Data Visualization for Revenue Consolidation

Introduction

A global market leader in Insurance Brokerage and our engagement was with their Middle East and North Africa business unit

Revenue consolidation from three systems is integrating data from different sources.

• Data Integration

Integrating data from different sources. Each system had its own data structure, formats, and terminology, making it difficult to merge and reconcile the data accurately. Ensuring data consistency, resolving data conflicts, and mapping data fields between systems pose significant challenges during the consolidation process

• System Compatibility

Ensuring that the systems can communicate effectively and that data can be accurately extracted, transformed, and loaded into a unified repository

• Data Quality and Cleansing

Inconsistencies, duplicates, and inaccuracies in data across the three systems

CodeBoard Tech built Python based system which can do complex macro front end user analysis. This included developing a robust data integration strategy, leveraging compatible tools and technologies for seamless data flow, implementing data quality and cleansing processes to ensure accurate and reliable data, and establishing clear business rules and requirements for revenue consolidation.

• Enhanced Data Accuracy

Improved data accuracy by eliminating duplication, inconsistencies, and errors. It provided a single, reliable source of truth for revenue-related information, enabling better decision-making and financial analysis.

• Improved Financial Visibility

Enabled better tracking of revenue trends, identification of growth opportunities, and improved financial forecasting.

• Streamlined Processes

Reduced the complexity of managing data across multiple systems, eliminated manual data reconciliation efforts, and saved time (weeks to hours) and resources by automating data integration and consolidation tasks periods of high demand or rapid growth.

• Enhanced Decision-Making

Allowed stakeholders to assess the profitability of different products, services, or business units, identify underperforming areas, and make strategic decisions to optimize revenue generation.