Use Case

Logistics tech companies reduce engineering time by 11 hours / month

Ian Yanusko
March 29, 2023
4
min read

Background

The Latin American e-commerce tech scene is ops-heavy. With cheap cost of labor comes a high number of ops workers that rely on familiar multi-purpose tools: mostly Google sheets and Notion.

The Problem

When ops teams grow so large, engineering can struggle to keep up with internal tool demands. We have worked with companies where 100-member ops teams rely on 3 engineers to maintain all of their data pipelines, including data fed through internal tools. And since ops teams heavily prefer easy-to-use tools like Google Sheets and Notion, the reality is that data often gets siloed in every-multiplying spreadsheets. It quickly becomes a headache for engineers to not only design, create, and maintain internal tools, but also convince huge ops teams to migrate their tooling.

Use Case

We stumbled on this same use case for e-commerce startups in Colombia, Brazil, and Mexico. 

Logistics startups have a ton of workers on the ground: field operations, warehouse operations, delivery operations, etc. Updating status along the lifecycle of an order, especially between teams, is a constant pain point, but one that can be solved when teams are able to use familiar tools that are syncing with a single source of truth. For example, when an ops worker acquires an order from the supplier, he can update the status on the Notion mobile app. That status will sync to Postgres, and from there it will update the customer (through a user-facing portal) as well as any other ops teams that are syncing from Postgres. Similarly, when a package is damaged in the warehouse, someone can update a Google sheet that syncs with Snowflake to indicate inventory changes and potentially trigger a restock alert. 

The common ground between these two examples is that in both cases, ops teams need to be able to read and write real-time data across an order’s life span. Engineers can either create and maintain internal tools from scratch and convince ops folks to use these tools, or they can integrate their data store with the tools that ops teams already love. In LATAM, we see that more and more eng teams are opting for the second option.