Turning Costa’s machine data into smarter decisions

Through its Podio coffee machines, Costa has expanded into international markets, offering consistent, premium coffee experiences across various models. The machines, tailored for different markets and needs (e.g. BIB (Bag-In-Box) vs. fresh milk), are a key part of Costa’s strategy to deliver quality at scale.

The challenge: Turning machine data into meaningful action

While Costa already had a system in place for gathering machine data, including the application of recipes, diagnostics in terms of alarms and events, they lacked a structured process for tracking feature changes, software releases, and reporting across machines.

This made it difficult to:

• maintain consistency across different markets and machine models
  plan feature rollouts strategically;
• monitor performance and optimise consumption and demand management;
• communicate the status of ongoing work internally

In addition, there was no centralised source of truth or ownership over feature documentation, requirements, or prioritisation. This led to fragmented communication between departments and made it harder to align teams around business goals.

The solution: Building a structure around complexity

Our role was to bring structure, clarity, and consistency to the product and development process. We stepped in to organise requirements, streamline internal workflows, and support release planning in a scalable way.

Here’s how we approached it:

• Requirement management: We collected requirements on a daily basis from internal teams, markets, and testing labs. These were organised based on machine type, priority, and planned release. Our goal was to map the flow of information, identify overlaps or gaps, and refine the input.
• Jira optimisation: We restructured Costa’s use of Jira to improve visibility, creating dashboards that track issues, feature requests, and consumption metrics in real time.
• Release organisation: All new and existing features were mapped to specific software releases by taking into account any hardware issues, GUI improvements, etc. to support their embedded system
• Process definition: Even without formal sprints, we introduced consistent validation flows to ensure each release was tracked and managed efficiently.

The results: Better decisions, faster delivery

Costa now has a foundation that supports ongoing improvement across markets and teams. Our collaboration enabled them to work in a more strategic, data-driven way and laid the groundwork for future growth and optimisation of their coffee machine platform.

With our support, Costa significantly improved their internal coordination and product lifecycle management. Key benefits include:

• a centralised and documented overview of platform capabilities and changes;
• improved tracking of performance and consumption metrics;
• more effective planning and communication across teams;
• a scalable process for introducing new features and improving machine functionality;
• reduced time spent on troubleshooting thanks to better visibility into machine behaviour

Tech stack

Jira

Power BI