Facts about the course
- Study points:
- Responsible department:
- Faculty of Logistics
- Course Leader:
- Yury Redutskiy
- Lecture Semester:
- Teaching language:
- ½ year
IDA710 Business Processes and Information Modelling (Spring 2019)
About the course
This course covers various perspectives on the modelling of human activity or related artefacts (machines, inventory, infrastructure, etc.). Analytic modelling helps us understand organizations, its actors and activities well enough to be able to make reasonable and useful changes. Design models are representations of elements of change, for instance, Information Systems, which directly support an activity or an organization, or employ a meta-model so that the properties of the activities and organizations may be investigated dynamically.
This course will be presenting the most important data, process, object-oriented and organizational model types using example techniques. As part of this, concepts of stakeholders and strategic governance will also be lectured.
Quality management will be taught as an important part of organizational governance, which also relies on understanding the modelling concepts, procedures, techniques, and methods that enable progression evaluation, engineering work products reviews, improvement procedures and effective testing.
Managing innovation is another application of models for patenting, attracting funds and partnerships, recruiting staff and handling the products in the market. The course contents emphasize transparency and communication using models for innovation.
Basics of various modelling techniques relevant for the data analysis in business processes will be taught in this course. Such approaches as time series analysis, decision trees, scenario trees, event trees, Markov analysis and others, will be presented by clear and straightforward examples.
Even more advanced topics will be addressed using cutting-edge research articles, which the students themselves contribute to present and discuss in the lectures. Generally, the content is going to be presented as interactively as possible and lively participation in exercises and arguments are expected.
The course is connected to the following study programs
Equivalent to requirements for the MSc programme in Logistics.
The student's learning outcomes after completing the course
Upon completing this course students will know what is implied by information systems-related governance principles and strategic alignment of pertaining technology. They will be able to recognize the organizational stakeholders, options and solution spaces for relevant use contexts, i.e., work and leisure-based activities for which the Information and Communication technology (ICT) can make a difference. The students will be able to understand and operationalize the ICT in innovation processes as a supporting technology, as well as a catalyst of disruptive change in the marketplace. In order to do this, the students will learn how to build representative models of organizations, their data and their processes. They will recognize supply chain models, data and process models, object-oriented models and finally, models of socio-technical systems. All of these are traditionally used in software engineering, but the out come of this course will be that the students know how to use them for intervention and organizational change processes, managing innovation and quality control as well as meta-modelling.
An important outcome is learning about the development of the ICT as a social as well as technical enterprise, for which requirements specifications, development and deployment entirely depend on the models used in the project. The students will learn to recognize the fundamental differences between various development life-cycle models and appreciate their strengths and weaknesses for various purposes. The students will understand the role and the importance of the information systems in value chains. They will be able to critically think and apply the information systems to efficiently organize the innovative processes, and understand the implications of trade-offs.
Upon finishing the course, the students will have the knowledge and skills to organize, structure, store, model and represent various data. They will be able to recognize the appropriate software tools to obtain/extract the data, operate, visualize and interpret it, and also, to draw their own conclusions from the obtained results. The students will be able to access, explore and analyse the data with a viewpoint of business process monitoring, obtain new insights to improve business planning and boost future performance.
Forms of teaching and learning
3 hours of lecturing per week, one mandatory assignment. There may also be optional group-work with assignments and self-study activities, that will comprise elements of the exam curricula, even if participation is not compulsory. Students who do not participate in the activities are themselves responsible to acquire equivalent material and knowledge.
Coursework requirements - conditions for taking the exam
- Mandatory coursework: Assignment(s)
- Courseworks given: 1
- Courseworks required: 1
- Presence: Required
- Comment: The assignment has to be completed and handed in by specified deadline, after which the submission is void and the work will not count as passed. The task has to be completed and submitted in the same semester as the examination.
- Form of assessment: Digital school assessment - Insperia
- Proportion: 100%
- Duration: 4 Hours
- Grouping: Individual
- Grading scale: Letter (A - F)
- Support material: Calculator that may contain data + general dictionary in mother tongue/Norwegian/English in paper version
Required reading list is given in Fronter at the semester start
Avison, D., Fitzgerald, G.: Information Systems Development Methodologies, Techniques and Tools, 4th ed, McGraw Hill, 2006
Alexandre Oliveira, Anne Gimeno: Executing the Supply Chain: Modeling Best-in-Class Processes and Performance Indicators, 2014 by Pearson FT Press. Part of the FT Press Operations Management series.
Bell, Peter, and Gregory Zaric. Analytics for Managers: With Excel. Routledge, 2012. (ISBN-13: 978-0415622684, ISBN-10: 0415622689)
Other books and selected articles may be recommended during lectures.