Course Description
Introduction to the practice of modeling business work systems as processes. Focus on establishing a framework for discovering, mapping, analyzing, and improving processes within organizations. Major topics covered include modeling, business processes using standard notation, assessing the performance of existing processes, generating and testing potential redesigns, the discovery of processes through data mining, and the automation of process components. Course leverages a variety of software tools to conduct business process analytics.
Athena Title
Bus Process Mgmt and Analytics
Equivalent Courses
Not open to students with credit in MIST 5750, MIST 5750E
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
An important goal of this class is to arm students with a fundamental understanding of next-generation tools and approaches to business process management, analytics, and improvement. These include: 1. Notation: BPMN 2.0 – the notation that has emerged as the standard for BPM. Students will gain hands-on experience with the notation for both human and machine-readable applications. Evidence: Homework assignments and exams testing knowledge of notation. 2. Simulation: Since BPMN is machine-readable, the simulation of process models has become never been more accessible. The course will involve gaining the ability to simulate process models in Signavio. Evidence: Assignment testing simulation skills as applied to process redesign. In-class cases using simulation software. 3. Mining: Process mining is a next-generation technique for process discovery and other applications. Students will gain hands-on experience using Celonis, a popular industry tool for process mining. Evidence: Homework assignments and exams testing mining skills. In-class cases using mining software. 4. Execution and Automation: Students will understand concepts regarding the automation of process components. We will discuss recent advances in robotic process automation and tools such as UiPath. Evidence: Case study building process automation tool. 5. Analysis: Students will understand how to assess the performance and efficiency of business processes. Analytic methods such as cycle time analysis, queuing, and capacity analysis will be covered. Evidence: Homework assignments and exams testing analytics skills.
Topical Outline
1. BPM Notation a. Basic process elements b. Level 1 and Level 2 models c. The decision model 2. Process Analysis a. Introduction to lean and six sigma concepts b. Cycle time analysis c. Cost and capacity of processes d. Queueing analysis 3. Process Simulation and Redesign a. Implementing process simulations b. Redesign heuristics c. Simulation as a tool for experimentation and testing 4. Process Mining a. Concepts of process mining and data requirements b. Overview of algorithms and approaches c. Software for conducting process mining d. Building dashboards and monitoring performance e. Conformance checking 5. Process Automation a. Identifying automation opportunities b. Introduction to RPA
Syllabus