How Nana, a managed marketplace for skilled trades specializing in appliance repair, decreases dependency on engineering resources with Avenue

Jul 25, 2023

Nana Appliance Repair is a vertically integrated student-to-operator B2B managed marketplace for skilled trades, specializing in the appliance repair trade. With a dedicated team of 30 people, Nana aims to provide efficient services to its customers while ensuring the highest quality standards. We spoke with Maksim Pecherskiy, engineering manager, on how he implemented Avenue and saved engineering time.

PageDuty for ops teams

Before implementing Avenue, Nana relied on a data warehouse that was in the early stages of development, lacking a cohesive structure. Data access was facilitated through a custom JavaScript interface built in-house on top of MongoDB, resulting in a cumbersome and non-intuitive user experience. As a consequence, the team struggled to make data-driven decisions, impacting their ability to optimize workflows and allocate resources effectively. “All hands on deck” situations took place in Slack which resulted in a lack of clear ownership and resolution and employees were unable to use SQL to query their data.

Prioritizing success factors with streamlined work orders

Nana recognized the importance of two key factors for their business success. Firstly, the company needed to maintain a high average hourly rate for their skilled technicians, which necessitated a steady stream of lucrative jobs. Secondly, Nana aimed to expedite work order completion by minimizing manual processes and introducing automation to leverage their operational teams' capabilities.

Taking the work out of the engineering queue

When Nana adopted Avenue, both ops and tech teams immediately witnessed improvements in their operations and decision-making processes. The vendor team utilizes Avenue's to manage partnerships with companies providing jobs, manage technicians, and market governance. While the engineering team uses Avenue to keep track of costs and ensure data quality. Tasks that would equate to a “Large T-shirt size” for engineers can now be done in a “Small T-shirt size” amount of time by non-engineers.

Intelligent Business Rule Monitoring: Nana leveraged Avenue to monitor complex business rules and automate decision-making processes. For instance, when a work order was created with no available professionals within a reasonable distance, Avenue automatically flagged it for cancellation, reducing penalties and enabling efficient reassignment of work orders. This proactive approach helped Nana avoid unnecessary delays and improve customer satisfaction.

Seamless Communication and Workflow Automation: Avenue plays a pivotal role in facilitating communication between Nana technicians (who are 1099 employees) and internal teams. For example, the parts team needed to notify technicians about the availability of parts for pickup as soon as they become available. Avenue allowed Nana to create automated email notifications based on predefined conditions, eliminating the need for a complicated workflow in Customer.io. This streamlined communication process improved overall efficiency and reduced the risk of miscommunication.

Cost Monitoring and Data Quality Assurance: By utilizing Avenue, Nana gained visibility into their Snowflake costs and received alerts for any unexpected spikes. This proactive monitoring helped the company identify and address cost anomalies promptly. Additionally, Nana leveraged Avenue's data quality monitoring capabilities to validate and verify their DBT tests, facilitating reliable data analysis and decision-making.

With Avenue, Nana reduced their dependence on engineering resources by automating critical processes, resulting in improved efficiency and reduced manual workload. The implementation of real-time alerts and intelligent business rule monitoring enabled Nana to make data-driven decisions, optimize workflows, and improve overall customer satisfaction. Furthermore, Avenue's seamless communication features and workflow automation streamlined interactions between technicians and internal teams, enhancing operational efficiency.