Introduction to Process Modeling for Data-Driven Lean Design

January 10th, 17th, 24th | 3 Week Virtual Master Class | $150

This three-part series will walk through the process of process modeling, from initial data mining and analysis to distribution identification and examining the process with a value stream map. We will use this information to build a baseline discrete event simulation (DES) model using Process Playground™, validate the baseline model against the value stream map, and then use the new digital twin of the process to model improvements to the process and expansions to our product line.

Whether you're a complete novice with process modeling or have previously worked with other software, this series is a fun and informative way to learn more about process modeling, data analysis, and building validated models that mimic process reality.

Introduction to Process Modeling Training Sessions

January 10, 2024

Session 1: Introduction to Process Modeling and DES

  • Overview of data mining and initial data analysis techniques
  • Introduction to value stream mapping for process visualization
  • Building a foundational discrete event simulation (DES) model in Process Playground™
  • Real-world application: Modeling a coffee shop’s airport launch

January 17, 2024

Session 2: Distribution Identification and Customer Segmentation

  • Using EngineRoom to analyze process data and identify sub-processes
  • Determining best-fit distributions and parameters for model accuracy
  • Expanding the baseline model with data-driven complexity
  • Practical case study: Enhancing the coffee shop model with real operational data

January 24, 2024

Session 3: Demand Variability and Staffing Optimization

  • Transitioning from intermediate to advanced model simulations
  • Using simulations to optimize staffing and predict performance under demand
  • Exploring scalability and process improvements through digital twin modeling
  • Applying insights to develop strategic plans for operational expansion

Maximize Your Data Analysis Skills with EngineRoom®

Included in your training, you'll receive full access to EngineRoom, our comprehensive data analysis and statistical software designed specifically for quality and process improvement professionals. With 60 days of unlimited access, you can dive deep into EngineRoom's powerful features, exploring tools and techniques that enhance your analytical skills.

  • Comprehensive Data Analysis: Utilize an extensive suite of tools, including statistics, diagramming, documentation and process modeling.
  • Process Playground: Experiment and simulate scenarios to see the impact of different process improvement techniques with EngineRoom's process modeling software.
  • Smart Assistant: Hexie, our AI chatbot, can answer questions, help explain statistics and direct you to process improvement tools.
  • 60-Day Access: Continue to explore and apply your learning with EngineRoom even after the course ends.

Registration is closed for this series

Get notified via email about upcoming webinars and future Master Series sessions.

Learn from Industry Leaders

Our instructors are seasoned professionals with extensive backgrounds in their fields, combining academic expertise with real-world experience. Expect interactive sessions, hands-on application, and expert guidance tailored to your learning journey.

Lars Maaseidvaag
Lars Maaseidvaag

MoreSteam Client Services

Dr. Lars Maaseidvaag continues to expand the breadth and depth of the MoreSteam curriculum by integrating the learning of Lean tools and concepts with advanced process modeling methods. Lars led the development of Process Playground, a Web-based discrete event simulation program. Before coming to MoreSteam in 2009, he was the Curriculum Director for Accenture/George Group and has also worked in operations research and management consulting.

Lars received a PhD in Operations Research from the Illinois Institute of Technology. Prior to his PhD, Lars earned a M.S. in Operations Research and Industrial Engineering as well as an MBA from The University of Texas in Austin.

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