Legacy Analytics Stifled Agero’s Ability to Meet Growing Data Demands
Responding to more than 30,000 incidents every day, Agero’s dispatching platform combines data on a drivers’ location, their type of breakdown and their vehicle, as well as other information, to select the service provider best able to assist. Within minutes, the chosen provider is on its way to the disablement location.
As the company entered into a period of accelerated growth, it started a complete transformation of its platform to scale with the business. But it soon became clear that its data analytics stack was struggling to support this transition and meet increasing demands for data-driven decisions around product testing and development, accelerating user migration to the new platform, and more.
The company was sitting on a goldmine of data ripe for analysis, including the number of breakdowns and accidents, issue types, vehicle info, location, details about the type of service performed and who performed the service, and feedback about the service. However, “Data was largely siloed across teams and really only accessible to experts. Only a few people in the org. had access to data through SQL or were trained in specific tools,” explains Michael Bell, Sr. Director of Data Science and Analytics at Agero.
Agero’s existing data analytics tools were not delivering the self-service analytics workflow the organization envisioned and was struggling to achieve. “Using existing software tools didn’t make us feel like we were moving towards a self-service process,” says Bell. The result was dozens of risky and instantly outdated data extracts.
Scale was also a major issue. “We ran into situations using our tools where we would be running a lot of extracts to try to get data out of our data warehouse to run reports,” tells Bell. “All of those would be running at once on Monday morning and extracts would fail. Things would grind to a halt. This usually resulted in a flurry of emails reporting issues with a dashboard or a lack of availability of data, and our team would spend much of our time at the start of a week or especially month cleaning up the mess.”
Upgrade to a Modern Cloud Data Analytics Strategy Powered by Sigma
With accelerating growth and a significant organizational transformation underway, it was clear to the team at Agero that they needed to modernize their data analytics tool and move into the cloud. “When we saw Sigma, it became clear it could help us with our strategy of getting more people access to data when they need it,” Bell explains.
At the same time, Agero has strict stipulations with each client on how its data is utilized. Additionally, some of the data that Agero collects is considered client-owned data, so Agero must be particularly cautious with how the data is accessed and used. Increasing the number of people directly working with data while maintaining strict compliance posed a challenge.
Sigma’s modern approach to data governance struck the right balance between control and access that the Agero team was looking for. The spreadsheet-like UI empowers anyone in the organization to explore live data directly in Snowflake, regardless of technical ability. Data stays safe and governed inside the cloud data warehouse and can be queried at scale — no extracts required.
“After being in business for nearly 50 years, our teams can finally access and leverage all our legacy data to improve our products and services. Sigma helps give us that competitive advantage.”
Michael Bell, Sr.
Director of Data Science and Analytics at Agero
The team uses Sigma’s data lineage functionality to help manage governance and make sure teams use the most accurate and relevant data in their analyses. “It’s critical for us to thoroughly understand our data — where it came from, how it was derived, when it was generated, who created it, and what it means,” Bell explains. “In the past we didn’t know any of those details. Now we know exactly that this worksheet came from that dataset, who is using it, and how.”
This increased level of data access and transparency also helps Agero’s product team zero in on and fix bugs faster. For example, when an update to its platform broke some business logic, the team at Agero was able to quickly leap into action. “Well-governed data sets make it easy to find issues if there is something that doesn’t look right. Using Sigma, our developers can more easily debug issues and improve the quality of our product,” says Bell.
Another Sigma feature that has helped the Agero team optimize its resources and deliver better service to its customers and clients is conditional scheduling. “We always monitor data elements and search for anomalies in our platform, but we don’t want our product and operations managers to watch a dashboard all day,” says Bell. “Conditional scheduling allows them to go about their day-to-day work because Sigma automatically alerts our managers to critical issues in their regions and they can take immediate action.”
Conditional scheduling allows them to go about their day-to-day work because Sigma automatically alerts our managers to critical issues in their regions and they can take immediate action.
True Self-Service BI Leads to Rapid Product Insights and Development
Agero’s investment in a cloud data stack powered by Sigma is already paying off. “Using Sigma, we have five times as many people independently accessing and exploring data without having to go to data scientists and engineers to answer questions for them.”
One key area where Sigma is having a direct impact on Agero is in the development and roll out of its new dispatch platform. “Our team is able to ask questions, identify opportunities for improvement, create a hypothesis, develop an A/B test, and within minutes build a dashboard in Sigma to visualize those test outcomes. It allows us to iterate and improve our product very rapidly,” says Bell.
We have been able to reduce BI tooling costs by 50% over a short period of time
Sigma is also helping Agero operate and scale the platform efficiently with their service providers. “We have been able to reduce BI tooling costs by 50% over a short period of time. And, Sigma has been critical in reducing operational costs that were hindering the rapid roll out of our new roadside platform. Sigma helps us analyze which service providers are more or less engaged on the new platform versus our legacy platform. Our operations team gets a prioritized list of folks to reach out to help them make the transition to the new platform,” explains Bell.
Another area of cost and resource savings has been the reduction in volume of ad-hoc data requests and the time it takes to fulfill them. “It’s a much more collaborative process. At least half of the time now, I can just point someone to a resource in Sigma that they can leverage or modify to answer their question,” Bell says. “We can also sit down with someone to build a data set together and after that they’re up and running. This used to take weeks, but now it takes about 30 minutes. Some people don’t even need to reach out to me anymore for help because they have access.”
“We can also sit down with someone to build a data set together and after that they’re up and running. This used to take weeks, but now it takes about 30 minutes. Some people don’t even need to reach out to me anymore for help because they have access.”
Michael Bell, Sr.
Director of Data Science and Analytics at Agero
With accelerated, data-driven product development, empowered business teams that can explore data on their own, and the implementation of a modern data governance strategy, Bell summarizes Sigma’s impact on the company this way: “We’re early in our transition but we’ve seen quick adoption. Sigma’s really transformed the way our business interacts with data.”