A look at the tug of war between the data driven tech team and the relationship-oriented Hollywood team at Netflix
As the company plunges deeper into originals, its L.A. wing is doing the once-unthinkable: overriding the metrics — Netflix Inc.'s executives were torn. Tweets: @ledgerstatus , @memles , @wsj , @asharma , @sub8u , @memles , @memles , @wsj , @memles , @trevornoren , and @filmmakermag See also Mediagazer Tweets: Ledger Status / @ledgerstatus : A challenge for me with this is a Netflix show used to be generally accepted as “good” by default until proven otherwise — like HBO. Now that is unlikely. Dilutes brand quality. Makes them more like a regular network, less appealing. http://twitter.com/... Myles McNutt / @memles : I've been thinking a lot over the past couple of days about Disney's streaming service, which is 100% built around drawing value from and adding value to existing brands within the company. But Netflix doesn't have a brand, and its Silicon Valley wing is the reason why. @wsj : “Are we killing enough shows?” As Netflix burns through cash, a debate rages between its Hollywood and Silicon Valley offices over how much to lean on its fabled data model. http://www.wsj.com/... Amol Sharma / @asharma : “The algorithm became this Wizard of Oz. It was this all-knowing, all-seeing, 'Don't f—with us' algorithm,” said one Hollywood executive. http://twitter.com/... Subrahmanyam Kvj / @sub8u : The inherent tensions and conflicts between human judgment and algorithmic recommendations coming to fore at Netflix. Soon, at every other company. In every other decision. Across every other day.http://www.wsj.com/... http://twitter.com/... Myles McNutt / @memles : This story does a lot to make the Netflix tech team into the Enemy. http://twitter.com/... Myles McNutt / @memles : The idea that they didn't want to bother with trailers for original movies, billboards for original series - they are utterly convinced that the algorithm overwrites any other marketing. But marketing isn't just about getting people to watch: it's about the brand. @wsj : Netflix's executives were torn. On one side was the company's trusted data model. On the other, the risk of offending Jane Fonda. http://www.wsj.com/... Myles McNutt / @memles : An algorithm has no brand, but Netflix needs ELEMENTS of one if it wants Oscars/Emmys, and if it doesn't want its bizarre mashup of strict external privacy and radical internal transparency to complicate its ability to draw the talent that will get them that. Trevor Noren / @trevornoren : “As Netflix plunges deeper into Hollywood production—set to release 700 new original shows & movies this year—it is learning to temper its love of data models and cater to the wishes of A-listers and image-conscious talent” http://www.wsj.com/... http://twitter.com/... Scott Macaulay / @filmmakermag : Really interesting article about how the algorithm is reshaping marketing and publicity clauses, talent relationships. http://twitter.com/... See also Mediagazer
Context & Ripple Effects
By 2018, Netflix's algorithmic greenlighting machine was the thing studios feared: back in 2016, channels were already fretting about a near-monopoly in entertainment built on that data edge. This story marks the first visible crack — the L.A. wing overriding the metrics to land A-list names and protect relationships, exactly as the company scales toward hundreds of originals a year.
The tension proved structural rather than episodic. Within a year, coverage framed Netflix as looking like the entertainment giants it disrupted, with subscriber misses and ballooning costs; by 2020, the WSJ was describing data-driven analytics reshaping creative development across Hollywood — meaning the industry absorbed Netflix's methods even as Netflix absorbed Hollywood's.
First-order effects
- A-list talent and their representatives gain direct leverage over greenlights: the L.A. team can now override what the recommendation data says, trading algorithmic confidence for star attachments and awards positioning.
- The override dilutes the brand promise observers like @ledgerstatus flagged — a Netflix show was accepted as 'good by default' like HBO, and metric-driven volume makes it read more like a regular network.
Second-order effects
- Legacy studios and HBO can now compete on the terrain where they always won — relationships and prestige — while Netflix's cost base inflates chasing stars and awards, feeding the ballooning-expenses dynamic that defined its 2019 results.
- Talent-side wins set a precedent other streamers must match, pushing the whole market toward relationship-priced deals rather than data-justified ones.
Third-order effects
- If the pattern holds, the data advantage stops being a moat: every major studio adopts analytics (as the 2020 coverage shows), so differentiation shifts back to taste, relationships, and brand — the exact structure Netflix disrupted.
- Rising content spend without a matching data edge points toward monetization pressure downstream — the path that later led Reed Hastings to put ad-supported tiers on the table.
The trend: Streaming platforms are converging with legacy studio logic, layering talent-driven prestige spending over their data models until the algorithmic edge that built them is no longer the differentiator.