Vava Cars
Vava Cars
Project overview :
Vava Cars, a prominent car selling company operating in Pakistan, caters to both Business-to-Business (B2B) and Business-to-Consumer (B2C) markets. The company sought to enhance its operational efficiency and sales and marketing funnels by implementing a data-driven approach. The primary goal of this project was to monitor and gain insights into the company’s operations using Power BI, a powerful data visualization tool.
What we did for this project :
For this project, we took the following key steps:
• Data Table Creation: We created a structured table in Power BI, featuring essential data, including purchase center name, car model, the number of available units, and purchase prices.
• Visual Representation: We developed a pie chart to visually represent the distribution of purchase centers across Pakistan. The chart provided insights into the allocation of resources and operations among key locations, including Gwadar, Islamabad, Karachi, Lahore, and Multan.
• Interactive Features: We added drop-down menus for car models, purchase centers, month, and year to enable users to filter and focus on specific data subsets.
• Data Analysis Tables: We designed two tables for data analysis. The first table displayed purchase center names alongside metrics like purchase inventory, total purchases, Cost of Goods Sold (COGS), sales, profit/loss, and the corresponding percentages. The second table showcased purchase center names, manager names, and their ranks, offering valuable insights into management and performance.
Project results :
The project yielded several significant results, including:
• Enhanced Operational Insight: The creation of a structured data table allowed for a comprehensive view of car inventory and prices at various purchase centers, aiding in operational decision-making.
• Geographical Allocation: The pie chart provided a clear view of how resources and operations were distributed among purchase centers across Pakistan, facilitating geographical optimization.
• Interactive Data Exploration: The implementation of drop-down menus empowered users to focus on specific data subsets, enhancing data exploration and analysis.
• Data-Driven Decision-Making: The data analysis tables enabled data-driven decision-making by offering insights into inventory, purchases, sales, profitability, and performance rankings.
• Operational Efficiency: The project contributed to improved operational efficiency, enabling Vava Cars to make informed decisions and optimize resource allocation.