1. Information Systems in Organizations – Decision Making
February 24, 2016 1

2. Mintzberg’s five 5 organizational parts2

3. Types of Organizations
An organization is an administrative and functional structure where people work toward a specific goal.
Understanding the organization’s IT needs requires a good understanding of its administrative and functional structure.
Hierarchical
Flat
Matrix
Holacratic
Other
Source:
Source: 3

4. IS & Hierarchical Organizational structure. 4

5. IS & Hierarchical Organizational structure. 5

6. Administrative Information Systems
Transaction Processing Systems (TPS)
Basic business system that serves the operational level (including analysts) in organizations
Capture & process data generated during day-to-day activities
Office Automation Systems (OAS)
Systems designed to help office workers in doing their job.
Decision Support Systems (DSS)
Systems designed to support middle managers and business professionals during the decision-making process
Executive Information Systems (EIS) or Executive Support Systems (ESS)
Specialized DSS that help senior level executives make decisions.
GDSS: computer-based systems that facilitate solving of unstructured problems by set of decision makers 6

7. Organization & IS: another view
Types of Information Systems: - Transaction Processing Systems - Office Automation Systems - Knowledge Worker Systems - Management Information Systems - Decision Support Systems - Executive Information Systems
Top Management Middle Management Lower Management Operational workers
Office workers
Office workers
Questions
Office workers
Office workers
Knowledge workers

8. Decision Making process
Simon’s decision-making process model
Intelligence
Design
Choice
(Implementation)
Simon, H. (1955), A Behavioral Model of Rational Choice, Quarterly Journal of Economics, vol. 69, 99–188
Newell, A., and Simon, H. A. (1972). Human problem solving Englewood Cliffs, Prentice-Hall, New Jersey.
Drucker Peter (1954), The Practice of Management, Harper & Brothers, New York 8

9. Intelligence Phase Scan the environment for a problem.
Data source
Scan the environment for a problem.
Determine if problem is real, important enough, solvable
Determine if problem within their scope of influence?
Fully define the problem by gathering more information.
Scan Environment for problem to be solved or decision to be made
Organizational IS & external data
Problem ? No
END
Yes
Problem within scope of influence? No
END
Yes
Gather more information about the problem
Internal & External data

10. Design Phase Develop a model of the problem. Verify model.
Determine type of model.
Verify model.
Develop and analyze potential solutions.
Develop a model of problem to be solved
Verify that the model is accurate
Develop potential solutions

11. Choice Phase Evaluate solutions and select the solution to implement.
More detailed analysis of selected solution might be needed.
Verify initial conditions.
Analyze proposed solution against real-world constraints.
Questions

12. 12

13. DSS structure Systems designed to help middle managers make decisions
User Interface
Systems designed to help middle managers make decisions
Major components
Data management subsystem
Internal and external data sources
Analysis subsystem
Typically mathematical in nature
User interface
How the people interact with the DSS
Data visualization is the key
Text
Graphs
Charts
Analysis
- Sensitivity Analysis - What-if Analysis
- Goal-seeking Analysis
Data-driven tools
-> Data mining
-> OLAP*
Data Management
- Transactional Data - Data warehouse - Business partners data - Economic data 13
* OLAP: OnLine Analytical Processing

14. DSS Analysis Tools
Simulation is used to examine proposed solutions and their impact
Sensitivity analysis
Determine how changes in one part of the model influence other parts of the model
What-if analysis
Manipulate variables to see what would happen in given scenarios
Goal-seeking analysis
Work backward from desired outcome 14
Determine monthly payment given various interest rates.
Works backward from a given monthly payment to determine various loans that would give that payment.

15. Executive Information Systems
Specialized DSS that supports senior level executives within the organization
Most EISs offer the following capabilities:
Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information
Drill-down – enables users to get details, and details of details, of information
Slice-and-dice – looks at information from different perspectives
Digital dashboards are common features 15

16. Artificial Intelligence (AI) systems
Common categories of AI systems:
Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems
Neural Network – attempts to emulate the way the human brain works
Analyses large quantities of info to establish patterns and characteristics in situations where logic or rules are unknown
Uses Fuzzy logic – a mathematical method of handling imprecise or subjective information
Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem
Intelligent agent – special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users
PBS Report on AI in today’s world 16 16

17. Expert Systems
Artificial Intelligence systems that codify human expertise in a computer system
Main goal is to transfer knowledge from one person to another
Wide range of subject areas
Medical diagnosis
Computer purchasing
Finance
Accounting ( )
Knowledge engineer elicits the expertise from the expert and encodes it in the expert system
System engineer: IT professional who develops AI inference engine and other components of the Expert System. 17

18. Expert Systems Components
Knowledge base: database of the expertise, often in IF THEN rules.
Inference engine: derives recommendations from knowledge base and problem-specific data
User interface: controls the dialog between the user and the system
Explanation system: Explain the how and why of recommendations
User
IF family is albatross AND color is white
THEN bird is laysan albatross.
IF family is albatross AND color is dark
THEN bird is black footed albatross
Example of rules
Domain Expert
User Interface
Expertise
System Engineer
Knowledge Engineer
Inference Engine
Encoded expertise
Knowledge base
Explanation System
- Knowledge engineer codify the human expert’s expertise into the systems’ knowledge base. - System engineer is the IT professional who develop the user interface, the inference engine, and the explanation system. 18

19. Expert Systems: Pros and Cons
More reliable than humans, incorporating expertise from many sources.
Able to deduce rules that are not apparent, even to experts
Capable of being extended, as the system is applied and knowledge grows
Built in high-level computer languages (called Shell – e.g. CLIPS, JESS, DROOLS) requiring few IT skills 19

20. Expert Systems: Pros and Cons
Often difficult to know a priori if experts who devise the rules really do know all they claim to.
Experts may sabotage the system with false information, or withhold information, particularly if their jobs are threatened.
Rule following is not the best approach for all situations.
Built in high-level computer languages (and “Shells” – e.g. CLIPS, JESS, DROOLS) that require few IT skills 20

21. Summary Questions
Notes
Compare Middle management and lower management tasks in terms of their structure.
2) Compare Middle management and lower management tasks in terms of their repetitiveness.
3) What is the difference between GDSS and DSS in terms of their target users?
What is the difference between Decision Support Systems (DSS) and Executive Information Systems (EIS) in terms of their target users.
Give an example of TPS.
(a) What are the major components in a DSS? (b) What is the function of each?
What is an Expert System? What are the main components of an Expert system? What is a knowledge engineer? 21

22. Mintzberg’s 5 organizational parts
Operating core
Those who perform the basic work related directly to the production of products and services.
Strategic apex
Charged with ensuring that the organization serve its mission in an effective way, and also that it serve the needs of those people who control or otherwise have power over the organization.
Middle line
Managers who stand in a direct line relationship between the strategic apex and the operating core.
Techostructure
The analysts who serve the organization by affecting the work of others. They may design it, plan it, change it, or train the people who do it, but they do not do it themselves. Examples: engineers, accountants, planners, researchers, etc.
Support staff
The specialists who provide support to the organization outside of its operating workflow. Examples: food service, busing, legal consel, etc.

23. References
Drucker Peter (1954), The Practice of Management, Harper & Brothers, New York
Hendry, J. (1997). Mintzberg’s theory of organization structure: a critical assessment and extension. Retrieved from content/uploads/2013/07/Mintzbergs-Theory-of-Organization- Structure.pdf on June 3, 2015.
Herbert S. (1955), A Behavioral Model of Rational Choice, Quarterly Journal of Economics, vol. 69, 99–188
Mintzberg, H. (1980). Structure in 5’s: A synthesis of the research on organization design. Management Science, 26(3), Available at: MgmtSci.pdf
Newell, A., and Simon, H. A. (1972). Human problem solving Englewood Cliffs, Prentice-Hall, New Jersey.