Which then begs the question - if someone using supposedly bad “predictions” ends up having a better track record than another person relying on “good predictions”, what are the chances that the bad predictions actually the good ones, and vice versa?
Ok, let's have a knock-out coin-tossing tournament: 1024 people pair up, toss a coin and the winner goes through to the next round. After 10 rounds there
will be a single winner who has won 10 tosses in succession: that person must be some sort of coin-tossing genius, right?
We're all speculating about a complex system based on insufficient data. Its all educated guesses. Anybody who could predict the impending demise of Apple with any degree of confidence wouldn't be posting it here, they'd be on the phone to their broker shorting AAPL.
You know, like when people claimed the iPhone X wouldn’t sell because it was too expensive. Which makes sense from an economic standpoint - something which costs more should sell less. Yet the iPhone X did very well,
Do we actually have the data to prove that? What does "wouldn't sell" or "did very well" mean? What is important in the long term - unit sales or revenue? Looking at
Apple's figures, total iPhone
unit sales were up 3% in Q2 2018 (...when the iPhone X was readily available) c.f. Q2 2017 (...when the newest iPhone was the non-spectacular, incremental, 7 and everybody was speculating about the forthcoming radical iPhone re-design). Is that good, or would you expect a surge in sales after a major once-in-2-3-years revamp? Revenue was up 14% - but then both the X and the 8 were more expensive than previous models - is making more money out of flat sales my hiking margins sustainable? Come September when the iPhone XI/Xs/whatever launches, will customers who have previously updated every year think twice because of the higher price?
Did the people making that prediction also anticipate that Apple's major competitor, Samsung, and arch-enemies, Google, would also hike the price of their flagship phones - (probably for the same reason, to make more money out of stagnant sales)?
Its a similar case for the 2016 MacBook Pros - they certainly didn't flop, but they didn't bring in a massive growth in
unit sales as you might expect from the first major re-design in years - revenue went up because the prices went up.
If someone makes a prediction based on a convincing-sounding argument (something which costs more should sell less) and that turns out not to happen, then the question has to be why?
The iPhone 7 was going to be a complete failure because it didn't have a headphone jack - the Samsung Galaxy Note 7 blew it out of the water... but then it turned out that the Note 7 tended to blow
itself out of the water. Did Apple maybe dodge a bullet there?