Cordance - VP, Product

• Partner with BU Presidents and Product Leaders • Help Presidents and Product leaders turn customer needs, market opportunities, and business priorities into clear product strategies and roadmaps. • Challenge assumptions on product-market fit, differentiation, prioritization, and investment before major decisions are made. • Help teams move beyond feature roadmaps toward stronger customer-, market-, and outcome-based product decisions. • Get directly involved in important product decisions where additional product leadership can materially improve the outcome. • Improve the Quality of Product Bets • Assess major product bets on customer value, market opportunity, differentiation, expected business impact, required investment, and execution feasibility. • Help teams determine where to invest, test, accelerate, modernize, or stop. • Bring rigor to early product validation so teams learn quickly before committing significant engineering capacity. • Connect product decisions to measurable results, including adoption, retention, expansion, ARR growth, and customer value. • Build Products in the AI Age • Help teams identify AI-native opportunities rather than simply adding AI features to existing products. • Help Product and Engineering teams use AI-assisted development to improve speed and time to market. • Bring practical fluency in AI-enabled UX, automation, agentic workflows, data, model economics, security, and privacy. • Ensure AI investments are grounded in real customer and business outcomes, not novelty. • Raise Product Capability Across the Portfolio • Coach senior Product leaders and PMs to become better product and business leaders. • Strengthen discovery, prioritization, MVP definition, roadmap strategy, experimentation, and product measurement. • Establish a small number of practical product standards and operating rhythms that improve execution without slowing teams down. • Identify common capabilities, tools, and patterns that can be leveraged across businesses where it makes sense. • Introduce current SaaS and AI product thinking while respecting the unique markets and customer needs of each business. • Connect Product, Engineering, and Business Strategy • Work closely with Engineering leaders so product strategy and technical decisions reinforce one another. • Engage credibly on SaaS architecture, cloud, APIs, data, platforms, AI, and scalability. • Help teams think clearly about build, buy, partner, and platform choices. • Maintain a strong customer and business orientation while working across technical and commercial teams. • Competencies: • Product Judgment – Identifies important customer problems, validates opportunities, and makes clear prioritization decisions. • Product Judgment • Builder Mindset – Creates and improves products rather than simply managing roadmaps or large Product organizations. • Builder Mindset • AI-Native Thinking – Sees where AI changes what gets built and how teams build it, and focuses on value over novelty. • AI-Native Thinking • Commercial Fluency – Connects product decisions to adoption, retention, expansion, monetization, and ARR growth. • Commercial Fluency • Influence Without Authority – Earns credibility with CEOs, Presidents, and Product leaders and influences through expertise and judgment. • Influence Without Authority • Leader Development – Coaches senior Product leaders and PMs to become stronger product and business leaders. • Leader Development • Technical Credibility – Engages effectively with Engineering while remaining fundamentally customer- and product-led. • Technical Credibility • Bias for Outcomes – Values judgment, speed, and measurable results over process for its own sake. • Bias for Outcomes