Senior Manager, S2P Analytics & Master Data

Job Description

Role Summary

The Senior Manager, S2P Analytics & Master Data serves as the business owner for the Source-to-Pay (S2P) data and analytics foundation. This role ensures that supplier, taxonomy/category, preferred supplier, item/service, contract, risk, and related reference data are accurate, governed, scalable, and fit for purpose—while translating that data into trusted insights, executive narratives, self-service analytics, automation, and AI-enabled decision support.

The role leads the business-side governance model, master-data lifecycle, data quality standards, analytics product portfolio, insight-generation capability, and enabling platform requirements across the S2P lifecycle. It partners closely with S2C and P2P Process & Platform Enablement, Strategy/Governance/Excellence, SBE, Finance, Legal, Risk, IT/Digital, enterprise Data Governance, and S2P Transformation teams.

This leader makes data a trusted business asset that powers reliable operations, decision-grade reporting, controls, intelligent routing, automation, performance management, and future-state AI capabilities.

Key Responsibilities

1. S2P Master Data, Taxonomy & Governance Ownership

• Serve as the senior business lead for S2P data domains, including supplier master, third-party entity types, taxonomy/category structures, preferred supplier designation, item/service data, contract/reference data, risk attributes, and related reference data.

• Own business-led governance standards for data ownership, stewardship, approval workflows, change control, escalation paths, and decision rights across Procurement, Finance, Legal, Risk, IT/Digital, and enterprise data teams.

• Establish data definitions, semantic standards, lineage expectations, quality requirements, and governance routines that enable consistent reporting, automation, analytics, and AI use cases.

• Ensure taxonomy and master-data standards support buying-channel guidance, preferred supplier utilization, supplier segmentation, risk screening, compliance monitoring, routing, value tracking, and performance analysis.

2. Master Data Lifecycle, Process & Platform Enablement

• Lead business requirements and lifecycle processes for data creation, validation, enrichment, maintenance, synchronization, change control, retirement, exception management, and remediation.

• Embed data management requirements into S2C, P2P, TPRM, CLM, intake/orchestration, and buying-channel workflows rather than treating data management as a separate manual activity.

• Partner with IT/Digital and platform owners to define requirements for MDM, Coupa, Icertis, ProcessUnity, Zip, VDP/Snowflake, Power BI, and related integrations.

• Drive standardization, integration, and automation to reduce rework, duplicate maintenance, manual spreadsheets, data defects, and point-to-point workarounds.

3. Analytics Product Ownership & Decision Support

• Own the S2P analytics product portfolio, including executive dashboards, KPI views, category and program dashboards, standard performance scorecards, self-service analytics, and automated insight products.

• Define and maintain an integrated data and analytics roadmap based on business priorities, stakeholder needs, technology maturity, data risk, automation dependency, and transformation value.

• Ensure each analytics product has a defined audience, business purpose, trusted KPI set, data source, adoption plan, and operating cadence.

• Translate data into clear executive narratives that explain what changed, why it matters, and what decisions or actions are required.

• Generate decision-ready insights across spend, sourcing, suppliers, P2P performance, value delivery, savings visibility, compliance, cycle times, preferred supplier utilization, supplier risk, and SBE visibility.

4. Data Quality, Controls, Compliance & Risk Enablement

• Define data-quality rules, validation logic, exception thresholds, monitoring routines, and remediation playbooks across S2P master-data and analytics domains.

• Partner with Compliance, Risk, Finance, Internal Audit, TPRM, Sourcing, and Procurement Operations to ensure data supports regulatory expectations, audit readiness, financial controls, segregation of duties, risk visibility, and policy adherence.

• Reduce operational, compliance, and reporting risk resulting from incomplete, inconsistent, duplicative, or poorly governed data.

5. Analytics Automation & AI Enablement

• Lead the business roadmap for data and analytics automation, including data validation, enrichment, deduplication, exception detection, stewardship workflows, automated insights, conversational analytics, and agent-enabled reporting.

• Partner with IT/Digital, enterprise Data Governance, and data-platform teams to establish AI-ready data foundations, including governed definitions, semantic consistency, lineage, quality controls, access standards, and Snowflake/VDP readiness.

• Evaluate and enable capabilities such as AI agents, natural-language analytics, automated insight generation, exception-based reporting, and self-service decision support.

• Identify opportunities to reduce manual reporting and data-cleanup effort, shifting capacity toward performance dialogue, insight generation, governance, and scalable capability building.

6. Intake, Operating Model & Adoption

• Design and lead a sustainable operating model for S2P data stewardship, analytics intake, prioritization, backlog management, issue resolution, and delivery governance.

• Establish predictable routines for data-quality monitoring, taxonomy changes, dashboard refreshes, performance reviews, stakeholder feedback, and roadmap decisions.

• Define clear accountability across Procurement Operations, Sourcing, Finance, Legal, Risk, IT/Digital, enterprise Data Governance, and offshore or managed-service support teams.

• Drive adoption through standards, documentation, playbooks, training, office hours, stakeholder engagement, and clear role definitions.

• Differentiate and spearhead the strategic ownership of data governance, analytics products, insight delivery, and enablement from the day-to-day report production, dashboard maintenance, transactional execution, and operational data cleanup in parallel.

7. Cross-COE & Cross-Platform Collaboration

• Partner with P2P Process & Platform Enablement to ensure supplier, item/service, and reference data support clean transaction execution, control integrity, and operational performance visibility.

• Partner with S2C Process & Platform Enablement to ensure sourcing and contracting activities create high-quality downstream data and enable sourcing-performance analytics.

• Partner with Strategy, Governance & Excellence, SBE, TPRM, and Supplier Performance leaders to support trusted metrics and visibility into savings, value delivery, SBE performance, risk, supplier segmentation, and program outcomes.

• Coordinate with IT/Digital, enterprise Data Governance, MDM, VDP/Snowflake, and platform teams on architecture, integrations, access, data flows, tooling alignment, and long-term scalability.

Ownership Boundaries

This role owns

• Business governance, standards, roadmap, requirements, and operating model for S2P master data, taxonomy, reference data, analytics products, insight delivery, and AI-enabled analytics.

• Data-quality frameworks, stewardship routines, analytics intake, analytics-product adoption, and business requirements for data and analytics platforms.

• Strategic level oversight of Day-to-day operational report production or routine dashboard maintenance

This role does not Own

• Transaction execution, sourcing execution, or supplier relationship strategy.

• Savings methodology, target setting, or SBE program ownership.

• Policy definition, legal determinations, or enterprise technology delivery.

• The role partners with accountable process, program, finance, governance, supplier, and platform owners