Coffee Shop Chain
A Symphony Case Study
A coffee shop chain with multiple locations in the UK and US, is currently in fast expansion mode, striving to establish themselves in a fast-moving market. Being very tech-savvy, the chain is keen to be on top of the newest technological advances and think different.
It became apparent that with their growth, came the respective challenges of data management, challenges that placed pressure on their existing infrastructure, which was clearly reaching its boundaries.
Another problem they faced was time efficiency during data entry. An example of this is when they need to add the details of a newly hired employee across 4 of the 5 existing systems. This translated to a huge time commitment and potential room for error when transferring information across.
The client was also looking to improve efficiency around his reporting; and gain real-time access to normalised data across all their locations.
As the coffee shop chain grew, they constantly required new systems and tools to be able to, on the one hand, manage their growing data and on the other, be able to keep track of their diverse business activities across all locations. They needed new systems to be able to manage their business more effectively.
However, they knew that adding new systems is often very disruptive and often involves employing a developer to handle data migration and system integration.
After using Symphony, client was extremely happy with their coffee shop chain’s new capabilities and is now able to grow even faster. With the ability to access living data, efficiently proliferate data and expand their system infrastructure in line with constant scaling requirements.
To find out how Symphony helped them by:
- Integrating all their existing solutions together and enabling them to add new or remove existing systems as they needed
- Delivering business intelligence with zero disruption to the current business model and within their budget
- Facilitating growth by easily adding new systems.
- Enabling Seamless data flow between systems.
- Giving access to Accurate data across all systems and time saving through automatic population of data from one source to all other systems.
- Developing new Key Performance Indicators (KPIs) through combining relevant factors across all their systems.