Book contents
- Frontmatter
- Contents
- SECTION 1 GETTING ORIENTED
- SECTION 2 HARVESTING INTELLIGENCE
- SECTION 3 LEVERAGING DYNAMIC ANALYSIS
- 8 Controlled Simulation Analysis
- 9 Scenario Generation and Optimization
- 10 Visualizing Complex Analytical Dynamics
- SECTION 4 ADVANCED AUTOMATION AND INTERFACING
- Glossary of Key Terms
- Appendix – Shortcut (Hot Key) Reference
- Index
8 - Controlled Simulation Analysis
from SECTION 3 - LEVERAGING DYNAMIC ANALYSIS
Published online by Cambridge University Press: 06 July 2010
- Frontmatter
- Contents
- SECTION 1 GETTING ORIENTED
- SECTION 2 HARVESTING INTELLIGENCE
- SECTION 3 LEVERAGING DYNAMIC ANALYSIS
- 8 Controlled Simulation Analysis
- 9 Scenario Generation and Optimization
- 10 Visualizing Complex Analytical Dynamics
- SECTION 4 ADVANCED AUTOMATION AND INTERFACING
- Glossary of Key Terms
- Appendix – Shortcut (Hot Key) Reference
- Index
Summary
We've talked about how difficult it can be to find or construct an optimal solution to real-world management problems – where we're faced with nonlinear relationships and constraints that make it difficult to predict how specific decisions work together to impact performance. But in a certain way we've continued to simplify these real-world problems. There may be some shortcomings in the approaches we take to finding solutions, but what about the approaches we use to come up with the problems that we're trying to solve?
When we create a mathematical form to represent reality so that we can ultimately use analytics to provide a solution that might apply to reality, are we missing something? And how much does that impact the real-world applicability and effectiveness of the solution we develop?
These are critical questions for managers who want additional support in their decision making. Project managers don't want suggestions that come out of inappropriate assumptions.
What steps can we take to help ensure that we are, in fact, providing appropriate characterizations of reality when we structure problems and make sense of solutions? Although there are a lot of good places to start, one obvious place is an attempt to take into account the uncertainty associated with just about everything that takes place in the real world. In the problems we've examined in the last few chapters, we really haven't dealt much with this issue; instead we've assumed that certain elements of our decision context are relatively fixed or constant, such as:
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- Information
- Excel Basics to BlackbeltAn Accelerated Guide to Decision Support Designs, pp. 183 - 208Publisher: Cambridge University PressPrint publication year: 2008