Ayushi Kedar

Lead the global Reporting & Analytics workstream and Spend Taxonomy & Categorization for a strategic procurement organization, managing data governance, spend visibility, and system integration across Coupa, SAP, Oracle, and Snowflake.

• Strategic Leadership & Governance:
  Spend Taxonomy Leadership: Spearheaded the Spend Taxonomy workstream during the major Coupa transition; partnered with Finance to design, implement, and govern a bespoke taxonomy mapped to GL accounts.
  Data Strategy: Acts as the primary liaison between Finance, Procurement, IT, and external vendors to resolve integration issues, validate vendor classification rules, and establish firm data governance standards.
  Global Rollout: Accelerated the global rollout of procurement analytics, establishing a centralized data warehouse as the "source of truth" and leading user training for KPI tracking.
• Financial Impact & Process Optimization:
  Cost Savings: Partnered with commodity managers to drive $90+M in savings by identifying addressable spend opportunities and developing category strategies across 6 Direct and Indirect towers.
  Working Capital Analytics: Drove DPO and working capital improvements by instituting rigorous payment terms reviews, AP aging analysis, and standardization protocols.
  Spend Correction: Conducted deep-dive spend analytics to identify and correct classification errors exceeding $3B, ensuring accurate baselines for fiscal planning.
• Technical Execution & Dashboarding:
  Executive Reporting: Designed and maintained executive-level Power BI and Tableau dashboards tracking Savings, Spend Visibility, Supplier Diversity, Cost Per Sq Ft, Non Employee workforce, Vendor management, Days Payable Outstanding, EHS/SGG, and Taxonomy compliance.
  Data Quality Initiative: Led agile sprint sessions to enhance data health, achieving a 98% data accuracy rate and reducing reporting Turn Around Time (TAT) to 5-6 days.
  End-to-End Pipeline: Managed the consolidation of internal/external data sources (Snowflake, Python, Databricks, IICS, Enterprise Data Warehouses) to automate forecasting and variance analysis.

• Requirements & Scoping: Led cross-functional requirements-gathering to define project scopes and translate business needs into technical data flow diagrams.
• Data Modeling: Engineered robust SQL and Excel data models for market trend analysis, streamlining reporting to eliminate 12+ hours of manual work per week.
• Visualization Strategy: Developed interactive Tableau and Power BI dashboards for operational KPIs, providing real-time visibility that accelerated executive decision-making.

• Process Automation & Data Quality: Developed advanced VBA scripts and complex lookup algorithms to automate data recovery and quality checks, eliminating 10+ hours of manual processing per week and reducing reporting errors by 25%.
• Customer Experience Analytics: Spearheaded analytics using Tableau and Excel to process unstructured datasets; identified process gaps and recommended optimization strategies that improved cross-departmental workflow efficiency by 15%.
• Financial Modeling & IT Alignment: Partnered with IT to design predictive business models for project-based incentive programs, aligning system functionality with business objectives and accelerating quarter-close reconciliation by 2 days.

• Revenue Growth: Wrote complex SQL queries to analyze booking and turnover rates; collaborated with marketing to optimize targeting strategies, leading to a 35% increase in revenue.
• Forecasting: Synthesized BI data to perform time-series forecasting and budgeting analysis, providing recommendations that optimized operational performance.
• Managed stakeholder expectations through transparent communication and timely status updates, ensuring alignment between project deliverables and business objectives.

• Web Analytics: Streamlined website navigation flow, reducing misdirected links by 40% and significantly improving user retention on neglected pages.
• Predictive Modeling: Performed multivariate analysis and data pre-processing to eliminate outliers, translating statistical outputs into actionable content strategies that grew social media engagement by 125%.
• Integrated multiple sources of disparate data into cohesive datasets using ETL processes, improving overall analytic capabilities.

• Algorithm Development: Designed and tested JAVA-based image recognition tools and SQL database modifications, enhancing data processing accuracy to 80%.
• Conducted thorough data quality assessments, ensuring integrity and reliability of analytical outputs.
• Optimized data collection methods to enhance quality and volume of data captured for analysis.