there is no clear and transparent path to making an opVmal choice 9/17/15 2 IMPERFECT TENSE: HUMANS AND CHOICE hDp://www.afoodaffair.me/recipe-‐feel-‐good-‐morning-‐food/#.VfrX5TU95XU hDp://www.bmw.com/com/en/newvehicles/i/i8/2014/showroom/ hDp://www.findmecoffee.com/
- 3. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 9/17/15 3 The Amazon Culture, Choice Overload, CogniVve Misers, Overconfidence and Post Purchase Dissonance DECISION FATIGUE: YES, THAT’S A THING Choices Decision confidence Anticipation of regret Perceived return on investment
- 4. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam ASK DISCOVEREXPLORE DECIDE VISUALIZE Ask questions for greater insight Natural language dialogue Natural language dialogue Find external information in real time Monitor social sentiment Find rationale for given responses Prompt for inputs to yield improved responses Ingest and analyze domain sources, info models Evidence-based decisions with greater confidence Consolidate and visualize information across enterprise applications and big data assets Watson enables five classes of cogniVve services working across structured and unstructured data with Natural Language Processing and Machine Learning WATSON’S 5 CORE CAPABILITIES
- 5. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 9/17/15 5
- 6. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 6 CHOOSING A DEVICE, CONSTRAINTS Our tradiVonal approaches rely on filtering and simple opVmizaVon approaches. We mask the complexity, make it hard to see criteria and how opVons rank TradiSonal filtering only gets you part of the way
- 7. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 7 • Pareto OpSmality • Visual exploraSon • SimulaSng Human Judgment CHOOSING A DEVICE, THE NEW FASHION Giving the choice maker more opVons isn’t the answer. Giving the choice maker more understandable opVons is.
- 8. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 8 RANGES OF COMPLEXITY The ability to bring choices in and out of the decision criteria allows the user to see the impact of the data and and the choices on the outcomes
- 9. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 9 CREATE YOUR OWN COGNITIVE BIAS Combining services in the IBM Blue Mix pordolio allows beeer decisions. It also enables more robust experiences NEW YORK CITY SCHOOL FINDER Personality Insights + Tradeoff Analytics OTHER COMBINATIONS? Product Matcher Connected Commerce Dynamic Scheduling & Routing Marketing Offer Management
- 10. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam 10 HANGING OUT IN ALL THE BEST PLACES Some of the places we are seeing Tradeoff AnalyVcs being applied include: Purchase SelecVon and Decisioning Human Resource Decision Making Inventory Balancing Medical Decision Management Strategic and Capital Planning Irregular OperaVons Redress MarkeVng and Offer Management Financial Decision Management AND, INTERESTINGLY ENOUGH, FANTASY LEAGUE SPORTS
- 11. © 2015 InternaSonal Business Machines CorporaSon What will you do with Watson? 11
- 12. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam In-‐store interacVve pladorm where the consumer enters their twieer handle to understand the breakdown of their personality with Watson’s Personality Insights API The consumer’s personality is matched to a bike
- 13. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam Bluemix is IBM’s Pladorm as a Service (PaaS) offering Customer Managed Service Provider Managed Infrastructure as a Service Code Data Runtime Middleware OS Virtualization Servers Storage Networking Code Data Runtime Middleware OS Virtualization Servers Storage Networking Platform as a Service Software as a Service Code Data Runtime Middleware OS Virtualization Servers Storage Networking Code Data Runtime Middleware OS Virtualization Servers Storage Networking Traditional Datacenter
- 14. ©IBM 2015 Developed by Cristene Gonzalez-‐Wertz for Watson Industry Value Tam WDC services can be consumed in different ways Watson Ecosystem PAYGO / SubscripVon Enhance WEX Embed • Powered by IBM Watson apps • Revenue share model • Pay as you go based on usage • SubscripSon model • Add cogniSve capabiliSes from WDC to WEX deployments • Embed cogniSve capabiliSes from WDC in other IBM products / soluSons WDC -‐ Enterprise • Enterprise subscripSon • 3 month minimum • On-‐site training and mentoring