Citing sources familiar with Apple’s supply chain, Nikkei is reporting that the company is scaling back iPhone 6s and 6s Plus production by as much as 30% for the January-March quarter.
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“This is an eye-opening production cut which speaks to the softer demand that Apple has seen with 6s out of the gates,” FBR Capital Markets analyst Daniel Ives told Reuters on Tuesday. “The Street was bracing for a cut but the magnitude here is a bit more worrisome.”
In turn, Wall Street hasn’t reacted kindly to the news, with shares of Apple falling as low as $102 in trading. In the last six months alone, Apple stock has dropped by nearly 30%.
While iPhone sales always cool off a bit following the busy holiday quarter, Nikkei notes that Apple’s initial supply order was on par with what it put in for last year’s iPhone 6 models. In other words, some are viewing the report as concrete evidence that iPhone sales this quarter will experience a year-over-year decline. Indeed, you might call that Morgan Stanley analyst Katy Huberty recently issued a research note opining that the iPhone in 2016 will experience its first drop in sales in history, largely due to “higher prices in international markets (ex-China) and maturing smartphone penetration in developed markets weighs on upgrades and new user growth.”
Personally, I think the doom and gloom scenarios about iPhone demand falling by the wayside are overblown. We’ll provide a more in-depth response soon, but for now, it’s probably a good time to quote Tim Cook on the veracity of supply chain rumors.
Addressing reports of a rumored drop in iPhone demand in 2013, Cook told analysts the following:
I know there has been lots of rumors about order cuts and so forth and so let me just take a moment to make a comment on these. I don’t want to comment on any particular rumor because I would spend my life doing that but I would suggest it’s good to question the accuracy of any kind of rumor about build plans.
I’d also stress that even if a particular data point were factual it would be impossible to accurately interpret the data point as to what it meant for our overall business because the supply chain is very complex and we obviously have multiple sources for things, yields might vary, supply performance can vary. The beginning inventory positions can vary, I mean there is just an inordinate long list of things that would make any single data point not a great proxy for what’s going on.
