Automotive Parts Retailer EDW Design & Implementation

The client operates in a fiercely competitive industry and environment. For over 75 years, they have been a leader in the automotive aftermarket industry in parts availability, price, and customer service. Its mission is to provide vehicle owners and enthusiasts with the products and knowledge that fulfill their needs at the right price.

Overview

This client sells automotive parts, accessories, batteries and maintenance items and gives customers access to thousands of parts that are available on a same-day or overnight basis.

Their growth plan and operational goals were hampered by an inability to access key data elements scattered in multiple silos and turn that information into insight. 

Strategy and Goals

With a strong commitment to growth, they are keenly focused on four key goals: raising sales productivity, expanding operating margins, generating strong free cash flow and increasing return on invested capital. The opportunity presented was to ensure the creation of an ETL architecture and design that would both meet the tight deadlines of their immediate effort and provide a strong foundation for future phases of the data warehouse project.

The technical environment represented challenges to meet those goals because it became increasingly difficult to get the data required by the business managers to forecast effectively. The intent was to provide an independent best practices review of the work performed. RCG wanted to ensure the creation of an ETL architecture and design that would meet both the tight deadlines of their immediate effort and provide a strong foundation for future phases of the data warehouse project. Simply stated, the business recognized that there were knowledge and communication gaps that needed to be bridged.

The company was working in silos and there was not an adequate system of control or standardization present. With a vast number of databases and spreadsheets that production reporting was done from, this represented a unique challenge to address. With all these parts and vendor relationships to manage, our client was looking for more efficiency and integration of data from one source system of record. It also needed to ensure data quality, integrity and reliability in order to update data daily and near-real-time when possible.  

The Final Results

As a result of the engagement, the client has a clear understanding and adherence to best practices vis-à-vis their ETL architecture and design. They also have a high-level view of the future work involved in creating a data warehouse. This project uncovered data inaccuracies that were corrected and demonstrated the importance of data governance.

RCG was able to guide the client in demonstrating the types of reports that could be generated and helped drive the understanding that could be gained from sales scorecards and dashboards. Another clear benefit realized through this project was an increase in productivity gained from standardized data use.

The Conclusion

The technical environment represented challenges to meet those goals because it became increasingly difficult to get the data required by the business managers to forecast effectively. The intent was to provide an independent best practices review of the work performed. RCG wanted to ensure the creation of an ETL architecture and design that would meet both the tight deadlines of their immediate effort and provide a strong foundation for future phases of the data warehouse project. Simply stated, the business recognized that there were knowledge and communication gaps that needed to be bridged.

The company was working in silos and there was not an adequate system of control or standardization present. With a vast number of databases and spreadsheets that production reporting was done from, this represented a unique challenge to address.

With all these parts and vendor relationships to manage, our client realized more efficiency and integration of data from one source system of record. It also was able to ensure data quality, integrity and reliability in order to update data daily and near-real-time when possible.