In order to gain advantage in today’s global environment, food supplying companies and railway authorities have to adopt AI/ ML analytics solutions that will optimize their transport operations. The goal for undertaking such a machine learning approach is to provide their operations teams - information essential to make intelligent decisions in real time.
Delivering food products to different locations involves keeping track of different routes, field workforce and cooler facilities - in order to make each delivery a success. This demands high-quality delivery of thousands products to millions of customers worldwide, from several distribution centers using different transportation means.
Problems and issues
The supplier’s tasks include procurement, routing, transport, stock and inventorymanagement that run in an ERP system. The main operational efficiency challengesinclude:
Manual tracking of all warehouse items is almost impossible. There is no real-time information of stock availability and list of undelivered items.
No information about train statuses, such as time-taken for delivery, trainhalt period, items damaged during the transit, etc.
Lack of freezer (coolant) temperature data obtained by the trains. If asupplier has such data, it would track and identify the optimal type for thedelivery of food items.
There isn’t unified data view at a given point of time to get a complete viewof the transport. If the supplier has such data, it would make the rightdecisions at the right time.
Missing information for the list of damaged products and the quantitypertaining to it in real-time.
AI / ML as a Viable solution
A well-designed and developed AI / ML solution will address all drawbacks smartly andwill provide a machine learning environment that will:
Provide intelligent decision-making; by utilizing the power of intuitivegraphics and reports - generated from analysis of large numbers ofcustomers, inventory and workforce data.
Enable consolidated view of the data retrieved from multiple sources; in theform of interactive dashboards.
Create efficient supply chain operations, with real-time insights ontemperature levels and train schedule, thus maximizing operationalefficiency.
Enable management of thousands of products through a unified dashboardview, that will display the damages and losses incurred every month.
Bring data from the food delivery process that will help determine thetemperature level patterns, and ensure minimal risk of customers returningthe items.
The Benefits
The AI/ML solution will provide a detailed stock damage analysis for a large number ofproducts. The AI analytics can provide critical insights into food delivery operations;starting from route planning, warehouse to successful fulfilling of clients orders. Withsuch AI analytics solutions, the suppliers will experience huge potential benefits thatwill improve their operations team in intelligent decision making, and efficientmanaging of their supply chain operations.
Fast insights from AI analytics
AI analytics can process huge sets of data in routeplanning and resource management, by acquiring access to all relevant databases anddatasets. Different data formats can easily be loaded and combined into the analyticstool. Also, different machine learning algorithms (cluster analysis, linear regression,decision trees, neural networks) can be applied for big data analysis.
Using different Data sources
Suppliers can increase the productivity of their dailyoperations by including the company’s internal data in the analyses. The analytics toolcan create a comprehensive and flexible mapping of their internal processes, liketransport, storage and logistics. Also, they can import an external data set - (public orcommercial) that will assist them to discover new areas of planning and management.
Reporting and Visualization
Different AI tools (e.g. Tableau) can generate reportswith visuals based on user’s search and performed data analyses. The reports can becreated in real-time and with just one-click. The users will have it in his dashboard interms of seconds. Thanks to advanced visual features, the suppliers can integrate thedata into their existing information system.
