Automating Analytics & Insights

Case Study 3
Client:
Middle East Logistics Company
Objective:
To automate reporting, enhance data visibility, and enable faster decision-making by implementing analytics and insights solutions.

Challenges

  • Lack of Analytical Dashboard:
    The company lacked a comprehensive dashboard for data visualization and decision-making, making it difficult to gain actionable insights.
  • Fragmented Data Reporting:
    Data reporting was scattered across different departments, making consolidation and analysis inefficient.
  • Limited Integration:
    The company’s systems, including ERP, HRMS, and QHSE, were not seamlessly integrated, complicating data extraction and analysis.
  • Inadequate Alert System:
    There was no automated system for sending alerts on critical SLA/KPI misses, impacting response times and business performance.
  • Manual Data Handling:
    Manual processes for data collation and manipulation were time-consuming and prone to errors.
  • Inconsistent Data Formats:
    Data came in varying formats, making it difficult to consolidate and analyze efficiently.

Solution Highlights

To address these issues, a range of automation and analytics solutions were implemented:

  • RPA Implementation:
    Robotic Process Automation (RPA) was used to automate Excel report handling and data loading, reducing manual work.
  • Custom Windows Service:
    Developed a custom service to connect with enterprise applications, extract data, and update the database in real time.
  • SLA/KPI Monitoring:
    Set up a system for tracking SLAs and KPIs, providing timely alerts to ensure performance targets were met.
  • Business Intelligence Platform:
    Implemented a robust platform for creating data-driven insights and real-time dashboards.
  • ACL-Based Access:
    Role-based access control (ACL) was introduced to ensure secure and efficient data access for different stakeholders.
  • Report Sharing:
    Enabled easy report sharing across departments to ensure stakeholders had real-time access to critical data.

Business Impact

  • Reduced Report Refresh Time:
    Report refresh time was reduced from every 15 days to daily, enabling real-time insights.
  • 175 Man Hours Saved Per Month:
    Automation of data extraction, transformation, and loading (ETL) processes, along with dashboard creation, saved significant time.
  • Close to 100% Accuracy:
    Automation significantly improved the accuracy of data processing and reporting.
  • Real-Time Visibility:
    Near real-time visibility into company performance led to faster, data-driven decision-making.

Technology Stack Used: