Byrider and Data Analytics

The Overview

Byrider is America’s largest buy-here, pay-here dealership network. Founded in 1989, Byrider automotive sales and service franchises have sold more than 1.2 million cars at more than 150 locations across the country. With the vision to be the consumer choice in helping people get a fresh opportunity to finance and own a quality vehicle, Byrider offers a range of fully inspected vehicles, backed with warranties, service options, and flexible financing, credit, and payment options.

The Challenge

As part of their ongoing strategy to modernize and transform their business, Byrider previously partnered with 2nd Watch to develop a digital platform for data consolidation. We created a new data model and designed ETL processes that enabled Byrider to take full advantage of the scale and speed of their Amazon Redshift data warehouse. While the data warehouse was a significant step forward, Byrider did not have the analytics and BI necessary to operationalize the data they sourced.

Without a unified data platform, internal stakeholders either had to piecemeal their analytics based on a variety of sources and methodologies or burden database developers and DevOps teams to help track down useful insights. Certain reports were generated directly from the online transactional processing (OLTP) system, or client-side applications, rather than the warehouse. Due to the origin of these reports, their history and context were difficult to understand. Another reporting was done in static spreadsheets with limited functionality and flexibility where, again, source tracking and logic were impossible to comprehend.

Without a universal platform, collaboration was stifled between teams and data silos grew. Contradictory outcomes and data discrepancies revealed inaccuracies that weren’t just confusing but threatened how, where, and for what purposes the data should even be applied. To derive reliable and actionable analysis from Byrider’s data sources, they needed to overhaul their analytics platform.

The Solution

2nd Watch consultants from the Data Insights practice implemented Looker, a BI software and big data analytics platform, to address the challenges faced by Byrider. We focused on utilizing LookML, Looker’s data modeling language to create a semantic layer for capturing business logic, rather than defining it in data warehouse dimensional tables. This approach empowers business users with powerful analytics tools. Armed with these tools, Byrider’s data teams can explore different aspects of the business and add new business logic, while establishing and maintaining their warehouse as a single source of truth.

Using a handful of fact and dimensional tables in the warehouse, we built dozens of modern dashboards to capture a range of diverse and complex facets of the business. We used Looker’s Git-based workflow to create and test dashboards based on constant feedback from stakeholders before going into production. With Looker’s semantic modeling layer, Byrider can standardize common metrics, definitions, data models, views, and dimensions across all user experiences. The interactive dashboards now offer new functionality and opportunities for collaboration that go well beyond static spreadsheets.

Byrider can get both high-level summary data and granular specific data, as well as tracking and source information, within the same dashboard. Filters, windows, and interactive map options are available for displaying time series and location-related data with clear visibility to enhance user understanding. For security and access, 2nd Watch enabled user attributes and row-level security. With these controls, the same dashboards can be accessed by multiple users, but users only have access to the data that is relevant to them. The result is custom dashboards that meet the unique business needs of Byrider and its internal teams and users.

2nd Watch consultants also took advantage of Looker’s advanced features to incorporate logic that could not be captured in their previous reporting processes. For example, one time-sensitive dashboard needed to track the number of business days remaining ahead of a set deadline. Byrider struggled to define business day logic in their old system and used calendar days instead, resulting in inaccurate measures. To solve this problem, 2nd Watch created a lookup table in Looker using its derived table feature. This allowed the dashboard to track remaining business days instantly and reliably, as intended. Because the data was derived from the date dimensional table in the warehouse, it reflects changes to company holidays or workday schedules in real-time for immediate accuracy.

The Outcome

After partnering with 2nd Watch, Byrider can harness their data for smarter decision-making to more efficiently and effectively impact their bottom line. With Looker as their BI platform, employees can participate in cross-team collaboration using a common data source with shared visibility into analytics and logic. Streamlined access to democratized data allows developers and DevOps teams to focus without distractions from people seeking reliable data. Resources can be reallocated toward growth and business outcomes, rather than wasting time chasing discrepancies and resolving conflict. Overall, reliable dashboards and analytics tools tackle business challenges intelligently, quickly, and cost-effectively for better business results.

Without manual legacy processes complicating insights and upstream database components, Byrider can achieve cost-efficiency through automation and innovation. Looker’s semantic model greatly reduces the coupling between data sources and BI, thereby increasing productivity and performance among teams. At the same time, the unified platform reduces redundancy, encourages data sharing, and improves the integrity of the data warehouse. Through Byrider’s partnership with 2nd Watch, they are finally able to make use of their data to uncover new insights and define new business logic. Byrider plans to apply these new capabilities to gain a significant competitive advantage in the market by being able to better serve consumers.