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Summary Decision Analytics
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Summary of Decision Analytics for MA2 Business Engineering at the VUB.
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Decision AnalyticsIntroduction:
Course contents:
This course aims at providing a hands-on introduction to four versatile analytical techniques
that are used for managerial decision making at different business levels:
- Strategical
- Tactical
- Operational
4 main topics:
• Chapter 1: Modelling
• Chapter 2: Sensitivity analysis
• Chapter 3: Searching for good solutions
• Chapter 4: Taking uncertainty into account
- The first chapter provides a general introduction to spreadsheet modelling for business
applications
o Emphasis on project evaluation
o Emphasis on cost benefit analysis
o Using indicators such as Net Present Value (NPV), Internal Rate of Return (IRR)
and payback period.
- Different forms of sensitivity and scenario analysis are discussed in the second chapter
o Using a macro extending the built-in features of Excel
o Using the goal-seek function and optimization
- The third chapter looks into optimization of decision making
o Using spreadsheet models
- The fourth chapter of the course discusses how uncertainty or risk may be taken into
account in a model
o By way of Monte Carlo simulation
o Using random number generation following a number of practical and
theoretical distributions
o Analysis of simulation results for decision making.
1
,General learning outcomes:
• Four general objectives of this course, theory and exercises combined:
o Gain knowledge and understanding:
§ Definitions of meanings of concepts
§ Knowing tools and models
o Advance your systematic thinking:
§ Approaching reality as a system
o Advance your logical thinking:
§ Deducing insight from facts and data
§ If-then-else approach
o Advance your abstract thinking:
§ Making abstraction of specifics
§ Reducing problems to their essence
§ Seeing the bigger picture
• Systematic, logical, and abstract thinking together constitute the scientific method
• They are instruments or tools:
o To observe and analyse reality
o To build models
o And as such to acquire knowledge and solve problems
• Which have a very broad use:
o Are being used across different fields of study
o By organizations and businesses in professional life
o By individuals in their personal life
Specific learning outcomes:
• Advanced use of spreadsheets for business case evaluation
• Problem analysis
• Model building
• Sensitivity analysis
• Optimization
• Monte Carlo simulation
• Practical interpretation of results
• Writing executive summary, computer-assisted presentation, and defence of case
2
,Assignment:
• Evaluation is fully based on a practical assignment, applying the taught spreadsheet
techniques to some self-chosen business case, and answering a number of relevant
management questions
• The project is to be submitted as an executive summary, together with the supporting
computer file, and has to be presented orally with computer assistance, introducing
the case, technical highlights, and motivated conclusions
Elements of grading:
• Quality of the analysis
• Quality of the report
• Quality of the presentation, including discussion of the case with the jury
3
, Chapter 1: Modelling
Learning outcomes:
At the end of this chapter, students should be able to:
• Explain what a model is
• Discuss how a model may be used for various business applications
• Understand the challenges of developing models
• Explain what cash-flow analysis is
• Discuss how a spreadsheet software may be used for building models and solving
business cases
• Enlist steps and principles of building good models Detect opportunities for applying
models
Outline:
1. Modelling
2. Cash-flow analysis
3. Building models in Excel
1. Modelling:
Introduction:
• Data-driven decision making:
o Fact- or evidence-based vs. intuitive decision making
o “In today’s complex economical society companies have to rely on quantitative
information to make daily decisions in a rational and optimal manner”
§ Six Sigma
§ Competing on analytics: The science of winning
§ Profit-driven business analytics
• Available information vs. required information:
o Available information may be transformed or used to obtain or estimate the
required information
o How to transform or turn input data into output data? various approaches
discussed in this course:
§ Data? = Input data
§ Information? = Output data
§ ...
§ Knowledge?
§ Insight?
§ Wisdom
4
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