91–100 of 106 posts
I want to say “prediction is hard, especially about the future” and it is no surprise that the predictions of a model built in the ‘70s might not hold some 50 years later. That they held so well for so long should, perhaps, be the headline. Does Forrester’s model get updated and re-run?
What an interesting and strange article. The author barely offers a definition of "systems thinking", only names one person to represent it, and then claims to refute the whole discipline based on a single incorrect prediction and the fact that government is bad at software projects. It's not clear what positive suggestions this article offers except to always disregard regulation and build your own thing from scratc…
The deeper question is why create models of a reality in which all models are wrong, but some extract value long enough to create both ecological collapse and poverty? These are the end states or even goals of models in a universe with limited resources to surfaces of planets.
Each optimization is designed to create dystopic conditions. This is obvious.
The citation to the beer game is a pretty fun one. About 15 years ago, John Sterman (a Forrester disciple) held a beer game "world championship" at a system dynamics conference, and my mother and I brought what we think is the optimal strategy and completely dominated the competition. Ironically, if you apply "systems thinking" in the right way, the beer game is a relatively simple thing to play extremely close to op…
The citation to the beer game is a pretty fun one. About 15 years ago, John Sterman (a Forrester disciple) held a beer game "world championship" at a system dynamics conference, and my mother and I brought what we think is the optimal strategy and completely dominated the competition. Ironically, if you apply "systems thinking" in the right way, the beer game is a relatively simple thing to play extremely close to op…
I thought the beer game challenge was because players didn't have information about the upstream or endpoints, only the downstream?
Earlier quoted context omitted.
I thought the beer game challenge was because players didn't have information about the upstream or endpoints, only the downstream?
Every player has global visibility of inventories, at least when you play the physical game, but many other things (orders, backlog, etc.) are hidden. However, you don't need more information than inventories. Incidentally, the only variable that no player has visibility of is the stream of future customer orders.
In this version, the manufacturer sees all the inventories, and all the middle layers pass all stock to the next layer. (The game also has a trivial demand function, so the only challenge is to detect or predict the single step change in demand rate, and then calculate 3 weeks ahead to smooth out the supply chain.)
https://forio.com/app/showcase/near-beer-game/
The game was played for 35 years before you demonstrated that it was a broken over-complication of a trivial game?
Or did you break the game by coordinating with your teammates on strategy (or, equivalently, all players computing the perfect Hofstadteran superrational strategy https://en.m.wikipedia.org/wiki/Superrationality ), when the game was meant to simulate the general human tendency for hyperlocal optimization, and the problem of dealing with chaotic incompetent peers?
Earlier quoted context omitted.
Every player has global visibility of inventories, at least when you play the physical game, but many other things (orders, backlog, etc.) are hidden. However, you don't need more information than inventories. Incidentally, the only variable that no player has visibility of is the stream of future customer orders.
I think the Near Beer Game models your logically reduced version of the game, ignoring the original game’s irrelevant information and non-positive-value options for the intermediate players. In this version, the manufacturer sees all the inventories, and all the middle layers pass all stock to the next layer. (The game also has a trivial demand function, so the only challenge is to detect or predict the single step c…
Earlier quoted context omitted.
Every player has global visibility of inventories, at least when you play the physical game, but many other things (orders, backlog, etc.) are hidden. However, you don't need more information than inventories. Incidentally, the only variable that no player has visibility of is the stream of future customer orders.
I think the Near Beer Game models your logically reduced version of the game, ignoring the original game’s irrelevant information and non-positive-value options for the intermediate players. In this version, the manufacturer sees all the inventories, and all the middle layers pass all stock to the next layer. (The game also has a trivial demand function, so the only challenge is to detect or predict the single step c…
If you use knowledge of the deck, you can obviously pre-solve things, but that was not an assumption here - our thing works without knowledge of the order deck.
The "new beer game" looks totally different, honestly.
I don’t think the author is accurately characterizing Systems thinking but is closer to talking about something like Agile vs Waterfall. Which i think they’re still correct about, and there has been a sharp turn into waterfall-like thinking (though they will never call it that) in software development recently.
Why was there a sharp turn to waterfall-like thinking? Why did we lose the learnings?
If you want to experiment with a version of the world model the article references, you can play with an implementation I put together here: https://insightmaker.com/insight/2pCL5ePy8wWgr4SN8BQ4DD/The-...
Earlier quoted context omitted.
> Systems don't do that. Only constituents who fear particular consequences do. These are part of a system. Ignoring these components gives you an incomplete model. (All models are incomplete, by definition, but ignoring constituents that have a major influence greatly reduces the effectiveness of your model)
You make a fine point. My simplified version of it is that there is no such thing as an isolated system. Things change. A system optimized for one environment is likely to fail when things change. Most of the hugely successful firms of today focus more on controlling their environment than on developing a capacity to adapt to unforeseeable consequences of unforeseen changes in their environment, even the ones that th…
> there is no such thing as an isolated system.
Very true.
Look no further than evolutionary biology, you see this all the time where extinctions occur because the environment changes such that the system is no longer optimal.