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Harnessing Intangible Business Factors with Dynamic Business Models

In the session “Harnessing Intangible Business Factors with Dynamic Business Models,” part of the “System Dynamics for Business Innovation” series led by Kim Warren, the conversation centered on how intangible assets like reputation, skills, data, and quality affect—and are affected by—the development of a business system and its performance. Here are the key takeaways from the session:

  1. Understanding Intangible Factors: Intangible factors such as reputation, skills, and data play crucial roles in business systems. Warren stated, “Intangible factors are not just qualitative; they can and should be quantified.”
  2. Specifying and Quantifying Intangibles: Participants learned methods to specify, quantify, and simulate intangible factors within dynamic business models (DBMs). Warren shared, “Dynamic business models can reliably incorporate intangible elements, allowing for better strategic decisions.”
  3. Leveraging Intangible Assets: Strategies to harness intangible assets for business growth and sustainability were discussed. “Understanding and managing intangibles can lead to significant improvements in business performance,” Warren noted.

Warren classified intangible factors into three main categories: State of Mind (e.g., reputation, motivation), Information-based (e.g., data, procedures), and Quality-related (e.g., product quality). Each category plays a crucial role in the overall dynamics of business systems, impacting everything from customer loyalty to operational efficiency.

State of mind intangibles influence behaviors such as customer loyalty and staff productivity. As Warren illustrated, “State of mind drives behavior, which in turn impacts business performance.” Information-based intangibles, including customer data and procedural knowledge, are vital for improving operational efficiency and customer satisfaction. Accurate and comprehensive information helps businesses operate smoothly and meet customer needs effectively. Additionally, improving product or service quality over time enhances reputation and fosters customer loyalty. Conversely, negative qualities, like software bugs, need to be minimized to avoid damaging the business’s reputation and customer trust.

Watch the full webinar recording below. It provides in-depth insights into the development, functionality, and applications of leveraging intangible business factors with dynamic business models, showcasing its potential to improve business strategy and operations.

Courses

How to Build Intangibles into Your Dynamic Business Models

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Modelling Intangible Factors + Modeling Essentials

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    About the Speaker

    Kim Warren is an experienced strategy professional, teacher, and publisher of online courses and teaching resources on business modeling – fast becoming a mainstream capability for executives, consultants, and business students. He was awarded the Jay Wright Forrester Award by the International System Dynamics Society in 2005 and was the Society’s President in 2013.

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    From Text to Map: A System Dynamics Bot for Constructing Causal Loop Diagrams

    We had an insightful webinar titled “From Text to Map: A System Dynamics Bot for Constructing Causal Loop Diagrams.” The session, led by Niyousha Hosseinichimeh, explored the capabilities and challenges of a novel tool designed to automate the creation of causal loop diagrams (CLDs) from textual data. Here are the key takeaways from the presentation:

    Overview of the System Dynamics Bot

    The System Dynamics Bot aims to automate the process of constructing CLDs from text, leveraging large language models and generative artificial intelligence. Niyousha Hosseinichimeh emphasized the tool’s potential by stating, “The System Dynamics Bot can streamline the modeling process, making it less labor-intensive and more efficient.”

    1. Capabilities of Large Language Models: The bot uses deep learning techniques to process and interpret text, identifying causal relationships and constructing CLDs. This demonstrates the potential of large language models in system dynamics and model building.
    2. Effectiveness and Practical Examples: Practical examples during the webinar showcased the bot’s ability to convert textual data into causal loop diagrams, effectively capturing significant feedback loops and causal links. Hosseinichimeh noted, “This tool offers a novel way to enhance our understanding of complex systems by automating the creation of causal loop diagrams.”

    Evaluation of the Bot’s Performance

    Two data sets were used for evaluation:

    1. Data Set One: Included 20 CLDs from system dynamics literature, capturing 60% of causal links and 66% of feedback loops on average.
    2. Data Set Two: Included responses from 30 individuals, with the bot capturing 56% of causal relationships and 83% of feedback loops.

    Applications and Future Directions

    The bot can significantly save time and effort in developing CLDs, assisting both novice modelers and experienced practitioners. Potential applications include:

    • Educational Tools: Enhancing the learning experience for system dynamics students.
    • Group Model Building: Supporting the creation of causal loop diagrams during group sessions.
    • Comparative Studies: Comparing human-generated and AI-generated models to improve accuracy and insights.
    • Literature Review-Based CLDs: Synthesizing information from various fields to create comprehensive diagrams.
    • Mapping Mental Models: Analyzing how different individuals perceive complex issues.

    Hosseinichimeh highlighted, “This program can be used to generate literature review-based causal loop diagrams and aid in group model building sessions,” showcasing its versatility and practical benefits.

    Watch the full webinar recording below. It provides in-depth insights into the development, functionality, and applications of the System Dynamics Bot, showcasing its potential to revolutionize how we construct and interpret causal loop diagrams.

    Watch the recording below

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    PRESENTERS

    Niyousha Hosseinichimeh has a PhD and a master’s degree in public administration and policy from State University of New York at Albany, and a bachelor’s degree in mechanical engineering from Sharif University, Iran. She is currently an assistant professor at the Department of Industrial and Systems Engineering at Virginia Tech. Her research focuses on developing and applying methods to improve health and healthcare systems. She uses simulation models to help stakeholders improve their understanding and decision making in complex dynamic systems. She has applied system dynamics approach to diverse health issues including infant mortality, mental health, and alcohol impaired driving among teens. Her methodological contributions include expanding calibration methods for dynamic models and developing techniques for system dynamics group model building. Her research has been funded by the National Institute of Health, National Science Foundation, Agency for Healthcare Research and Quality, Ohio State Department of Health, and Burroughs Wellcome Fund.

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    Leveraging Dynamic Business Models for Enterprise Architecture

    In the session Leveraging Dynamic Business Models for Enterprise Architecture, part of the System Dynamics for Business Innovation series led by Kim Warren, the conversation centered on enriching Enterprise Architectures (EAs) through the integration of quantitative Dynamic Business Models (DBMs). This approach significantly amplifies the efficacy and reliability of IT strategies and planning.

    Course

    Dynamic Business Modelling

    How to build powerful living models of plans or issues in half the time of using spreadsheets

    Key Insights:

    1. Foundation of Enterprise Architectures (EAs):
      • EAs provide a structural blueprint for IT strategy development, focusing on the organization’s processes and how these support its operational goals.
      • The webinar highlighted the importance of understanding these frameworks for implementing effective IT systems aligned with business objectives.
    2. Role of Dynamic Business Models (DBMs):
      • DBMs contribute to a more robust EA by introducing quantitative analyses that validate and enhance the traditionally qualitative aspects of EA.
      • By modeling business dynamics quantitatively, DBMs facilitate more accurate IT system alignment with strategic business goals, improving resource allocation and change management.
    3. Synergies between EAs and DBMs:
      • The webinar illustrated how DBMs strengthen EAs by providing a rigorous analytical foundation that accelerates and refines the architecture building process.
      • These models help predict the impact of IT strategies on business performance, making implementation more effective.
    4. Applications and Validation:
      • DBMs offer a structured approach to testing and validating IT strategies before full-scale implementation, ensuring that IT plans are both effective and aligned with overarching business strategies.
      • The session underscored the utility of DBMs in real-world applications, demonstrating their capacity to support complex decision-making across diverse business domains.
    5. Impact on IT Strategy and System Planning:
      • Incorporating DBMs into EA efforts leads to more informed decision-making, with enhanced insights into the interactions between various business functions and IT systems.
      • This integrated approach supports a proactive stance in IT strategy formulation, emphasizing continuous adaptation and alignment with business changes.

    The webinar was particularly relevant for IT professionals, systems architects, business analysts, and strategic managers. It also offered critical insights for academics and students in business and technology disciplines.

    Watch the recording below

    Whoops, this recording is available for members and ticket purchasers only. Please login to verify. If you’re not a member, purchase a membership here. You can also buy a ticket to watch the recording here

    About the Speaker

    Kim Warren is an experienced strategy professional, teacher, and publisher of online courses and teaching resources on business modeling – fast becoming a mainstream capability for executives, consultants, and business students. He was awarded the Jay Wright Forrester Award by the International System Dynamics Society in 2005 and was the Society’s President in 2013.

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    Cancer Prevention and Control with System Dynamics

    The webinar titled “Cancer Prevention and Control with System Dynamics” presented a systematic review focused on the use of System Dynamics modeling in the field of cancer research. The main objective was to evaluate how this methodology is applied across various studies to address complex issues in cancer prevention and control, including treatments, risk assessments, and intervention strategies.

    System Dynamics Modeling for Cancer Prevention and Control: A Systematic Review

    Key insights from the webinar included:

    1. Application of System Dynamics: The review detailed how both simulation models and causal-loop diagrams are utilized to study the dynamics of cancer-related issues, ranging from chemotherapy effectiveness to the impacts of environmental contaminants on cancer risks.
    2. Quality Assessment: The studies were assessed for quality based on criteria like clarity of objectives, adequacy of information sources, and the involvement of stakeholders. This highlighted a need for more rigorous standards in modeling to enhance reliability and applicability.
    3. Focus Areas and Interventions: The research covered diverse topics such as the effectiveness of cancer treatments, prevention through behavioral changes, and early detection techniques. It also underscored the importance of System Dynamics in modeling interventions like tobacco use reduction and vaccination strategies.
    4. Recommendations for Improvement: The presentation stressed the necessity for greater transparency and rigor in System Dynamics studies within cancer research. It called for the development of supportive infrastructures and best practices to foster multidisciplinary collaborations.

    The presenters, Erin Kenzie and Wayne Wakeland, through their extensive backgrounds in systems science and health policy, emphasized the potential of System Dynamics to offer comprehensive insights and effective solutions in cancer prevention and control.

    For those interested in exploring innovative methodologies and their practical applications in addressing complex health issues, watching the recording of this webinar is highly recommended. It promises valuable learnings in System Dynamics and its significant role in advancing cancer research.

    Watch the recording below

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    PRESENTERS

    Erin Kenzie is an Assistant Professor at the OHSU-PSU School of Public Health at Oregon Health and Science University in Portland, Oregon and holds faculty roles at the Portland State University System Science Program and the Oregon Rural Practice-based Research Network. She received her PhD in Systems Science from PSU in 2021. Dr. Kenzie’s research spans system dynamics, implementation science, and public health. She has been involved in research applying System Dynamics to colorectal cancer screening, behavioral health system capacity, unhealthy alcohol use screening and treatment, rural Veteran access to care, health plan-clinic partnerships, behavioral health integration, traumatic brain injury recovery, and climate change mitigation behavior.

    Wayne Wakeland is Professor Emeritus of Systems Science at Portland State University. He also served as the Systems Science Program Chair for many years. He earned a B.S. and a Master of Engineering at Harvey Mudd College (1973); and a Ph.D. in Systems Science at Portland State U. (1977). He developed and taught courses on computer simulation methods and more recently a course on system sustainability and organizational resilience. His research focused on the use of computational models for studying a variety of topics, including complications during human pregnancy, recovery from concussion, and policies to reduce opioid drug diversion, abuse, and overdose deaths. Other topics included environmental/ecological sustainability and elevated intracranial pressure due to traumatic brain injusy. He has been active in the System Dynamics Society for many years and helps lead its Health Policy Special Interest Group.

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    New Member Orientation and Networking April 2024

    Member Orientation

    The System Dynamics Society has recently hosted a New Member Orientation aimed at introducing new participants in the community. The session, led by SDS President, Allyson Beall King, and Director of Outreach, Meagan Colvin, provided an overview of the Society’s structure, mission, and opportunities for member involvement. The agenda included an introduction to the Society’s objectives, its staff, and the myriad of resources it offers.

    Highlights from the Orientation

    Introduction to Staff and Structure: The session provided detailed information on the organizational structure of the Society, introducing key personnel and their roles within the Society, from various locations around the globe.

    Member Resources and Benefits: The orientation highlighted several benefits for members, such as:

    • Discount on conference registration fee
    • Free access to all seminars and recordings
    • Reduced prices and some free courses for online learning.
    • Free access to the System Dynamics Review.
    • Membership in various Special Interest Groups (SIG) and Chapters with networking opportunities.

    Interactive Sessions: The event included a question-and-answer segment where participants engaged directly with leaders, enhancing the interactive nature of the orientation.

    Networking Opportunities: There was a special segment for networking, where Chapter and SIG leaders introduced themselves and shared insights into their activities, promoting community interaction among members.

    The New Member Orientation underscored the System Dynamics Society’s commitment to providing valuable resources and fostering a collaborative environment. It emphasized the Society’s dedication to tackling significant global issues through System Dynamics.

    For those interested in a deeper understanding of the membership benefits and to hear firsthand from Society leaders, we encourage watching the recording of the event. This will provide prospective and current members with a comprehensive view of the opportunities available within the System Dynamics Society.

    Watch the recording below

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    Artificial Intelligence and System Dynamics in Business and Management

    The recent webinar, titled “The Dynamic Interplay Between Artificial Intelligence (AI) and System Dynamics (SD) in Business and Management,” provided deep insights into the evolving relationship between AI and SD. This session was part of the System Dynamics Society’s ongoing Seminar Series. It aimed to dissect the convergence of AI and SD within the business and management landscapes.

    Key Takeaways from the Webinar:

    1. In-Depth Bibliometric Analysis: The session kicked off with a comprehensive bibliometric analysis, highlighting how academic discussions on System Dynamics and AI intersect, charting their evolution and emerging patterns. This approach provided a solid base for understanding the convergence trajectory of these fields.
    2. Advanced Topic Modeling Discoveries: The webinar delved into the intricacies of AI and SD integration through cutting-edge topic modeling techniques. This analysis offered a detailed perspective on how these fields are blending, adding depth to our understanding.
    3. Dual Convergence Pathways: The discussion highlighted two main convergence pathways: ‘soft convergence’ and ‘hard convergence.’ Soft convergence looks at how AI augments SD with a focus on social dynamics, while hard convergence explores AI’s role in reengineering system design and interdependencies.
    4. Emerging Trends and Strategic Implications: An interesting aspect of the session was the exploration of current trends. It was noted that soft convergence is more prevalent in today’s business landscape, but hard convergence is gaining momentum and could revolutionize SD research and application.
    5. Practical Applications of AI and SD: The session also covered how AI technologies are being used across various domains like healthcare, risk management, and customer service, providing real-world examples of their impact.
    6. Theoretical Framework Necessity: A crucial point raised was the need for a convincing theoretical framework to effectively combine AI’s data-based approaches with SD’s organizational strategies.

    In closing, this seminar not only presented an analysis of AI and SD convergence but also invited scholars, researchers, and industry practitioners to further explore this synergy. The insights gained from this webinar are invaluable for anyone interested in the intersection of these two fields.

    Watch the recording below

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    About the Speakers

    Francesca Iandolo, PhD: A Tenure-track Assistant Professor in Management at Sapienza University of Rome, Francesca Iandolo specializes in corporate sustainability and technology in digital platforms. With a master’s in accounting and a PhD focusing on the Viable Systems Approach, she actively contributes to academic coordination and research, and consults for private companies.

    Giuliano Maielli: Researcher in business history and organization studies, focuses on technological and organizational innovation. His work, emphasizing design hierarchies, path-dependence, and socio-organizational phenomena, delves into platform innovation dynamics and the Internet of Things, contributing significantly to peer-reviewed academic publications.

    Stefano Armenia: Tenure-track Lecturer at the Università Telematica degli Studi in Florence, specializes in Business Organizations and Dynamical Systems. With a background in Computer Engineering and Business Engineering, he contributes to System Dynamics societies, edits scientific journals, and researches in fields ranging from cybersecurity to sustainable transportation.

    Pietro Vito, PhD: A researcher in Economics and Business Management at Sapienza University of Rome, Pietro Vito’s research spans systemic and vital perspectives in business management. His interests include sustainability, environmental protection, intellectual capital, and artificial intelligence, contributing to a broader understanding of management methodologies.

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    Dynamic Business Models for Dealing with Competition

    In the latest webinar of the System Dynamics for Business Innovation special series, Kim Warren delved into Dynamic Business Models for Dealing with Competition. This session, rich in practical advice and strategic insights, is pivotal for professionals seeking to sharpen their competitive edge. Here’s a breakdown of the webinar’s key points.

    Key Takeaways from the Webinar:

    1. Understanding Competitive Dynamics: The session focused on the use of dynamic business models to navigate competitive business environments. Warren highlighted the importance of understanding how competition plays out in real-time and the impacts on prices, marketing spending, and profits.
    2. Case Studies and Applications: Warren used two illustrative case studies to demonstrate the practical application of these models. He discussed GSK’s travel vaccines business and its response to a new competitor, and Beyond Meat’s strategy in creating a market for non-meat products. Both cases highlighted the strategic challenges and responses in dynamic competitive environments.
    3. Types of Competition: Warren outlined three standard competition mechanisms, covering most competitive scenarios. These include racing to capture new potential customers, maintaining existing customers while attracting competitors’ customers, and handling situations where customers can switch between suppliers.
    4. Practical Strategy Development: The session also touched upon practical aspects of strategic planning, like leveraging dynamic models for both long-term strategy and short-term operational decision-making.

    Invitation for Further Learning

    This webinar is a must-watch for those interested in refining their competitive strategies and understanding the application of dynamic business models. Viewing the recording will provide a deeper insight into the discussed concepts.

    Furthermore, the series will continue to offer rich content on strategic business areas such as IT systems architecture and environmental impact reporting. These upcoming sessions represent a unique opportunity to gain advanced knowledge and skills in the field.

    Join us for the upcoming webinars to deepen your understanding of dynamic business models and their critical role in shaping successful competitive strategies

    Certificate

    Attendees who participate in at least 6 out of the 9 webinars in the series will be eligible to receive a certificate titled “Introduction to Dynamic Business Models.” This is an opportunity to gain recognition of your learning in this innovative field. For those who cannot attend live sessions, recordings will be available, allowing you to review the material and complete the series at your convenience.

    Watch the recording to get your certificate code.

    Watch the recording below

    Whoops, this recording is available for members and ticket purchasers only. Please login to verify. If you’re not a member, purchase a membership here. You can also buy a ticket to watch the recording here

    About the Speaker

    Kim Warren is an experienced strategy professional, teacher, and publisher of online courses and teaching resources on business modeling – fast becoming a mainstream capability for executives, consultants, and business students. He was awarded the Jay Wright Forrester Award by the International System Dynamics Society in 2005 and was the Society’s President in 2013.

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    Escape from Model Land – How Mathematical Models Can Lead Us Astray and What We Can Do About it

    In the third episode of MINDS CAST, we had the privilege of engaging with Erica Thompson, the author of “Escape from Model Land” This session delved into the intricacies of using mathematical models in decision-making, highlighting both the potential benefits and the pitfalls of relying heavily on these models. Here, we summarize the key insights from this enlightening discussion, including Thompson’s perspectives on the role of models in understanding complex issues and the importance of critical engagement with these tools.

    About the Presenter:

    Dr. Erica Thompson, Associate Professor of Modelling for Decision Making at UCL’s Department of Science, Technology, Engineering, and Public Policy, brings a wealth of expertise to the topic. Her research focuses on the application of mathematical and computational models in decision-making, with a particular emphasis on developing techniques for assessing and interpreting models. As a Fellow of the London Mathematical Laboratory and a Visiting Senior Fellow at the LSE Data Science Institute, her work also delves into the philosophical aspects of model outputs and their integration with expert judgment in decision-making processes.

    Webinar Overview:

    1. The Essence of Models in Decision-Making: Thompson opened the discussion by exploring the role of mathematical models in aiding our understanding of complex issues like economic regulation, climate change, and pandemics. She emphasized that while models are crucial tools, they do not produce perfect predictions of the future.
    2. Challenges in Mathematical and Social Contexts: The conversation highlighted the mathematical and social challenges in using models for decision-making. Drawing on examples from climate change and COVID-19, Thompson underscored the importance of recognizing the limitations and assumptions underlying these models.
    3. Best Practices for Responsible Modeling: The session also touched upon best practices for responsible modeling, especially in politically charged contexts. Thompson stressed the need for transparency, accountability, and the acknowledgment of value judgments embedded within models.
    4. Navigating Model Land: The concept of ‘Model Land’ – a metaphorical space where models exist in their idealized form – was a key focus. Thompson discussed the risks of becoming overly reliant on models and strategies for effectively navigating out of Model Land while still leveraging the benefits they offer.

    Key Points from the Discussion:

    • Model Diversity and Assumption Transparency: Thompson advocated for the diversity of models and perspectives in modeling processes. She emphasized the need for models to make their assumptions and biases explicit, allowing for more critical engagement and evaluation of their outputs.
    • The Role of Experts in Modeling: The discussion also addressed the evolving concept of expertise in modeling. Thompson highlighted the importance of involving a range of experts in the modeling process to ensure diverse perspectives and assumptions are considered.
    • Models as Conviction Narratives: Thompson described models as ‘conviction narratives,’ tools that provide a structured way of thinking about the future. She stressed the importance of understanding models as narratives that require translation and interpretation to be effectively used in decision-making.
    • Future of Modeling: Looking ahead, Thompson envisioned a modeling landscape that is more integrally connected with social and political contexts. She called for models that are transparent about their value judgments and capable of incorporating diverse perspectives to enhance trust and utility in decision-making.

    Erica Thompson’s insights in the MINDS CAST episode provide a valuable perspective on the complexities of mathematical modeling. Her emphasis on critical engagement, diversity of perspectives, and the need for transparency in modeling practices offers a roadmap for navigating the challenges and potentials of models in decision-making. As we continue to rely on models to understand and shape our world, Thompson’s call for a more nuanced and responsible approach to modeling is both timely and essential.

    Watch the recording below

    About the Speaker

    Dr. Erica Thompson holds the position of Associate Professor of Modelling for Decision Making at UCL’s Department of Science, Technology, Engineering and Public Policy, where I work on a programme of research funded by a UKRI Future Leaders Fellowship. She is also a Fellow of the London Mathematical Laboratory, where she leads the research programme on Inference from Models, and a Visiting Senior Fellow at the LSE Data Science Institute.

    Her research focuses on leveraging mathematical and computational models to guide decision-making in practical contexts. Dr. Thompson has dedicated her efforts to developing mathematical and statistical techniques for assessing and interpreting models. Additionally, she explores essential philosophical inquiries concerning the true significance of model outputs and the integration of models with expert judgement in decision-making processes.

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    Making Systems Mapping Accessible

    June 26 at 11 am NY | 4 pm London | 11 pm Beijing | Time Converter

    From Text to Map: A System Dynamics Bot for Constructing Causal Loop Diagrams

    May, 15 at 11 am NY | 4 pm London | 11 pm Beijing | Time Converter

    From Text to Map: A System Dynamics Bot for Constructing Causal Loop Diagrams

    Join us to delve into the innovative System Dynamics Bot, a tool designed to automate causal loop diagram creation from text. Learn how it performs in converting text to maps, see practical examples, and understand the challenges and solutions in its development.

    Learning Outcomes:

    • Gain insight into the capabilities of large language models in system dynamics and model building.
    • Understand the effectiveness of the System Dynamics Bot in identifying key relationships within textual data.
    • Discover the challenges encountered and solutions implemented during the development of this tool.

    This webinar is ideal for system dynamics practitioners, data analysts, and anyone interested in the intersection of artificial intelligence and model building. Sign up to explore how this technology can streamline your modeling processes and enhance your understanding of complex systems.

    About the Presenters

    Niyousha Hosseinichimeh has a PhD and a master’s degree in public administration and policy from State University of New York at Albany, and a bachelor’s degree in mechanical engineering from Sharif University, Iran. She is currently an assistant professor at the Department of Industrial and Systems Engineering at Virginia Tech. Her research focuses on developing and applying methods to improve health and healthcare systems. She uses simulation models to help stakeholders improve their understanding and decision making in complex dynamic systems. She has applied system dynamics approach to diverse health issues including infant mortality, mental health, and alcohol impaired driving among teens. Her methodological contributions include expanding calibration methods for dynamic models and developing techniques for system dynamics group model building. Her research has been funded by the National Institute of Health, National Science Foundation, Agency for Healthcare Research and Quality, Ohio State Department of Health, and Burroughs Wellcome Fund.