Leaders in this journey face key challenges:
- Data use cases must be chosen that yield tangible business impact and implemented in scalable, repeated manners. This means handling growing volumes of data and ensuring high performance standards without delays.
- Technological modernization must synthesize business objectives on a global and regional level. To bridge the business-tech disconnect, technology solutions must align seamlessly with logistics needs at speed and scale.
- Logistics teams must be equipped with self-service analytics capabilities to enhance decision-making. Teams must be enabled to extract insights autonomously, thereby cultivating a data-driven culture and driving higher operational efficiency.
- Operational models must be re-evaluated to embrace agility and innovation. Adapting to GenAI and product-based methodologies is key for progress.