Big Data Munich – Decision Automation and Big Data
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My presentation from Big Data Munich: How decision automation based on big data and machine learning can help you run a better business and avoid common cognitive biases.
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Big Data Munich – Decision Automation and Big Data
- 1. LARS TRIELOFF – BLUE YONDER – I’M @TRIELOFF ON TWITTER AUTOMATED DECISION MAKING
- 2. WHAT NOBODY TELLS YOU ABOUT THE FRONTIER
- 3. WHO IS USING BIG DATA TODAY
- 4. WHERE BIG DATA IS USED Effective Use Marketing Finance Everyone Else SOURCE: OWN, POTENTIALLY BIASED OBSERVATIONS
- 5. WHERE BIG DATA SHOULD BE USED Potential Use Marketing Finance Everyone Else SOURCE: OWN, POTENTIALLY BIASED OBSERVATIONS
- 6. THREE APPROACHES More Data Faster Data Better Decisions
- 7. DIGITAL MARKETING’S APPROACH: MORE DATA
- 8. FINANCE’S APPROACH FASTER DATA
- 9. BUT WHAT ABOUT BETTER DECISIONS?
- 10. Self-Actualization Love/Belonging Safety Physiological Esteem
- 11. Storage Collection Prediction Analysis Decision
- 12. Storage Collection Prediction Analysis Decision Self-Actualization Love/Belonging Safety Physiological Esteem
- 14. “… all others bring data.” — W. EDWARDS DEMING
- 15. HOW DATA-DRIVEN DECISIONS SHOULD WORK COMPUTER COLLECTS COMPUTER STORES HUMAN ANALYZES HUMAN PREDICTS HUMAN DECIDES
- 16. HOW DATA-DRIVEN DECISIONS REALLY WORK COMPUTER COLLECTS COMPUTER STORES HUMAN ANALYZES COMMUNICATION BREAKDOWN HUMAN DECIDES
- 17. COMMUNICATION BREAKDOWN Communication Breakdown, It's always the same, I'm having a nervous breakdown, Drive me insane! — LED ZEPPELIN • Drill-down analysis … misunderstood or distorted • Metrics dashboards … contradictory and confusing • Monthly reports … ignored after two iterations • In-house analyst teams … overworked and powerless
- 18. HOW DATA-DRIVEN DECISIONS REALLY WORK HTTP://DILBERT.COM/STRIPS/COMIC/2007-05-16/
- 19. HOW DECISIONS REALLY SHOULD WORK COMPUTER COLLECTS COMPUTER STORES COMPUTER ANALYZES COMPUTER PREDICTS COMPUTER DECIDES
- 20. 99.9% of all business decisions can be automated
- 21. HOW DECISIONS ARE BEING MADE
- 22. HOW DECISIONS ARE BEING MADE
- 23. 90% NO DECISION IS MADE
- 24. 90% NO DECISION IS MADE
- 25. 9% DECISION FOLLOWS RULE
- 26. 9% DECISION FOLLOWS RULE
- 27. 1% HUMAN DECISION MAKING
- 28. 1% HUMAN DECISION MAKING
- 29. “Making no decision is a decision. To do nothing. And nothing always brings you nowhere..” –ROBIN SHARMA
- 30. BUSINESS RULES FOR BEGINNERS Not doing anything is the simplest business rule in the world – and also the most popular
- 31. ADVANCED BUSINESS RULES Computers are machines following rules. This means business rules are programs.
- 32. BUSINESS RULES ARE PROGRAMS, JUST NOT VERY GOOD PROGRAMS. • Business rules are like programs – written by non-programmers • Business rules can be contradictory, incomplete, and complex beyond comprehension • Business rules have no built-in feedback mechanism: “It is the rule, because it is the rule”
- 33. HUMAN DECISION MAKING • • System 1: Fast, automatic, frequent, emotional, stereotypic, subconscious • • System 2: Slow, effortful, infrequent, logical, calculating, conscious DANIEL KAHNEMANN, THINKING FAST AND SLOW
- 34. HOW TO DECIDE FAST FREQUENT DECISION MAKING MEANS FAST DECISION MAKING, MEANS USING HEURISTICS OR COGNITIVE BIASES Anchoring effect IKEA effect Over-justification effect Bandwagon effect Confirmation bias Substitution Availability heuristic Texas Sharpshooter Fallacy Gambler’s fallacy Illusory correlation Rhyme as reason effect Hindsight bias Zero-risk bias Framing effect Sunk cost fallacy Overconfidence Outcome bias Inattentional Blindness Benjamin Franklin effect Anecdotal evidence Negativity bias Loss aversion Backfire effect
- 36. • Abraham Lincoln and John F. Kennedy were both presidents of the United States, elected 100 years apart. • Both were shot and killed by assassins who were known by three names with 15 letters, John Wilkes Booth and Lee Harvey Oswald, and neither killer would make it to trial. • Lincoln had a secretary named Kennedy, and Kennedy had a secretary named Lincoln. • They were both killed on a Friday while sitting next to their wives, Lincoln in the Ford Theater, Kennedy in a Lincoln made by Ford.
- 37. • Abraham Lincoln and John F. Kennedy were both presidents of the United States, elected 100 years apart. • Both were shot and killed by assassins who were known by three names with 15 letters, John Wilkes Booth and Lee Harvey Oswald, and neither killer would make it to trial. • Lincoln had a secretary named Kennedy, and Kennedy had a secretary named Lincoln. • They were both killed on a Friday while sitting next to their wives, Lincoln in the Ford Theater, Kennedy in a Lincoln made by Ford.
- 38. HOW COMPUTERS DECIDE FAST MACHINE LEARNING OFFERS AN ALTERNATIVE TO HUMAN COGNITIVE BIASES AND CAN BE MADE FAST THROUGH BIG DATA K-Means Clustering Markov Chain Monte Carlo Support Vector Machines Naive Bayes Affinity Propagation Decision Trees Nearest Neighbors Least Angle Regression Logistic Regression Spectral clustering Restricted Bolzmann Machines
- 39. MACHINE LEARNING MEANS PROGRAMS THAT WRITE PROGRAMS • A machine learning algorithm is a system that derives a set of rules based on a set of data • It is based on systematic observation, double-checking and cross-validation • There is no magic, just data – and without data there no magic either
- 40. Better decisions through predictive applications
- 41. HOW PREDICTIVE APPLICATIONS WORK COLLECT & STORE ANALYZE CORRELATIONS BUILD DECISION MODEL DECIDE & TEST OPTIMIZE
- 42. WHY TEST? “Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’” –RANDALL MUNROE
- 43. STORY TIME (Not safe for vegetarians)
- 44. THE GROUND BEEF DILEMMA
- 45. THE GROUND BEEF DILEMMA Yesterday Today Tomorrow Next Delivery Next Day In Stock Demand
- 46. THE GROUND BEEF DILEMMA • Order too much and you will have to throw meat away when it goes bad. You lose money and cows die in vain • Order too little and you won’t serve all your potential customers. You lose money and customers stay hungry.
- 47. CHALLENGE #1 ACCURATELY PREDICT DEMAND
- 48. CHALLENGE #2 AUTOMATE REPLENISHMENT COLLECT STOCK AND SALES PREDICT DEMAND TRADE OFF COSTS CREATE ORDERS IN ERP SYSTEM OPTIMIZE & REPEAT
- 49. Batch and streaming data ingestion, batch and streaming decision delivery (with realtime option) Optimize Returns Reduce risk and cost, increase profit and revenue Trend Estimation Classification Event Prediction Collect Data Predict Outcomes Drive Decisions
- 50. powered by Blue Yonder Platform Flex Storage Auto APIs Job Control & Data Services Relational, Flat File ML Toolkit Runtime and In-Memory Storage Service Application RESTful APIs for easy integration and data access Pluggable machine learning pipelines HTML5 based Web UI and API Builder Public data prepared for machine learning Multi-Tenant Runtime Environment Secure Micro Cloud Infrastructure