PEMDSRPI Process and Innovation Management

School of Business Administration in Karvina
Winter 2024
Extent and Intensity
0/0/0. 10 credit(s). Type of Completion: dzk.
Teacher(s)
doc. Mgr. Tomáš Gongol, Ph.D. (lecturer)
Ing. et Ing. Michal Halaška, Ph.D. (lecturer)
doc. RNDr. Ing. Roman Šperka, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Ing. Roman Šperka, Ph.D.
Department of Business Economics and Management – School of Business Administration in Karvina
Contact Person: Ing. Žaneta Rylková, Ph.D.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives

The objective of the course is to expand and deepen theoretical knowledge and practical methods for improving conditions for business activities within organizations. The course content also promotes the development of students' creative approach. In each thematic section, emphasis is placed on integrating theoretical and practical concepts, beginning with the identification of business needs and their detailed analysis, followed by process and organizational changes, and innovation management in response to identified issues within organizations. The teaching assumes the use of standard modeling methods, procedures, tools, and data analytics.

Syllabus

  • 1. Business Analysis
    Basic concepts and the role of business analysis. Planning the analysis and monitoring the progress of work within an organization. Negotiating and documenting requirements for changes in business needs. Business analysis strategy. Solution design and architecture. Business case.
    2. Business Process Management
    Functional vs. process management of organizations. The essence of business process management and its lifecycle. Basic types and notations for business process modeling. Simulation tools and models.
    3. Process Mining
    Discovery of as-is process models. Specification of log data on the execution of business processes. The essence and purpose of process mining. Tools and techniques for process mining analysis. Synthesis and interpretation of results.
    4. Innovation Management
    Innovation ecosystem and corporate innovation strategies. Legal and economic aspects of innovation. Implementation processes for innovations. Project management of innovations. Methods and techniques of innovative thinking. Innovative potential of a learning organization.

Literature
    required literature
  • ŠPERKA, Roman, Michal HALAŠKA and Dalibor ŠIMEK. Techniky a nástroje v oblasti řízení podnikových procesů: Distanční studijní text. 1st ed. Karviná, 2018, 188 pp. ISBN 978-80-7510-312-3. info
  • DUMAS, M, M LA ROSA, J MENDLING and H. A. REIJERS. Fundamentals of Business Process Management. 2nd ed. Berlin: Springer (Berlin) Verlag, 2018. ISBN 978-3-662-58585-6. info
  • DRUCKER, PF. Inovace a podnikavost. Praxe a principy. Praha: Management Press, 1993. ISBN 80-85603-29-2. info
  • AALST, V. D. and M. P. WIL. Process Mining. Data Science in Action. Berlin Heidelberg: Springer Verlag, 2016. ISBN 978-3-662-49851-4. info
    recommended literature
  • ŠPERKA, Roman. Informační podpora podnikových procesů (Information support of business processes). Jesenice: Ekopress, s.r.o., 2019, 191 pp. 1. vydání. ISBN 978-80-87865-55-2. URL info
  • PILJ, P, J LOKITZ and SOLOMON. Design a Better Business: New Tools, Skills, and Mindset for Strategy and Innovation. New Jersey: John Wiley& Sons, 2016. ISBN 978-1-119-27211-3. info
  • CADLE, J, D PAUL and P TURNER. Business Analysis Techniques: 99 Essential Tools for Success. London: BCS, The Chartered Institute for IT, 2014. ISBN 978-1-78017-273-6. info
Assessment methods

The oral exam consists of a specialized discussion and a defense of the seminar paper. Within the specialized discussion, two questions are posed based on the course content. The seminar paper is mostly thematically linked to the focus of the dissertation work. The seminar paper identifies a research problem, presents existing theoretical and application approaches to its solution, conducts a comparison of these approaches, and discusses their application in the dissertation work. If the dissertation does not relate to the course content, students will conduct a process mining analysis using real data that they will receive. To prepare for the exam, students will use study materials available in the interactive course in the study information system.

Language of instruction
Czech
Further Comments
Study Materials
The course is also listed under the following terms Summer 2023, Winter 2023.
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