Mourya Gupta Vakacharla

Krenicki Center for Business Analytics and Machine LearningWest Lafayette, Indiana

Business Analyst ConsultantNovember 2023 - Present

Client: Kimball International, Inc.

• Correlation (Excel | Python): Analyzed SAP SD & SFDC data to identify interdependencies between metrics
• K-Means Clustering (Excel | Python): Identified customer segments for targeted leak detection & trend analysis
• Time Series Forecasting (ARIMA | LSTM): Enhanced decision-making through data-driven KPI prediction
• Executive Briefing (Power BI): Translated complex data & results into actionable insights for leadership

Gupta Sales CorporationMandapeta, India

Worked in retail, distribution, and manufacturing company

Business Development AnalystNovember 2021 - July 2023

Sales & Network Expansion and Strategic Partnership
Key Partnership with Finolex: Achieved 25% sales growth using Tableau for compelling analytics.

• Supplier Onboarding: Identified and partnered with top suppliers through market research.
• Initial Acquisition: Tested market with Nandi, leveraging strong state-level market share.
• Sales Analysis: Conducted a three-month analysis of Nandi’s sales and competition.
• Financial Planning: Developed financial plans to support proposals.
• Proposal Presentation: Highlighted sales performance and future estimates.
• Market Trends & KPIs: Used Tableau to showcase growth opportunities.
• Investment Analysis: Evaluated and negotiated marketing support and discounts.

Retail Unit Launch
New Retail Division: Improved cash flow and product development, reducing inventory turnaround by 13 days.

• Market Analysis: Assessed product demand, competitors, and strategic positioning.
• Location Analysis: Selected sites based on foot traffic and demographics.
• Financial Analysis: Evaluated costs and revenue projections.
• Product & Assortment: Selected profitable products.
• Marketing & Promotion: Launched targeted campaigns.
• Risk Analysis: Identified and mitigated risks.
• IPerformance Measurement: Monitored KPIs for continuous improvement.
• Pricing Advantage: Leveraged discounts for competitive pricing.

New Product Division Introduction
Electrical Products Division: Enhanced cross-selling with plumbing products.

• Cross-Functional Team: Assembled for integration.
• Part of Retail Launch: Incorporated into retail strategy.

Supply Chain Optimization
Direct Sourcing & Partnerships: Enhanced margins and efficiency.

• Margin Analysis: Identified cost-saving opportunities.
• Direct Sourcing: Shifted to manufacturers for better pricing.
• Strategic Partnerships: Streamlined the supply chain.
• Logistics Coordination: Negotiated shipping discounts.
• Bulk Direct Supply: Partnered with contractors and firms for high-volume sales.

Strategic Business AnalystMay 2020 - October 2021

Cost-Benefit Analysis (Excel | SQL)
Tripled UPVC Division’s Profit Margin: Analyzed suppliers' prices to identify underperformance.

• Root Cause Analysis: Discovered higher-than-average purchase prices.
• Supplier Price Comparison: Evaluated prices from different suppliers.
• Risk Identification: Assessed risks of changing suppliers.
• Price-Quality Matrix: Analyzed price vs. quality to find the best supplier.
• Negotiation & Terms: Secured discounts and favorable delivery terms.

Production Optimization (MS Project)
Efficiency Improvement: Revamped resource allocation and scheduling, increasing efficiency by 30%.

• Production Bottlenecks: Identified and addressed inefficiencies impacting productivity.
• Resource Allocation: Optimized resources and streamlined packaging operations.
• Real-Time Adjustments: Monitored progress and made adjustments to enhance productivity.
• Team Collaboration: Worked with the packaging team to reduce downtime.
• KPIs Implementation: Established KPIs to measure and track improvements.

Price Prediction (Python | GRU)
Resin Price Forecasting: Predicted LLDPE resin prices to aid budgeting and procurement.

• Data Utilization: Used historical LLDPE data, crude oil prices, and procurement data.
• Model Development: Created ARIMA, LSTM, and GRU models in Python.
• Strategic Impact: Optimized procurement strategies and reduced costs by hedging against price increases.

Pricing Strategy (Scenario Analysis)
Optimized Pricing: Reduced delivery times and logistics overhead by 25%.

• Sales Data Analysis: Analyzed segmented sales data and truck capacities.
• Discount Structure: Developed an optimal discount structure based on sales volume.
• Finalized Discounts: Implemented discounts of 20 paise/ltr for 3000 ltr orders and 30 paise/ltr for 10000 ltr orders.

Business AnalystMay 2019 - April 2020

Inventory Management
Streamlined Inventory through Seasonal Sales Analysis: Utilized Excel, SQL, and Tally ERP to analyze seasonal sales trends.

• Sales Trends Analysis: Identified seasonal patterns in historical sales data.
• Inventory Forecasting: Forecasted inventory needs using SQL and Excel models.
• Demand Planning: Enhanced planning to reduce overstock and stockouts.
• Reorder Point Adjustment: Adjusted reorder points to ensure availability and minimize excess.
• Economic Order Quantity (EOQ): Calculated EOQ to minimize total inventory costs.

Route Optimization
Cost Reduction through Vehicle Route Optimization: Reduced costs by 25% using Python and Google Maps API.

• Data Collection: Assessed product demand, competitors, and strategic positioning.
• Algorithm Development: Selected sites based on foot traffic and demographics.
• API Integration: Evaluated costs and revenue projections.
• Real-Time Adjustments: Selected profitable products.
• Cost Analysis: Launched targeted campaigns.

Retail Unit Launch
Boosted Targeted Marketing by 15%: Analyzed regional sales data with Python.

• Data Aggregation: Compiled data from multiple sources.
• Growth Market Identification: Analyzed sales by region and product category.
• Visualization: Presented findings with visualizations.
• Campaign Optimization: Tailored marketing based on regional trends and product success.
• Performance Tracking: Monitored effectiveness using sales data.

Risk Mitigation
Reduced Stock-Outs by 27%: Mitigated supply chain risks with SQL and @RISK.

• Data Extraction: Used SQL for supply chain data extraction.
• Risk Analysis: Identified vulnerabilities with Monte Carlo simulations.
• Scenario Planning: Anticipated disruptions through scenario analysis.
• Alternate Suppliers: Engaged alternate suppliers for unreliable ones.
• Mitigation Strategies: Developed strategies to address risks.
• Stock-Out Reduction: Adjusted procurement to maintain supply.