We explore how organizations can use system dynamics as the core analytical decision technology to achieve mission-critical goals.
In the The Basics of System Dynamics course we build and apply several basic System Dynamics models in the first 5 weeks of the course. In the last two weeks, 6 and 7, we will apply our inventory of skills and models to the problem of simulating a B (Benefits) Corporation in the context of a practical Business Canvas approach. For this portion of our studies we will use paper, pencil, and the VensimPLE platform for all of our work.
In the System Dynamics Inference course we apply Bayesian data analytics to calibrate, fit, simulate, and infer conclusions consistent with the causal model of the decisions we are studying. The causal model will be built in VensimPLE, read into R, where we can mash the model with data and use Stan to make probabilistic inferences. During the first 5 of 7 weeks we will build basic system dynamics causal models of various business decision, estimate probability models of decisions based on the causal models, and infer probabilistic results using Machine Learning and information criteria.
[UNDER CONSTRUCTION] The Informing Decisions course will help us formulate and solve problems to inform decision-makers within organizations using simulation and optimization, all deployed with spreadsheets. We will develop the skills and practice the techniques to structure and analyze a wide range of complex business problems to inform and support managerial decision-making in functional business application areas such as finance (e.g., capital budgeting, cash planning, portfolio optimization, valuing options, hedging investments), marketing (e.g., pricing, sales force allocation, planning advertising budgets) and operations (e.g., production planning, workforce scheduling, facility location, project management). Spreadsheets are used to assist in modeling, analysis, and communication of results and findings.
For these courses we will cross four computing platforms.
VensimPLE will help us build and simulate generative causal models, visualize results, and develop scenarios for decision makers.
The R programming language (with R Studio - Posit), the tidyverse of data, optimization, numerical integration, and visualization packages will provide a platform for analysis, inference, and visualization of results.
The Stan (for Stanislaus Ulam) probabilistic programming library with its ability to estimate systems of differential equations (the underlying mathematics of system dynamics) using Hamiltonian Monte Carlo simulation will allow us to estimate the uncertainty within the causal models we have built.
Lastly, spreadsheets? Yes, the ubiquitous, immediate satisfaction of near instantaneous results spreadsheet environment is used by millions. As a prototype it surpasses most other environments. But beware its use in production! We will use spreadsheet engineering practices to improve on modeling hygiene and model deployment for decision makers on the run.
(During the Spring 2025 session from January 13th to March 9th, the Basic System Dynamics course is offered as MBA 645 Special Topics: Strategic Management Science by the Manhattan College MBA Program. Please contact Dr. Marc Waldman, Program Director, at marc.waldman@manhattan.edu for more information about the program.)1
We are now nearing the end of the 6th week. It is time to put all our learning togethe into a model of your favorite B Corp, NGO, or not-for-profit organizations. We will hold our sixth Live Session tomorrow Saturday, February 22, 2025 from 10am-11am (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured again will be questions and answers and not a few solutions as we crank up not only the mechanics. This week we feature the way income and balance sheet components interact with management intervention.
We will also continue to grow in our interpretative abilities using these models as our backdrop. Insights will also continue to emanate from what if and why not questions at the core of sensitivity analysis. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this term’s course experience. Further grist for our mill comes from the quaestio disputata and 6-step frameworks and the notorious canons of empirical method.
Canons of Empirical Method
Our approach to decision making is not ethereal, it is concrete, yes, but supplemented with insight, so much so we feel compelled to decide on something different. Our horizons will remain static and decay; or they will expand and grow. We might ponder our approach to building models using Bernard Lonergan’s Canons of Empirical Method. Here is a synopsis of these guidelines. There are 6: selection, operations, relevance, followed by complete explanation, parsimony, and statistical residues.
Look at the details in Week 6. We might want to incorporate some of this methodological thinking into our building of the B Corp model this week.
Here is the recording for the Week 5 live session deposited into the 2025 playlist for this course.
System Dynamics: Spring 2025 Live Sessions
More sigmoids this week as we study the interactions of hours worked and worker quality,limited by the carrying capacity of worker recovery and stress alonside production requirements, the system dynamics archetype of limits to growth. This week we apply so much of what we have learned from the previous 4 weeks into this study of the impact of worker stress on hours worked. Does production, productivity matter? What an interesting question it would be to ask whether and to what extent the quality of work life impacts productivity and the retention of workers. We also delve into a framework for developing and formulating actionable management recommendations, the indomitable quaestio disputata system dynamic.
We have rounded the bend and now at the end of the 5th week. Congratulations. We will hold our fifth Live Session tomorrow Saturday, February 15, 2025 from 10am-11am (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured again will be questions and answers and not a few solutions as we crank up not only the mechanics. This week we feature the way income and balance sheet components interact with management intervention.
We will also continue to grow in our interpretative abilities using these models as our backdrop. Insights will also continue to emanate from what if and why not questions at the core of sensitivity analysis. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this term’s course experience.
Here is the recording for the Week 4 live session deposited into the 2025 playlist for this course.
System Dynamics: Spring 2025 Live Sessions
Sigmoids, those lovely upward (and downward) S-curves. These were first introduced by Pierre Verhulst in 1830 to model population growth limited by carrying capacity, the system dynamics archetype of limits to growth. We apply this model to adopters of a market innovation. The limits there include popularity and the size of the potential market. This approach winds up in understanding probabilities and is the core of the AI self-attention matrix. In self-attention the logistic function generalizes to the softmax mapping. In this session we also walk into a key model for finance, non-renewable resource management, reservoir depletion, goodwill amortization, and economic depreciation of long-lived assets and liabilities.
Try to attend our fourth (already!) Live Session tomorrow Saturday, February 8, 2025 from 10am-noon (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured again will be questions and answers and not a few solutions as we crank up not only the mechanics. We will also continue to grow in our interpretative abilities using these models as our backdrop. Insights will also continue to emanate from what if and why not questions at the core of sensitivity analysis. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this term’s course experience.
Let it grow…let it blossom…let it grow
Through the eyes of all the work we’ve done so far, we look at growth and decline. A finance example helps us with decline while marketing with growth.peer into the maw of every day we work. This week presents a very basic, yet another kernel of a model of innovation. We can imagine as well the limits to growth saga from the system archetypes.
Enjoy!
Here is the recording for the Week 3 live session deposited into the 2025 playlist for this course.
System Dynamics: Spring 2025 Live Sessions
Through the eyes of the week 2 supply chain example, we peer into the maw of every day we work. This week presents a very basic, the inexorable kernel of a model of project work. A major upsetting condition is the quality of work completed, reworked, yet to be done. When do we consider burnout and morale? We imagine how project dynamics might assert, and inject, itself (even rearing its ugly head!) in the week 2 inventory-workforce model. Aren’t we effectively creating an inventory of remaining work and rework through the dynamics of project completion? Can we imagine measuring ontime-in full through service levels?
Try to attend our third Live Session tomorrow Saturday, February 1, 2025 from 10am-noon (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured again will be questions and answers and not a few solutions as we crank up not only the mechanics. We will also continue to grow in our interpretative abilities using these models as our backdrop. Insights will also continue to emanate from what if and why not questions at the core of sensitivity analysis. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this term’s course experience.
Are there yet? Are we finished? When, when, when?
Through the eyes of the week 2 supply chain example, we peer into the maw of every day we work. This week presents a very basic, the inexorable kernel of a model of project work. A major upsetting condition is the quality of work completed, reworked, yet to be done. When do we consider burnout and morale? We imagine how project dynamics might assert, and inject, itself (even rearing its ugly head!) in the week 2 inventory-workforce model. Aren’t we effectively creating an inventory of remaining work and rework?
Enjoy!
Here is the recording for the Week 2 live session deposited into the 2025 playlist for this course.
System Dynamics: Spring 2025 Live Sessions
In this session we delve into yet another highly interactive model with two states: inventory and workforce. This model illustrates the two-loop limits to success model in Kim and Anderson where management constraints come in the form of target inventory, production, hiring, and inventory coverage (a sort of safety stock). The model is also a variant of a predator-prey interaction.
Try to attend our second Live Session tomorrow Saturday, January 25, 2025 from 10am-noon (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured will be questions and answers and not a few solutions as we crank up the mechanics of this online course. While mechanics might annoy us from time to time, the purpose of modeling is to enable insightful analysis and interpretation. Sensitivity analysis will dominate much of the discussion. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this terms’s course experience.
Though in week2 with a supply chain example, we might look at this model of a the interaction between inventory and workforce dynamics. It is in a spreadsheet! A great exercise is to draw the Forrester diagram (like in Vensim) for this example. Another great exercise is to use this spreadsheet as a template to make simulations for the week 2 model.
Google Sheet system dynamics model.
So, which is easier to use: VensimPLE or Google Sheets?
Enjoy!
Thanks to all who were able to join us at our first Live Session. Videos for the live sessions are accessible at this YouTube site:
Spring 2025 Live Sessions playlist
Yes, we do quite a bit of meandering, that’s what the |> button is for :)
Enjoy on your own and with your team mates.
Try to attend our first Live Session tomorrow Saturday, January 18, 2025 from 10am-noon (ET, UTC-5) on Zoom: https://us06web.zoom.us/j/9177353014. Featured will be questions and answers and not a few solutions as we crank up the mechanics of this online course. While mechanics might annoy us fromm time to time, the purpose of modeling is to enable insightful analysis and interpretation. Sensitivity analysis will dominate much of the discussion. The session will be video’d for posterity and deposited on a Youtube playlist dedicated to this terms’s course experience.
Some housekeeping notes:
For those registered in a current Manhattan University MBA course, access the WALL course blog-site on the course Learning Management System (Moodle) and post your response there for credit. Examples of responses from other participants in the course are located at this public site https://systemdynamics101.blogspot.com/.
For those registered in a current Manhattan University MBA course, access the weekly grade assignment activity on the course Learning Management System (Moodle) and post your response there for credit. For those who are self-studying, you may access the Workbook,. In either case, answer the questions, and upload your first model joint-venture.mdl.
Due dates are not deadlines. The only deadline in the course is at its completion when grades must be posted to the Registrar for credit. But the due dates are there to help us pace ourselves, keep up with readings, and simply digestion of the complex of ideas we are attempting to conform to the reality of what we are modeling and ultimately interpreting for decision makers.
We begin our first week together in MBA 645 Strategic Decision Analysis at Manhattan University with The Basics. Welcome to all who enrolled. A welcome to those who might begin a self-study course for your own edification.
Enjoy the ride!
You can text me on my mobile (917-767-7980) anytime. Please let me know who you are and give me 24 hours to respond. I’m usually a bit quicker than that. We will have live sessions on zoom every Saturdays from 10am-noon.
Thanks, Bill
Enjoy, and always encourage one another daily, while it is still today!
William G. Foote, Ph.D.
Mobile/Text: 917-767-7980
Zoom: https://us06web.zoom.us/j/9177353014
GitHub: https://github.com/wgfoote/
Office hours (MBA 645 Summer 2024):
At the end of these courses students can expect to demonstrate progress in meeting the following goals, proposed here as actions with verbs in the imperative mood.
Pose a researched business question, model the causal influences implicit in the question, simulate potential causal relationships and counterfactual inferences and their sensitivities, and align inferences with decision alternatives and plausible choices for stakeholders.
Deploy analyses which produce interactive analytical products using an industry-grade computational platform engineered according to a tradition of design principles.
Using endogenous generative models, summarize experience and beliefs about stakeholders, their data, and the processes that the generated data used, to infer potential outcomes to answer business questions.
Practice quantitative critical thinking skills through a compound of statistical and normative problem solving which links strategic policies and practices with stakeholders.
Understand the role of the analyst and the analytics process in the decision-making context of complex organizations and their environments.
Communicate analytical decision results to decision makers and other consumers of analytical products effectively using interactive tables and graphs.
For my part this curriculum emanates from over 45 years of learning from and teaching managers system dynamics and statistical inference at Fordham University, Clarkson University, Syracuse University and LeMoyne College. I have used SD techniques and simulations at a variety of financial institutions, high tech, energy, retail, governmental and not-for-profit organizations world-wide. I especially want to acknowledge the many years of working with my son, Andrew Foote, who, with his company Paraclete Risk Solutions LLC, was critical in the development, promotion, and delivery of systems models, strategy, consulting, and services to multiple public and private sector clients over the past 20 years.
I have taken liberally materials and ideas (some might say I curated materials) from several extant courses. They all flow from the avowed discoverer of the systems dynamics methodology, Jay W. Forrester, and his decades of work, and students, at the Sloan School of Management, MIT.
First, the maths: Harry Hochstadt’s Differential equations : a modern approach (1963-4) in the first 84 pages details the math behind system dynamics, namely solving systems of simultaneous differential equations.
Second, the numerics: Joel Ferziger’s Numerical Methods for Engineering Applications, 1978. Yes, FORTRAN. I moved most of these routines to MATLAB and APL2 in the 80’s.
Jay Forrester’s 1998 MIT Introduction to System Dynamics self-study course Everything you will need to know about the formulation and interpretation of System Dynamics models from the inventor.
George Richardson’s 2013 Albany University Public Policy courses.
John Sterman’s 2013 Introduction to System Dynamics MIT-OCW course
Ventana System’s VensimPLE Modeling Guide and Tutorial along with Tom Fiddaman’s MetaSD model library
The premise of this curriculum is that learning is inference. Learning can be reading, understanding, reflecting whether in our heads or with complex computing environments. We begin with the following chain of reasoning:
All events, and data collected from events, have a truth value.
Probability is the strength of plausibility of a truth value.
Inference is a process of attaining justified true belief, otherwise called knowledge; learning is inference.
Justification derives from strength of plausibility, that is, the probability distribution of a hypothesis conditional on the data and any background, prior, and assumptive knowledge.
The amount of surprise, or informativeness, of the probability distribution of data given our experiences, is the criterion for statistical decision making – it is the divergence between what we known to be true and what we find out to be true.
All statistical analysis, and reasoning within analysis, begins from a disturbance in the status quo. The disturbance is the outlier, the error, the lack of understanding, the inattentiveness to experience, the irrationality of actions that is the inconsistency of knowledge and action based on knowledge.
We are surprised when the divergence between what we used to know and what we come to know is wider than we expected, that is, believed. The analysis of surprise is the core tool of this course. In a state of surprise we achieve insight, the aha! moment of discovery, the eureka of innovation.
The course will boil down to the statistics (minimum, maximum, mean, quantiles, deviations, skewness, kurtosis) and the probability that the evidence we have to support any proposition(s) we claim.
The evidence is the strength (for example in decibels, base 10) of our hypothesis or claim. The measure of evidence is the measure of surprise and its complement informativeness of the data, current and underlying, inherent in the claim.
Copyright 2024, William G. Foote, all rights reserved.↩