SlideShare uma empresa Scribd logo
1 de 35
Baixar para ler offline
LARS TRIELOFF – BLUE YONDER – I’M @TRIELOFF ON TWITTER 
AUTOMATING DECISIONS – THE 
NEXT FRONTIER FOR BIG DATA
WHAT NOBODY TELLS YOU ABOUT 
THE FRONTIER
WHO IS USING BIG DATA TODAY
WHERE BIG DATA IS USED 
Effective Use 
Marketing 
Finance 
Everyone Else 
SOURCE: OWN, POTENTIALLY BIASED OBSERVATIONS
WHERE BIG DATA IS USED 
Potential Use 
Marketing 
Finance 
Everyone Else 
SOURCE: OWN, POTENTIALLY BIASED OBSERVATIONS
Better Decisions 
Faster Data 
More Data 
THREE APPROACHES
DIGITAL MARKETING’S APPROACH: 
MORE DATA
FINANCE’S APPROACH 
FASTER DATA
BUT WHAT ABOUT BETTER 
DECISIONS?
Self-Actualization 
Love/Belonging 
Safety 
Physiological 
Esteem
Storage 
Collection 
Prediction 
Analysis 
Decision
Storage 
Collection 
Prediction 
Analysis 
Decision 
Self-Actualization 
Love/Belonging 
Safety 
Physiological 
Esteem
Big Data Berlin – Automating Decisions is the Next Frontier for Big Data
“… all others bring data.” 
! 
— W. EDWARDS DEMING
HOW DATA-DRIVEN DECISIONS SHOULD WORK 
COMPUTER 
COLLECTS 
COMPUTER 
STORES 
HUMAN 
ANALYZES 
HUMAN 
PREDICTS 
HUMAN 
DECIDES
HOW DATA-DRIVEN DECISIONS REALLY WORK 
COMPUTER 
COLLECTS 
COMPUTER 
STORES 
HUMAN 
ANALYZES 
COMMUNICATION 
BREAKDOWN 
HUMAN 
DECIDES
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
HOW DATA-DRIVEN DECISIONS REALLY WORK 
HTTP://DILBERT.COM/STRIPS/COMIC/2007-05-16/
HOW DECISIONS REALLY SHOULD WORK 
COMPUTER 
COLLECTS 
COMPUTER 
STORES 
COMPUTER 
ANALYZES 
COMPUTER 
PREDICTS 
COMPUTER 
DECIDES
99.9% of all business decisions can be automated
HOW DECISIONS ARE MADE 
Human Decisions 
Business Rules 
No Decision, Decision-by-default
BUSINESS RULES = PROGRAMMING 
• 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”
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
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
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
Better decisions through predictive applications
HOW PREDICTIVE APPLICATIONS WORK 
COLLECT & 
STORE 
ANALYZE 
CORRELATIONS 
BUILD 
DECISION 
MODEL 
DECIDE & 
TEST OPTIMIZE
WHY TEST? 
“Correlation doesn’t imply causation, but it does waggle its 
eyebrows suggestively and gesture furtively while mouthing ‘look 
over there’” 
–RANDALL MUNROE
STORY TIME 
(Not safe for vegetarians)
THE GROUND BEEF DILEMMA
THE GROUND BEEF DILEMMA 
Yesterday Today Tomorrow Next Delivery Next Day 
In Stock Demand
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.
CHALLENGE #1 
ACCURATELY PREDICT DEMAND
CHALLENGE #2 
AUTOMATE REPLENISHMENT 
COLLECT 
STOCK AND 
SALES 
PREDICT 
DEMAND 
TRADE OFF 
COSTS 
CREATE 
ORDERS IN ERP 
SYSTEM 
OPTIMIZE & 
REPEAT
@BYANALYTICS_EN 
@TRIELOFF

Mais conteúdo relacionado

Mais procurados

Become an Exponential Organization, Change the World Faster
Become an Exponential Organization, Change the World FasterBecome an Exponential Organization, Change the World Faster
Become an Exponential Organization, Change the World FasterGary A. Bolles
 
Marcus Ranum on Bad Idea Zombies
Marcus Ranum on Bad Idea Zombies Marcus Ranum on Bad Idea Zombies
Marcus Ranum on Bad Idea Zombies David Strom
 
Brain Hacking: Using behavioural economics and consumer psychology to improve...
Brain Hacking: Using behavioural economics and consumer psychology to improve...Brain Hacking: Using behavioural economics and consumer psychology to improve...
Brain Hacking: Using behavioural economics and consumer psychology to improve...David Greenwood
 
Talking Tech - the art and science of communicating complex ideas (Bristech2...
Talking Tech  - the art and science of communicating complex ideas (Bristech2...Talking Tech  - the art and science of communicating complex ideas (Bristech2...
Talking Tech - the art and science of communicating complex ideas (Bristech2...Cecilia Thirlway
 
Carrot stick-consequences-app secdc-2010
Carrot stick-consequences-app secdc-2010Carrot stick-consequences-app secdc-2010
Carrot stick-consequences-app secdc-2010orcus666
 
Black Swan Risk Management - Aditya Yadav
Black Swan Risk Management - Aditya YadavBlack Swan Risk Management - Aditya Yadav
Black Swan Risk Management - Aditya YadavAditya Yadav
 
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...Protectionandmanagement
 
Solving the Wanamaker Problem for Healthcare (keynote file)
Solving the Wanamaker Problem for Healthcare (keynote file)Solving the Wanamaker Problem for Healthcare (keynote file)
Solving the Wanamaker Problem for Healthcare (keynote file)Tim O'Reilly
 
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...Travel Tech Conference Russia
 
Who is your Company’s Chief Decision Officer
Who is your Company’s Chief Decision Officer Who is your Company’s Chief Decision Officer
Who is your Company’s Chief Decision Officer June Boda, GPHR
 
Strategies to make anyone use your Product | Product that Count
Strategies to make anyone use your Product | Product that CountStrategies to make anyone use your Product | Product that Count
Strategies to make anyone use your Product | Product that CountCastle
 
How Four Cognitive Biases Deceive Analysts and Destroy Actionability
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityHow Four Cognitive Biases Deceive Analysts and Destroy Actionability
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityEric Garland
 
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...Eric Garland
 
Finding out what could go wrong before it does – Modelling Risk and Uncertainty
Finding out what could go wrong before it does – Modelling Risk and UncertaintyFinding out what could go wrong before it does – Modelling Risk and Uncertainty
Finding out what could go wrong before it does – Modelling Risk and UncertaintyBruce Edmonds
 
Ficod 2011 (keynote file)
Ficod 2011 (keynote file)Ficod 2011 (keynote file)
Ficod 2011 (keynote file)Tim O'Reilly
 
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter..."Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...Data Driven Innovation
 
What Internet Operations Teach Us About the Future of Management
What Internet Operations Teach Us About the Future of ManagementWhat Internet Operations Teach Us About the Future of Management
What Internet Operations Teach Us About the Future of ManagementAPNIC
 

Mais procurados (20)

Become an Exponential Organization, Change the World Faster
Become an Exponential Organization, Change the World FasterBecome an Exponential Organization, Change the World Faster
Become an Exponential Organization, Change the World Faster
 
Marcus Ranum on Bad Idea Zombies
Marcus Ranum on Bad Idea Zombies Marcus Ranum on Bad Idea Zombies
Marcus Ranum on Bad Idea Zombies
 
Brain Hacking: Using behavioural economics and consumer psychology to improve...
Brain Hacking: Using behavioural economics and consumer psychology to improve...Brain Hacking: Using behavioural economics and consumer psychology to improve...
Brain Hacking: Using behavioural economics and consumer psychology to improve...
 
Talking Tech - the art and science of communicating complex ideas (Bristech2...
Talking Tech  - the art and science of communicating complex ideas (Bristech2...Talking Tech  - the art and science of communicating complex ideas (Bristech2...
Talking Tech - the art and science of communicating complex ideas (Bristech2...
 
Carrot stick-consequences-app secdc-2010
Carrot stick-consequences-app secdc-2010Carrot stick-consequences-app secdc-2010
Carrot stick-consequences-app secdc-2010
 
Black Swan Risk Management - Aditya Yadav
Black Swan Risk Management - Aditya YadavBlack Swan Risk Management - Aditya Yadav
Black Swan Risk Management - Aditya Yadav
 
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...
Want to change people's behaviour just ask (and nudge, hug, shove and smack) ...
 
Where are your project saboteurs? webinar, 2 March 2020
Where are your project saboteurs? webinar, 2 March 2020Where are your project saboteurs? webinar, 2 March 2020
Where are your project saboteurs? webinar, 2 March 2020
 
Solving the Wanamaker Problem for Healthcare (keynote file)
Solving the Wanamaker Problem for Healthcare (keynote file)Solving the Wanamaker Problem for Healthcare (keynote file)
Solving the Wanamaker Problem for Healthcare (keynote file)
 
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...
David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man i...
 
Who is your Company’s Chief Decision Officer
Who is your Company’s Chief Decision Officer Who is your Company’s Chief Decision Officer
Who is your Company’s Chief Decision Officer
 
Strategies to make anyone use your Product | Product that Count
Strategies to make anyone use your Product | Product that CountStrategies to make anyone use your Product | Product that Count
Strategies to make anyone use your Product | Product that Count
 
How Four Cognitive Biases Deceive Analysts and Destroy Actionability
How Four Cognitive Biases Deceive Analysts and Destroy ActionabilityHow Four Cognitive Biases Deceive Analysts and Destroy Actionability
How Four Cognitive Biases Deceive Analysts and Destroy Actionability
 
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...
How to Spot and Cope with Emerging Transitions in Complex Systems for Organiz...
 
Nudge v final
Nudge   v finalNudge   v final
Nudge v final
 
Finding out what could go wrong before it does – Modelling Risk and Uncertainty
Finding out what could go wrong before it does – Modelling Risk and UncertaintyFinding out what could go wrong before it does – Modelling Risk and Uncertainty
Finding out what could go wrong before it does – Modelling Risk and Uncertainty
 
Nudge
NudgeNudge
Nudge
 
Ficod 2011 (keynote file)
Ficod 2011 (keynote file)Ficod 2011 (keynote file)
Ficod 2011 (keynote file)
 
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter..."Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...
"Trust" in the (Big) Data Era(Christian Racca ,TOP-IX / TOrino Piemonte Inter...
 
What Internet Operations Teach Us About the Future of Management
What Internet Operations Teach Us About the Future of ManagementWhat Internet Operations Teach Us About the Future of Management
What Internet Operations Teach Us About the Future of Management
 

Destaque

Automated Decision Making with Predictive Applications – Big Data Düsseldorf
Automated Decision Making with Predictive Applications – Big Data DüsseldorfAutomated Decision Making with Predictive Applications – Big Data Düsseldorf
Automated Decision Making with Predictive Applications – Big Data DüsseldorfLars Trieloff
 
Big Data Munich – Decision Automation and Big Data
Big Data Munich – Decision Automation and Big DataBig Data Munich – Decision Automation and Big Data
Big Data Munich – Decision Automation and Big DataLars Trieloff
 
Automated Decision making with Predictive Applications – Big Data Hamburg
Automated Decision making with Predictive Applications – Big Data HamburgAutomated Decision making with Predictive Applications – Big Data Hamburg
Automated Decision making with Predictive Applications – Big Data HamburgLars Trieloff
 
Automated decision making with predictive applications – Big Data Amsterdam
Automated decision making with predictive applications – Big Data AmsterdamAutomated decision making with predictive applications – Big Data Amsterdam
Automated decision making with predictive applications – Big Data AmsterdamLars Trieloff
 
Serverless adventures with AWS Lambda and Clojure
Serverless adventures with AWS Lambda and ClojureServerless adventures with AWS Lambda and Clojure
Serverless adventures with AWS Lambda and ClojureLars Trieloff
 
Automated decision making with predictive applications – Big Data Frankfurt
Automated decision making with predictive applications – Big Data FrankfurtAutomated decision making with predictive applications – Big Data Frankfurt
Automated decision making with predictive applications – Big Data FrankfurtLars Trieloff
 

Destaque (7)

Automated Decision Making with Predictive Applications – Big Data Düsseldorf
Automated Decision Making with Predictive Applications – Big Data DüsseldorfAutomated Decision Making with Predictive Applications – Big Data Düsseldorf
Automated Decision Making with Predictive Applications – Big Data Düsseldorf
 
Web Forms 2.0
Web Forms 2.0Web Forms 2.0
Web Forms 2.0
 
Big Data Munich – Decision Automation and Big Data
Big Data Munich – Decision Automation and Big DataBig Data Munich – Decision Automation and Big Data
Big Data Munich – Decision Automation and Big Data
 
Automated Decision making with Predictive Applications – Big Data Hamburg
Automated Decision making with Predictive Applications – Big Data HamburgAutomated Decision making with Predictive Applications – Big Data Hamburg
Automated Decision making with Predictive Applications – Big Data Hamburg
 
Automated decision making with predictive applications – Big Data Amsterdam
Automated decision making with predictive applications – Big Data AmsterdamAutomated decision making with predictive applications – Big Data Amsterdam
Automated decision making with predictive applications – Big Data Amsterdam
 
Serverless adventures with AWS Lambda and Clojure
Serverless adventures with AWS Lambda and ClojureServerless adventures with AWS Lambda and Clojure
Serverless adventures with AWS Lambda and Clojure
 
Automated decision making with predictive applications – Big Data Frankfurt
Automated decision making with predictive applications – Big Data FrankfurtAutomated decision making with predictive applications – Big Data Frankfurt
Automated decision making with predictive applications – Big Data Frankfurt
 

Semelhante a Big Data Berlin – Automating Decisions is the Next Frontier for Big Data

Automated decision making using Predictive Applications – Big Data Paris
Automated decision making using Predictive Applications – Big Data ParisAutomated decision making using Predictive Applications – Big Data Paris
Automated decision making using Predictive Applications – Big Data ParisLars Trieloff
 
20161109_Mahan_Brighttalk_Webinar_Final
20161109_Mahan_Brighttalk_Webinar_Final20161109_Mahan_Brighttalk_Webinar_Final
20161109_Mahan_Brighttalk_Webinar_FinalPhillip Mahan
 
Automated decision making with big data – Big Data Vienna
Automated decision making with big data – Big Data ViennaAutomated decision making with big data – Big Data Vienna
Automated decision making with big data – Big Data ViennaLars Trieloff
 
2018 10 igneous
2018 10 igneous2018 10 igneous
2018 10 igneousChris Dwan
 
116 Machine learning for Product Managers
116   Machine learning for Product Managers116   Machine learning for Product Managers
116 Machine learning for Product ManagersProductCamp Boston
 
Machine learning for product managers. Presented at Boston ProductCamp (June...
Machine learning for product  managers. Presented at Boston ProductCamp (June...Machine learning for product  managers. Presented at Boston ProductCamp (June...
Machine learning for product managers. Presented at Boston ProductCamp (June...Mukund Seshadri
 
How to win at Conversion Optimization
How to win at Conversion OptimizationHow to win at Conversion Optimization
How to win at Conversion OptimizationSnehal Samant
 
How Digital Trends Are Compressing Processes
How Digital Trends Are Compressing ProcessesHow Digital Trends Are Compressing Processes
How Digital Trends Are Compressing ProcessesSharon Richardson
 
Healthcare Best Practices in Data Warehousing & Analytics
Healthcare Best Practices in Data Warehousing & AnalyticsHealthcare Best Practices in Data Warehousing & Analytics
Healthcare Best Practices in Data Warehousing & AnalyticsDale Sanders
 
Big data hype (and reality)
Big data hype (and reality)Big data hype (and reality)
Big data hype (and reality)Tarang Jain
 
Decisions and Technical Leadership
Decisions and Technical LeadershipDecisions and Technical Leadership
Decisions and Technical LeadershipRuth Malan
 
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101Felipe Prado
 
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Matt Hathaway
 
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Alexandre Sieira
 
Maintenance: How not to hate it - v.13
Maintenance: How not to hate it - v.13Maintenance: How not to hate it - v.13
Maintenance: How not to hate it - v.13Brian Gongol
 
The Bigger They Are The Harder They Fall
The Bigger They Are The Harder They FallThe Bigger They Are The Harder They Fall
The Bigger They Are The Harder They FallTrillium Software
 

Semelhante a Big Data Berlin – Automating Decisions is the Next Frontier for Big Data (20)

Automated decision making using Predictive Applications – Big Data Paris
Automated decision making using Predictive Applications – Big Data ParisAutomated decision making using Predictive Applications – Big Data Paris
Automated decision making using Predictive Applications – Big Data Paris
 
20161109_Mahan_Brighttalk_Webinar_Final
20161109_Mahan_Brighttalk_Webinar_Final20161109_Mahan_Brighttalk_Webinar_Final
20161109_Mahan_Brighttalk_Webinar_Final
 
Automated decision making with big data – Big Data Vienna
Automated decision making with big data – Big Data ViennaAutomated decision making with big data – Big Data Vienna
Automated decision making with big data – Big Data Vienna
 
2018 10 igneous
2018 10 igneous2018 10 igneous
2018 10 igneous
 
Simplify your analytics strategy
Simplify your analytics strategySimplify your analytics strategy
Simplify your analytics strategy
 
IBM Watson Brand Overview
IBM Watson Brand OverviewIBM Watson Brand Overview
IBM Watson Brand Overview
 
Big Data – Are You Ready?
Big Data – Are You Ready?Big Data – Are You Ready?
Big Data – Are You Ready?
 
116 Machine learning for Product Managers
116   Machine learning for Product Managers116   Machine learning for Product Managers
116 Machine learning for Product Managers
 
Machine learning for product managers. Presented at Boston ProductCamp (June...
Machine learning for product  managers. Presented at Boston ProductCamp (June...Machine learning for product  managers. Presented at Boston ProductCamp (June...
Machine learning for product managers. Presented at Boston ProductCamp (June...
 
How to win at Conversion Optimization
How to win at Conversion OptimizationHow to win at Conversion Optimization
How to win at Conversion Optimization
 
How Digital Trends Are Compressing Processes
How Digital Trends Are Compressing ProcessesHow Digital Trends Are Compressing Processes
How Digital Trends Are Compressing Processes
 
Healthcare Best Practices in Data Warehousing & Analytics
Healthcare Best Practices in Data Warehousing & AnalyticsHealthcare Best Practices in Data Warehousing & Analytics
Healthcare Best Practices in Data Warehousing & Analytics
 
Big Data Tsunami
Big Data TsunamiBig Data Tsunami
Big Data Tsunami
 
Big data hype (and reality)
Big data hype (and reality)Big data hype (and reality)
Big data hype (and reality)
 
Decisions and Technical Leadership
Decisions and Technical LeadershipDecisions and Technical Leadership
Decisions and Technical Leadership
 
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101
DEF CON 27 - workshop - KRISTY WESTPHAL - analysis 101
 
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
 
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
Reverse Engineering the Wetware: Understanding Human Behavior to Improve Info...
 
Maintenance: How not to hate it - v.13
Maintenance: How not to hate it - v.13Maintenance: How not to hate it - v.13
Maintenance: How not to hate it - v.13
 
The Bigger They Are The Harder They Fall
The Bigger They Are The Harder They FallThe Bigger They Are The Harder They Fall
The Bigger They Are The Harder They Fall
 

Mais de Lars Trieloff

Putting the F in FaaS: Functional Compositional Patterns in a Serverless World
Putting the F in FaaS: Functional Compositional Patterns in a Serverless WorldPutting the F in FaaS: Functional Compositional Patterns in a Serverless World
Putting the F in FaaS: Functional Compositional Patterns in a Serverless WorldLars Trieloff
 
10 Things I Learned About Pricing – Product Camp Berlin 2014
10 Things I Learned About Pricing – Product Camp Berlin 201410 Things I Learned About Pricing – Product Camp Berlin 2014
10 Things I Learned About Pricing – Product Camp Berlin 2014Lars Trieloff
 
The DNA of Marketing
The DNA of MarketingThe DNA of Marketing
The DNA of MarketingLars Trieloff
 
Cross community campaigns with CQ5
Cross community campaigns with CQ5Cross community campaigns with CQ5
Cross community campaigns with CQ5Lars Trieloff
 
Mastering the customer engagement ecosystem with CQ5
Mastering the customer engagement ecosystem with CQ5Mastering the customer engagement ecosystem with CQ5
Mastering the customer engagement ecosystem with CQ5Lars Trieloff
 
Advanced Collaboration And Beyond
Advanced Collaboration And BeyondAdvanced Collaboration And Beyond
Advanced Collaboration And BeyondLars Trieloff
 
Getting Into The Flow With CQ DAM
Getting Into The Flow With CQ DAMGetting Into The Flow With CQ DAM
Getting Into The Flow With CQ DAMLars Trieloff
 
The Zero Bullshit Architecture
The Zero Bullshit ArchitectureThe Zero Bullshit Architecture
The Zero Bullshit ArchitectureLars Trieloff
 
Creating Value In Social Networking
Creating Value In Social NetworkingCreating Value In Social Networking
Creating Value In Social NetworkingLars Trieloff
 
5 Ways To Build Asset Centric Applications
5 Ways To Build Asset Centric Applications5 Ways To Build Asset Centric Applications
5 Ways To Build Asset Centric ApplicationsLars Trieloff
 
REST and AJAX Reconciled
REST and AJAX ReconciledREST and AJAX Reconciled
REST and AJAX ReconciledLars Trieloff
 
µjax in 30 minutes (for Stockholm)
µjax in 30 minutes (for Stockholm)µjax in 30 minutes (for Stockholm)
µjax in 30 minutes (for Stockholm)Lars Trieloff
 
Living in a multiligual world: Internationalization for Web 2.0 Applications
Living in a multiligual world: Internationalization for Web 2.0 ApplicationsLiving in a multiligual world: Internationalization for Web 2.0 Applications
Living in a multiligual world: Internationalization for Web 2.0 ApplicationsLars Trieloff
 
Mindquarry For Cocoon Users
Mindquarry For Cocoon UsersMindquarry For Cocoon Users
Mindquarry For Cocoon UsersLars Trieloff
 

Mais de Lars Trieloff (15)

Putting the F in FaaS: Functional Compositional Patterns in a Serverless World
Putting the F in FaaS: Functional Compositional Patterns in a Serverless WorldPutting the F in FaaS: Functional Compositional Patterns in a Serverless World
Putting the F in FaaS: Functional Compositional Patterns in a Serverless World
 
10 Things I Learned About Pricing – Product Camp Berlin 2014
10 Things I Learned About Pricing – Product Camp Berlin 201410 Things I Learned About Pricing – Product Camp Berlin 2014
10 Things I Learned About Pricing – Product Camp Berlin 2014
 
The DNA of Marketing
The DNA of MarketingThe DNA of Marketing
The DNA of Marketing
 
Cross community campaigns with CQ5
Cross community campaigns with CQ5Cross community campaigns with CQ5
Cross community campaigns with CQ5
 
Mastering the customer engagement ecosystem with CQ5
Mastering the customer engagement ecosystem with CQ5Mastering the customer engagement ecosystem with CQ5
Mastering the customer engagement ecosystem with CQ5
 
Advanced Collaboration And Beyond
Advanced Collaboration And BeyondAdvanced Collaboration And Beyond
Advanced Collaboration And Beyond
 
Getting Into The Flow With CQ DAM
Getting Into The Flow With CQ DAMGetting Into The Flow With CQ DAM
Getting Into The Flow With CQ DAM
 
The Zero Bullshit Architecture
The Zero Bullshit ArchitectureThe Zero Bullshit Architecture
The Zero Bullshit Architecture
 
Creating Value In Social Networking
Creating Value In Social NetworkingCreating Value In Social Networking
Creating Value In Social Networking
 
5 Ways To Build Asset Centric Applications
5 Ways To Build Asset Centric Applications5 Ways To Build Asset Centric Applications
5 Ways To Build Asset Centric Applications
 
REST and AJAX Reconciled
REST and AJAX ReconciledREST and AJAX Reconciled
REST and AJAX Reconciled
 
µjax in 30 minutes (for Stockholm)
µjax in 30 minutes (for Stockholm)µjax in 30 minutes (for Stockholm)
µjax in 30 minutes (for Stockholm)
 
µjax in 30 minutes
µjax in 30 minutesµjax in 30 minutes
µjax in 30 minutes
 
Living in a multiligual world: Internationalization for Web 2.0 Applications
Living in a multiligual world: Internationalization for Web 2.0 ApplicationsLiving in a multiligual world: Internationalization for Web 2.0 Applications
Living in a multiligual world: Internationalization for Web 2.0 Applications
 
Mindquarry For Cocoon Users
Mindquarry For Cocoon UsersMindquarry For Cocoon Users
Mindquarry For Cocoon Users
 

Último

Fields in Java and Kotlin and what to expect.pptx
Fields in Java and Kotlin and what to expect.pptxFields in Java and Kotlin and what to expect.pptx
Fields in Java and Kotlin and what to expect.pptxJoão Esperancinha
 
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmony
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine HarmonyLeveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmony
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmonyelliciumsolutionspun
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeNeo4j
 
Sales Territory Management: A Definitive Guide to Expand Sales Coverage
Sales Territory Management: A Definitive Guide to Expand Sales CoverageSales Territory Management: A Definitive Guide to Expand Sales Coverage
Sales Territory Management: A Definitive Guide to Expand Sales CoverageDista
 
eAuditor Audits & Inspections - conduct field inspections
eAuditor Audits & Inspections - conduct field inspectionseAuditor Audits & Inspections - conduct field inspections
eAuditor Audits & Inspections - conduct field inspectionsNirav Modi
 
Top Software Development Trends in 2024
Top Software Development Trends in  2024Top Software Development Trends in  2024
Top Software Development Trends in 2024Mind IT Systems
 
Enterprise Document Management System - Qualityze Inc
Enterprise Document Management System - Qualityze IncEnterprise Document Management System - Qualityze Inc
Enterprise Document Management System - Qualityze Incrobinwilliams8624
 
Webinar_050417_LeClair12345666777889.ppt
Webinar_050417_LeClair12345666777889.pptWebinar_050417_LeClair12345666777889.ppt
Webinar_050417_LeClair12345666777889.pptkinjal48
 
AI Embracing Every Shade of Human Beauty
AI Embracing Every Shade of Human BeautyAI Embracing Every Shade of Human Beauty
AI Embracing Every Shade of Human BeautyRaymond Okyere-Forson
 
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...Jaydeep Chhasatia
 
Kawika Technologies pvt ltd Software Development Company in Trivandrum
Kawika Technologies pvt ltd Software Development Company in TrivandrumKawika Technologies pvt ltd Software Development Company in Trivandrum
Kawika Technologies pvt ltd Software Development Company in TrivandrumKawika Technologies
 
How Does the Epitome of Spyware Differ from Other Malicious Software?
How Does the Epitome of Spyware Differ from Other Malicious Software?How Does the Epitome of Spyware Differ from Other Malicious Software?
How Does the Epitome of Spyware Differ from Other Malicious Software?AmeliaSmith90
 
Streamlining Your Application Builds with Cloud Native Buildpacks
Streamlining Your Application Builds  with Cloud Native BuildpacksStreamlining Your Application Builds  with Cloud Native Buildpacks
Streamlining Your Application Builds with Cloud Native BuildpacksVish Abrams
 
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/MLBig Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/MLAlluxio, Inc.
 
OpenChain Webinar: Universal CVSS Calculator
OpenChain Webinar: Universal CVSS CalculatorOpenChain Webinar: Universal CVSS Calculator
OpenChain Webinar: Universal CVSS CalculatorShane Coughlan
 
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdf
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdfARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdf
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdfTobias Schneck
 
Watermarking in Source Code: Applications and Security Challenges
Watermarking in Source Code: Applications and Security ChallengesWatermarking in Source Code: Applications and Security Challenges
Watermarking in Source Code: Applications and Security ChallengesShyamsundar Das
 
Introduction-to-Software-Development-Outsourcing.pptx
Introduction-to-Software-Development-Outsourcing.pptxIntroduction-to-Software-Development-Outsourcing.pptx
Introduction-to-Software-Development-Outsourcing.pptxIntelliSource Technologies
 
Generative AI for Cybersecurity - EC-Council
Generative AI for Cybersecurity - EC-CouncilGenerative AI for Cybersecurity - EC-Council
Generative AI for Cybersecurity - EC-CouncilVICTOR MAESTRE RAMIREZ
 

Último (20)

Fields in Java and Kotlin and what to expect.pptx
Fields in Java and Kotlin and what to expect.pptxFields in Java and Kotlin and what to expect.pptx
Fields in Java and Kotlin and what to expect.pptx
 
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmony
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine HarmonyLeveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmony
Leveraging DxSherpa's Generative AI Services to Unlock Human-Machine Harmony
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG time
 
Sales Territory Management: A Definitive Guide to Expand Sales Coverage
Sales Territory Management: A Definitive Guide to Expand Sales CoverageSales Territory Management: A Definitive Guide to Expand Sales Coverage
Sales Territory Management: A Definitive Guide to Expand Sales Coverage
 
eAuditor Audits & Inspections - conduct field inspections
eAuditor Audits & Inspections - conduct field inspectionseAuditor Audits & Inspections - conduct field inspections
eAuditor Audits & Inspections - conduct field inspections
 
Top Software Development Trends in 2024
Top Software Development Trends in  2024Top Software Development Trends in  2024
Top Software Development Trends in 2024
 
Enterprise Document Management System - Qualityze Inc
Enterprise Document Management System - Qualityze IncEnterprise Document Management System - Qualityze Inc
Enterprise Document Management System - Qualityze Inc
 
Webinar_050417_LeClair12345666777889.ppt
Webinar_050417_LeClair12345666777889.pptWebinar_050417_LeClair12345666777889.ppt
Webinar_050417_LeClair12345666777889.ppt
 
AI Embracing Every Shade of Human Beauty
AI Embracing Every Shade of Human BeautyAI Embracing Every Shade of Human Beauty
AI Embracing Every Shade of Human Beauty
 
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...
Optimizing Business Potential: A Guide to Outsourcing Engineering Services in...
 
Kawika Technologies pvt ltd Software Development Company in Trivandrum
Kawika Technologies pvt ltd Software Development Company in TrivandrumKawika Technologies pvt ltd Software Development Company in Trivandrum
Kawika Technologies pvt ltd Software Development Company in Trivandrum
 
How Does the Epitome of Spyware Differ from Other Malicious Software?
How Does the Epitome of Spyware Differ from Other Malicious Software?How Does the Epitome of Spyware Differ from Other Malicious Software?
How Does the Epitome of Spyware Differ from Other Malicious Software?
 
Streamlining Your Application Builds with Cloud Native Buildpacks
Streamlining Your Application Builds  with Cloud Native BuildpacksStreamlining Your Application Builds  with Cloud Native Buildpacks
Streamlining Your Application Builds with Cloud Native Buildpacks
 
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/MLBig Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/ML
 
OpenChain Webinar: Universal CVSS Calculator
OpenChain Webinar: Universal CVSS CalculatorOpenChain Webinar: Universal CVSS Calculator
OpenChain Webinar: Universal CVSS Calculator
 
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdf
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdfARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdf
ARM Talk @ Rejekts - Will ARM be the new Mainstream in our Data Centers_.pdf
 
Watermarking in Source Code: Applications and Security Challenges
Watermarking in Source Code: Applications and Security ChallengesWatermarking in Source Code: Applications and Security Challenges
Watermarking in Source Code: Applications and Security Challenges
 
Introduction-to-Software-Development-Outsourcing.pptx
Introduction-to-Software-Development-Outsourcing.pptxIntroduction-to-Software-Development-Outsourcing.pptx
Introduction-to-Software-Development-Outsourcing.pptx
 
Salesforce AI Associate Certification.pptx
Salesforce AI Associate Certification.pptxSalesforce AI Associate Certification.pptx
Salesforce AI Associate Certification.pptx
 
Generative AI for Cybersecurity - EC-Council
Generative AI for Cybersecurity - EC-CouncilGenerative AI for Cybersecurity - EC-Council
Generative AI for Cybersecurity - EC-Council
 

Big Data Berlin – Automating Decisions is the Next Frontier for Big Data

  • 1. LARS TRIELOFF – BLUE YONDER – I’M @TRIELOFF ON TWITTER AUTOMATING DECISIONS – THE NEXT FRONTIER FOR BIG DATA
  • 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 IS USED Potential Use Marketing Finance Everyone Else SOURCE: OWN, POTENTIALLY BIASED OBSERVATIONS
  • 6. Better Decisions Faster Data More Data THREE APPROACHES
  • 9. BUT WHAT ABOUT BETTER DECISIONS?
  • 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 MADE Human Decisions Business Rules No Decision, Decision-by-default
  • 22. BUSINESS RULES = PROGRAMMING • 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”
  • 23. 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
  • 24. 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
  • 25. 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
  • 26. Better decisions through predictive applications
  • 27. HOW PREDICTIVE APPLICATIONS WORK COLLECT & STORE ANALYZE CORRELATIONS BUILD DECISION MODEL DECIDE & TEST OPTIMIZE
  • 28. WHY TEST? “Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’” –RANDALL MUNROE
  • 29. STORY TIME (Not safe for vegetarians)
  • 30. THE GROUND BEEF DILEMMA
  • 31. THE GROUND BEEF DILEMMA Yesterday Today Tomorrow Next Delivery Next Day In Stock Demand
  • 32. 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.
  • 33. CHALLENGE #1 ACCURATELY PREDICT DEMAND
  • 34. CHALLENGE #2 AUTOMATE REPLENISHMENT COLLECT STOCK AND SALES PREDICT DEMAND TRADE OFF COSTS CREATE ORDERS IN ERP SYSTEM OPTIMIZE & REPEAT