Master 2020/2021

IT-projects Risk Managment

Type: Elective course (Business Informatics)

Area of studies: Business Informatics

Delivered by: Department of Business Informatics

Where: Graduate School of Business

When: 1 year, 3, 4 module

Mode of studies: offline

Instructors: Dmitry Sizykh

Master’s programme: Business Informatics

Language: English

ECTS credits: 5

Contact hours: 40

Course Syllabus

Abstract

The program is developed in accordance with: with the educational standard of the Federal State Autonomous Educational Institution for Higher Professional Education "National Research University Higher School of Economics" (HSE) in the training direction of 38.04.05, "Business Informatics", qualification: "Master", approved 02.02.2018, protocol № 1; working curriculum of the university in the training direction 38.04.05 "BusinessInformatics", training level - Master, 1st course, approved in 2018 The purpose of mastering the discipline The purpose of mastering the discipline is to form students' knowledge and skills that are necessary for understanding, developing, implementing and managing the risks of investing in information technology projects. The discipline "IT Project Risk Management" is lectured in English.. Competences of the student, which are planned to be formed at the as a result of the discipline mastering. As part of the master's program "Business Informatics" this discipline is a discipline by a choice. The study of this discipline is based on the following disciplines: “Designing IP”, “Methodology and tools for modeling business processes”, “Improving enterprise architecture”. In order to master an academic discipline, students should know econometrics, conceptual foundations of enterprise architecture, business process modeling methodology, and have an understanding of the organization of information technology management. The main provisions of the discipline should be used in the future when writing course and final qualifying works, the preparation of scientific articles, reports, presentations of research works, in practical and research activities.

Learning Objectives

• Knowing the methodology for making decisions on investments in information technology and risk management of these investments
• Be able to analyze the risks of investing in IT projects and manage these risks using modern methodologies
• To have the skills (to gain experience in the implementation of case studies / case studies) of risk management of an IT project based on a real option analysis using the Monte Carlo method for numerical modeling of the main project factors.

Expected Learning Outcomes

• He knows the basic concepts and technologies of information risk management. He knows the basic methods for evaluating the effectiveness of investment projects.
• Applies methods for analyzing project performance in evaluating IT investment projects. Compares possible alternatives based on project performance criteria.
• Describes the possibility of using the “game theory” of investment risk assessment.
• Analyzes and describes various types of investment portfolio methodologies used in making investment decisions in the field of IT.
• Describes the “cost analysis methodology” and applies this methodology when making investment decisions.
• Applies the methodology of modeling options using the Black-Scholes method to assess and reduce project risks.

Course Contents

• Introduction to Information Technology Investments Risk Management
  Information Technology Investment Decision-Making Issues. Needs Analysis and Alternative Information Technology Investment Strategies. Measuring Information Technology Investment Performance. Basic Financial Methods. Cost / Benefit Analysis. Critical Success Factors. Delphi Method and the Balanced Scorecard Method. Multi-Factor Scoring Methods and the Analytic Hierarchy Process.
• Decision Analysis and Multi-Objective Programming Methods
  Explain what “decision analysis” is and how it can be used in IT investment decisionmaking. Explain how to compute answers for a variety of “decision analysis” methods. Define the decision environments under which “decision analysis” can operate, and explain how differing environments require differing methodology. Explain what “goal programming” is and how as a multi- objective programming approach can be used in IT investment decision-making. Understand how to formulate “goal programming” models.
• Benchmarking Techniques and Game Theory
  Explain what “benchmarking” is and how it can be implemented for information technology planning. Explain what “gap analysis” is and how it can be used to identify and graphically display performance issues in information technology management. Describe “game theory” as a means of selecting information technology investment alternatives. Explain the difference between “pure strategy” and “mixed strategy” decision situations. Explain the consequences of information technology alternative investment selections when a “game theory” problem has a “saddle point” solution.
• Investment Portfolio Methodologies
  Describe different types of investment portfolio methodologies used in IT investment decision-making. Describe Wards portfolio approach and how it can be used to set priorities in IT investments. Describe Peter's portfolio mapping methodology and how it is used to map IT investment strategies.
• Value Analysis and Benefit/Risk Methodologies
  Explain what "value analysis methodology" is and how it can be used in lT investment decision-making. Describe the steps in a "value analysis". Explain what "Benefithsk analysis methodology" is and how it can be used for in lT investment decision-making. Explain how "risk assessment" questions can be used in IT investment decision-making.
• Real Options Valuation
  Modeling the European & American Call and Put Options Values using binominal tree approach (problem in Excel). Modeling the European Call and Put Options Values using BlackSholes formula. Modeling the European & American Call and Put Options Values using Monte Carlo method (problem in Excel). Modeling the Real Option Value with the Binominal Tree Method. Modeling the Real Option Value with the Black-Scholes Method. Staged Investments, Decision Tree Valuation Approach with Project Gates. Sensitivity Analysis, Value Drivers, Tornado Diagram and Critical Success Drivers for a Real Option. Modeling the Real Option Value with the Monte Carlo correlated simulation for the Real Option Critical Success Drivers (problem in Excel).

Assessment Elements

• Attendance and activity
• Practical works
• Exam test
  During the exam for calculations is allowed to use next programs: MS Windows Calculator and MS Excel. During the exam is allowed to use draft, pen and handy calculator for solving of tasks.

Interim Assessment

• Interim assessment (4 module)
  0.1 * Attendance and activity + 0.4 * Exam test + 0.5 * Practical works

Bibliography

Recommended Core Bibliography

• Fundamentals of project management, Heagney, J., 2012
• Information technology project management : providing measurable organizational value, Marchewka, J. T., 2003
• PMP: project management professional exam : study guide, Heldman, K., 2007
• Project risk management : processes, techniques and insights, Chapman, C., 1997

Recommended Additional Bibliography

• Information systems project management, Avison, D., 2009
• Information technology project management, Marchewka, J. T., 2006
• Information technology project management, Schwalbe, K., 2006
• Managing risks in projects : proceedings of the IPMA Symposium on Project Management, 1997, , 1997
• Project management best practices : achieving global excellence, Kerzner, H., 2006
• Project Management, Field, M., 1998
• Project management, Maylor, H., 2003
• The implementation of project management : The professional's handbook, , 1996