L'insegnamento prevede 5.0 CFU erogati con Didattica Innovativa come segue:
Cotutela con mondo esterno
Corso di Studi
Codice Piano di Studio preventivamente approvato
Ing Ind - Inf (Mag.)(ord. 270) - BV (479) MANAGEMENT ENGINEERING - INGEGNERIA GESTIONALE
052817 - ADVANCED SUPPLY CHAIN PLANNING LAB
The global business environment and the increased complexity in supply chain planning require an extended set of competences, ranging from new collaborative planning methods to advanced IT tools. In this scenario, the Lab objective is to provide state-of-the-art knowledge on techniques and tools for advanced Supply Chain planning tasks, including also some issues about Supply Chain Execution . By mixing traditional theoretical lessons business games and application cases, guest speakers, hands-on lab sessions and a company-based project work a thorough yet practical knowledge will be transferred to the students.
The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:
Identify trends, technologies and key methodologies in a specific domain
Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment
Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members
Risultati di apprendimento attesi
Given the above mentioned learning goals, the following learning outcomes are expected:
Knowledge of the state-of-the-art challenges, practices and tools related to the task of planning complex supply chains. E.g.: the relevance of financials performances in planning, the most used practices to enhance collaboration, data exchange and risks sharing in supply chains, the available technologies in the IoT arena, the adoption of cloud platforms and application to collect data and to enable business integration. These elements will be have to be known both in general terms, as well as contextualized (knowing relevance / priority) in specific industries;
Capability to use basic (e.g. ms Excel) and advanced (e.g. r) tools to analyse data so as to support plannign related-decision, e.g. data preparation and cleaning, basic clustering, time series analysis, etc.
Capability to analyse, redesign and improve a real SC planning process, starting from the detailed map of the current process of a company (activities, tools, responsibilities) and the quantititive assessment of the current performances, then moving to the identification of criticalities (process, organization, technology), then re-designing all of the above mentioned process elements, including the assessment of cost/benefits and the definition of a roadmap to implement the new process (considering organizational, technological, financial, regulation etc. constraints).
Capability to accomplish several (i.e. parallel) demanding tasks during the semester, managing stress, working in multi-language & multi-cultural team, interacting with external company stakeholders and respecting deadlines in internal (for the teacher) and external (for the company) deliverables.
The Lab program will encompass the following contents:
Introduction / reprise about supply chain planning tasks, examples from different industries; the relevance of information in nowadays planning.
Models and techniques for advanced planning: from Vendor Managed Inventory to Supply Chain simulation.
Technologies for Advanced Planning: APS systems, Internet of Things, Industrial Analytics, Cloud IoT platforms, Cloud SaaS and ecosystem, blockchain;
Tools: data analytics for planning, fundamentals of "r" and its application to planning problems
Methodologies for Value Assessment: a framework for tangible and intangible benefits, approaches and models for a quantitative assessment, and for business case constructing
Industries and vertical markets: special focus on Advanced planning in Automotive, Retailing, Food, Construction and Fashion Luxury industries.
Outlook on the job market: the role of human planner in the future technology playground.
Approach and Methodologies
Each topic will be first introduced through a short traditional lesson, and then followed by extensive applicative contents. Overall, the Lab will resort to the following teaching methodologies:
Traditional lessons, providing theoretical background, scenario analysis, outlook on market needs and technology solutions;
Business cases, so as to practice with specific planning problems, techniques and tools in limited-size problems. Students' presentations will enhance presentation skills and will be used to assess the degree of involvement with the proposed contents
Computer aided learning (e.g. business games)
Visit to the Internet of Things Lab of Politecnico di Milano (if allowed by logistic constraints)
Company guest speakers
Autonomous work on assignment(s) (both thematic and company project work)
Short literature reviews / Market searches as elective, bonus assignments
Fundamentals of Operations Management and Supply Chain Management
Modalità di valutazione
Two assignments are arranged, a thematic one (focused on data analysis for planning) and a company project work.
The first assignment will rely on real-company data, disguised for the sake of confidentiality. In the Project Work, the students will be involved for 2 months with a real company, under the guidance of a company tutor and of an academic tutor, in order to solve a real planning problem. The Project work will be held in parallel with the Supplier Relationship Management course.
The thematic assignment will therefore assess the second learning outcome, while the Project work will assess the third and the fourth learning outcome.
For both assignments, students will be divided in groups (4/5 people, arranged by the teachers so as to mix and balance people’s experience and background). The assignments will be given during the semester (1st after 30% of the course, 2nd after 60% of the course) and will require autonomous work of the team, with in-class assistance by Lab teachers.
Exam and evaluation
The evaluation will be based on:
Assignment(s): The assignment(s) evaluation will allow to achieve a maximum mark of 26/30, and will be valid for one academic year (till next next years' February sessions).
Class participation: assessed through the number of business case discussions proposed and uploaded in the course folder by every student, required to score an extra 2/30 point. NB: uploaded discussions of business cases are not evaluated per se, just analysed to assess the students participation
Oral examination: The oral examination will cover both the assignments, so as to assess the individual contribution to the teamwork, as well as the course’s topics, including those presented by geuas speakers, so as to assess the understanding of the theoretical elements provided. The oral examination could give an extra 3/30 point, so allowing to reach the top mark.
Elective additional short assignments, offered by companies and guest speakers, will be awarded with bonus extra scores (+1 or +2 points, depending on assignments’ difficulty and quality of the work).
Recommended readings Note:
Several recommended readings, mostly academic papers and business research reports will be uploaded / recommended during the course, also depending on current business trends and on the selected guest speakers
Tipo Forma Didattica
Ore di attività svolte in aula
Ore di studio autonome
Laboratorio Di Progetto
Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese