Gripple

Gripple is a quintessential Sheffield success story. Born in 1989 from an ingenious invention for joining agricultural wire fencing, they have scaled into a global powerhouse. Today, they employ 850 people across 15 worldwide locations while proudly keeping their manufacturing roots in Sheffield.

But with incredible growth comes a predictable friction point: legacy infrastructure. Gripple was attempting to orchestrate a global marketing and sales operation using shared cells and disparate data.

The paradox of scaling is that the tools that helped you build the business are often the exact things holding you back from the next level. Spreadsheets don't scale. When data is siloed across different geographies, there is no single version of the truth. To sustain their trajectory, Gripple needed a central, strategic data platform accessible from anywhere on the planet—a unified warehouse that spoke one universal language.

Rather than rushing straight into code, we started with alignment. We embedded with Gripple in a discovery workshop to map out the real heart of the issue. If the vision isn’t shared, the software will fail.

Once we understood the exact friction points, we built a system focused entirely on automation, simplicity, and user empowerment.

Phase 1: The Dynamic Metadata Engine

Because Gripple didn't have a defined schema to start with, we had to build something highly adaptable. We created a metadata-driven solution powered by a dynamic set of rules that feeds directly into the new data warehouse. It doesn't force data into a rigid box; it adapts.

Phase 2: Drag, Drop, and Automate

We engineered an automated pipeline that creates a "star schema", allowing for clear, immediate dashboard visibility with perfect lineage back to the producing source system. Now, the Gripple team can simply drag and drop data into the platform. The system automatically extracts the essentials, organizes them against the schema, and eliminates the risk of human error.

Phase 3: Choosing Pragmatism Over Ego

We deliberately decided against creating a complex, bespoke application. Instead, we utilized Azure Data Factory. While this was actually one of our first projects using this specific tech stack, our developers embraced the challenge for a vital reason: handover. By using Azure Data Factory, we ensured that Gripple's internal team could easily maintain, own, and expand the platform the moment we stepped back.

We didn't just deliver a piece of software; we acted as a catalyst to accelerate and validate the brilliant work Gripple’s internal team had already started.

Evolutionary Analytics: By utilizing data dimensions and the star schema, Gripple can now track historical data evolution over time and instantly see how it affects end sales results—a feat mathematically impossible to do manually in a spreadsheet.

Seamless Expansion: Because the solution wasn't a hard-coded bespoke app, the Data Factory architecture plugs effortlessly into the next evolution of their business. They’ve already extended it to pull in data from two additional cloud-based applications.

Empowered Internal Teams: We handed a robust, easy-to-use platform back to the original internal team, who are now actively using, enjoying, and developing the application further. Our partnership got them to the finish line vastly quicker than if they had stayed totally in-house.

This project wasn’t just a business transaction; it was about radical collaboration. We partnered with a people-first company to transform a core operational process. We brought an endless curiosity to the table, learned a new technology stack on the fly, and fundamentally believed that the best engineering solution is the one that gets out of the client's way and empowers them to build the future.