Sustainable Supply Chain & Logistics Wired by Data Analytics

This BIP offers a unique opportunity for students to explore supply chain sustainability and to
gain data analytics knowledge, welcoming participants from diverse backgrounds without
requiring prior experience. The program is opened to undergraduate and master’s students from
partner universities and it comprises two phases: virtual and in-person.
The virtual phase (May-June) includes 20 hours of learning via Microsoft Teams and autonomous
work. The in-person phase, held in Coimbra in July, provides an immersive experience where
students apply the acquired skills in practical scenarios.
A key feature of the program is its project-based learning approach, fostering collaboration,
problem-solving, and critical thinking. Additionally, students benefit from a Job Shadowing
opportunity, gaining real-world business insights.
By the end, it is expected that participants will gain robust foundations on Supply Chain
Sustainable Planning and Management and Reverse Logistics supported by Data Analysis and
Optimization tools to achieve optimal Data-driven Decision Making.

This BIP offers a unique opportunity for students to explore supply chain sustainability and to gain data
analytics and optimization knowledge, welcoming participants from diverse backgrounds without
requiring prior experience. The program is opened to undergraduate and master’s students from
partner universities and it comprises two phases: virtual and in-person.
Now a days, logistics and supply chain subjects are perceived by researchers, academics and
organizational partitioners as critical factors to achieve future developments. Also, the technological
progress contributed significantly to enhance traceability and provide real time analysis to improve
supply chain responsiveness and resilience pillars.
Moreover, different operational research applications for decision-making in areas such as
Management, Logistics, Warehouse and Stock Optimization, Supplier & Vendor selection, Transport
and Distribution, Marketing, and the overall Supply Chain can be found. Additionally, topics on
sustainability can introduce important insights for design and planning analysis.
Besides that, Data Analytics (DA) is increasingly famous due to the impact that data analysis has
revealed, both for individual citizens and for organizations. In both cases, Data Analytics presents itself
as a powerful aid for more assertive and informed decision-making. In here, data analysis and data
visualization represent important decision-making insights and support tools. These are expected to be
increasingly robust and available closer to real time.
So, extracting insights from data and introducing optimal model proposals’ result in a progressively high
important scope to logistics and supply chain sustainable planning and management. This is due to
deep understanding that may be brought from optimization techniques and from data analysis to
promote data-driven decisions on different field of applications.

O1. Consolidate the principles of sustainability in real-world supply chains;
O2. Develop risk mitigation strategies with integrative sustainable partnerships;
O3. Expand process analysis to enhance sustainability through robust optimal decisions;
O4. Gain skills on data analysis to improve logistics efficiency;
O5. Improve decision making capacity using Data Analytics;
O6. Apply novel logistics strategies to reduce climate and environmental impacts;
O7. Acquire decision effectiveness and efficiency.
Therefore, preparing the students with an academic background focused on contents as:
o Exploratory concepts on logistics sustainability and green strategies;
o Uncertainty and risk mitigation on supply chain demand and supply processes;
o Logistic key indicators and strategies to mitigate climate and environmental effects;
o Foundation on optimization models and tools;
o Optimization tools applied to green supply chains;
o Overview on Data Analytics and Digital Transformation
o Data Analysis and Data Visualization Techniques
o Applications of Data Analysis to Logistics Sustainability and Supply Chain Digital Transformation
o Optimal and Data-driven decision proposals.
These will allow students to acquire important academic and organizational Data-driven skills, as it
was previously mentioned and summarized.

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