0
Teaching Computers to Think Like
Decision Makers
Mark Zangari
CEO, Quantellia LLC
San Francisco University
May 23, 2014
Ma...
Robert McNamara
• Secretary of Defense (1961-68)
• Ford Motor Co. (1946-61)
• USAF “Statistical Control” (1943-46)
Data System
Analysis
Decision
http://sunsite.berkeley.edu/FindingAids/dynaweb/calher/jvac/figures/j12EB-644A.jpg
http://www.whatswrongwiththeworld.net/o...
http://sunsite.berkeley.edu/FindingAids/dynaweb/calher/jvac/figures/j12EB-644A.jpg
http://www.whatswrongwiththeworld.net/o...
Data
Instrumented
Code / Sensors
Data
Management
Analytics
Presentation
System
Analysis
Decision
Data
Instrumented
Code / ...
Units Cost Per Unit
1-100 $12.00
101-500 $10.00
501-1000 $9.00
1001-10000 $7.50
10001+ $6.00
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7...
Even with all the data you need,
and clear visualizations, making good
decisions is still very hard to do.
Why?
Data
Syste...
Because:
a) Humans are not good at running
Systems in their heads.
b) Unlike Data, there is little
mainstream computerized...
Build a Computable Systems Model Visually
• Attributes
• Dependencies
The Product Manager’s Model
Identify Model Elements:
• Outcomes / Goals
“What are we trying to achieve?”
• Levers
“What can we control?”
• Externals
“...
Identify Dependencies
Dependencies
“How are A, B and C related to X, Y and Z?”
Intermediates
When outcomes are not directl...
Quantify Dependencies
Dependencies
“How are A, B and C related to X, Y and Z?”
Build a Computable Systems Model Visually
0...
Quantify Dependencies
Dependencies
“How are A, B and C related to X, Y and Z?”
Build a Computable Systems Model Visually
M...
While humans are not good at processing systems models,
we are much better at analyzing and designing them. This
leads to ...
The Product Manager’s Decision:
a) How many units do I order from
the manufacturer?
b) What retail price to I charge?
c) H...
The Product Manager’s Decision:
Most decisions are made not just
to optimize outcomes, but to manage
risk.
A bi-product of...
Some Interesting Structural Characteristics of Models…
Build a Computable Systems Model Visually
Feedback Loop
… Lead to Important Behaviors.
Equilibrium and Transient States
• Real-life systems, even if they are stable, are
not stat...
Data System
Analysis
Decision
Big Data / Business Intelligence:
Data
System Analysis
Decision
Decision Intelligence
Analyze system
Build model
Integrate Data to
specify dependencies
Sear...
Decision Intelligence:
• Gives decision makers what they need most, and they cannot get
from Business Intelligence: help a...
New Kinds of Visualizations
• Familiar data visualizations still have their place in
Decision Intelligence, but note that ...
Call to Action:
Now that the “Big Data” problem is mostly solved,
we need invest our talents to return to the “Big
Picture...
Download a free trial
of World Modeler
from
www.quantellia.com
Mark Zangari
CEO, Quantellia LLC
San Francisco University
M...
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Teaching Computers to Think Like Decision Makers: the next revolution in the data sciences

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“Big Data” and analytics have revolutionized "micro-decisions", those myriads of tiny decisions that follow a similar pattern, are made frequently, but each of which has relatively low risk and low value (e.g. the cross-sell to “things we might also like” that almost every e-commerce checkout page displays using our purchase history and possibly other data). By contrast, "macro-decisions" are less frequent, but higher-stakes. They are more complex and also need to take risk into account. Software support for macro decisions today is usually provided as “Business Intelligence” or “Dashboards”, both of which typically derive aggregate statistics from existing data, and present these in ways that are “meaningful” and “insightful” to humans. However, once the data has been presented, the synthesis and evaluation tasks at the core of the decision-making process are left to the human decision-maker. This is despite a large and well-accepted body of research (most notably by Kahneman and Tversky) clearly demonstrating that humans systematically lack the ability to perform such tasks accurately. A significant and as-yet untapped opportunity therefore exists for augmenting the existing BI paradigm with new data science techniques developed to assist decision makers.

This presentation introduces the “Decision Intelligence” approach which transfers the decision-related inference tasks from human intelligence to machine intelligence. The approach includes a structured framework for decomposing decisions so they can be represented as computable models. Using simulation and optimization techniques, these models generate data sets to which existing BI tools can be applied, giving decision makers the ability to generate data from “possible futures” and to evaluate decision and their outcomes in familiar, existing environments.

Mark is a leader in innovative research, software development and services delivery, and business development in the academic and commercial sectors for over two decades. He is co-founder and CEO of Quantellia, a leading Data Science innovator and developer of the award-winning World Modeler software. From 2000-2010, he held the position of CTO at Spatial info (now Synchronoss) where he co-founded the company’s US operations, and led technical operations. Prior to this, he was the architect of StatPlay, software developed jointly at La Trobe University and the University of Melbourne that explored how computer visualizations affect people’s innate abilities to perform statistical reasoning. Mark has also worked as a systems engineer for EDS (now HP) and Anderson Consulting (now Accenture). In 1994-5, he held a British Council Post Graduate Bursary at the University of Cambridge in the UK and from 1996-2000 was an Honorary Fellow at the University of Melbourne. He is the author of numerous publications and has frequently made speaking appearances.

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Transcript of "Teaching Computers to Think Like Decision Makers: the next revolution in the data sciences"

  1. 1. Teaching Computers to Think Like Decision Makers Mark Zangari CEO, Quantellia LLC San Francisco University May 23, 2014 Mark.zangari@quantellia.com 303 717 4221 Copyright © 2014 Quantellia LLC. All Rights Reserved.
  2. 2. Robert McNamara • Secretary of Defense (1961-68) • Ford Motor Co. (1946-61) • USAF “Statistical Control” (1943-46)
  3. 3. Data System Analysis Decision
  4. 4. http://sunsite.berkeley.edu/FindingAids/dynaweb/calher/jvac/figures/j12EB-644A.jpg http://www.whatswrongwiththeworld.net/office-interior-1940s.jpg http://www.biega.com/bcbphotos/biega-engineer.jpg Data Acquisition… Data Mining… Analytics… Data
  5. 5. http://sunsite.berkeley.edu/FindingAids/dynaweb/calher/jvac/figures/j12EB-644A.jpg http://www.whatswrongwiththeworld.net/office-interior-1940s.jpg http://www.biega.com/bcbphotos/biega-engineer.jpg Data Acquisition… Data Mining… Analytics… Data
  6. 6. Data Instrumented Code / Sensors Data Management Analytics Presentation System Analysis Decision Data Instrumented Code / Sensors Data Management Analytics Presentation Demarcation between automated (computer-centric) and manual (human-centric) information processing. Gap between computer and human bridged by Data Visualization.
  7. 7. Units Cost Per Unit 1-100 $12.00 101-500 $10.00 501-1000 $9.00 1001-10000 $7.50 10001+ $6.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 SalesVolume/MarketSize Retail Price Base Demand 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 $3,500 $4,000 $4,500 $5,000 $5,500 $6,000 $6,500 $7,000 $7,500 $8,000 $8,500 $9,000 $9,500 $10,000 $10,500 $11,000 $11,500 $11,750 Pct.IncreaseinDemand Marketing Spend Marketing Driven Demand Uplift Manufacturing Unit Cost by Volume The Product Manager’s Decision: To maximize profit… a) How many units do I order from the manufacturer? b) What retail price do I charge? c) How much of my profit do I re-invest in marketing? (Mkt Size = 50,000)
  8. 8. Even with all the data you need, and clear visualizations, making good decisions is still very hard to do. Why? Data System Analysis Decision 
  9. 9. Because: a) Humans are not good at running Systems in their heads. b) Unlike Data, there is little mainstream computerized support for modeling and analyzing Systems.
  10. 10. Build a Computable Systems Model Visually • Attributes • Dependencies The Product Manager’s Model
  11. 11. Identify Model Elements: • Outcomes / Goals “What are we trying to achieve?” • Levers “What can we control?” • Externals “What affects our outcomes that we can’t control?” Build a Computable Systems Model Visually
  12. 12. Identify Dependencies Dependencies “How are A, B and C related to X, Y and Z?” Intermediates When outcomes are not directly related to levers or externals. Build a Computable Systems Model Visually
  13. 13. Quantify Dependencies Dependencies “How are A, B and C related to X, Y and Z?” Build a Computable Systems Model Visually 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 SalesVolume/MarketSize Retail Price Base Demand Expressions External Data Sources / AnalyticsSketch Graphs
  14. 14. Quantify Dependencies Dependencies “How are A, B and C related to X, Y and Z?” Build a Computable Systems Model Visually Models also provide a systematic way to assess the impact of uncertainty, sensitivity, precision and risk on the decisions they support.
  15. 15. While humans are not good at processing systems models, we are much better at analyzing and designing them. This leads to a natural human-computer partnership. Build a Computable Systems Model Visually
  16. 16. The Product Manager’s Decision: a) How many units do I order from the manufacturer? b) What retail price to I charge? c) How much of my profit do I re-invest in marketing? … to maximize profit? But wait, there’s more. 38,000 $15 7%
  17. 17. The Product Manager’s Decision: Most decisions are made not just to optimize outcomes, but to manage risk. A bi-product of the optimization search is data that can be used to: • Assess sensitivity of the desired outcome to particular levers and externals. • Assess downside risk associated with each positive outcome. Opportunity envelope Risk envelope Gradient shows sensitivity
  18. 18. Some Interesting Structural Characteristics of Models… Build a Computable Systems Model Visually Feedback Loop
  19. 19. … Lead to Important Behaviors. Equilibrium and Transient States • Real-life systems, even if they are stable, are not static, but in a steady state or equilibrium. • When such systems are perturbed, they oscillate, or experience a transient. • Effective decision makers need to be able to understand the effects their decisions will have both on the transient phase and on the new equilibrium. Build a Computable Systems Model Visually Equilibrium with price at $12 Price raised to $15 New equilibrium with price at $15 Transient phase
  20. 20. Data System Analysis Decision Big Data / Business Intelligence:
  21. 21. Data System Analysis Decision Decision Intelligence Analyze system Build model Integrate Data to specify dependencies Search the space of decision levers and externals to determine optimal outcomes and risk profiles Gap between computer and human bridged by Data Visualization of Decision Variables, not the Input Variables as before.
  22. 22. Decision Intelligence: • Gives decision makers what they need most, and they cannot get from Business Intelligence: help answering the question “If I make this decision, then what will be the likely results, and what risks am I exposed to?” • Provides a framework for the most effective use of existing data and analytics tools in a given problem. • Provides visual and other artifacts that assure team alignment and act as a form of “institutional memory”
  23. 23. New Kinds of Visualizations • Familiar data visualizations still have their place in Decision Intelligence, but note that the “axes” are now more meaningful to decision makers as each represents an “actionable” quantity. • In addition, there is a powerful role for new dynamic System Visualizations.
  24. 24. Call to Action: Now that the “Big Data” problem is mostly solved, we need invest our talents to return to the “Big Picture”. We must develop software tools and methodologies that integrate data and systems to produce the kinds of insights real users really need.
  25. 25. Download a free trial of World Modeler from www.quantellia.com Mark Zangari CEO, Quantellia LLC San Francisco University May 23, 2014 Mark.zangari@quantellia.com 303 717 4221 Copyright © 2014 Quantellia LLC. All Rights Reserved.
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