About Arrive Logistics
Founded in 2014 with a vision to redefine transportation logistics, Arrive Logistics boasts over 3,500 customers and 60,000 carriers. In 2021, the company exceeded $1.6 billion in revenue, a testament to its robust market presence and growth trajectory.
The Challenges
Despite leveraging Snowflake, one of the most advanced data warehouses available, and having an exceptional data team, Arrive Logistics was inundated with requests from business teams. The high demand for data consistently outstripped the team’s capacity to deliver timely insights.
Demand for Rapid Insights Outstripped Supply
Arrive Logistics maintained comprehensive data assets and BI dashboards. However, the continuous requirement for more tailored insights posed significant challenges. For instance, the need to analyze support call data to enhance service level agreements (SLAs) necessitated the creation of new data pipelines. Typically, this process would take 2-4 weeks to complete.
The Data Engineering Team Was Oversubscribed
The data engineering team was perpetually overextended, prioritizing maintenance of the existing data platform and the development of new pipelines over strategic initiatives. This imbalance often resulted in a trade-off between addressing immediate needs and focusing on long-term priorities.
Manual Integration in the Last Mile of Analytics
The integration of analytics into daily business operations remained a manual and labor-intensive process. Business teams required data to be accessible and up-to-date within the applications they used daily, such as CRM systems, Google Sheets and Slack. The need for custom integrations to make data actionable in these platforms frequently became a low priority.
Exponential Growth in Data Management Costs
As Arrive Logistics expanded, so did the scale of its operations and the complexity of its data needs. The company experienced annual revenue and data footprint growth, typically doubling each year, with analytics assets increasing fourfold annually. This rapid expansion rendered traditional data sync tools inadequate and expensive to maintain, as they lacked the agility to develop new connectors and adapt to evolving requirements.
Cumulative Impact on Business Performance
Collectively, these challenges led to an 8-10x year-over-year increase in the volume of data processed. While this data was a crucial asset for enhancing business performance and maintaining a competitive edge, the existing tools and processes were no longer sustainable or cost-effective.
The Solution
Arrive partnered with Savant to refine their data management processes using our no-code analytics automation technology. This full-stack platform facilitated seamless data sync, analytics and delivery, allowing Arrive’s analysts to automate end-to-end dataflows daily and deliver insights more efficiently without overburdening the data engineering team.
Insight Generation Time Was Reduced From Weeks to Days
By integrating Savant’s advanced analytics automation, Arrive was able to significantly expedite the analysis of new business strategies, particularly in pricing adjustments. This capability enabled the quick aggregation and analysis of diverse data sources, which traditionally would have taken weeks to process. As a result, within just one month, Arrive generated over $500,000 in new revenue opportunities by rapidly deploying new data pipelines essential for testing and refining these strategies.
Developed Over 25 Analytics Bots To Streamline Operations
In the first quarter of implementation, the Arrive team developed over 25 analytics bots on Savant’s platform, significantly enhancing operations in key areas such as marketing, sales, HR, finance and product analytics. Each bot saved at least 30 minutes of manual analytics work per run. Operating numerous times throughout the year, these bots collectively saved approximately 450 hours of manual labor each month. Annually, this automation reclaimed over 5,000 hours, significantly freeing up time for strategic business initiatives.
Decreased data Engineering Workload
Arrive Logistics was able to autonomously extract, transform and load (ETL) data, perform analytics, and manage reverse ETL processes without writing any code. This significantly decreased their reliance on data engineers, reducing demands on the engineering team by at least 25%.
Cut Data Management Costs by 25%
Savant’s bi-directional connectors have optimized data synchronization operations at Arrive, especially in systems with large data volumes or those traditionally unsupported by other tools. This efficient approach decreased data infrastructure costs by 25% over the period of 12 months, despite an 8-10x growth in data volume.
Established Data Governance and Best Practices
By leveraging Savant’s platform, Arrive has been able to implement robust data governance and best practices more effectively, avoiding the pitfalls of ad-hoc, unsanctioned data solutions often created by business teams. This strategic approach helps ensure data systems are scalable, maintainable and properly documented from the outset.
