1. CHAPTER 4 ANALYTICS, DECISION SUPPORT, AND ARTIFICIAL INTELLIGENCE
Brainpower for Your Business

2. Opening Case: Online Learning
Notice the increase in online learning and the decrease in traditional enrollments.

3. Phases of Decision Making
Intelligence
Design
Choice
Implementation

4. Types of Decisions Structured decision Semi-Structured decision
Nonstructured decision

5. What Job Do I Take?

6. Types of Decisions
Recurring decision
Nonrecurring (ad hoc) decision

7. Types of Decisions You Face
EASIEST
MOST DIFFICULT

8. Decision Support Systems
Decision support system (DSS)
Helps you analyze, but you must know how to solve the problem, and how to use the results of the analysis

9. Components of a DSS Model management component
Data management component
User interface management component

10. Components of a DSS

11. Geographic Information Systems
Geographic information system (GIS)
Spatial information is any information in map form
Used to analyze information, generate business intelligence, and make decisions

12. Google Earth as a GIS

13. DATA-MINING TOOLS AND MODELS
Business need IT-based analytics tools
Databases and DBMSs
Query-and-reporting tools
Multidimensional analysis tools
Digital dashboards
Statistical tools
GISs
Specialized analytics
Artificial intelligence
Our focus

14. Data-Mining: Predictive Analytics
highly computational data-mining technology that uses information and business intelligence to build a predictive model for a given business application
Insurance, retail, healthcare, travel, financial services, CRM, SCM, credit scoring, etc

15. Data-Mining: Predictive Analytics Example
Prediction goal
What customers are most likely to respond to a social media campaign within 30 days by purchasing at least 2 products in the advertised product line?
Prediction indicators
Frequency of purchases
Proximity of date of last purchase
Presence on Facebook and Twitter
Number of multiple-product purchases

16. Data-Mining: Text Analytics
uses statistical, AI, and linguistic technologies to convert textual information into structured information
Gaylord Hotels uses text analytics to make sense of customer satisfaction surveys

17. Data-Mining: Endless Analytics
Web analytics – understanding and optimizing Web page usage
Search engine optimization (SEO) – improving the visibility of Web site using tags and key terms
HR analytics – analysis of human resource and talent management data
Marketing analytics – analysis of marketing-related data to improve product placement, marketing mix, etc

18. Data-Mining: Endless Analytics
CRM analytics – analysis of CRM data to improve sales force automation, customer service, and support
Social media analytics – analysis of social media data to better understand customer/organization interaction dynamics
Mobile analytics – analysis of data related to the use of mobile devices to support mobile computing and mobile e-commerce (m-commerce)

19. Artificial Intelligence
Artificial intelligence (AI)
Types of AI systems used in business
Expert systems
Neural networks
Genetic algorithms
Agent-based technologies
AI systems deliver the conclusion (rather than helping you analyze the options)

20. Expert Systems Expert (knowledge-based) system Used for
Diagnostic problems (what’s wrong?)
Prescriptive problems (what to do?)

21. Expert System Example: Traffic Light

22. Expert System: Components
Information Types
Problem facts
Domain expertise
“Why?” information
People
Domain expert
Knowledge engineer
Knowledge worker
IT Components
Knowledge acquisition
Knowledge base
Inference engine
User interface
Explanation module

23. Expert System: Components

24. What Expert Systems Can and Can’t Do
An expert system can
Reduce errors
Improve customer service
Reduce cost
An expert system can’t
Use common sense
Automate all processes

25. Neural Networks and Fuzzy Logic
Neural network (NN)
(or artificial neural network (ANN))
Learns through training
Finds patterns

26. The Layers of a Neural Network

27. Neural Networks Can…
Learn and adjust to new circumstances on their own
Take part in massive parallel processing
Function without complete information
Cope with huge volumes of information
Analyze nonlinear relationships

28. Fuzzy Logic Fuzzy logic
a mathematical method of handling imprecise or subjective information
Used to make ambiguous information such as “short” usable in computer systems
Applications
Google’s search engine
Washing machines
Antilock breaks

29. Genetic Algorithms Genetic algorithm (GA)
Takes thousands or even millions of possible solutions, combining and recombining them until it finds the optimal solution
Work in environments where no model of how to find the right solution exists

30. Genetic Algorithm: Examples
Staples – determine optimal package design characteristics
Boeing – design aircraft parts such as fan blades
Many retailers – better manage inventory and optimize display areas

31. Agent-Based Technologies
Intelligent Agents
Multi-Agent Systems

32. Intelligent Agents Intelligent agent
Information agents or shopping/buyer agents
Monitoring-and-surveillance agents
User or personal agents
Data-mining agents

33. Multi-Agent Systems
Biomimicry
Swarm (collective) Intelligence