Snezhana Sulova
ABSTRACT
The digital age we live in requires the application of new, specific, and sophisticated methods for processing the large amounts of data available. Discovering relationships and data models is a way to predict behaviour and events and it can successfully be used in logistics. Companies in this industry recognize the importance of big data predictive analytics but at the same time a big obstacle is the lack of a comprehensive framework to integrate predictive analytics with corporate strategies for digital transformation. The framework will be described at a conceptual level and suitable technologies for its implementation will be recommended. The applicability of the proposed framework will be demonstrated with a typical use case scenario in the logistics industry. The proposed predictive analytics framework provides opportunities for the improvement of the operational efficiency and better decision making in the logistics industry.
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Index Terms
- A Predictive Analytics Framework Using Machine Learning for the Logistics Industry
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