Overview

During deployment of an automation system that supported part of a customer’s box packing workflow, I helped redirect a product feature based on customer discovery.

The original plan focused on building a performance dashboard, but customer conversations revealed something different:

They didn’t want another dashboard. They wanted access to their data.

This shift led to the introduction of a data export capability that better aligned with real customer workflows.

Note: Project details have been generalized to remove sensitive information.

Context

System: Industrial automation platform

Environment: High-throughput packaging site

Users: Machine operators, process engineers

Stakeholders: Engineering, field support, sales, customer teams

My Role: Senior Applications Engineer bridging customer and internal teams

The Original Assumption

We believed customers needed:

• A built-in dashboard

• Usage metrics over time

• Visual performance tracking inside the UI

The goal was to demonstrate value through visualization.

What We Discovered

During deployment discussions and early usage reviews, customers repeatedly asked:

• “Can we pull the data out?”

• “Can we analyze this in our own system?”

• “Is there a way to export this?”

That was the turning point - even when visiting their site during the initial system installs, I could see that they already had:

• Internal reporting systems

• Standardized analytics workflows

• Established performance review processes

The real friction wasn’t a lack of visualization.

It was data accessibility.

The Solution

We introduced a data export capability that allowed customers to retrieve collected performance metrics in a portable format compatible with their existing tools.

This enabled:

• Independent analysis

• Internal reporting

• Cross-team visibility

All without forcing the adoption of a new dashboard UI.

Outcomes

While exact metrics are confidential, the impact included:

• Improved customer adoption

• Reduced reporting friction

• Increased perceived system value

• Stronger alignment with customer workflows

• A scalable pattern for future deployments

Key Takeaways

• Customer discovery doesn’t stop after launch

• Features should enable outcomes, not just look good

• Sometimes the highest-leverage feature is the simplest one

• Workflow alignment drives adoption