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Explore What Others Are Building
Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.
As initially proposed by Pr. William M White of Cornell University:
Success to the successful archetype represents two reinforcing structures which may be in a delicate balance though as soon as one gains a small advantage the resource allocation favors the more successful and the result is then rapidly skewed in the direction of the more successful. See also Archetypes.
Video
This model is part of
And? Understanding Relationships & Their Implications.
This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process.
By adjusting the sliders below you can
observe the work process without any work in process limitations (WIP Limits),
with process step specific WIP Limits* (work state WIP limits),
or you may want to see the impact of the Tameflow approach with Kanban Token and Replenishment Token
or see the impact of the Drum-Buffer-Rope** method.
* Well know in (agile) Kanban
** Known in the physical world of factory production
The "Tameflow approach" using Kanban Token and Replenishment Token as well as the Drum-Buffer-Rope method take oth the Constraint (the weakest link of the work process) into consideration when pulling in new work items into the delivery "system".
You can also simulate the effects of PUSH instead of PULL.
Feel free to play around and recognize the different effects of work scheduling methods.
If you have questions or feedback get in touch via twitter @swilluda
The work flow itself
Look at the simulation as if you would look on a kanban board.
The simulation mimics a "typical" software delivery process.
From left to right you find the following ten process steps.
Input Queue (Backlog)
Selected for work (waiting for analysis or work break down)
Westley, F. R., O. Tjornbo, L. Schultz, P. Olsson, C. Folke, B. Crona and Ö. Bodin. 2013. A theory of transformative agency in linked social-ecological systems. Ecology and Society18(3): 27. link
World4 is a predictive model for world population. Population has grown hyper-exponentially in the last millenium, with the doubling time decreasing from 900 years in 1000 CE to a minimum of ~35 years in 1963 CE. Technology is defined as that which decreases the death rate and/or increases the effective birth rate (i.e. by decreasing infant mortality). Technology grows exponentially, therefore population fits a hyper-exponential (exponent within an exponent). Models for the end of growth are explored using equations that express the ways humans are depleting Earth's biocapacity, the nature of resource depletion, and the relationship between natural resources and human carrying capacity. This simple model, containing just two closed systems, captures the subtle shifts in the population trajectory of the last 50 years. Specifically, hyperexponential growth has given way to subexponential growth. A peak is predicted for the time around 2028. [Bystroff, C. (2021). Footprints to singularity: A global population model explains late 20th century slow-down and predicts peak within ten years. PloS one, 16(5), e0247214.]
