Dan Finn

About Dan Finn

I help complex value streams become simpler, more predictable, and more resilient—without sacrificing throughput, service, or long-term capability.I currently serve as Global Head of Supply Chain Management Digitalization at Continental, with more than 20 years of experience spanning lean manufacturing, supply chain design, and advanced analytics.My work focuses on improving flow and lead-time reliability by increasing transparency where it matters and systematically reducing unnecessary variability. In practice, this means balancing speed, visibility, and stability across end-to-end value streams rather than optimizing one dimension at the expense of the others.I integrate Lean principles with SAP S/4HANA, advanced analytics, and AI-enabled decision support, developing predictive and prescriptive models (Python, R) grounded in real operational constraints—not abstract optimization.At the core of my approach is a simple belief: some complexity is waste, some complexity is competitive edge. Knowing the difference is what allows organizations to reduce noise, protect critical capabilities, and build processes that perform reliably over time.

Experience

1. Global Head of Supply Chain Management Digitalization, Group Sector Contitech

   Continental

   Apr 2022 — Present

   Lead the global digitalization of Supply Chain Management across 60 factories and distribution centers focusing on making complex industrial systems simpler, more predictable, and more resilient — improving flow, lead time, and transparency without compromising throughput, service, or long-term capability.Own the end-to-end SCM digitalization strategy, establishing standardized, best-practice processes that balance global consistency with local operational realities.Drive global implementation of SAP S/4HANA Forecast-to-Deliver, creating a unified digital backbone across suppliers, manufacturing, logistics, and customer fulfillment.Design and implement a company-wide SIOP program using SAP Analytics Cloud, integrated with SAP S/4HANA and SAP R/3 Long-Term Planning, enabling scenario-based, data-driven decisions across demand, supply, capacity, and inventory.Develop and deploy predictive and prescriptive analytics (Python, R, machine learning, AI) to improve forecasting accuracy, inventory positioning, lead-time reliability, and operational decision quality.Apply lean manufacturing, value-stream mapping, and constraint-based thinking to reduce variability, eliminate non-value-adding complexity, and protect throughput.Translate operational behavior into financial, service, and risk implications, supporting senior leadership decisions and sustainable performance improvement.

Education

• University of Nebraska-Lincoln

  Post Masters Graduate Certificate , Business Analytics

  2017 — 2020

• University of South Dakota

  Master of Business Administration (M.B.A.)

• University of Nebraska-Lincoln

  Bachelor's degree, Chemical Engineering