Systems Thinking in Business Administration

Master of Science in Business Administration Module SNM: Strategic Network and Business Ecosystem Management Instructor: Dr. Andreas Hieronymi (andreas.hieronymi@hslu.ch)

Systems Thinking I

Introduction

Course Content Overview

Systems Thinking I

  • Topics Covered:

    • Definition of systems, networks, and stakeholders

    • Interdisciplinarity and long-term thinking

    • Stakeholder needs analysis and business ecosystems

    • Cause and effect relationships, variables, and trends

    • Understanding cause and effect: Variables, values, and needs

    • Trends, behavior over time, growth and decline

    • Causal diagrams and digital tools

    • Causal Loop Diagrams (CLD)

    • Software tools for diagrams and simulations

Systems Thinking II

  • Topics Covered:

    • Ideation and decision making

    • Leverage points for intervention

    • Decision matrix to compare options

    • Communication and negotiation

    • Case studies on complex effects of growth and decline

    • Approaches to communicate complex cases

    • Critical thinking and evaluation

    • Mental models and addressing thinking errors

    • Model critique and improvement

Learning Goals

  • Identify systems (projects, problems, opportunities) and articulate their purposes and boundaries

  • Analyze relevant variables and describe their behavior over time

  • Interpret diagrams of interconnected variables and convert diagrams to textual representation

  • Draw causal loop diagrams

  • Identify intervention points (leverage points) and formulate relevant decision criteria

  • Effectively communicate complex cases to groups, including negotiation and decision making

  • Critically evaluate causal statements and diagrams, provide feedback to enhance diagrams and strategies

Key Terminology in Systems Thinking

  • Systems Thinking (Systemdenken, systemisches Denken):

    • Interconnected thinking, holistic thinking.

  • VUCA (Volatility, Uncertainty, Complexity, Ambiguity):

    • Framework describing complex and unpredictable environments.

  • Causal Loop Diagram (CLD) (Kausales Schleifendiagramm):

    • A visual representation of the interactions within a system showing cause-and-effect relationships.

  • Feedback Loop (Rückkopplungsschleife):

    • A mechanism where the outputs of a system are fed back and used as inputs, influencing the system's behavior.

  • Leverage Point (Hebelpunkt):

    • A point within a complex system where a small change could produce a significant change or effect.

Teaching Methodology

  • Blending theory and methods of systems thinking with practical cases and exercises.

  • Structure of various sessions includes:

    • Discussion of reflective questions

    • Exercises with real-world business contexts

    • Evaluation and feedback sessions

Case Studies and Applications

  • Mini-Cases Included:

    • Traffic congestion in Accra, Ghana

    • Patagonia's business model

Critical Thinking and Evaluation

  • Importance of mental models in analyzing complex situations

  • Encouragement to present both subjective and objective information

  • Utilizing tools such as the Iceberg Model and Behavior-over-Time graphs for comprehensive analysis

Complex Problem Solving

  • Competencies required:

    • Collaborative systems thinking skills

    • Understanding the interplay between social, economic, and ecological challenges

  • Encouragement of visual systemic approaches with digital tools (e.g., Miro.com)

Systems Thinking Iceberg Model

  • Observed behaviors and events often have deeper systemic structures behind them.

  • Patterns can be explained through the understanding of stocks, flows, and feedback loops.

Limits to Growth: Systems Archetypes

  • Overview of general behavior patterns seen across systems:

    • Limits to growth, success to the successful, erosion of goals, escalation, tragedy of the commons, and others.

Practical Tools for Systems Thinking

  • Recommended tools:

    • Software like Vensim, InsightMaker for causal loop diagramming

    • Techniques for effectively recognizing and modeling causal relationships

Feedback Loops & Loop Polarity

  • Understanding systems’ behavioral dynamics through positive (reinforcing) and negative (balancing) feedback loops.

  • Use of loop polarity signs (+ or -) to indicate relationships between variables within a model.

Conclusion

  • Emphasis on the significance of systems thinking skills for tackling current and future complex problems in various sectors.

  • Encouragement to apply these principles in real-world situations to develop robust strategies aimed at sustainable organizational success.

  • Contact for further inquiries: Dr. Andreas Hieronymi (andreas.hieronymi@hslu.ch)