The course aims at understanding the basic of lean thinking and agile methodologies. The course provides an overview of lean methodologies in manufacturing, product and software development, offering tools to plan and manage projects with agile methodologies like scrum and kanban and basic understanding of software development based projects.
At the end of the course students will
- understand core principles of lean thinking - understand how lean priciples are applied in manufacturing - understand how lean principles are apolied in product development - understand how lean principles can be translated to software development contexts - understand how companies applying agile methodologies handle projects and planning - understand how scrum and kanban work - understand probabilistic forecasts and their advantages over traditional forecasting approaches.
Course Prerequisites
None
Teaching Methods
Frontal lectures integrated with practical activities, interactive slides to foster discussion and exploration of the topics covered.
Assessment Methods
Option A) Quiz at the beginning of each lesson (15 true/false question on the topic of the previous lesson) + final laboratory (team-based scrum simulation)
Option B) Stand alone oral exam on the topics discussed during the course, with the goal of assessing user understanding of the topics and ability to create connection autonomously.
Contents
DETAILED PROGRAM
- Lean principles and lean manufacturing: Waste, Value, 8 Kind of wastes, Lead Time, Cycle Time, 5S, Theory of constraints - Lean Startup Methodology: Build-measure-learn cycle, Validated learning, MVP, Innovation accounting - Traditional approach to software development and its limitation - Agile Methodologies: Agile Manifesto, Scrum (Inspect&Adapt, Roles, Cerimonies, Events) - User Stories - Kanban (Defining and visualizing workflow, managing items in workflow, improving workflow), Flow metrics (WIP, Throughput, Work Item Age, Cycle time) - Forecasting and planning: Estimation VS no estimation, probabilistic forecasts, Monte Carlo Method
