To pinpoint companies in need of SVA's services, numerous Excel files from multiple sources were previously compiled, transformed, and analyzed manually. This labor-intensive and time consuming process involved cross referencing data, cleaning inconsistencies, and consolidating information to identify potential clients and market opportunities.It required reviewing thousands of records with varying formats and quality and performing repetitive data manipulation tasks, which increased the likelihood of human error and limited the team's ability to act quickly on insights.

To address this challenge, our team collaborated with SVA to gain a comprehensive understanding of the key metrics and criteria used to identify at-risk companies. This involved working closely with stakeholders to map out existing workflows, define business rules, and prioritize the data points most critical to decision-making. We developed a Power BI solution that integrates data from Excel workbooks and Salesforce, enabling the creation of dynamic visuals for SVA's reporting needs. This integration allowed for real-time access to a centralized dataset, greatly improving efficiency and data accuracy. These visuals included maps to display the geographic distribution of companies, tables summarizing critical company information, and customizable filters to refine results based on specific risk indicators or business attributes.