CEU Electronic Theses and Dissertations, 2025
| Author | Nagy, Marton |
|---|---|
| Title | Ahead of Expiry: Machine Learning Driven Alerts for Smarter Procurement in the Petrochemical Sector |
| Summary | Procurement plays a crucial role in ensuring the smooth operation of large-scale industrial companies. However, the time it takes to renew or renegotiate procurement contracts (that is, the lead time of the process) can be extremely variable and it depends on multiple factors. As a result, it may not be correctly predicted solely based on expert judgement. However, if a new contract is not in place by the time the previous one expires or is exhausted, companies face the risk of rushed decisions, higher costs, and limited supplier options. The primary goal of the project was thus to build a smart alert system, powered by a machine learning driven prediction engine, that ranks contracts based on the ideal start dates to begin the renegotiation process, therefore helping procurement professionals of the Client identify which contracts to prioritize. |
| Supervisor | De la Rubia, Eduardo Arino |
| Department | Economics MSc |
| Full text | https://www.etd.ceu.edu/2025/nagy_marton.pdf |
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