Neev implemented a system for estimating cost of logistics for a leading supply chain analytics company. Neev developed a web portal that houses a cost estimator. This estimator assists in quantifying the sourcing events by estimating the price a shipper has to pay for over-the-road truckload moves.
Chainalytics is a global leader in providing services in the areas of supply chain consulting, market intelligence and analytics. Chainalytics helps companies transform their supply chains. They have a presence across North America, Europe and Asia.
A business when looking at sourcing events needs various metrics to enable it to decide on the costs it could incur and also an understanding of the current market trends in logistics.This very need was catered to by the implementation of the MBB model for the client’s existing application by Neev. Model-Based Benchmarking is a statistical model that estimates the price a shipper may have to pay for over-the-road truckload (TL) moves. It analyzes millions of TL moves to analyze the effect of a specific shipment feature or management policy on the cost per load. This model can be used by organizations for benchmarking against market costs.
Neev handled the entire Software Development Life Cycle (SDLC) right from requirement analysis to deployment of this model in adherence to all set NFRs. Inbuilt design patterns that exist in .NET framework were used. UI/ UX was detailed out and created.Neev built a web portal that enabled visitors to use the rate estimator. The rate estimator built by us has two forms – Batch and Real Time. The Batch Estimator can execute varied lane data in high volumes. The data is input through an excel sheet and processed in batches, generating a combined result at the end. The Real Time Estimator can process data one at a time. This is useful in verifying metrics for a particular lane or a combination of input parameters. Stored procedures were used to expedite back-end data processing and the result was displayed as CSV files. WCF and REST services were also employed.
Implementation of LINQ and SQL bulk upload which were used to upload large volumes of records into the database in one go.