Decision Support Systems For Business Intelligence
    by Vicki L. Sauter

 
 
Chapter 2: Decision Making


Decision Making in Action
Crime-Fighting by Computer Widens Scope
Questions for Helping you Make a Decision
IBM's Business Intelligence Page
Moving into Real Time
Mystery of Dying Industry Giants
Persuasive Technologies
Financial Executives Use their ABC's
Finding the Decision Making Sweet Spot
Strategic Knowledge Management
You Can’t Be a Wimp—Make the Tough Calls


Business Intelligence
Big Data: Lessons From Earlier Revolutions
Are We All Being Fooled by Big Data?
A Brief History of Business Intelligence
Admiral Mike Mullen
Business Analytics: Numbers and Nuance
Critical Success Factors for Business Intelligence Systems
Defining Business Analytics and its Impact on Organizational Decision-Making
Business Intelligence in Action from Information Builders
History of Business Intelligence
What is Business Intelligence
Business Intelligence Focus Shifts From Tactical to Strategic
Deal or No Deal: Hormones Impact Business
End-User Defined Data Mashup
Deliver Process-Driven Business Intelligence With a Balanced BI Platform
Successful BI
Business Intelligence Forum
Business Intelligence Network
Follow the Data (go to page 10)
Make Better Decisions
Corporate-wide customer analytics strategy doesn’t start with data, tools
Ganthead project management -- BI portal
The resource for business intelligence
TechWeb’s Intelligent Enterprise BI Channel
Key Issues for Business Intelligence and Performance Management Initiatives, 2008
Key Metrics for Measuring BI
Knowledge Management Resources
Business Intelligence Platform Usage and Quality Dynamics, 2008
Gartner's Business Intelligence and Performance Management Framework
Magic Quadrant for Business Intelligence Platforms
Beyond Data Warehousing: What's Next in Business Intelligence
Obtaining Business Intelligence on the Internet
Pervasive Business Intelligence
Staffing for Intelligence
Smarter Systems Help Busy Doctors Remember
Worst Practices in Business Intelligence
How to Compete on Analytics
Getting the Most out of BI in a Tough Economy
Solutions-Driven Marketing
Analytics: The Multi-Tasking Magician (page 2, page 3, and page 4)
'The BI Survey 7' Details Purchase Practices, Ranks Loyalty by Brand
BI by Accenture
BI from Oracle ... more
Business Intelligence Forum
Business Intelligence Network
Ganthead project management -- BI portal
A Prescription for Timely BI
Risk Management and Decision Support
The resource for business intelligence
TechWeb’s Intelligent Enterprise Content Management Channel
TechWeb’s Business Intelligence Pipeline
Teradata's Blogs
Terror Queues
Roundup of Business Intelligence and Information Management Research

BI in the Presidential Election Five Thirty Eight: Nate Silver's Political Calculus
538.blog on Election Night
How Obama's data crunchers helped him win
Business Intelligence explained
Business Intelligence Blog
Business Intelligence -- Oracle
BI Questions Blog
BI Review Magazine Current Issue
BI This Week
BI-Nerd.com
Blog: Robert S. Seiner
Boulder BI Brain Trust Blog
Business Intelligence Advantages
Business Intelligence for Business People
Business Intelligence Guru Online
Business Intelligence Network, Latest Blog Postings
Business Intelligence Network, Latest News
Business Intelligence News by Marcus Borba
Business Intelligence Pipeline
Chris Webb's BI Blog
Cyril on Business Intelligence
Daryl's Data Quality Blog
Data and Process Advantage Blog
Databases, Structures, and the Damn Data Itself
datadoodle
DM Review Online Current Issue
Hub Designs Blog
Intelligent Enterprise
Monash University Business Intelligence Blog
OCDQ Blog Feed
THE BI Blog
The Business Intelligence Blog
The Business Intelligence Blog
Wouter on Business Intelligence

Business Objects Blogs
Business Objects Community
Business Objects Support for Crystal Reports and Xcelsius
Business Objects Webinar Series
BusinessObjects Enterprise XI 3.1 - Articles
BusinessObjects Enterprise XI Release 2 - Articles
BusinessObjects Metadata Management XI 3.0 - Articles
SAP Subscriptions Home


Feasibility
Political Feasibility: ANOTHER STATE COMPUTER PROJECT FAILS
California has recently declared another costly computer project a failure, indicating a need for new techniques in developing technology projects. For at least the fifth time this decade, California's state government has spent millions of dollars on a failed computer project. This project, the Statewide Automated Welfare System-Technical Architecture, would have linked four welfare networks to allow welfare offices in different counties to communicate with each other. California's string of failures can be attributed mainly to a difficulty in adapting to change. Legislators are often removed from technology, and therefore may not realize the importance of these projects. Political power may also complicate the projects, as local elected officials may protest sacrificing their individual systems to a central design. To prevent further failures, the state plans to incorporate business solutions such as dividing projects into smaller tasks, choosing experienced managers, hiring independent consultants to oversee each phase, and involving in every design the potential users of the project. (Los Angeles Times 07/12/99)
TechWeb’s Intelligent Enterprise Content Management Channel
Decision Making and Problem Solving
More about Herb Simon
James March wrote in 1978, "Prescriptive theories of choice are dedicated to perfecting the intelligence of human action by imagining that action stems from reason and by improving the technology of decision. Descriptive theories of choice are dedicated to perfecting the understanding of human action by imagining that action makes sense. Not all behavior makes sense; some of it is unreasonable. Not all decision technology is intelligent; some of it is foolish." (p. 604) -- from March, J. G. "Bounded Rationality, Ambiguity, and the Engineering of Choice", Bell Journal of Economics, Vol. 9, 1978, pp. 587-608. "New business procedures would then be analogous to new mutations in nature. Of a number of procedures, none of which can be shown either at the time or subsequently to be truly rational, some may supplant others because they do in fact lead to better results. Thus while they may have originated by accident, it would not be by accident that they are still used. For this reason, if an economist finds a procedure widely established in fact, he ought to regard it with more respect than he would be inclined to give in the light of his own analytic method." (Roy F. Harrod, 1939, Oxford EP) .... from The Maximization Debates.
US firms put social values before big profits
Why Risk Analysis Fails


Decision Making
Brain study maps mechanics of decision-making
Distinguishing Still from Luck
Folk Wisdom Saves Lives
How to make choosing easier The Interaction Between Knowledge Codification and Knowledge-Sharing Networks
Minority Rules: Scientists Discover Tipping Point for the Spread of Ideas
From Can DSS Impact Decision Outcomes?
Nobel Laureate Herbert Simon (1965) argued we need to understand the thought process that computerized decision aids will support if we are to create effective support systems. Our understanding of decision and thought processes remains incomplete and we need to be especially cautious in assessing when and how a DSS will be used prior to its design and implementation. Effective decision oriented analysis and design helps insure that a DSS positively impacts decision outcomes.
Picture this: better decisions through data visualization
10 curses of the analytical thinker
What Was I Thinking?


Intuition, Brainstorming, and Decision Making
Brainstorming Software
Computer Creativity Machine Simulates the Human Brain
David Brooks argues against relying solely on analytics in his interview with Steven Colbert
Forecasting in Conflicts: How to Predict What Your Opponent Will Do
Helping Students Bridge their Rational and Intuitive Minds
In Battle, Hunches Prove to Be Valuable
Inspiration for Brainstorming
Is the Evidence on Forecasting Conflicts Based on Proper Science?
Jumping to Conclusions
Predicting the Future without a Crystal Ball
Software Helps Develop Hunches
To-Do List: Shop, Pay Bills, Organize Brain
Tool for Thought
The Brain for brainstorming
Tracing the Spark of Creative Problem-Solving
The Eureka Hunt: Where in our brains do insights come from?" by Jonah Lehrer)
"Moody Computers, " Interactive Week (02/26/01) Vol. 8, No. 8, P. 47;
Steinert-Threlkeld, Tom (as seen in Tech News, Volume 3, Issue 172: Monday, March 5, 2001):

     Martin Minsky, co-founder of the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology and author of "Society of Mind" and its forthcoming sequel, "The Emotion Machine," argues that emotions are merely another way in which human beings think, rather than a process independent of or antithetical to thinking. His central idea, he says, "is that each of the major emotions is quite different. They have different management organizations for how you are thinking you will proceed." Minsky contends that common-sense reasoning is what allows us to handle and manipulate these different emotions, to choose which emotion is best for handling which situation, even though we are not aware when each type of thinking is occurring. This is also, he says, what separates machine thinking from human thinking. Machines are not able to see the same piece of knowledge represented in multiple ways. Minsky says, "You have to build a system that looks at two representations, two expressions or two data structures, and quickly says in what ways are they similar and what ways are they different. Then another knowledge base says which kinds of differences are important for which kind of preference." He contends that such ways of thinking could, for example, benefit search engines, allowing software to consider how to organize and execute a search based on what human users might want rather than relying on keywords and algorithms. The ability to approach a problem from many different ways and then solve it is how Minsky defines intelligence and is what he means by an intelligent, emotional machine. He dismisses the fear that "emotional" machines could somehow become irrational, as an emotional human being can become irrational and commit an act that may endanger or harm others, because that again reflects the human bias that emotions and thinking are two entirely different things.


Knowledge Management
Humans vs. Computers, Again. But There's Help for Our Side
Software to Look for Experts Among Your Friends
KMNetwork and the WWW Virtual Library on Knowledge Management
Harvard Business School Working Knowledge Report
Global Development Research Center KM Portal
APQC Knowledge Management
Global Community for Knowledge
Knowledge Management networks
Knowledge Management Organizations and Gateways
Lawrence Lessig’s Messianic Manifesto: A Doomsday Look at Cyberspace
APQC Knowledge Management
Global Community for Knowledge
Global Development Research Center KM Portal
Harvard Business School Working Knowledge Report
KMNetwork and the WWW Virtual Library on Knowledge
Knowledge Management Knowledge Base
Knowledge Management Networks


Group Decision Making
Computer-Based Delphi Processes
Distributed Team Decision Making

 

   Page Owner: Professor Sauter (Vicki.Sauter AT umsl.edu)