Manager, Presales Value Consultant

Protect high-quality deal support by aligning Value Engineering capacity to the opportunities where specialist involvement is most likely to improve executive alignment, competitive differentiation, win probability, deal value, or strategic positioning. Partner with Sales and Solutions leadership to review demand, make capacity and deployment decisions, manage competing priorities, and identify when lower-complexity requests should be served through guided or self-service experiences. Drive adoption of the common enterprise value methodology, including approved value drivers, KPI definitions, benefit models, financial standards, benchmarks, assumption rules, and quality requirements. Reinforce strong governance and quality controls so customer-facing value claims are credible, supportable, appropriately documented, and aligned with approved financial and benchmark standards. Help scale Value through reusable assets, guided experiences, self-service tools, and governed automation while preserving direct Value Engineering involvement for the customers and opportunities where it creates the greatest return. Support the responsible use of AI-enabled capabilities for defined use cases such as discovery preparation, value-driver recommendations, business-case drafting, model quality assurance, lifecycle handoffs, and insight capture. Ensure human review, approved data sources, calculation guardrails, and appropriate customer-data protections remain central to the workflow. Track and communicate performance using measures such as value penetration, pipeline and revenue influenced, win-rate and deal-size impact, engagement mix, strategic allocation of VE capacity, self-service adoption, Value Traveler completeness, cycle time, stakeholder satisfaction, and reuse of value insights. Create an inclusive, high-performing team environment characterized by accountability, collaboration, curiosity, customer focus, and continuous improvement. Set clear expectations and development plans for each team member, provide timely and actionable feedback, recognize strong performance, address performance gaps, and support career progression across practitioner, leadership, and specialist paths. Represent Value Engineering in cross-functional planning and governance forums, bringing a practical field perspective to decisions about methodology, customer experience, technology, enablement, measurement, and go-to-market execution. 8 or more years of relevant experience in value engineering, value consulting, management consulting, business value services, sales strategy, solution consulting, financial analysis, or a related customer-facing discipline. Demonstrated success supporting complex HCM/WFM sales cycles and engaging credibly with senior customer and internal executives. Strong command of value discovery, business-case development, financial modeling, ROI and payback analysis, benchmarking, executive storytelling, and outcome-based selling. Experience translating a common methodology into consistent field execution without limiting the judgment required for complex customer situations. Strong understanding of the customer lifecycle and the connections among presales, implementation, adoption, value realization, renewal, and expansion. Experience driving adoption of new methodologies, tools, processes, or operating models across a team or broader go-to-market organization with a focus on innovation for global value framework. Proven ability to manage competing demands, establish prioritization criteria, allocate specialist capacity, and make sound tradeoffs in a high-volume commercial environment. Demonstrated ability to collaborate across Sales, Solutions, Services, Customer Success, Finance, Marketing, Product, and Operations. Strong analytical orientation and experience using performance data to evaluate commercial impact, operational effectiveness, capacity allocation, adoption, and team performance. Excellent executive communication, presentation, facilitation, and stakeholder-management skills, with the ability to simplify complex business and financial concepts. Sound judgment regarding the responsible use of customer data, benchmarks, financial assumptions, automation, and AI-generated outputs. Commitment to inclusive leadership, continuous learning, candid feedback, and the development of diverse talent. Bachelor's degree or equivalent practical experience in business, finance, economics, analytics, technology, or a related discipline. Advanced degree preferred.