Big Data is definitely shaking business processes! Huge amount of heterogeneous data, real-time, machine learning … Big Data is pushing companies and logistics services providers to better collect, analyse and exploit data. The target? Better anticipate customer needs, improve efficiency and performance.
Big Data Analytics: logistics becomes more efficient
Holding sometimes more data on end-users than its own clients, logistics services providers are now able to play an even more strategic role. The supply chain is going digital, so the collection of relevant data is faster and processes are optimised to deliver higher operational efficiency and consumer experience. Thanks to Big Data, 3PL are in a position to react and optimise their resources, planning and routing in real-time.
According to two Boston Consulting Group’s recent reports, Big Data can boost logistics performance at four levels: strategic network planning, demand-driven management, resilience and risk management and dynamic deliveries optimisation.
1. Strategic network planning
Interconnecting data (internal, supplier, factory, etc.) so it can be analysed simultaneously. The network gets faster, supply chain costs are reduced and schedules can be adjusted in real-time.
2. Demand-driven management
By synchronising data from checkout, shelf-sensors, social networks and the weather forecast, it is possible to become more reactive to changes in demand and fine-tune sales forecasts.
3. Resilience and risk management
Risk factors can be identified and preventive maintenance measures implemented through external data analysis (roads, equipment and suppliers).
4. Dynamic deliveries optimisation
By combining geofencing with other data like road traffic, decisions can be taken to reroute deliveries with a positive impact on transport costs and reliability.
Supply chain 4.0: openness and collaboration
We are still only at the beginning of the Big Data era. Therefore, all players must first get information systems ready to integrate new concepts (connected objects, cloud, digitisation, mobility, etc.). From a processing model based on the analysis of records to unveil trends and areas for improvement, the objective is to implement a more open model. This more open model will be capable of consolidating the data and allowing the different sources of information to communicate with each other in real-time. Deciding to take the path of Big Data is to open the door to process optimisation for all players in the logistics chain, making them more agile, faster, efficient, reactive and qualitative. The phenomenon is likely to accelerate as technologies move forward.