General Manager

Role: Business Relationship Manager

Location: Bangalore

Role Purpose

The Business Relationship Manager – is responsible for bridging business strategy and data capabilities by partnering with internal brands and corporate functions to identify, prioritize, and realize high-impact data, analytics, and AI use cases.

The role ensures that data initiatives are business-led, outcome-driven, and scalable across brands, converting insights into measurable value across revenue, margins, customer experience, and operational efficiency.

Key Accountabilities

1. Business Partnership & Demand Management

• Act as the single point of contact between assigned brands/functions and the Data team.
• Develop deep understanding of brand strategy, P&L drivers, and operating metrics.
• Identify opportunities where data & analytics can solve critical business problems.
• Own and manage the data demand intake, prioritization, and alignment process.

2. Data Use Case Definition & Prioritization

• Translate business needs into clear, well-defined data use cases with:
• Problem statements
• Hypotheses
• Success metrics and value potential
• Prioritize use cases based on business impact, feasibility, and reusability.
• Maintain a centralized use-case portfolio across brands and functions.

3. Delivery Coordination & Execution Oversight

• Partner with Data Engineering, Analytics, and Data Science teams to:
• Finalize scope and timelines
• Align on data sources and dependencies
• Ensure timely delivery of decision-ready outputs, not just reports or models.
• Proactively manage risks, dependencies, and stakeholder expectations.

4. Value Realization & Adoption

• Define value realization metrics upfront (revenue uplift, margin improvement, cost savings, working capital).
• Ensure analytics outputs are embedded into:
• Business processes
• Planning forums (S&OP, pricing, marketing reviews)
• Digital products and dashboards
• Track post-implementation adoption and realized benefits.

5. Governance, Standards & Data Maturity

• Ensure all initiatives align with:
• Group data architecture and platforms
• Data governance, privacy, and security policies
• Drive standardization and reuse of data models and analytics assets.

Reduce ad-hoc reporting through self-serve analytics enablement.

6. Stakeholder Enablement & Data Literacy

• Act as a translator between business and data teams.
• Educate stakeholders on:
• Analytics and AI capabilities and limitations
• Interpretation of insights and model outputs
• Build strong credibility and trust across senior leadership.

Execution Excellence

• Cycle time from use-case approval to production
• % of initiatives delivered on time and within scope
• Stakeholder satisfaction score

Capability & Maturity

• Increase in adoption of analytics-driven decisions
• Reduction in manual / ad-hoc reporting requests
• Reuse of data assets across brands

Skills & Competencies

Functional Skills

• Strong understanding of retail data domains:
• Sales, inventory, merchandising, supply chain, customer, pricing
• Ability to structure ambiguous business problems analytically
• Experience working in centralized COE / GCC models

Technical Awareness (Hands-on not mandatory)

• Data platforms (Snowflake, Azure, Databricks, Big Query)
• BI & visualization tools (Power BI, Tableau)
• Familiarity with ML use cases (forecasting, recommendations, segmentation)

Behavioral Competencies

• Executive stakeholder management
• Strong influencing and communication skills
• Commercial mindset with outcome orientation
• Ability to work across geographies and cultures

Education & Experience

• Bachelor’s degree in engineering, Analytics, Business, or related field
• 15+ years of experience in:
• Analytics consulting
• Retail / consumer data & analytics roles
• Product analytics or transformation roles
• Experience in multi-brand, multi-geo retail environments preferred

Key Competencies Required

Strategic Thinking - Ability to see the big picture, anticipate business needs, and align data initiatives with long-term organizational goals

Influence & Negotiation - Proven capability to influence decisions, negotiate priorities, and secure commitment from senior stakeholders without direct authority

Data Storytelling - Exceptional ability to transform complex analytical findings and AI model outputs into compelling narratives that drive action and demonstrate measurable business impact

Business Partnership - Collaborative approach with ability to work as a trusted advisor to business leaders

Adaptability - Comfort with ambiguity and ability to thrive in a fast-paced, evolving retail environment

Results Orientation - Track record of delivering measurable business impact through data-driven initiatives

Cross-functional Leadership - Ability to lead through influence across matrix organizations, partner with Product, Growth, Marketing, and Operations teams, and drive initiatives to completion

Team Collaboration & Capability Building - Strong ability to work with and enable data science teams, fostering knowledge sharing and building organizational AI/analytics capabilities