Development of a Data Analytics Dashboard Solution for Ecom Express
Overview
Our client, Ecom Express is one of the reputed logistic brand in India. To enable streamlined and smooth order picking and delivery operation, the company needed a data analytics dashboard. This helps them to process large datasets to drive crucial insights. This would facilitate more efficient resource allocation and decision-making in the company’s logistic businesses. However, the client’s constant expansion, leading to numerous data mismatches. They hired OrangeMantra, an experienced provider of dashboard solutions. By teaming up, Ecom Express were able to access an advanced data analytics platform to automate backend work. The solution was a powerful combination of big data technology with supply chain management. The company leveraged our expertise, to gain unified, real-time insights into millions of shipment records.
Transportation
eCommerce Solutions
Our Process
The OrangeMantra team of developers, and testers connected with Ecom Express team to gather client’s business and technical needs. Next, we provided a detailed roadmap for solution development. After its approval by our client’s decision makers, our team set to work, improving, building on, and testing the data analytics solution. We started by building and analyzing our client’s data lake for collecting, accumulating, and storing inventory records. The metrics gathered ranged from business and sales data to technical information.
Conceptualization
Regular sessions with stakeholders were performed to identify business goals and desired analytics metrics. Analysis of existing data sources and additional data integration requirements.
Design
Collaboration with client on design elements was done to build an engaging and user-friendly dashboard interface. Incorporation of key performance indicators (KPIs) and appealing visualizations.
Development
Creation of functionality to forecast demand, estimate delivery times, and identify potential issues was the next step. Iterative testing for the refinement of models and to achieve accuracy was performed.
Deployment
Rigorous testing of data relevancy, accuracy, dashboard operations, were performed. Gradual deployment with continuous monitoring was done for addressing issues or optimizations.
