SupplyHouse.com - Director of Product

• Accountability across the pod structure • Pod ownership. Own outcome accountability for every product pod, ensuring each has a clear mission, a primary success metric, and explicit guardrail metrics. • Pod ownership. • Decision rights and shared accountability. Establish clear decision rights across Product, UX, and Engineering. Product leads customer problem definition, business outcomes, prioritization, and roadmap decisions; UX leads research and experience design; Engineering leads technical architecture and implementation. Hold each trio jointly accountable for delivering measurable outcomes, with unresolved tradeoffs escalated and decided quickly. • Decision rights and shared accountability. • Cross-pod seams. Resolve cross-pod dependencies, sequencing conflicts, and platform-versus-feature tradeoffs before they become delivery risk. • Cross-pod seams. • Operating cadence. Define and maintain the standards that make pods legible to leadership: how bets are written, how success is defined up front, how results get reported, and what happens when we need to pivot. • Operating cadence. • Leading and developing product managers • People leadership. Directly manage and coach a team of product managers with clear leveling expectations and honest, specific feedback. • People leadership. • Craft development. Build Product Management craft across discovery and delivery: opportunity framing, jobs-to-be-done and customer problem definition, hypothesis writing, experiment design, and evidence-based prioritization. • Craft development. • Hiring. Recruit, onboard, and retain strong product talent. Own the hiring bar and the interview loop for the function. • Hiring. • Influence without authority. Coach Product Managers to lead through influence across Merchandising, Marketing, Operations, Customer Service, and Engineering without relying on formal authority. • Influence without authority. • Managing to outcomes, not outputs • Outcome definition. Translate company strategy into a product strategy with a north star metric and a supporting metric tree, so every pod can trace its work to a business result. • Outcome definition. • Measurement. Replace feature-count reporting with outcome reporting: leading and lagging indicators, target versus actual, and a clear read on what we learned. • Measurement. • Continuous discovery. Partner with the Director of Customer Experience to establish a consistent customer research and usability practice across product teams, validate bets before they consume significant engineering capacity, and stop or pivot work that is not moving the intended metric. • Continuous discovery. • Evidence-based prioritization. Ensure prioritization reflects qualitative customer insight, behavioral data, business performance, and operational feedback rather than stakeholder preference alone. • Evidence-based prioritization. • Customer proximity. Build direct exposure to professional tradespeople and internal users into the product management operating model. • Customer proximity. • Portfolio balance. Manage capacity as a portfolio of bets across core growth, platform health, and exploratory work, and be able to defend that allocation to the executive team. • Portfolio balance. • Roadmap ownership • Annual roadmap. Build and publish the annual product roadmap, then maintain it as a living now / next / later view rather than a fixed feature calendar with dates attached to everything. • Annual roadmap. • Quarterly planning. Run the quarterly planning process: OKR setting, bet selection, capacity modeling, and tradeoff decisions with clear rationale. • Quarterly planning. • Executive alignment. Keep the roadmap credible with senior leadership and the board through clear, unhedged communication about what is committed, what is a bet, and what changed. • Executive alignment. • Backlog health. Maintain a rigorously prioritized backlog with a real definition of ready and definition of done, so pods are never blocked on ambiguity. • Backlog health. • Project management and delivery • Integrated planning. Ensure significant initiatives have clear scope, milestones, owners, dependencies, resource assumptions, risks, decision points, and launch criteria. • Integrated planning. • Risk management. Establish a consistent process for identifying, escalating, and resolving delivery risks before they affect committed outcomes or timelines. • Risk management. • Delivery accountability. Hold product managers accountable for maintaining clear plans, decisions, status reporting, and stakeholder alignment from discovery through post-launch evaluation. • Delivery accountability. • Cross-functional execution. Coordinate dependencies across Product, IT, UX, AI Enterprise Enablement, Marketing, Merchandising, Operations, Customer Service, and other impacted teams. • Cross-functional execution. • Commitment discipline. Differentiate committed work from discovery, experiments, and potential future investments so leadership has an accurate view of delivery confidence. • Commitment discipline. • Change management and adoption. Ensure significant product launches include stakeholder communication, training, operational readiness, adoption planning, and feedback mechanisms. Hold product teams accountable for sustained adoption and value realization, not only technical release. • Change management and adoption. • Delivery health. Measure and improve delivery health through indicators such as cycle time, throughput, and predictability. • Delivery health. • Process stewardship. Improve the tools and operating rhythms that make delivery visible, while removing process that does not improve decisions, accountability, or execution. • Process stewardship. • Technical product leadership • Partner with the VP of IT and engineering leaders to align the product roadmap with technical strategy, architecture, capacity, security, reliability, scalability, and platform health. • Ensure product managers can translate business and customer needs into requirements that account for system dependencies, integrations, data flows, APIs, and nonfunctional requirements. • Evaluate build, buy, and partner options using customer value, business impact, technical feasibility, implementation risk, total cost, and long-term maintainability. • Balance customer-facing enhancements with platform modernization, technical debt reduction, system reliability, and foundational capabilities. • Ensure technical constraints and dependencies are surfaced early enough to inform prioritization, sequencing, and executive decisions. • Establish strong partnership between product managers and technical leads without expecting product managers to dictate engineering solutions. • AI-enabled product strategy • Partner closely with the Director of AI Enterprise Enablement to identify, evaluate, and prioritize AI opportunities across customer-facing products and internal workflows. • Translate validated AI opportunities into product roadmaps with clear users, business outcomes, success measures, data requirements, and adoption plans. • Ensure AI-enabled product decisions consider usability, data quality, security, responsible-use expectations, technical feasibility, and ongoing performance. • Distinguish between experimentation and scalable production capabilities, with clear criteria for piloting, measuring, expanding, or discontinuing AI solutions. • Promote reuse of enterprise AI capabilities and prevent fragmented tools or duplicative solutions from developing across product teams. • Data and analytics • Product measurement. Establish the analytics, instrumentation, and reporting needed to evaluate product adoption, customer behavior, operational impact, and business results. • Product measurement. • Measurement readiness. Partner with data and technical teams to ensure product decisions are based on reliable information and that measurement requirements are defined before launch. • Measurement readiness.