Applied System Analysis

2022/2023

Type: Mago-Lego

Delivered by: School of Software Engineering

When: 2, 3 module

Online hours: 20

Open to: students of all HSE University campuses

Instructors: Konstantin Y. Degtyarev

Language: English

ECTS credits: 6

Contact hours: 66

Full Syllabus

Abstract

The course 'Applied System Analysis' (рус. Прикладной системный анализ) is offered to students of the Master's degree Program 'System and Software Engineering' (area code 09.04.04) in the School of Software Engineering, Faculty of Computer Science of the National Research University Higher School of Economics. The course is a part of MS curriculum pool of compulsory courses (1st year, Base Clause – Module 'Major'). It is a two-module course (semester A quartile 2 thru semester B quartile 3). In general, system analysis (SA) can be considered as a set of approaches, methods, and techniques aimed at understanding peculiarities of the problematic situation faced by its owner(s), and the development of improving interventions into the problem based on the options (alternatives) generated. As a rule, the causes of the problem are subjective, and they are related to one person or group of persons (stakeholders), his/her (their) perception of reality. Therefore, Applied System Analysis (ASA), i.e. the application of SA as a universal approach to solving problems in different (applied) fields of human activity (engineering, management, economics, to name a few), is based on the concepts of the problem, system, model, alternatives and monitoring (management). Classification of problems as well-defined (very rarely occurring in practice), weakly defined, and ill-defined ones (the latter are more realistic and constantly arising in practice) requires the use of different models (approaches) in each particular situation. This fact has led to the formation of so-called 'hard' and 'soft' system methodologies (SSM) based on formal and informal approaches within the framework of system analysis, respectively.

Learning Objectives

The main objective of the course 'Applied System Analysis' is to present, examine and discuss with students fundamentals and principles of both System Analysis and Systems Thinking that emerged in response to (1) a steadily growing complexity of problems arising in various areas of day-to-day and professional human activity, and (2) a necessity to structure problems and to present (viz. to develop mental/visual or formal model(s)) and to assess emerged situations complemented with a search for acceptable solutions (problem-solving) based on the analysis and the elaboration of alternatives for action. In particular, the vast field of software engineering (SE) is concerned with such problems and their solutions that cannot be fully understood and explained clearly from the very beginning, but nevertheless, we can claim that software engineers deal with systems, real products.

Expected Learning Outcomes

To formulate clearly potential role, attractive aspects / disputable points of SA approach use when solving problems arising in the present professional activity; to demonstrate the competence to credibly defend viewpoint(s).
To know basic definitions related to Q-analysis (polyhedral dynamics) procedure.
To know different definitions of the system; to understand the importance of systems thinking in solving engineering problems (and not only).
To know the origins of systems analysis (SA) and history of SA emergence, basic concepts SA is grounded on.
To know the specifics of causal loop diagrams (CLD as models), their use in systems studying; to be able to identify in CLD balancing (B) and reinforcing (R) loops that determine the dynamics of systems (problems).
To understand heuristic approaches to problem solving (means-ends analysis, hill climbing, approach by analogies); to be able to apply them in solving problems.
To understand how to draw conclusions concerning the peculiarities of system’s structure on the basis of analysis’ results obtained.
To understand peculiarities of hard and soft approaches (methodologies) in systems modelling.
To understand problem structuring approaches and to know how to improve insight (to make progress in analysis) into ill-structured problems.
To understand the details and to carry out steps relating to the calculation of the structural vector of complex К (system’s model) and eccentricities of simplices.
To understand the details of multi-criteria decision analysis (MCDA) approaches covered in the course and apply them while solving the learning tasks.
To understand the importance of a systemic approach applied to complex problems arising within various human activities and to engineered systems, classification of problems (well-structured, unstructured and ill-structured).
To understand the layered approach to systems thinking, the need to gradually move from the level of observed events to the identification of patterns and to further understanding of the system’s (problem’s) structure.
To understand the particulars of working with experts, using Delphi method.
To understand the purpose and relevance of a stakeholder analysis; to know the ways to perform a stakeholder analysis.

Course Contents

Introduction and overview of the course (in particular, comments concerning grading policy applied and course-related control activities). Origins of systems analysis (SA). Notions of system, core definitions of a system.
Systems thinking, problem-solving, and systems engineering. Stages of SA. System approach and system paradigm. Problem and system – is there any relationship between them? What is a system in problem-solving?
Classification of systems (problems); systems, problems, and mental models, and problem-solving. Systems and complexity. The role of models (modeling) in SA. Models of systems. The problematic situation, problem as a system, its analysis, and modeling.
Hard and soft methodologies in the analysis of systems. Operations research, optimization problems (hard models in System Analysis / SA)
Soft models in system analysis. SPE-pyramid (approach to grasp system’s structure), cognitive maps (e.g. B.Kosko, C.Eden, et al.), causal schemes (Causal Loop Diagrams / CLD), definition, and basic features.
BOT graph, and what can we “see” in CLD (our perception)? How to construct CLDs? Rich pictures, CLDs (examples, discussion), PQR formula, CATWOE analysis. Specificities of SSM.
Work with experts. Multi-criteria decision analysis (MCDA). Main steps in MCDM, decision-making models. MCDM – managerial and engineering levels.
Hypotheses in problem solving, use of heuristic methods in problem-solving (viz. informal analysis). Who are the stakeholders? Stakeholder analysis and its importance.
Classification of stakeholders, influence-importance matrix (IIM), Olander’s model (matrix). SWOT-analysis

Assessment Elements

Quiz_1
(computer-based test) is offered in the Module 2 (preliminary estimate)
Quiz_2
(computer-based test) is offered in the Module 3 (preliminary estimate)
Quiz_3
The presentation of the results of the Quiz_3
Part_seminar

Interim Assessment

2022/2023 3rd module
0.2 * The presentation of the results of the Quiz_3 + 0.25 * Quiz_2 + 0.1 * Part_seminar + 0.25 * Quiz_3 + 0.2 * Quiz_1

Bibliography

Recommended Core Bibliography

Gorod, A., Gandhi, S. J., Sauser, B., White, B. E., & Ireland, V. (2014). Case Studies in System of Systems, Enterprise Systems, and Complex Systems Engineering. Boca Raton: CRC Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=802172
Jaap Schaveling, & Bill Bryan. (2018). Making Better Decisions Using Systems Thinking. Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.spr.sprbok.978.3.319.63880.5
Системный анализ, оптимизация и принятие решений : учеб. пособие для вузов, Козлов, В. Н., 2010
Теория и методы принятия решений, а также Хроника событий в Волшебных Странах : учебник для вузов, Ларичев, О. И., 2002
Теория систем и системный анализ : учебник для вузов, Волкова, В. Н., 2010

Recommended Additional Bibliography

Системный анализ : учебник для вузов, Антонов, А. В., 2006

Course Syllabus