Management Decision Support

Overview for Today

• Exam coming up next week…• Draft of project due Fri Apr 10…• Management & Decision Making

– Why decision making is hard

• Models to support decision making• Technologies to support decision making

So Just What is a DSS?

• Interactive systems that help decision makers use data and models to solve semi- & un-structured problems– A counter example: Towers of Hanoi– What are examples of these types of problems?

• Used by middle & upper level management since 1970’s for analytical & quantitative decisions

Difficulty of Decision Making

• ALL managerial jobs require decision making skills

• People are BAD at decision making (study from Gettys)

Difficulty of Decision Making

The Need for Decision Support

• Impossible to make decisions without information– What’s the relationship between quantity of information

and decision quality? – Moore’s law also relevant…

• New pressures/needs for improved decision making– What are these new pressures?– What are new needs of managers today?– What factors create these new pressures?

(From our environ, business partners, customers)

Modeling & Decision Making

• Modeling is one way to aid decision making• Generic tool, can be implemented w/o IT• The business case for modeling:

– Why do/should managers use models?– What are some benefits of modeling?– Are there any drawbacks to modeling?

Four Types of Models

• Mental: description of how you think about a situation, includes beliefs, assumptions, relationships, used to generate descriptions or make predictions, ex: “better to promote old workers than younger ones” - this is often a first step in modeling

• Scale: least abstract, physical replica of system, used for designing cars, planes, production lines, Bermuda…

Four Types of Models

• Analog: behaves like real system, doesn’t look like it, ex: org charts, topo maps, blueprints

Four Types of Models

• Mathematical: complex modeling of weather patterns, economic trends, physical systems, etc– Eisenhower vs. Stevenson, 1952– Bush vs. Gore in 2000; 2004– Airplane design

More Mathematical Models

Decision Support Technologies

• Information systems to support decision making:– Decision Support Systems– Group Decision Support Systems– Artificial Intelligence– Expert Systems

• Each provides a different set of tools to aid the decision maker

• Each is geared to a specific situation/context• Goal: match the appropriate tech with needs of the

situation

Characteristics of a DSS

• Typical Feature Set:– Often based on mathematical models (Mgmt 102)– Integrates human judgment & data warehousing– Is adaptable by the user over time– Models provide sensitivity analysis– Utilizes models to promote learning – especially when

you can’t “play” with reality… `

DSS Examples

• GM Healthcare program– Spent $4.5B in 2002, includes 127 providers– $1,360 per vehicle for healthcare & pensions

• Uses OLAP & DSS to help slow the growth of premiums– Compares diagnosis with treatments– Appropriate drug choices, generics, etc.– Correlate absenteeism with medical conditions– Allows ROI calculations for health care providers…

• “Good cop, Bad cop” system in LA

Group Decision Support Systems

• Similar to DSS with additional functionality:– Teams of people work together to solve complex

problems – Teams can be real or “virtual”– Provides tool set for group process such as: anonymity,

brainstorming, voting, ranking, categorizing, group consensus

– Tools help keep group coordinated/focused on task

• Examples of uses include:– Strategic planning– Support groups for victims of AIDS, rape…

Artificial Intelligence

• Attempts to represent human thought process with machines– Able to sense data, process it, draw its own

conclusions, act on those conclusions• Examples:

– Automatic categorization useful with GDSS applications: UA AI Categorizer

– “The Turing Test” (Alan Turing 1912-1954)

– IBM’s Watson, Deep Blue, Deep Jr.

AI Characteristics

• Capabilities:– Learn from past experience– “Sense Making” ambiguous / contradictory information– Quickly and successfully responding to a new situation– Infer rules from observed data– Use reasoning, logic as opposed to numeric formulas…

• Benefits– Increase speed & consistency of problem solving,

especially when data are incomplete, inconsistent – Helps in handling information overload by summarizing

or interpreting information

Expert Systems

• Allows employees to make better, faster decisions – Mimic human experts– Contains expertise from multiple individuals– Can support or replace decision makers– Can explain its recommendations– “Software IDs visible symptoms” story

• Some drawbacks– Expertise is hard to extract from people– Have very narrow fields of application– Construction is costly– Can be lack of trust by end users

Expert Systems

• Dept of the Treasury detects money laundering– Banks report cash xacts > $10,000 (200,000/week)– Don’t have the staff to examine each xact– ES detect suspicious transactions and changes in

patterns; 100 cases/year since 1993• State Street Bank and Trust Company

– Audits daily and month-end data against corresp GL account balance, highlighting exceptions

– Increased the productivity of the auditors as well as the quality of error detection

Automation of Mgmt’s Job

• Decision making involves specific tasks that can take a long time to perform– Automation can potentially save time, increase

consistency, enable better decisions– Can decision responsibilities be completely

automated? (top mgmt? middle mgmt? lower mgmt?)

– Decisions/tasks that can’t be automated?– What are advantages? Disadvantages?

Important Concepts to Know

• Management & Decision Making– Why decision making is hard

• Models to aid decision making– Mental, Analog, Scale, Mathematical Models

• Types of Decision Support Technologies– DSS, GDSS, AI, ES

For Next Time…

• No cases this time around• Exam Review on Monday

– Go through your notes– Re-do case studies– Make questions– Ask during class– Re-read “Exam Study Hints” on webpage