With the virtual learning lab Probabilistic Investment Analysis you will learn:
- the benefits of a probabilistic approach for investment analysis,
- a range of methodologies and innovative tools to execute such an analysis pragmatically,
- how to incorporate the results in decision making.
This Virtual Learning Lab consists of pre-programmed live virtual expert lectures, online self-study materials (split up in blocks) and optional check ins.
Target audience: decision analysts, project managers, project economists, financial analysts, technical project staff.
Price: € 950 ( ~ US$ 1100), this is the nominal price. Early bird and other discounts will be available.
Time period: 1 April – 28 June 2019
Total time to be spent by participant over this period ~ 20 hours (7 hours per month); this includes the time for online work as well as the virtual engagements.
The five virtual expert lectures and three optional check-in sessions are reguarly spaced across this period. Time in the day is 4 PM GMT.
Virtual Expert Lectures
Lecture 1: Investment decision making and risk
- The unhappy marriage of discount rate and ‘risk’
- What are alternative approaches for addressing ‘risk’ when making investment decisions
Henk Krijnen founded NavIncerta after completing a career of 35 years with Shell which took him to Indonesia, Thailand, the United States and the Netherlands. During his last five years in Shell’s corporate strategy department he played a pivotal role in establishing new approaches for risk and scenario analysis within the company.
Prof Reidar Bratvold
Lecture 2: The state of the application of probabilistic methods in industry
- How well have probabilistic methods been adopted in industry and what could be the barriers for implementation
- How do results of investment decisions stack up against prior assessments
Lecture 3: Getting to grips with uncertainty
- Why is it so difficult to handle uncertainty comfortably
- How can we incorporate uncertainty in decision making and what are the key benefits
Reidar Bratvold is Professor of Investment and Decision Analysis at the University of Stavanger. His research interests include decision analysis, project valuation, portfolio analysis, real-option valuation, and behavioral challenges in decision-making. Prior to academia, he spent 15 years in the industry in various technical and management roles. He is a co-author of the SPE book Making Good Decisions. Professor Bratvold has three times served as an SPE Distinguished Lecturer.
Lecture 4: Implementing change when introducing new methodologies
- How to overcome resistance to change in your organization
- How to encourage a new set of decision making behaviors in an organization that is comfortable with the existing approach
Lecture 5: Engaging with senior leaders
- How to help decision makers to recognize that embracing and understanding uncertainty wil improve their decision making
- How to shift the decision making conversation from advocacy to curiosity and understanding
Frank Koch, retired from Chevron, specializes in decision-maker coaching and the development of decision-making organizational capability. He has over 35 years of experience in decision analysis and related disciplines. Frank is a founding fellow of the Society of Decision Professionals and is a past president. Along with colleagues Larry Neal and Brian Putt, Frank won the 2010 Decision Analysis Society Practice Award.
Part 1: The basics
- Why bother: Why would you take a probabilistic approach?
- Statistical concepts: Refresher of some basic statistical concepts
- Range and probability assessment: How to assess ranges and probabilities – a brief overview (more detail in the risk quantification course or virtual learning lab)
Part 2: Tools
- Tornados: A visual to show the key risks and uncertainties
- Decision Trees: Structuring decision problems and communication
- Monte Carlo simulation demystified: using spreadsheets only!
Part 3: Analysis
- Analytical methods: Probabilistics on a mathematical basis including the novel DeltaLogN method
- Tornado based probabilistics: Three ways to generate an NPV distribution from a tornado
- Decision tree based probabilistics: Combining a decision tree with tornados
Part 4: Decision making