Transforming Retail Operations with Forecasting & BI on AWS QuickSight

A leading Sri Lanka-based retail chain was looking to take its first step towards Business Intelligence (BI) and data-driven decision-making. Operating across multiple locations, they faced inefficiencies in inventory planning, vehicle utilization, and order fulfillment. With no centralized data repository or analytics framework, they lacked visibility into operational bottlenecks and customer demand trends. To optimize their retail operations, they partnered with NeenOpal to implement a data warehousing solution integrated with predictive forecasting and an interactive BI dashboard using Amazon QuickSight.

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Customer Challenges

With rapid business expansion and growing operational complexity, the retailer faced significant roadblocks in achieving efficiency and scalability. Their existing processes heavily relied on manual efforts and lacked insight-driven decision-making. Key challenges included:

Challenges in Implementing Vendor Agreement

Lack of Centralized Data

Data was scattered across different operational systems, making it difficult to gain a unified view of key business metrics. Without a centralized repository, using AWS reporting tools for consolidated analysis was nearly impossible.

Inefficient Demand Forecasting

Inventory planning was based on historical intuition rather than data-driven predictions. In the absence of automated forecasting models, the business frequently experienced overstock or stockouts, reducing profitability.

Defining Metadata Coverage and Monitoring Levels

Suboptimal Vehicle Utilization

Delivery routes and vehicle scheduling were manually managed, resulting in inefficiencies and increased operational costs. The business lacked data-supported analysis and forecast tools to improve logistics.

Low Adoption of Existing Tableau Dashboards

Limited Visibility into Order and Customer Trends

The absence of a real-time dashboard meant stakeholders could not track order volumes or customer buying patterns dynamically. This limited their ability to respond to market demands or customer preferences quickly.

No Existing BI Framework

As a newcomer to data analytics, the retailer needed a structured approach to build data pipelines, create KPIs, and define a visualization strategy. Implementing a solution that combined backend infrastructure with intuitive AWS reporting tools was crucial.

Solutions

To transform their operational capabilities, NeenOpal implemented a robust data foundation coupled with advanced analytics and intuitive dashboards. The multi-phase solution combined cloud infrastructure, machine learning, and real-time Business Intelligence (BI).

Optimized Data Structure for Seamless Agreement Implementation

Building a Scalable Data Warehousing Foundation

NeenOpal designed and implemented a data warehouse on AWS, consolidating data from multiple operational sources. The architecture ensured a structured, scalable, and high-performance analytical environment, laying the groundwork for advanced analytics and BI adoption.

Enhanced Metadata Checks with Program-Specific Classification

Demand Forecasting with Machine Learning

To improve inventory planning, NeenOpal developed a forecasting model using Amazon SageMaker, AWS Lambda, and other AWS services. This SageMaker-powered model analyzed historical sales data, seasonal trends, and external signals to deliver accurate demand forecasts. The shift from gut-based planning to automated forecasting enabled the retailer to reduce stockouts, overstock, and waste.

Optimizing Vehicle Utilization & Route Planning

A data-driven vehicle utilization model was developed, analyzing delivery routes, order volumes, and vehicle availability. By optimizing these parameters, the retailer improved delivery efficiency, reduced fuel costs, and minimized idle vehicle time.

BI Implementation with Amazon QuickSight

The insights from forecasting models and operational data were integrated into AWS QuickSight, creating a real-time dashboard with key metrics across delivery routes, customer behavior, vehicle utilization, and inventory levels. It also offered a centralized view of vehicle, inventory, and store master data to support better planning and governance.

Why choose NeenOpal?

NeenOpal combines expertise in BI, predictive analytics, and cloud infrastructure to deliver scalable, business-focused analytics solutions. With certified AWS professionals and a proven track record, NeenOpal is the ideal partner for organizations beginning their data transformation journey.

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A Path to BI Success

A Business Intelligence (BI) roadmap is a plan that guides how to set up and use data analytics tools and processes to gain valuable insights and make informed decisions. It helps organizations build a clear path for integrating data solutions that support long-term growth and success. By aligning technology with business goals, it fosters efficient data management and drives continuous improvement. Learn more.

Benefits

The solution enabled the retailer to shift from reactive decisions to proactive, data-driven strategies. With enhanced visibility and operational efficiency, the business is now better equipped to meet customer demand and scale intelligently.

Conclusion

For this Sri Lankan retail giant, partnering with NeenOpal marked a crucial milestone in their journey towards data-driven transformation. By combining predictive forecasting with an intuitive QuickSight dashboard, they gained visibility into their operations and optimized their decision-making processes. This project not only addressed immediate business inefficiencies but also laid the foundation for future BI and analytics initiatives, positioning them for sustained growth in a competitive market.