Recently, I’ve come across the concept that helps me understand a lot of so-called “discrepancies” in ways organizations, or even individuals, operate. As a consultant, joining new organization usually makes you pause and ask yourself “Are these people for real? How come this organization works this way?” The POSIWID principle, or “The Purpose of the System Is What It Does”, has allowed me to get past that pausing point and opened up opportunities to truly understand what’s happening.
But before we dive into POSIWID, let’s get some additional context. Let’s kick things off with a quirky little brain teaser known as the Duck Test. Imagine stumbling upon a creature that, for all intents and purposes, looks like a duck, struts around like it owns the pond, and quacks like it’s gossiping with the other ducks. Your brain does a quick calculation and concludes: Yep, that’s probably a duck. This isn’t rocket science, folks. It’s just good old-fashioned logic. And no, it has nothing to do with alien abductions, despite the fancy term “abductive reasoning.” Which is, in turn, a form of logical inference. If all that sounds familiar — it’s because you probably heard something like this:
- All fish live in the water
- All trout are fish
- Therefore, all trout live in the water
Except if you’re a sandtrout, and you live on Arrakis.
This should help us understand how the duck test works. Best put by Douglas Adams, author of The Hitchhiker’s Guide to the Galaxy, it goes like this: If it looks like a duck and quacks like a duck, we have at least to consider the possibility that we have a small aquatic bird of the family Anatidae on our hands. In other words, if it looks like a duck, it walks like a duck and quacks like a duck — it probably is a duck.
This is the Duck Test. Neat, right?
There are, of course, exceptions, like the one presented by famous standup philosophers Marx Brothers: “He may look like an idiot and talk like an idiot, but don’t let that fool you. He really is an idiot.” But it’s more of an exception that confirms the rule.
So, does it work on other things or just ducks? Let’s check out ancient history records.
In 2016–2018, Apple and its iPhone devices went through what is known as “Batterygate”. Many users have reported unexpected device slowdowns and shutdowns at low battery charge levels. Apple initially responded with a couple of “bug fixes” and “you’re holding it wrong”-style explanations. Yet, Apple’s iPhone, the jewel of tech, kept acting more like a lazy sloth than a shiny top-of-a-line gadget.
However, systematic testing performed by the developers of Geekbench, a well-known computer benchmarking tool, has spotted a pattern of performance degradation. Under the pressure of the overwhelming evidence, Apple was forced to admit to setting up a “planned obsolescence” of its devices through intentional slowdowns of the phones where battery allegedly “degraded.” Having their duck legs boiled in duck test soup, Apple was forced to issue another update that disabled these performance controls.
This was a practical application of the Duck Test in real life.
We observe that phones keep slowing down or shutting down more often as they age. It is logical then to infer that the phone’s operating system is slowing them down as devices age. If it walks like a duck, and it quacks like a duck… you got the picture.
Of course, there are other examples of the Duck Test application. Let’s rewind to a year earlier when the California Franchise Tax Board decided that Blue Shield of California was hoarding cash like a dragon sitting on gold. Over $4 billion in reserves? That’s not very nonprofit-like, is it? The tax board’s verdict: If it hoards cash like a for-profit, then it should be taxed like a for-profit. In the words of the head of the California Consumer Advocacy Group: “If it looks like a duck and talks like a duck, it should be taxed like a duck.” Well, you know what Ben Franklin says: death and taxes are the only two certainties in life.
By now, it should be evident that although there might be exceptions, the logical inference of identifying the subject by its habitual characteristics works. You’re probably already nodding along, seeing the pattern. But can we generalize this approach? Is there a principle that we can apply to all systems as we analyze their behavior? Can there be a universal “quacking duck” principle?
Luckily, there is. Enter the world of POSIWID (The Purpose Of a System Is What It Does), which sounds like something you’d rather not step into, but stick with me.
POSIWID is a pragmatic approach to understanding systems based on their outputs and behaviors rather than their stated intents. This concept, foundational in systems thinking, suggests that a system’s true “purpose” can be discerned not from its stated objectives but from its actual effects and outcomes. In other words, it is a decoder ring for understanding the real deal behind fluffy words, mission statements, and PR stunts.
From the POSIWID point of view, the purpose of the iOS performance management system was not to make the Apple device perform at the highest level. It was to degrade the device’s performance to a degree that allowed the allegedly aged battery to still power the device and nudge the owner to purchase a newer model.
Applying the POSIWID principle to the real-world situations is pretty straightforward. Just like we applied the Duck Test to the behaviors of a bird, we can apply POSIWID to larger systems to observe and recognize patterns. Based on this, we will infer the system’s “real” purpose. It’s what it does!
For example, let’s explore Project Nessie, one of the secret internal pricing algorithms employed by Amazon, which resulted in the FTC filing a lawsuit against the company in 2023.
The project Nessie algorithm’s stated intent was price optimization and preventing “unusual” pricing caused by Amazon’s regular pricing algorithms. Coincidentally, it brought the company an additional $1 billion in revenue. Amazon claims that the algorithm’s true purpose is to prevent unintended pricing fluctuations and to remedy technical issues with Amazon’s other price-matching algorithms.
However, the observed behavior (the walking and the quaking of the system in question) differed. The algorithm identified opportunities to raise prices instead of optimizing them. This suggests that the true purpose was maximizing the profit over price stabilization. Additionally, the algorithm looked for situations where competitors would likely follow suit on raising prices by raising prices in response. This suggests that the true purpose was influencing the market, not reacting to it. Finally, even after the competition raises their prices, the algorithm would keep prices elevated, which suggests long-term profit maximization through price manipulation.
As of writing this article, the case is still unresolved. Amazon claims that the project Nessie has been scrapped. Walking and quaking was a little too loud this time.
So, there you have it. Whether it’s tech giants playing fast and loose with device performance or online behemoths tweaking prices for fun and profit, a dash of logic and a good dose of systems thinking can shed light on the truth. Because at the end of the day, if it walks like a duck and quacks like a duck, it’s probably time to pay attention to what that duck is really up to.
