Seems like a paper from a young student who needs to get his 3000 wordcount.
It just bloats the article and makes it difficult to get the information out of it.
I think it's great, it shows there's always a human side to trends and large statistics.
Call me inhumane, but a single story doesn't mean anything. It's just some random point in the set. Drawing any conclusions from such a single point is dangerous (the larger the set, the more), as we humans just love to extrapolate single points and even tend have quite strong emotional defenses about their importance.
To remove the emotional part, just think of something from IT, like response times or test coverages. See, a story of an obscenely long API response (out of thousands) doesn't make much sense anymore. Debugging individual cases may even lead you on a completely wrong track. Unless you want to merely resolve that particular single request.
I'm sorry about the tone. Stories about others make humans relate (which is good), but they also have such undesirable effects (hype over facts, extrapolating, etc).
Averages and generalizations only tell a portion of the story. Anecdotes can shed light on "noise".
That's also a single aggregated number. Until the data doesn't cover those millions dire situation, it's a bad data. Emotionless analogy: like a green status page when some percentile of requests is failing.
See, you've mentioned "millions" rather than some "that person.". That's exactly what I mean.