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I would say that a reasonable person could have foreseen Concord failing. Perhaps not necessarily as hard as it did, but there were a number of red flags before it released. The character designs were bland and bad, which is worse than just being bad. They drummed up a whole bunch of controversy, and the marketing outside of that controversy was basically non-existent. Almost nobody had heard of the product until it already had failed. Even when it was in beta for free, they only garnered about a couple of thousand players at any given time.

Then you add on that they already missed the train for hero shooters by about eight years and their modern competition is all free to play and has already sucked up the entire market for the most part. I saw an analysis by a former game producer that thought that perhaps they had a work environment that stifled criticism and commentary from developers and I think that that might have been an accurate assessment; The entire product was released in a way that myself and a number of other people that I've seen online simply can't believe that nobody was throwing their hands up and saying that this was a bad idea before release.

> I would say that a reasonable person could have foreseen Concord failing.

> Then you add on that they already missed the train for hero shooters by about eight years

There's an analysis video I saw on Youtube which touches upon this fact: data-driven production suffer from two major problems: when they register a signal (i.e. people like hero shooters), it's already too late. It is impossible to catch a growing trend, just one that has already reached its peak.

The second problem is that the data is misleading in the first place. Using social media sentiment, for example, is pure nonsense because social media personas are not real people. They don't buy toilet paper, they don't talk (or Google) about 99% of their boring existence, and the signal is manipulated by bots and malicious agents. It is absolutely crazy that companies still haven't learned that you cannot hire a bunch of data scientists and predict the next major hit. They have tried for the past 20 years, but human ingenuity (and the chaotic human psychology) is totally elusive to their silly models.

> "And now, in the current era of the remake, which still has to reach the film industry"

You haven't heard of the Disney live-action remakes of the old classics? It's already starting to happen.

I am not at all surprised. It's pure exploitation of a bias of human psychology: we do not like to leave our comfort zone, that's a fact. Why should they try to risk making something original, when remaking stuff that already exists guarantees you an audience and packed theatres? We had the decade of superhero flicks, we're entering the decade of remakes and re-imagining of beloved franchises of the past 100 years.

What if the 20th century was the unusual time? How much "novel IP" was produced before, in the majority of human history and before? My impression is that inventing unique "3D" characters became common in the modern era. In deep time, people told stories with their cast of characters from their mythology, legends and sages. Folk tales are often written about trope, archetypal characters that are flat and predictable by modern standards.

The expectation that new stories must be set in a freshly created "universe" with fully new characters is quite new. We may be returning to that old mode of storytelling where we repeat more. Just as people still play Shakespeare with new actors each time, why can't we retell a 20th century film with today's actors and technology? And why can't we make sequels about already beloved and known characters? Seems quite natural in fact.

We now have a new canon for this era, and it consists of superman, and Darth Vader etc.

The one (big) difference of course is that in the old times there was no concept of copyright and trademarks so people were free to recombine characters as they wished.

> It's so easy to blame this phenomenon on rose-tinted glasses and older people like us thinking all old things are better than modern, but when the world wasn't decided by "data scientists" and corporate committees, there was more variety, more volatility. Lower lows but higher highs as well.

There's a trend of thinking that our age is the most accepting and inclusive and the past was rigid and conformist but in many regards it's the opposite. Through all the metrics and quantification and SEO-like data analysis-based incentives and judgments we are being "snapped to grid". The risk averseness is growing. There's only a narrow path and people must tick many boxes or get disqualified. Just as movie producers make the nth superhero movie and everything is a sequel of old IP, science is similarly turned into a formulaic churn.

Just think about how Peter Higgs said he couldn't fit the mold of today's academia and the pressure of producing a stream of consistent (and hence typically consistently mediocre - like the consistent taste of a BigMac) output.

The other day I watched this interview with a pioneer of artifical neural networks Warren McCulloch (https://www.youtube.com/watch?v=wawMjJUCMVw). I wonder if today we're letting such personalities thrive in academia. He was originally headed to the Christian ministry and learned a lot of theology then got drawn rather to math, and his pondering of abstractions, understanding, humans and theology moved him to study neurology and to use math to model logic expressed as neural networks. Nowadays, you must specialize early and grind for tests, no "forgiveness" if you go off-track, you must be single-mindedly focus on optimizing your path towards tenure for it to be realistic. Can't even get a PhD position without having published several of your original research papers beforehand. While hiring committees say they reward well-roundedness and try to avoid a monoculture, what that becomes in practice is checking if your parents sent you to one of these trendy types of extracurriculars or foreign "volunteer" programs, and whether you later were engaged with some shortlist of trendy buzzword issues.

This breeds conformity, uniformity and bland predictability.

Check out how Snow White has been going. The film industry is absolutely there, but the good news is it's going exactly as horribly as you predicted.