MIS 300 Management Information Systems

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MIS 300 Management Information Systems

• Model Based Decision Support
• Expert Systems/AI (Chap 7)

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Overview

• OR/MS Video
• Modeling and Model Examples
• Expert Systems and AI
• HW5,6 Help

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Recall Decision Support Systems
Other CBIS
Internal and External data
Data Management
Model Management
Knowledge Management
User Interface
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Models

• Simplified representation or abstraction of
  reality.
• Capture essence of system without unnecessary
  details
• Models tailored for specific types of problems
• Models help us understand the world
• Prediction (What if?)
• Optimization (Whats best?)

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Descriptive vs. Prescriptive Models

• Descriptive Model
• Describes a system in terms of parameters and
  variables
• If we change some input parameter, what will
  happen to our output performance measure?

• Prescriptive Model
• Suggests good or optimal solutions
• Also made up of parameters and variables
• Searches over many possible solutions to find
  best solution (in some sense)

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Basic Modeling Concepts
Inputs
relationships
Outputs
roles in model
constraints
Decision Variables
relationships
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A Simple Modeling Process
Create model
forces detailed examination and thought about a
problem

• structures our thinking
• must articulate our assumptions, preconceived
  notions

Validate model - Does it mimic reality well
enough?
Modify model
Use the model to support decision making

• Searching for general insights
• Specific numeric answers

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Exercising the ModelThings we might do with a
model

• Create graphic representation of model parameter
  relationships (visualization)
• Example GolfClubs_Isken.xls
• Find values of decision variables that minimize
  or maximize the outputs (optimization)
• Example SchedulingDSS.xls
• How do input and/or decision variable values
  affect outputs (sensitivity analysis)?
• Example GreatThreads_Isken.xls

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Examples of Specific Questions we might want to
answer

• How does time spent waiting in line to order a
  Whopper change if we add another staffed cash
  register between 4p-6p?
• Does the proposed assembly line change increase
  throughput and reduce work in process?
• How does response time change in our computer
  network if we increase bandwidth by 30?
• What is the likelihood that this project will
  have a negative NPV?
• How do different organ allocation policies affect
  the death rates among people on organ transplant
  lists?

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What is OR/MS?Operations Research/Management
Science
Hyperlink

• Application of information technology for
  informed decision making.
• Build models to help understand complex systems
  comprised of people, technology and processes.
• Related to applied mathematics, MIS, computer
  science, economics, industrial engineering,
  systems engineering
• Applied broadly in many industries

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A Few OR/MS Applications

• Vehicle routing
• Inventory control
• Scheduling
• People
• Machines
• Capacity planning
• Decision analysis
• Medical
• investment

• Financial modeling
• Design and analysis of telecommunications systems
• Call centers
• Military tactics/strategy
• Healthcare policy

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The OR/MS Toolbox

• Statistics
• Computer simulation
• Queuing models
• Forecasting
• Decision analysis
• Optimization

• Computer programming
• Spreadsheets
• Databases
• IT
• Business knowledge

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Why Spreadsheets?

• Spreadsheets are the de facto standard platform
  for modeling and analysis in business today
• The language of business
• Excel has rich set of modeling and analysis tools
• Many sophisticated add-ins available
• Spreadsheet based modeling wave in many business
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• Can tie with other products such as DBMS

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The Traveling Salesman Problem Revisited

• Find minimum cost route through N cities
• Visit each city exactly once, return home
• N! possible tours
• Classic optimization problem with many variants
• Applications in vehicle routing (e.g. Fed Ex),
  computer chip manufacturing, robot control

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TSP is a Big Problem
How long would it take just to list all the
possible routes and calculate their distance?
Days to Evaluate is based on a fast computer
capable of evaluate one million routes per
SECOND!
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Solving The TSP
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Overview of Computer Simulation

• A technique for conducting what if? experiments
  with a computer on a model of a management
  system.
• Imitation of operation of real world process or
  system over time using a computer
• generates an artificial history of the process
• statistical inferences can be drawn from analysis
  of this artificial history

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The Bookstore Problem

• Bookstore purchases books at start of term to
  sell

Return unsold Books _at_ this price.

• Demand is uncertain

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The Bookstore Problem

• Decision Problem How many books to buy to
  maximize profit? (DECISION VARIABLE)
• Assume just going to place one order at beginning
  of term.
• What makes this problem hard?
• See MIS300_Walton.xls for spreadsheet simulation
  approach.

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Bookstore ExampleUsing a Spreadsheet Simulation
Model
(1) Inputs
Given these
Predict these
(2) Simulation Model
A computer program or set of Excel formulas
(3) Outputs
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Why Simulation?

• Enables study and experimentation with the
  internal interactions of a complex system
• Often easier, cheaper to experiment with model
  than real system
• Knowledge gained in designing simulation
• Assessing sensitivity to input variables
• Teaching and/or training tool
• Experiment with new designs and/or policies

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The Scheduling Problem

• Staff works 5 consecutive days
• Can start any day of the week
• Ex T, W, Th, F, Sa

• Objective
• Minimize total amount of staff needed
• By Finding
• Number of employees starting their 5-day
  workstretch each day of the week
• Subject to constraints
• Daily staffing requirements are met

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Solving Optimization Problems with the Excel
Solver

• Solver is Excel add-in (Frontline Systems, Inc.)
• Pretty sophisticated optimization program
• Minimize or Maximize some cell
• By manipulating values in decision variable cells
• Subject to constraints (on the decision
  variables) in other cells

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The Solver Interface
Our model of the scheduling problem
Solver
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About Optimization Problems

• Can be very, very, very, very hard to solve
  optimally
• Very good solutions to very difficult problems
  are found routinely using computerized
• Mathematical models
• Intelligent heuristics smart rules of thumb
• Many, many, many business applications
• Staff scheduling (airlines, hospitals, call
  centers, etc.)
• Routing (Fed Ex, supply chain)
• Production scheduling
• Financial porfolio planning
• Computer/telecommunications network planning

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Artificial Intelligence

• People, procedures, hardware, software, data, and
  knowledge needed to develop computer systems and
  machines that demonstrate characteristics of
  intelligence

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Branches of AI/Machine Learning

• Expert Systems
• Robotics
• Vision Systems
• Natural Language Processing
• Learning Systems
• Neural Networks

Example Games
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Conceptual Model of AI
A broad term
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Intelligent Behavior

• The ability to learn from experience and apply
  knowledge acquired from experience, handle
  complex situations, solve problems when important
  information is missing, determine what is
  important, and react quickly and correctly to a
  new situation

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Natural and Artificial Intelligence
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Components of an Expert System
How did you reach that conclusion?
The thinking part
Facts, rules, relationships
Can be very difficult to acquire knowledge
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Rules for a Credit Application
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Neural Networks

• Train network with historical data
• Use network to make predictions on new data

From Alter, S., Information Systems A
Management Perspective, 3rd Ed., Addison-Wesley,
1999.
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Fuzzy Logic
From Alter, S., Information Systems A
Management Perspective, 3rd Ed., Addison-Wesley,
1999.
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Case Based Reasoning
http//www.mathemedics.com/
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Bots or Intelligent Agents

• Software based robots that perform specified
  tasks on behalf of the user with some degree of
  autonomy
• Different degrees of intelligence
• search engines
• user profile based web watchers
• adaptive, learning agents
• Email agents, network security, e-commerce
  (procurement), support of desktop applications
• http//www.salesmountain.com/
• http//www.watchguard.com/
• Agents may collaborate with other agents