Around the 7:00 minute mark Newson begins to talk about a stream of what brings him and Ive together: what they didn’t like. In a sense that the two are intellectual partners not by virtue of what interests them, but almost by virtue of what they are dissatisfied by. Ive turns this into a characteristic exploration of why things are produced.
Ive’s identification of carelessness apparent in modern production is now familiar to those that follow his ideas.1 It’s been hard for me to pinpoint exactly what this ‘carelessness’ implies. What actual facets of a finished product imply carelessness?2 Ive’s description here is more lucid than any I have come across before I think.
He describes that much of what we see around us is produced to hit a price point or a schedule, and what differentiates Apple’s work, and what gives it the care it deserves, is that it is produced to represent the values of the people that produce it. Of course all of these things – price, schedule, values – are factors in many good production processes, but I think the difference lies in what one considers non-negotiable.
For most companies today business metrics seem to be the primary non-negotiable. This is becoming harder with increasing data-fetishization.3 Few businesses now have the courage and self-awareness to stand up for values, and I wish more did.
Values can be moral and ethical in nature, but they have power even when they take a more fickle form. What you produce for can just be what you like, in fact that is the form that a lot of art takes. That many employees of modern businesses don’t care about what they do is a great sign of our extraordinary ability as humans to get together and feel nothing.
- This echoes the sentiments of Dieter Rams who has been known to inspire much of Apple’s work. ↩
- Could be how nothing aligns on the new Samsung phones ↩
- Data fetishization: the need to optimize for measurable outcomes, often leading to short-sighted, uninspired goals around improving metrics that incompletely capture impact.4 ↩
- I think there is an argument to be made that I should clarify that I do in fact, love data. I think it’s stupid to not measure impact when you have the tools to do so. Measure what you can. But this can be a trap. As what was formerly totally intangible now becomes partly tangible, partly intangible, there is a tendency to restrict analysis only to the numbers at hand. And to forget the stuff we haven’t been able to measure or analyze correctly. In this scenario the lesser analysis will restrict itself only to the numbers, whereas the harder, and correct thing to do is to use the numbers when you can and to keep the intangibles part of the analysis. Overriding the numbers is harder when you have numbers, but that’s also not a reason to not have numbers at all. ↩