Christina M. Lanham

WORK HISTORY

EDUCATION

SKILLS

ABOUT CHRISTINA M. LANHAM

I am a \"Builder\" at heart. Most organizations suffer from a gap between boardroom strategy and technical reality; I have spent my career standing in that gap. Whether I am launching an international entity as a solo venture in the UK or architecting a Salesforce CPQ environment that vendors deemed \"impossible,\" I specialize in turning operational complexity into scalable, automated machines.My approach is rooted in information velocity. I don’t just identify bottlenecks; I engineer the systems to break them. From my early days in the U.S. Navy—where I digitized manual communications to eliminate reams of daily paperwork—to my recent work in M&A integration, my goal is always to move data faster and more accurately to drive better decision-making.Key Achievements:• Defying \"Impossible\" Logic: Orchestrated a solo, full-cycle implementation of Salesforce CPQ, designing a custom architecture with 100+ dependencies to handle complex bundling that external consultants claimed required a massive team.• Predictive Resource Strategy: Developed a geospatial analytics model in Power BI to monitor instructor utilization across North America. By tracking \"nights-away\" thresholds (20 nights/30 days), I moved the organization from reactive historical reporting to proactive forecasting, protecting our talent from burnout.• International Entity Launch: Relocated to the UK as a solo executive to establish and lead ITI’s European entity. • M&A Systems Orchestration: Led the technical merger of ITI into Interplay Learning, managing a dual-NetSuite environment and migrating legacy infrastructure. I am at my best when I am architecting the \"Order-to-Cash\" journey, bypassing system limits with creative logic (Salesforce Flow, Celigo, Power BI), and leading teams through periods of high-growth or acquisition-led change.Core Expertise: RevOps Strategy, ERP/CRM Architecture (NetSuite & Salesforce), M&A Integration, International Operations, and Predictive Data Modeling.