THESIS PROJECT: Supply Chain Resilience

Background
Aftermarket supply chain planning is complex due to an extensive supply network, a vast number of SKUs with great variety and the customer's requirement for spare parts in different life cycle phases.
Furthermore, the competition is high, there is a high pressure on cost efficiency and the business environment is exposed to multiple disruptions, which are expected to continue or increase.


Thesis questions and expected outcome
Investigating and analyzing different strategies for improving the resilience of the aftermarket supply chain. Propose ways of working, tools and methods to handle disruptions, e.g. advanced Sales and Operations Execution (S&OE) and Sales and Operations Management (S&OP).
Conduct a meta-analysis of the supply chain to identify vulnerabilities. Maturity models of S&OP/E propose to expand the scope of the monitored data of both supply and demand. For that reason, an expectation for this master thesis involves advanced analytical methods, such as graph theory, machine learning and classification methods, to improve the firm's capabilities to manage disruptions and imbalances of supply and demand.
Expected outcome: in-depth resilience analysis and proposed concepts to improve the supply chain planning and expected business value.


Student profile and application
MSc student in Supply Chain or other related discipline.
Strong analytical skills, utilizing tools such as Python, MatLab, R.
Application deadline: TBD, we will continuously review the applications so don’t wait with submitting.


Contact information
For further information, please contact:
Recruiting manager:
Thomas Nordenskjöld at Advanced Analytics Europe
E-mail: Thomas.nordenskjold@volvo.com
Phone: +46739025355


Mentor:
Joakim Andersson, Supply Chain and Analytics Expert at Advanced Analytics
E-mail: joakim.andersson.3@volvo.com
Phone: +46739025112


Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.