Most supply chain managers have limited visibility into which of their first-tier suppliers have risks and exposures arising from second and third-tier suppliers. Essentially, they do not know who supplies their Tier 1 suppliers.
Location analytics can identify unknown hidden participants or nodes in supply chains, thus helping to minimize and better control the risks of disruption.
Big Data is transforming the way leaders manage supply chains across all touch points, from manufacturing and provisioning to logistics and customer service.
What is Big Data applied to supply chain?
The application of Big Data for supply chain sustainability is the application of high-level intelligence derived from an organization’s data analytics of its operational processes, from procurement and processing to inventory management, distribution, etc., providing a basis for automation efforts and continuous improvement of logistics operations. Read the complete article here
Logistics managers need to implement location intelligence in supply chains in order to reduce delays, keep costs down, generate a competitive advantage, and thereby improve the global network of multiple carriers, service providers and physical locations from the constant threat of unexpected problems.
By leveraging location intelligence, decision makers gain deeper insight into market trends, consumer behaviors, foot traffic patterns, manufacturing activity, competitors’ logistics operations and much more.
The use of geospatial data provides deep insight into the logistical, legal, and commercial relationships between corporations and facilities of different companies all over the world.
Location intelligence and foot traffic analytics have revolutionized the way in which businesses generate competitive advantages within the various business sectors, being able to infer the behavior and relationships of companies has become a reality thanks to this type of technological technique.
Location intelligence through techniques based on Big Data collects spatial data in order to improve the decisions made in logistics centers, allowing the use of location and its related data points, creating solutions and optimizing distribution routes.
This new technological tool finds its immediate application in space-dependent businesses, such as delivery and logistics companies. The data collected through infrastructure sensors, cameras and traffic mapping not only allows them to determine the best locations for their businesses, warehouses and centers, but also allows them to know why certain locations have a direct impact on the success or failure of a business.
The current global crisis in supply chains is forcing companies to manage their distribution methods by adopting a proactive approach based on Big Data and advanced analytics.
The supply chain crisis has resulted in restaurant chains and fast food outlets running out of key ingredients (e.g.
COVID-19 and climate change have directly impacted the supply chains of the sectors and industries that generate the most economic output.
Unfortunately, fiction has become reality, and a global pandemic coupled with sudden climate changes have increased these problems worldwide, also due to unforeseen events in logistics routes and the exponential increase in online shopping, forcing industries to increase the load of transportation, vehicles, staff and resources in general.
Unlike historical analytics, predictive supply chain analytics allows you to anticipate and prepare for the future, taking out the conjectures planning processes and improving decision making.
Predictive supply chain analytics use advanced technological tools such as machine learning, geomarketing, data mining that enables organizations to identify hidden patterns, understand market trends, identify demand, establish pricing strategies, achieve a high return on investment, optimize and reduce inventory costs.
The last mile is the journey of a product from the warehouse shelf to the back of a truck and the customer's door, thus being the final step in the operational process, when the package finally arrives at the consumer's door. In addition to being one of the keys to customer satisfaction, last mile delivery is the most problematic part of the shipping process.
It is one of the logistics areas where Big Data can have a real impact on daily operations, offering the opportunity to optimize internal processes and better control external factors, developing qualitative and quantitative improvements in operations, supply chain areas and logistics processes, bringing significant improvements in last mile deliveries.
Through geospatial data analysis techniques, CentralAmericaData carried out an analysis of five Walmart distribution centers in Florida, United States, with the aim of identifying patterns in the supply chains of these five centers and their relationships with commercial establishments and other logistics complexes in the State.
Through this analysis, whose objective is to show how geospatial data science techniques can be applied to solve problems in the logistics sector, the existing relationships between Walmart distribution centers and their supply sites were identified and characterized, so that different large commercial chains can evaluate and at the same time improve processes in their respective supply chains.
By analyzing the large volumes of anonymous data generated by mobile devices, it is possible to establish whether a distribution center has a commercial relationship with other logistics complexes, and even with establishments that serve the end consumer.
Using the most advanced Big Data tools, it is possible to understand the behavior of the supply chains of companies in the retail sector, since by monitoring delivery parts and counting mutual visits between suppliers and vendors, it is possible to identify and establish which are the most important relationships between distribution centers and points of sale to the end consumer, such as stores.
In Guatemala, according to the air transport union, the project of the new cargo airport to be developed in the Port of San Jose, Escuintla, is unfeasible in operational and commercial terms.
Salvadoran carriers estimate that between January and May 2021, the cost of freight between El Salvador and Guatemala has increased from $500 to $548, a rise that is largely explained by the increase in the price of diesel.
Representatives of the Asociacion Salvadorena de Transportistas Internacionales de Carga (ASTIC) state that in recent months the price of a gallon of diesel has increased by $0.63 in the central zone.
The Panamanian government announced that Grupo Rey plans to invest in the construction of a distribution center, which will be located in the community of Pacora on a 55-hectare plot of land.
According to the Government of Panama, the Ecuadorian consortium Corporacion Favorita, owner of Grupo Rey, which groups a chain of supermarkets and stores, is planning to execute an ambitious investment plan in the next few years.
Accurately calculating freight costs and delivery times to make online sales profitable for companies are, in this context of the e-commerce rise, some of the most important challenges for the retail sector.
The changes in consumer habits reported in the context of the new commercial reality, which arose quickly as a result of the Covid-19 outbreak and the restrictions imposed on mobility, have forced companies to transform the way they operate.
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