Tech support case study

Cut support costs in half

Large indoor retail and logistics company is using Formant to manage their robot operations, streamline technical support, and improve customer satisfaction.
As their fleet grew, this retail and logistics company struggled to stay on top of technical support and respond to issues quickly which impacted uptime, productivity, and customer satisfaction. This forced the organization to scale operations and field teams linearly, sacrificing the unit economics and productivity.

The operations team was faced with:

Tools were complex and insufficient to manage operations at scale.

Operators had a complex ecosystem of tools including in-house developed applications and scripts, native ROS tools like RViz, and log analysis tools such as LogDNA and Grafana running on a variety of systems including native Linux machines, making their workflow even more complex. Requiring operators to switch between systems and tools to resolve an issue.

Lacked timely access to robot and field data to investigate issues.

The organization had no way to access robot data if the robot was offline. To retrieve specific logs or run diagnostic scripts the operator typically had to make a call to the site or deploy a field resource to turn the robot on, which often took days.

Bandwidth costs were exceeding budgets.

To ensure each team always had the data they needed and nothing was missed, all types of data were captured and data acquisition was set to “always-on”. Treating all data the same and capturing it all lead to excessive bandwidth costs.

The solution

The Formant data and operations platform transformed the unit economics and cut support costs in half by centralizing fleet operations, improving speed to issue resolution, and controlling bandwidth costs.

Command center

Replaced a number of native Linux servers and disparate tools with a single web-based monitoring and diagnostics visualization solution to debug, collaborate and understand the issue quicker. Removed the need to switch between tools which reduced complexity and modernized the support process, increasing the overall productivity of the team.

Remote commands

Improved access to robot data and reduced the number of field visits by issuing remote commands that run diagnostics scripts or retrieve logs. If the robot is offline the command is queued in the cloud until the device is back online, automating a once manual and time consuming process.

Customized ingestion

Optimized data ingestion based on importance, resolution, and connectivity. Triggering ingestion based on events, ensuring low priority data is ingested at a lower resolution, and implementing on-demand ingestion for high priority, high-resolution needs ensures the right people get the right information at the right time.

The impact

Increase support velocity

Resolved issues in half the time with a single platform that supports event-based navigation & search workflows, advanced visualizations, and managed remote diagnostics & data acquisition requests. Scale resources quickly and empower junior team members with a sophisticated yet easy to use solution that integrates with existing ticket system and promotes collaborative resolution of workflows.

Eliminate field visits

Due to an increased capacity for understanding the true root cause of an issue remotely, field support teams saw a significant decrease in on-site visits that were previously necessary to diagnose problems. Both the number of visits and the length of time spent on-site was seen to decrease. Remote monitoring also allowed teams to spend less time in the field during the first days of a new deployment, or eliminate the site visit altogether.

Reduce bandwidth expenses

Formant’s on-demand data ingestion allowed for a massive decrease in the volume of data collected from the field - most of which was not actually useful or necessary but had to be collected just in case. Instead, support teams configured always-on data acquisition to only occur for the most valuable data and implemented manual or triggered historical uploads for the larger, less immediately necessary data.

See it in action

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