About Me
Hi, I'm Pragati – a data-driven Business Intelligence professional with 4+ years of experience turning complex data into actionable insights. This portfolio showcases real-world business problems I’ve solved using analytics, dashboard development, and data storytelling across domains such as revenue analytics, supply chain, and inventory management.
📊 Revenue & Sales Analytics
Tools & Technologies: Tableau, PostgreSQL, Excel
Stakeholders: Chief Revenue Officer (CRO), Revenue & Sales Teams
1. Use Case: Streamlining Revenue Insight through Dashboard Automation
Business Problem: At the outset of my role, the organization lacked a unified system for monitoring revenue performance. The Chief Revenue Officer (CRO) and sales team depended on three separate Excel exports and manual formula-driven calculations to perform revenue and quantity sold analysis. This process was not only time-consuming but also error-prone and incapable of providing real-time insights, significantly delaying critical business decisions.
Task: To address this inefficiency, I was assigned to develop a centralized and interactive dashboard capable of:
- Replacing Excel-based processes
- Delivering real-time revenue and sales metrics
- Providing drill-down capabilities for product and regional performance
- Enabling executives to monitor trends and make data-driven decisions
Analytical approach:
- Collaborated with the CRO and sales team to gather reporting requirements and define key performance indicators.
- Connected directly to the PostgreSQL database to automate data pulls, eliminating the need for manual data exports.
- Developed a Sales & Revenue Performance Tracker Tableau Dashboard providing comprehensive Revenue and Sales insights at the product category level, Store locations and monthly sales trends, with interactive drilldowns to product name and date-level granularity.
Business Impact:
- This dashboard became the primary tool for revenue planning and performance tracking, used daily by Chief Revenue Officer and leadership teams.
- Supported strategic decisions such as product pricing adjustments, promotional planning, and regional sales optimization by identifying spikes or seasonal patterns.
- Reduced reporting time by 80% by eliminating manual data extraction and Excel-based processing.
2. Use Case: 6-Months Production Planning Tool
Business Problem:
The CRO faced challenges with production planning due to the lack of a consolidated, data-driven view that linked historical sales trends, revenue contribution, and real-time inventory levels. Production quantities were often determined based on assumptions or short-term sales trends, resulting in mismatches between product availability and actual demand. This led to an excess stock of low-performing products and frequent shortages of high-performing items, directly impacting revenue and operational efficiency.
Task: To support the CRO in making informed, long-term production decisions, I was assigned to develop a dashboard that would provide:
- Revenue-aligned production goals over a 6-month horizon
- Product-level sales performance and contribution to total revenue
- Real-time visibility into inventory gaps relative to projected targets
- A centralized view to align decisions across revenue, production, and supply chain teams
Analytical approach:
- Conducted analysis on the last 90 days of sales and quantity sold data to identify historical performance trends and designed a 6-Month Production Goals Tableau Dashboard.
- Computed revenue contribution percentages for each product, enabling prioritization of high-impact products for production planning.
- Derived target revenue estimates based on historical contribution and projected growth, forming the basis for forward-looking production goals.
- Merged this revenue insight with real-time inventory data, allowing for an accurate assessment of current stock levels and supply gaps.
Business Impact:
- Empowered the CRO to lead revenue-aligned production planning between revenue, inventory, and supply chain teams, aligning them around a single source of truth.
- Reduced risk of overproduction and stockouts by aligning production goals with product-level demand and inventory insights — resulting in a 25% improvement in inventory turnover rate and a 30% increase in production planning accuracy within the first planning cycle.
📦 Inventory Distribution Management
Tools & Technologies: Tableau, PostgreSQL, Excel
Stakeholders: Supply Chain Manager, Inventory Managers, Retail operations lead
1. Use Case: Real-Time Inventory Distribution Dashboard for Strategic Stock Alignment
Business Problem:
Managing inventory across multiple retail locations posed a major operational challenge. The organization lacked a centralized system to monitor real-time inventory levels and compare them against optimal stock benchmarks. This led to imbalances: some stores were overstocked, tying up capital in unsold goods, while others experienced frequent stockouts, resulting in lost sales and dissatisfied customers. Without a clear view of where inventory discrepancies existed, the supply chain team struggled to take timely corrective action.
Task: To address this issue, I was assigned to design a Tableau dashboard that would:
- Consolidate inventory data across all store locations.
- Visually highlight variances between current inventory and target stock levels.
- Enable drilldowns from product categories to specific SKUs.
- Provide store-level insights to support data-driven redistribution of inventory.
Analytical approach:
- Collaborated with inventory managers and store supervisors to define target inventory benchmarks for each product category and store location.
- Wrote optimized SQL queries to extract inventory data from the database and calculate the variance between actual and ideal stock levels.
- Built an Inventory Redistribution Tableau dashboard that displayed current inventory by location and product category, color-coded variance indicators for overstock and understock conditions, and state-level and region-specific panels to provide localized insights into inventory imbalances.
Business Impact:
- Reduced logistics costs by 22% by preventing overstock shipments to already saturated locations, leading to more efficient transportation and storage utilization.
- Enabled just-in-time redistribution for high-demand SKUs, shortening stockout resolution time by 40% and increasing weekly revenue by 12% in key underperforming regions.
🚚 Supply Chain Optimization
Tools & Technologies: Tableau, PostgreSQL, Excel
Stakeholders: Supply Chain Manager, Inventory Managers
Use Case: In-Stock to Sale Dashboard for Inventory Risk Mitigation and Supply Chain Decision-Making
Business Problem:
In a fast-paced retail environment with fluctuating demand, the company faced recurring issues related to inventory misalignment. Products with high demand were frequently out of stock, while slower-moving SKUs sat idle, tying up capital and shelf space. These imbalances directly impacted revenue, customer satisfaction, and operational efficiency. The lack of a consolidated, visual system to monitor product-level sales velocity, inventory days coverage, and financial risk limited the team’s ability to make data-driven replenishment and redistribution decisions.
Task: To support proactive inventory management, the Supply Chain Manager shared a detailed Excel mockup representing critical inventory KPIs. I was assigned to convert this static spreadsheet into a dynamic, interactive Tableau dashboard that would:
- Calculate sales velocity to understand how quickly inventory is selling.
- Highlight stockouts, overstocks, and inventory at financial risk.
- Provide actionable insights for redistribution, clearance planning, and replenishment.
Analytical approach: To bring the Supply Chain Manager’s vision to life, I followed a structured, data-driven approach:
- Conducted an initial review of the Excel mockup to understand stakeholder expectations and translated key columns into measurable KPIs such as 60-day POS units, current inventory units, target inventory, days of coverage, and stock-to-sale ratio.
- Extracted and merged historical POS data and real-time inventory snapshots, ensuring data integrity across regions, stores, and product categories.
- Used Excel to calculate baseline metrics and validate logic for unit variance and financial risk exposure before integrating them into Tableau Dashboard.
Business Impact:
- Identified and visualized over $250K worth of inventory at financial risk, leading to timely redistribution and markdowns that protected revenue margins.
- Increased inventory turnover by 18% by aligning inventory availability with actual sales patterns, reducing capital held in stagnant stock.
🛍️ Retail Operations Analytics
Tools & Technologies: Tableau, PostgreSQL, Excel
Stakeholders: Retail lead, Regional Managers, Revenue and sales team
Use Case: Average Ticket Overview Dashboard for Daily Retail Operations
Business Problem:
Retail store managers are responsible for hitting daily revenue goals and ensuring transaction efficiency. However, they previously lacked a centralized tool that could provide near real-time visibility into how average ticket size was trending at their stores. Without this, it was difficult to assess whether daily performance was on track, which stores were underperforming, or how regional trends were compared. Static Excel reports offered only high-level summaries and lacked the granularity to drive meaningful day-to-day decisions on the floor.
Task: To address this gap, I was tasked with designing a dashboard that would:
- Display real-time average ticket metrics by store and region.
- Compare performance against daily and monthly targets.
- Break down ticket performance by day to capture trends and variances.
- Help managers make operational decisions to improve average spending per customer.
Analytical approach: To address the needs of regional managers, I applied a structured, insight-driven approach combining stakeholder alignment, metric engineering, and data visualization design:
- Engaged with regional sales directors to map out their daily decision-making process, pinpointing the most actionable metrics—average ticket value, transaction volume, and payout eligibility—as core KPIs.
- Designed and implemented an intuitive Tableau dashboard that included:
- Dynamic trend lines to track day-over-day average ticket fluctuations at both region and store levels
- Target-based KPI indicators that immediately surfaced underperforming stores
- Region- and store-specific drilldowns for root-cause exploration
Business Impact:
- Store managers now use the dashboard daily to monitor average ticket performance and identify shifts in purchasing behavior.
- Managers can proactively address performance gaps (e.g., increase upselling efforts, adjust promotions) before end-of-day targets are missed.
- Resulted in a 10–15% improvement in regional average ticket performance by enabling timely, data-informed decisions at the store level.