Data workflows

Making new data useful enough to become a business capability

A new dispute data source became usable through collection, parsing, reporting, and UI workflow support.

At Midigator, the operations team needed to work with a new dispute data type called RDR. The project required collecting data from an SFTP server, parsing it, integrating it into existing and new data models, reporting on it, and giving users UI tools to manage the information.

The challenge was that the data could not just be pulled in. It had to be understood, structured, connected, and made usable inside a larger system. That meant thinking through backend services, data models, reporting needs, and frontend workflows together.

I wrote the technical designs for collecting and parsing the data, connecting it to the existing architecture, and reporting on what was collected. I directed my team on development and implementation, worked with design on the UI tools, and managed the integration between the data service and the user-facing tools.

The result was a successful project that created a new data and revenue stream for the company.

How this applies

The same pattern shows up in smaller business systems too.

The scale may change, but the work still starts the same way: understand what is really happening, organize the moving parts, then build the next useful thing.

MethodMade translation

For a small business, that might mean clearer service pages, cleaner intake, better follow-up, usable documentation, or one practical automation.

Understand the real situation

Start by separating the visible problem from the actual workflow, people, tools, constraints, and risks underneath it.

Organize the moving parts

Turn the scattered pieces into a clearer map: what exists, what matters, what is missing, and what should happen next.

Build the next useful system

Create the practical next layer: a page, process, automation, document, or tool that can be understood and maintained.

Use this thinking for

•Data cleanup
•Reporting dashboards

Helpful when you need

•Tool integration
•Intake workflows

Often connected to

•Operational visibility
•Scattered information cleanup

Proof notes

New data and revenue stream

Next step

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