In the intricate and ever-shifting regulatory reporting landscape, accuracy is paramount. Yet many energy enterprises face challenges of meeting reporting deadlines and avoiding fines.
For one energy enterprise with a looming deadline, our team harnessed data analytics capabilities to enable this precision and pave the way for a long-term shift in reporting.
The task at hand was daunting: support regulatory reporting on surveying assets and fault resolution, all within a tight two-month window. The client's challenges were formidable, from poor data quality to siloed systems and regional process disparities. Their reliance on error-prone Excel only compounded the complexity.
Mesh-AI's strategy wasn't just about meeting the deadline; it was about fundamentally transforming how data was leveraged. By understanding the technical intricacies but also the underlying processes and cultural dynamics at play, we took a holistic approach, laying the foundations for a long-term solution.
Workshops were conducted to unravel the intricacies of surveying and fault resolution processes across multiple regions. Data consolidation into a relational database, followed by initial data cleansing, laid the groundwork for in-depth analysis. Even the initial analysis revealed startling insights - over half of surveys conducted deemed assets out of scope.
The team encountered a host of challenges, from inconsistent data formats to the unexpected prevalence of test data. By following an iterative process of discovery, we not only refined the data but also deepened the team's understanding of the client's operations, paving the way for more informed decision-making.
Data analytics emerged as the linchpin of success. With a pragmatic approach to tooling choices, favouring easy to deploy solutions like AWS Aurora and databrew for transformative insights.
Exploratory data analysis was the key to this project. While the workshops were informative, data analysis revealed further nuances in the data. By remaining curious we developed a deep understanding of the relevant data and proposed a well-informed methodology for building this report.
By interrogating assumptions and challenging conventional wisdom we discovered unexpected trends and patterns that had previously gone unnoticed. Our tooling allowed us to establish transparent, repeatable transformations which would support the accuracy of the report and the ability to understand the figures.
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With meticulously documented reporting, fortified by a robust methodology, stakeholder confidence in the reporting and insights grew. Individual figures were accompanied by a narrative of lineage, empowering the client to navigate inquiries with ease. Having laid the groundwork for data proficiency, we were able to offer recommendations for specific long-term data quality enhancements to address quality and accessibility concerns.
The quality of reporting was greatly enhanced in the short term. But with a shift away from Excel and adopting a new approach to data analysis and transformation, the client not only met regulatory requirements but set themselves up for future success in their reporting and analysis to support growth and innovation.
In the complex realm of regulatory reporting, data analytics is more than just a tool, but a catalyst for long-term transformation. Mesh-AI's journey with the energy enterprise underscores the importance of the curiosity, pragmatism, and precision inherent to data analytics. As businesses embark on their own data-driven journeys, the right approach, even with a myriad of challenges, can help extract more acute insights for more informed decision making.
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