IBP Strategy & Transformational Lead

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Job Summary: We are seeking a highly capable Inventory Transformation Process Leader to drive the evolution of our planning and execution ecosystem. This role blends deep systems expertise (SAP IBP) and supply chain systems expertise with strong business judgement and operational pragmatism. The successful candidate will challenge existing planning processes and systems architecture, apply decision-ready data sets , and implement exception-based planning to enable faster, higher-quality decisions. This role is hands-on and outcome-driven, focused on turning data into action and planning into a true operational decision engine. This is an exciting time to start this journey, providing the candidate the opportunity to blueprint and drive change. The successful candidate will bring in relevant industry experience, vision for continuous improvements, influencing ability to drive process and solution standardization, and collaboration with various stakeholders to achieve common goals, while delivering consistent and thorough deliverables as required. The ideal candidate will be someone who challenges "how it's always been done", is highly analytical, is a hands-on-leader who is equally comfortable at the whiteboard and in system configuration. One who values practical outcomes over theoretical perfection, builds systems that support how people actually work and is capable of articulating plans and ideas with all levels of the organization. Job Expectations: Strategy & Business Transformation Partner with Supply Chain Operations, Finance, Merchandising, Marketing, and IT leaders to redefine and/or optimize end-to-end planning processes , including Demand, Supply, Inventory, and IBP/S&OP Translate business strategy into a clear, executable IBP and Inventory Optimization roadmap Challenge legacy processes, assumptions, and system designs to improve speed, focus, and decision quality Drive measurable business outcomes across service, inventory, cost, and agility Decision Enablement & Exception-Based Planning Design and apply integrated, decision-ready data sets that align demand, supply, inventory, capacity, and financial views. Shift planning from calendar-driven review cycles to exception-driven workflows using clearly defined thresholds and tolerances. Ensure exceptions are actionable by defining: Business meaning Decision ownership Recommended actions and trade-offs Embed decision logic directly into IBP workflows to enable same-day or next-day decisions . Reduce planner effort by eliminating manual data preparation and focusing attention on the few critical issues that matter most . SAP IBP & Systems Architecture Own the solution design and architecture for SAP IBP (Demand, Supply, Inventory Optimization, Response & Supply, and related capabilities). Configure SAP IBP to support daily and weekly operational decision cycles , not just monthly IBP cadence. Design alerts, dashboards, and planning views that clearly answer: What changed? Why does it matter? What decision is required now? Ensure tight integration between SAP IBP, SAP S/4HANA (or ECC), BW/HANA, and execution systems to support fast response and closed-loop learning. Balance SAP standard best practices with practical usability for planners and operators . Data, Analytics & Applied Insights Apply forecasting, supply, and inventory analytics to prioritize action , not just improve model accuracy. Enable rapid scenario analysis and what-if simulations focused on real operational trade-offs (service vs. inventory, cost vs. speed). Partner with data and analytics teams to operationalize advanced models into repeatable, explainable decisions . Focus on speed to insight and decision clarity over analytical complexity. Execution, Delivery & Adoption Lead or support IBP and SAP supply chain implementations, enhancements, and upgrades. Collaborate with internal teams and external partners to deliver high-quality, usable solutions. Define success metrics and ensure solutions deliver tangible, measurable business value . Drive adoption through training, governance, and continuous improvement. Key Performance Indicators: Decision Speed & Focus Decision latency (time from exception detection to decision) Exception aging (open exceptions beyond defined thresholds) Exception volume per planner (trend downward) % of alerts acted upon vs. ignored Planning Effectiveness Forecast accuracy and bias at agreed aggregation levels Plan stability (week-over-week or cycle-over-cycle changes) Scenario cycle time (time to evaluate and decide) % of plans auto-approved vs. manually adjusted Inventory & Service Outcomes Service level / fill rate Inventory turns and days of supply Excess and obsolete inventory Stockout recovery time System & Adoption Health Planner touches per planning cycle Manual overrides as a % of total decisions Alert precision (true vs. false positives) Active user adoption and engagement rates The dut

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