MBA 669 Special Topics: IT-enabled organizational Forms

1. MBA 669Special Topics: IT-enabled organizational Forms Dave Salisbury salisbury@udayton.edu (email) http://www.davesalisbury.com/ (web site)

2. This Week’s Fun Stuff • Codification of knowledge, expertise and procedures • IT and the control of information/decision-making • IT and the standardization and homogenization of organizations and industries • Issues surrounding the codification of expertise and decision-making

3. Why We Invest in IS&T Revenue + + + ManagementSupport & DecisionSystems IS&TInvestment Profit – – – Costs

4. IT and locus of control • Some cases used to push decision-making to lower levels • Some cases used to get control • What is the effect of advanced IT in organizations? • Liberating or constraining? • Autonomy or top-down control?

5. Isomorphism and homogenization • Infrastructure • Standards • Systems • Codified procedures

6. Simon & the rational person • Humans can be rational actors, their rationality is bounded by their limitations • Humans tend to satisfice, or settle on the first acceptable option, rather optimizing • Information stored in computers can increase human rationality if accessible when needed • The central problem is not how to organize to produce efficiently, but how to organize to make decisions (i.e. process information)

7. IT provides assistance to... • Communicate and/or distribute knowledge • Collaborate with other workers • Routinize procedures • Capture and codify knowledge • Create knowledge

8. Two key issues • Uncertainty • Lack of information • Ambiguity • Lack of structure

9. Online analytical processing • Enables interactive examination/manipulation of detailed & consolidated data from many perspectives • Analyze complex relationships to discover patterns, trends, and exception conditions in real time • Consolidation • The aggregation of data. • From simple roll-ups to complex groupings of interrelated data • Drill-Down • Display detail data that comprise consolidated data • Slicing and Dicing • The ability to look at the database from different viewpoints. • When performed along a time axis, helps analyze trends and find patterns

10. Important Decision Support Systems Analytical Models What If-Analysis Sensitivity Analysis Goal-Seeking Analysis Optimization Analysis Decision support systems

11. Data mining for decision support • Software analyzes vast amounts of data • Attempts to discover patterns, trends, & correlations • May perform regression, decision tree, neural network, cluster detection, or market basket analysis

12. Models as decision making aids • A model (in decision making) is a simplified representation of reality. • The benefits of modeling in decision making are: • Cost of virtual experimentation is much lower • Simulated compression of time. • Manipulating the model is much easier • The cost of mistakes are much lower • Modeling for “what-ifs” • Analysis and comparison of a large number alternatives • Models enhance and reinforce learning

13. Artificial Intelligence Cognitive Science Applications Robotics Applications Natural Interface Applications • Expert Systems • Fuzzy Logic • Genetic Algorithms • Neural Networks • Visual Perceptions • Locomotion • Navigation • Tactility • Natural Language • Speech Recognition • Multisensory Interface • Virtual Reality Artificial intelligence

14. Neural Networks AI Application Areas in Business Fuzzy Logic Systems Genetic Algorithms Virtual Reality Intelligent Agents Expert Systems AI application areas in business

15. The Expert System Expert Advice Knowledge Base User Interface Programs Inference Engine Program Workstation User Expert System Development Knowledge Engineering Knowledge Acquisition Program Expert and/or Knowledge Engineer Workstation Expert systems

16. Major Application Categories of Expert Systems Decision Management Diagnostic/Troubleshooting Maintenance/Scheduling Design/Configuration Selection/Classification Process Monitoring/Control Expert system applications

17. Why have expert systems? • Standardize procedures and their application throughout organization • Share codified procedures more readily • Protect against loss of expertise • Preserve expertise for more important tasks • Replace expertise with systems

18. Codification & leveraging processes • Focus on business processes rather than divisions or functions • Processes tend to cross divisions and functions • IT as enabler of process focus • Choosing what goes to people and what goes to IT • Re-engineering focus

19. Standardization • Standardization as diminishing freedom or as enhancing reliability? • Does structure constrain or enable? • What impact does it have on codification of knowledge (see more on this Tuesday)? • Good or bad? Why or why not?

20. Widespread analytics • Heavy use of modeling and optimization routines • Enterprise approach (can’t be piecemeal to get the big benefits) • Ever more sophisticated tools • Again, most of this was not doable until the advent of sophisticated IT • Still need to apply expertise, experience and intuition

21. Diffusion of responsibility • The “myth” of technology neutrality that enables blame to be passed • “The computer did it” • “That’s what the model came up with” • “The computer requires it” • Use of technology implies control by technology • At once empowered and dominated • Dependent on it to complete tasks

22. Lost expertise • Codification detaches knowledge from context • Experts are no longer so, and considered expendable • Technology replaces bodies • This effect is moving up the corporate ladder • Lack of flexibility in applying the rules