BUS460 Operational Risk Management

• Topics

  The everyday running a company is often what separates success from failure. Innovations, as well as well established companies, even when well funded, can fail if operations are not well planned and carried out. A major issue when planning operations is the handling of uncertainty; Short-term uncertainty in demand, price, transit times or the weather, as well as longer-term uncertainties from regulation, competition or other external or internal factors. Without uncertainty, planning and management would be rather simple. Some uncertainty can be handled financially, but most cannot. The following topics will be discussed:

  • The relationship between strategic, tactical and operational decisions when handling uncertainty.
  • Our intuitive understanding of uncertainty from behavioral psychology.
  • What makes a decision (or the principles behind it) right? How can we say that an approach is incorrect?
  • Why what-if analysis  (scenario analysis)  does not work.
  • The concepts of real options, regret and other alternatives to utility theory.
  • The dynamics of decisions; what is known when?
  • The role of luck in decision-making.
  • The IQ of hindsight.
  • The value of information - what can we use if for?
  • The role of reactive and proactive decision rules. How can we measure the difference?
  • The role of rolling horizon approaches.
  • There will be many guest lectures discussing operational risk management across industries.

  The course will not use complicated tools, only provide an understanding of what the tools actually provide - often contrary to what they claim to provide.

  Difficulty of the course: The course is technically simple, but conceptually challenging.

• Learning outcome

  The course will give students knowledge about how to handle operational uncertainty with operational tools, and develop understanding of what can go wrong if decisions are made based on intuition. In particular

  Knowledge: Upon completion the student

  • understands how decisions under uncertainty are made when quantitative tools are not used; How intuitive decision making can lead us astray in systematic ways,
  • understands how uncertainty should be handled in both risk neutral and risk averse companies,
  • understands what different quantitative modeling ideas provide, and where they go wrong, and thereby be a good buyer of decision support systems.
  • know how operational risk is handled in many industrial setting.

  Skill: Upon completion the student is

  • able to handle uncertainty of any kind in operations, by understanding the connections between strategic, tactical and operational decisions,
  • able to argue coherently about uncertainty and its effects on service and operational flexibility.

  Competences: Upon completion the student can

  • reflect critically on theories, methods and tools within operational risk management, read relevant literature.

• Teaching

  The course will be a mix of lectures and casework. Some weeks will be free from teaching, and the emphasis will be on the analysis of relevant cases. There will be many guest lectures reporting from actual operational risk management.

  It will be possible to follow the course digitally.

• Recommended prerequisites

  Though the course in not very technical, it is necessary to have some basic experience from modeling decision problem from such as operations research, industrial engineering or optimization. 

• Requirements for course approval

  A mandatory case study (in groups of two or three) must be completed within a week in the middle of the semester. Will be graded pass / fail. Students can organize groups themselves. If not done, they will be assigned to a group. 

• Assessment

  A second case study (home exam, 4 days) in groups of two or three (50%) plus an oral exam of about 20 minutes (in person or electronically) (50%). The exams are in English.

  Students can retake each exam separately.

• Grading Scale

  A-F

• Computer tools

  No specific tools are required, but the case studied will require some types of quantitative analysis. 

• Literature

  Daniel Kahneman, Thinking Fast and Slow, Penguin Books, 2011, Parts II and III. Students are advised, but not required, to read the whole book.

  A compendium developed by the instructor. Will be posted.