Business Intelligence & Performance Analytics Manager

The Manager, Business Intelligence & Performance Analytics serves as the strategic analytics,, responsible for transforming raw retail, inventory, and manpower data into meaningful business insights. The role oversees inventory intelligence, manpower planning analytics, and retail performance monitoring, supporting operational decisions through forecasting, scenario modeling, and root-cause analysis. This position manages enterprise dashboards, ensures data accuracy and governance, consolidates performance reporting across all RCOE pillars, and conducts market and competitor benchmarking to guide commercial and store strategies.

Key Responsibilities:

Retail Data Analysis, Inventory Intelligence, and Insights Development

• Leads end-to-end analysis of retail KPIs and converts trends into actionable insights for RCOE decision-making.
• Oversees all inventory management data, including stock movement, replenishment performance, stockouts/overstocks, aging items, variances, and shrinkage. Provides clear insights and recommendations to improve inventory health and availability.
• Develops and maintains dashboards that track inventory health, manpower productivity, store performance drivers, and other critical retail indicators.
• Conducts deep-dive analytics and scenario modeling (e.g., productivity, labor efficiency, replenishment cycles, category performance) to support strategic projects and operational improvements.
• Leads manpower planning analytics, including FTE forecasting, labor productivity ratios, staffing scenarios, and store manpower requirement validation.
• Drives manpower control and headcount budget planning, ensuring staffing proposals align with labor budgets, productivity targets, and cost parameters.
• Consolidates and validates data across multiple systems to provide accurate, decision-ready insights.

Performance Monitoring and Reporting

• Develops, automates, and manages performance dashboards for RTM leadership, Area Managers, and RCOE units.
• Consolidates daily, weekly, and monthly performance reports across pillars (Customer Experience, Merchandising, Supply & Availability, Innovations & Systems Improvement).
• Ensures accuracy, timeliness, and consistency of performance reporting across all business units.

Data Management, Governance and Quality Control

• Establishes standards for data accuracy, completeness, validation, and integrity across RTM data sources.
• Oversees the maintenance of analytics databases, KPIs trackers, and data repositories.
• Works with IT and relevant teams to improve data pipelines, availability, and accessibility.

Business Partnering & Cross-functional Collaboration

• Partners closely with RCOE units, Retail Operations, ITDM, Warehouse, Finance, and HRBP to align insights, validate assumptions, and support joint initiatives.
• Translates analytics insights into operational recommendations (e.g., manpower planning, stock availability, POS behavior, store patterns, promotional impact).
• Supports the implementation of insights-driven strategies and monitors impact and performance.

Market Intelligence & External benchmarking

• Monitors market trends, competitor behavior, consumer patterns, and retail benchmarks.
• Provides intelligence reports that support category decisions, pricing strategies, and store operations planning.

Team Leadership and Capability Building

• Leads data analysts, providing guidance on methodologies, analytics approach, and quality of output.
• Builds analytics capability across RCOE and Retail Operations through training on data literacy, dashboard usage, and interpretation of KPIs.
• Establishes work standards, templates, and repeatable processes for analytics reporting.

Continuous Improvement & Systems Enhancement

• Identifies opportunities to automate reporting, streamline data collection, and use new tools
• (Power BI, SQL, cloud-based platforms).
• Drives adoption of structured KPI frameworks across RTM to ensure consistent business monitoring.
• Recommends system enhancements and tools to improve analytics maturity.

Qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Economics, Computer Science, or