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L11C11: Improving Decision Making and Managing Artificial Intelligence,…
L11C11: Improving Decision Making and Managing Artificial Intelligence
Decision Making and Information Systems
Business Value of Improved Decision Making
Possible to measure value of improved decision making
Decisions made at all levels of the firm
Some are common, routine, and numerous
Although value of improving any single decision may be small, improving hundreds of thousands of “small” decisions adds up to large annual value for the business
The Decision-Making Process
Intelligence
Discovering, identifying, and understanding the problems occurring in the organization
Design
Identifying and exploring various solutions
Choice
Choosing among solution alternatives
Implementation
Making chosen alternative work and monitoring how well solution is working
High-Velocity Automated Decision Making
Humans eliminated
Decision-making process captured by computer algorithms
Predefined range of acceptable solutions
Decisions made faster than managers can monitor and control
Quality
Accuracy
Comprehensiveness
Fairness
Speed (efficiency)
Coherence
Due process
Types of Decisions
Structured
Repetitive and routine
Involve definite procedure for handling them so do not have to be treated as new
Unstructured
Decision maker must provide judgment to solve problem
Novel, important, nonroutine
No well-understood or agreed-upon procedure for making them
Semi-structured
Only part of problem has clear-cut answer provided by accepted procedure
Business Intelligence in the Enterprise
What Is Business Intelligence?
Infrastructure for managing data from business environment
Warehousing
Integrating
Reporting
Analyzing
Hadoop, OLAP, analytics
Products defined by technology vendors and consulting firms
The Business Intelligence Environment
6 Elements
Data from business environment
Business intelligence infrastructure
Business analytics toolset
Managerial users and methods
Delivery platform
MSS, DSS, ESS
User Interface
Business Intelligence and Analytics Capabilities
Production reports
Parameterized reports
Dashboards/scorecards
Ad-hoc query/search/report creation
Drill-down
Forecasts, scenarios, models
Linear forecasting, what-if scenario analysis, data analysis
Uses
Predictive Analytics
Extracts information from data to predict future trends and behavior patterns
Responses to direct marketing campaigns
Best potential customers for credit cards
At-risk customers
Customer response to price changes and new services
Uses statistical analytics, data mining, historical data; assumptions of future conditions
Accuracies range from 65 to 90 percent
Operational Intelligence and Analytics
Operational intelligence
Day-to-day monitoring of business decisions and activity
Real-time monitoring
Schneider National truckload logistics services provider
Data developed from sensors in trucks, trains, industrial systems
The Internet of Things (IoT ) providing huge streams of data from connected sensors and devices
Location Analytics and GIS
Location analytics
Big data analytics that uses location data from mobile phones, sensors, and maps
GIS – Geographic information systems
Help decision makers visualize problems with mapping
Tie location data about resources to map
Support for Semi-Structured Decisions
Decision-support systems (DSS)
What-if analysis
Sensitivity analysis
Backward sensitivity analysis
Pivot tables: Spreadsheet function for multidimensional analysis
Intensive modeling techniques
BI delivery platform for “super-users” who want to create own reports, use more sophisticated analytics and models
Artificial Intelligence Techniques
Evolution of AI
Big data databases
Reduction in the price of processors
Expansion in capacity of processors
Refinement and explosion of algorithms
Large investments in IT and AI
Progress in image recognition and natural language
Siri, Alexa, facial recognition
Major Types of AI Techniques and How Do They Benefit Organizations
Expert systems
Capture human expertise in a limited domain of knowledge
Express expertise as a set of rules in a software system
Knowledge base
Inference engine
Machine learning
Computers improving performance by using algorithms to learn patterns from data and examples
Neural networks
Find patterns and relationships in very large amounts of data
Sensoring and processing nodes
“Deep Learning” neural networks
Natural language processing
Software that can process voice or text commands using natural human language
Computer vision systems
Emulate human visual system to view and extract information from real-world images
Robotics
Design and use of movable machines that can substitute for humans
Intelligent Agents
Software programs that imitate humans and perform tasks on command
The agent uses a limited built-in or learned knowledge base
Accomplish tasks or make decisions on the user’s behalf, e.g. chatbots finding cheap fares, routing calls in a call center
Benjamin