1. MBA 669 Special Topics: IT-enabled organizational Forms Dave Salisbury salisbury@udayton.edusalisbury@udayton.edu (email) http://www.davesalisbury.com/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. IS&T Investment Profit Revenue Costs + – + – Why We Invest in IS&T Management Support & Decision Systems – +

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

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 Cognitive Science Applications Artificial Intelligence Artificial Intelligence Robotics Applications Robotics Applications Natural Interface 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

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

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

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

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