First define the observation.Haha you're funny. You really want to stick with using Occam's razor? This debate with you is too easy.
Occam's razor is only a last resort to make a guess when there is no evidence. When there is evidence, people analyze the evidence to see which is true regardless of how complicated it is. Evidence rules above all. Only when there is no evidence can you possibly use Occam's razor to get the best chance of a correct answer even though it is still entirely unreliable and inaccurate. I have provided direct proof against the theory that China's car purchase decrease is due to declining spending power, therefore no philosophical theory, especially not Occam's Razor, can vouch for its truth.
By logic and common sense, you can understand why the statement that "the simplest answer is always true" is entirely flawed, right? I just provided you with a real world example. When iphone sales drop, it is not the Occam's razor solution that people are poorer, but the solution that is more complicated and supported by evidence, which is a purposed withdrawal in anticipation for the new release. What else can you say against this?
Your example of the Ford carrier is wrong and self-defeating as any support for Occam's razor. The correct example to support Occam's razor is if a tree were to be found broken, the explanation that a storm broke it is much better than something random like hundreds of animals kept hitting it through the night to break it. Yes, that's true if there were no evidence, but if there is evidence of blood and carcasses or storm or ax marks or vehicular strike (or even alien activity, for that matter), then obviously, evidence would determine the truth, NOT simplicity and NOT Occam's razor.
Occam's razer is not acceptable as an argument in science or in law. It is a detail of ancient philosophy and theory taught for trivial purposes. It is completely useless to any craft or trade where accuracy is important.
You can not state "the tree get broken in the last 24 hours".
Say there was a huge storm last night .
Can we say that the tree fall down BECAUSE the storm?
No, because that doesn't give explanation why the other trees doesn't get broken.
If there is 1000 tree in the forest, and we found a broken one in a 24 hours period, then we can say that "there was a storm when the tree snap".
If 20 tree fall in the forest in each average year then then is 5% of chance on every day to see a fallen tree.
So even if there is blood on the tree,or mark of a car or whatever on its own not a proof for anything.
To prove that we have it require not evidence of whatever, but statistically significant evidence.
Example no one said " hey, mate, I found the highs bozon in my beer" , but that "with 6sigma confidence we observed the higgs decay"
Now, get back china.
Next observations :
Phone falling sales >explanation is the lack of iphone features, and lack of whatever with android
Falling pork sales >lot of people get healthy
Falling poultry sales > lot of people eat fish
Falling fish sales>lot of people started to hate fishes
Falling car sales>government wants clean cities
Falling tv sales > lot of people has enough tv at home
decelerate (maybe falling ) house sales > everyone has enough house (or whatever)
Or , we can explain the above by simply falling income, ( consumer spending = income-savings+credit)
Now, all above can be attached a probability.
Now, the 7 first observation explained by seven independent probability, the falling income is one probability.
So, to know how much chance we have to explain the falling sales of everything with 7 INDEPENDENT probability. The sum chance of this explanation against the simpler one is a multiplication of 7 number. It will be infinitesimally small.
This is Occam's razor in probability language....
Same for the argument about "china is different ".
That has a chance, but as the pattern of consumer debt example become similar like many other before recession/crisis/whatever landing it chance will be small.
Sum: if there is several independent probability (each with around 50% ) that sum explain an event, or a single probability then the single one has higher chance.