When a business says it's "data-driven," it means it makes decisions based on facts rather than guesswork or intuition. That's because data helps organizations understand how they run, what their customers want, and how they manage risk.
But turning those facts into smarter operations requires a skilled data engineer.
For Natapong Sornprom, a data engineer at IKEA North America Service, the key is bridging the gap between technical expertise and business strategy. Beyond simply presenting numbers to executives, Natapong has designed and developed pipelines to connect data systems and enable rich, data-driven insights across the organization. He's also played a key role in the analyzing of supply chain data to help Chevron save hundreds of thousands of dollars.
Learn how Natapong's blend of technical innovation and effective communication has helped some of the biggest multinational organizations in the world use data to make better decisions, improve their products, and stay competitive.
How Natapong Built His Expertise in Data Engineering
Natapong began his career with a degree in petroleum engineering and a role at Chevron in Bangkok, Thailand. He worked as a drilling engineer and later moved into supply chain management, where he first learned how complex data visualization tools can actually help businesses solve their problems and grow.
Natapong then moved to Chicago to earn a Master's in data science. During his studies, he worked at Argonne National Laboratory under the U.S. Department of Energy.
"Collaborating with brilliant minds, including peers from institutions like MIT, was both humbling and inspiring," Natapong recalls. "Seeing my contributions featured on Argonne's website reinforced my passion for data engineering and its ability to solve complex challenges."
After he earned his degree, Natapong joined a Chicago startup, CDL1000, where he worked on machine learning and data analytics projects. Today, he is a data engineer at IKEA U.S., leading projects to improve supply chain transparency and create faster data systems.
Employing Automation at Chevron
At Chevron, Natapong helped transform complex, disparate data into practical solutions. For example, in one major project, he led the implementation and adoption of robotic process automation (scripted bots that execute rule-based tasks like filling out forms and generating reports), combining Excel macros and custom scripting to automate procurement processes.
He also brought together supply chain data like invoices, products, purchase orders, inventory, performance metrics, supplier information, and market demands to help Chevron make informed decisions about its inventory and risk management.
In order to make this complex data digestible for warehouse teams and decision-makers, Natapong used Power BI—a tool that turns numbers into clear visual reports—and built dashboards to track inventory and monitor how well Chevron's warehouses were running.
Using Data for Logistics and Pricing at CDL 1000
After his time at Chevron, Natapong joined CDL 1000, a logistics company in Chicago that focuses on drayage (transporting goods from ports), intermodal transport (using multiple forms of transportation like rail and trucking), and warehouse operations. CDL 1000 helps businesses move and store goods while keeping track of each process along the way.
Natapong led a team to build dashboards in Power BI (interactive data visualization software) that gave decision-makers a clear and instant view of logistics data. These dashboards tracked container movement, warehouse operations, and shipping schedules, which helped CDL executives and teams make timely decisions about where to allocate resources, how to build delivery timelines, and how the supply chain was functioning overall.
Natapong also worked on a dynamic pricing system based on supply and demand to make sure the company charged the right amount at the right time. This meant CDL 1000 wasn't undercharging when demand was high or overcharging when it was low, helping them stay competitive while maximizing revenue. To make this work, Natapong gathered data like order records, inventory, industry trends, and fuel prices. He then used time series forecasting to predict future outcomes and allow CDL 1000 to set smarter prices.
To free up the account management team, Natapong developed tools that could automate their more routine tasks, like organizing shipment data and generating operational performance reports. This gave them more time to focus on strategy instead of busy work.
To do this, Natapong used Cloud Composer (a tool that helps schedule and monitor tasks within a workflow) and Streamlit (an open-source Python framework that makes it easy to build interactive apps for data visualization and analysis).
By putting these tools together, Natapong created a system that dramatically reduced data processing time and sped up repetitive tasks, streamlining operations and empowering the team to get their work done faster and focus on growing relationships with clients.
Improving Supply Chain Visibility and Data Security at IKEA
At IKEA, Natapong developed and maintained a hybrid cloud solution to extract, transform, and load data into a data warehouse. In doing so, he achieved sub-50-second pipeline latency, enabled cost visibility, and enhanced supply chain transparency.
In conjunction with these contributions, Natapong also set a new standard for cross-functional communication within the company, recognizing that organizations often struggle to align technical capabilities with business goals, leading to inefficiencies and missed opportunities.
"One of the biggest challenges I've faced in my career is bridging the gap between technical and non-technical communication," explains Natapong. "Learning how to explain complex technical achievements in a way that resonates with non-technical audiences has been a significant element of my professional growth."
To overcome this, Natapong takes a practical, visual approach to communication, using tools like Miro—a digital whiteboard platform for brainstorming and collaboration—to present complex workflows in a way that's easy to follow.
This approach not only brings teams together but also makes it easier for Natapong to explain technical concepts to people without a technical background. For instance, when he developed a prototype data pipeline migration—a test version of a system that moves and processes data between platforms—he used it to show stakeholders how the system would work in practice.
By breaking it down step by step, he helped them understand how the pipeline would power a business intelligence solution for IKEA's U.S. distribution centers and why it mattered for their goals.
"These experiences have truly transformed my professional journey, sharpening my communication skills and enhancing my ability to lead diverse teams," Natapong concludes.
Turning Data into Decisions with Natapong Sornprom
Businesses can have access to mountains of data and still make poor decisions. Without the right people in place to enable, interpret, and use that data to make practical improvements to business operations, data is just unused potential.
Natapong Sornprom's career shows how a skilled data engineer can bridge the gap between raw data and meaningful business outcomes, and his accomplishments speak for themselves. He's a Gold Winner at the Titan Innovation Awards for his cloud-based analytics solutions and the author of a research paper exploring the role of AI and cloud computing in logistics and supply chains.
To explore more of Natapong Sornprom's work, follow him on Linkedin.
