Sushi 2×1 had two main objectives. First, they wanted to develop a simple and easy-to-read solution that provided visibility into key business metrics for both the central office and each franchise. Second, they aimed to positively impact revenue by consolidating information and fostering data-driven decision-making based on real, concrete data.

The primary challenge was data fragmentation, with information coming from different systems, such as the POS (Thinkion) and ERP (Sinergis), requiring centralization. Although some information was visualized in PowerBi, key metrics such as sales, consumption, supplies, and billing were updated manually, making strategic decisions slow, such as forecasting future revenue, estimating expected workloads, and optimizing purchasing levels to minimize waste. With the constant growth of the franchises, it was crucial to scale data solutions and automate processes to improve operational efficiency and provide comprehensive monitoring that identified the most successful franchises and provided visibility into revenue by channel.

In summary, a tool was needed that would enable decisions to be based not just on experience but on precise, real-time data, with the goal of optimizing every aspect of the business.

Solution implemented

Our team developed a comprehensive data solution that centralized information from multiple sources that the client already had but was either underutilized or disorganized. These sources included the Point of Sale (POS) system, Enterprise Resource Planning (ERP) system, Google Analytics, and others.

Various dashboards were created to monitor key KPIs for daily, monthly, and annual operations, both for individual locations and the parent company. Indicators were also included to identify deviations in production and stock consumption.

Additionally, predictive tools were implemented to project daily sales and calculate the necessary consumption of supplies, improving production planning and inventory management.


Impact:

  • Centralization and organization of information from different data sources.
  • Efficient monitoring of daily operations by franchise.
  • Improved visibility and control of KPIs.
  • Optimization of production and sales processes.
  • Increased cost efficiency in production.
  • Early detection of anomalies in sales channels.
  • Significant value added from the franchisor to the franchisee, directly impacting profit margins.

    • Technology stack:

  • Python: For the creation of interactive dashboards for metrics and KPIs.
  • AWS (Amazon Web Services): For the development of the custom ETL process.
  • Thinkion: Platform hosting the ETL server.
  • Sinergis: POS system used in the franchises.
  • PowerBi: ERP system managing the client’s internal processes.

    • Project duration

    The project has been in development for 10 months and continues to evolve with the addition of new franchises and additional features.

    Team:

  • Functional Analyst: Responsible for analyzing client requirements, managing data integration, and defining performance indicators.
  • Full Stack Developer with a specialization in databases: Responsible for implementing the ETL in Python, integrating systems, and developing the PowerBi dashboards.
  • Delivery Manager: Responsible for project management and ensuring timely and quality deliverables that meet the client’s expectations.