Overview
Effective data management is a persistent challenge for businesses across industries. For our client, a leading petroleum and petrochemical company in Thailand, the issue was particularly pronounced due to the immense volume of data generated daily. In some instances, for example in our case with the sales team, data collection was relying on manual processes that limited efficiency and scalability.
Manual data entry was both labor-intensive and time-consuming, often leading to errors that resulted in inaccurate quotations. These inefficiencies not only increased operational costs but also posed risks to the client’s ability to manage the growing volume of data effectively. To address these challenges, the client needed a more streamlined and reliable approach to data handling.
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Our solution
We developed a quotation engine designed to streamline workflows by consolidating data from manual processes and various internal platforms. This solution automated integration and calculation tasks, ensuring accurate results, eliminating manual errors, and significantly improving client satisfaction
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Higher Close Rate, Increased Customer Satisfaction Our quotation engine helped our client achieve higher closing rates and boost customer satisfaction |
Increased Workflow Efficiency We replaced manual operations with process automation to enhance workflow efficiency |
Eliminated Human Errors We removed human-made errors from quotations with system integration |
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Our Approach
To ensure a seamless engagement, our team first focused on understanding the client’s data integration and quotation production processes. This involved analyzing manual operations performed through Excel files and data sourced from existing automation platforms such as SAP and other machine learning systems.
Next, we combined multi-sourced data into an accessible data repository with system integration to ensure that manually inputted data were accurate before being executed and visualized on screen. Our automated data integration pipelines provided notifications when data was ready to be computed or when errors occurred.
Upon entering the data visualization process, our team categorized data by product type to ensure cohesion. After, we organized them into tables to create user-friendly visuals. Designed with the end-user in mind, the platform prioritized delivering the most relevant data insights, ensuring customers were presented with meaningful information upon logging in.
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Key Achievements
1. Navigating large amounts of data
Managing and processing large volumes of data were key challenges in this project. Leveraging our extensive experience in handling large-scale projects, our team of solution architects effectively coordinated efforts to ensure seamless data ingestion. We approached the task systematically, applying proven methodologies to streamline research and data management. This allowed us to accelerate the early stages of data processing and set a strong foundation for the project’s success.
2. Handling complex data
In addition to managing the large volume of data, our team faced the technical complexity of implementing the client’s specific business logic. Despite the challenges, we drew on our expertise to navigate these difficulties and maintain project momentum. When additional clarification from the client was needed, we quickly integrated this new information into our approach, allowing us to stay on track and deliver the project on time.
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