Building a BI Tool-Based Business Dashboard for an Apparel RetailerConsumer Products
Objective
The client, a retail chain with 85 stores across India, including major locations like Mumbai, Delhi, Bengaluru, and Kolkata, sought to enhance its operational efficiency and decision-making capabilities. The goal was to develop a BI tool offering a seamless, centralized view of key performance indicators (KPIs) across business functions, integrating data from sales, finance, and loyalty programs.
Data
Methodology
Outcome
Business Impact
Data
Data Used:
- Financial Data:
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Annual revenue of ₹450 crores
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Operational expenses segmented by store locations
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Profit margins and year-over-year growth data
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- Trade Data:
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- Daily sales transactions averaging ₹1.2 crores across all stores
- Inventory data for 3,500 SKUs per store
- Supplier performance metrics for 60 suppliers
- Loyalty Program Data:
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- Insights from 1.2 million loyalty program members
- Data on repeat purchases contributing 40% of total revenue
- Customer segmentation by purchase frequency and product preferences
Methodology
OrangeTree Global employed the following approach to develop the BI dashboard using Power BI:
- Data Integration:
Consolidated data from multiple sources, including the client’s ERP system (SAP), sales platform, and CRM tools. - Data Cleaning and Transformation:
Applied ETL processes to handle missing data and standardize formats for accurate reporting. - Dashboard Design:
- Created interactive dashboards with visualizations like heatmaps for regional sales performance and line graphs for revenue trends.
- Comparative charts for monthly sales growth (e.g., Mumbai grew 12%, while Bengaluru declined 3% in Q3).
- User Access Control:
Role-based access ensured secure, need-based data visibility:
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- Regional managers could access store-level data.
- Executives could view consolidated financial performance.
- Automation:
Set up automated data refresh schedules to ensure near real-time data availability, updating dashboards every 4 hours.
Outcome
- A unified dashboard displaying:
- Daily, weekly, and monthly revenue trends
- Inventory turnover rates, highlighting items with low stock or high overstock (e.g., SKU #2345 had only 5 units left in Delhi).
- Customer segmentation insights, e.g., 25% of loyalty members in Mumbai spent over ₹10,000 last month.
- Drill-down capabilities allowing managers to analyze specific regions, stores, or product categories.
- Figures from Dashboard Insights:
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- Inventory accuracy improved by 18%, reducing stock-outs from 14% to 6%.
- Regional performance comparison showed that northern stores outperformed others, generating ₹190 crores in annual sales.
Business Impact
- Enhanced Decision-Making:
- Reduced reporting time from 3 days to 1 hour, enabling faster decisions.
- Identified underperforming categories (e.g., men’s formal wear declined by 10%, prompting targeted marketing).
- Operational Efficiency:
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- Saved approximately ₹30 lakhs annually by optimizing inventory levels.
- Reduced overtime for data analysts, saving 500+ hours per year.
- Customer Engagement:
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- Targeted campaigns increased loyalty program usage by 15% in Tier 1 cities.
- Personalized offers led to an 8% increase in average transaction value.
- Competitive Edge:
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- Dynamic sales monitoring enabled the launch of flash sales that boosted daily revenue by ₹5 crores during peak seasons.