Today, let’s look at our org charts a bit more closely — the product-led organisation versus the engineering-led organisation:
Data falls under the business-side engine of the company … whether product or engineering
Data can fall under either. The question is: Is there a reason why an organisation is going to put data under product or under engineering? Let’s look at two cases here: Financial Times and Axios.
I think we can all agree that the FT is a long-time leader when it comes to having extremely advanced research and development for its data programme, usage, and engineering. I mean, from the outside, data seems to rule everything at the FT (back in the early 2010s, it already had a data team of 30+). At the FT, data falls under product. The chief product officer runs product, engineering, and data.
Meanwhile, Axios’ story couldn’t be more different than the FT — a young company, born digital, no legacy revenue. Axios runs data (and product) under its engineering organisation. The CTO drives product, engineering, and data.
But Axios isn’t product-led … it is journalism-led.
Its three founders come from a deep editorial background and (famously) built Axios to meet a need that expressed itself in very journalistic terms: “Why it matters.” So its choice of an engineering-led organisation on the business side is very logical: When journalism is a dominant current of the product’s development, it is the product. The New York Times was slower to build the world-class product team it now has because the newsroom for years, essentially, was the product team (I speak from insider knowledge here).
Looking at the enablement of its business, Axios wrapped all under tech because product was already heavily “represented” in the other force of the company, which was the journalism itself.
The same org chart can be used by a small or large organisation
Something that’s interesting here is that in both cases, these are organisations with both very solid and advanced foundations in data — both in terms of the relative size of the team and the ways in which data plays a part in how the product is built, how the company is run and markets its products, and how it uses data in its products.
So it’s not like one type of org chart speaks to “big companies” vs “small companies” or “companies that have large data teams” vs “companies that have smaller data teams.”
I mentioned Sonda Loncar, the head of the product and data team at Kleine Zeitung in Austria. Her data team runs under product and it works for them. That’s the model of the FT. It works for them, too. There’s no doubt these are pretty different organisations, but in this case, their org charts look similar.
Data under its own steam, reporting to the CEO
But there is a model of an org chart we haven’t really discussed yet and which does seem to reliably track with a later stage: The org chart model where data is under neither the head of product nor the head of engineering (whether these are C-level titles or VPs). This is the model at The New York Times — data reports directly to the CEO, as does product and as does tech.
So on the one hand, you could certainly point out that it can just be for practical reasons: the data team of the NYT is now about 100 people. But there is another reason (or incentive) for this one, and it’s not just headcount.
The New York Times has publicly stated (on several occasions) its belief that the future of its overall revenue was direct consumer revenue. But at the moment, it still has a significant share of anonymous digital traffic, supported by advertising (and of course, there is subscriber-generated advertising revenue as well).
For the NYT, the evolution of its revenue between digital consumer revenue and digital advertising is still hanging closer to a middle split. Digital consumer revenue is higher than digital advertising, and the Times has gone full speed ahead acquiring more digital properties like The Atlantic to further complement the value of its subscription bundles.
On the other hand, the NYT also did acquire Wirecutter, whose revenue model is advertising-driven for the most part. Even if the strategic goal of The New York Times is to continue to build its direct consumer revenue, it certainly isn’t discounting the opportunity of advertising revenue.
But consider then the case of the FT — whose foray into digital consumer revenue is one of the earliest successful demonstrations that it could be done. At the FT, there is a clear path forward that consumer revenue can be the lion’s share of the company’s revenue. As of the end of 2021, the FT’s digital content revenue is three times bigger than its next biggest component — print.
This doesn’t mean advertising revenue is discounted. Of course, the FT may have a lower volume of pageviews than, say, CNN, but its revenue per page for advertising is very high because most of its traffic is logged in and seen by valuable subscribers, which fit the juiciest advertising demographic, to boot.
In other words, even where advertising revenue is concerned (and rich), it is so because product data is rich, too: “It’s the result of deeper audience data and, as a result, an increasingly effective marketing proposition. So it isn’t ads versus subs — there is strong growth to be had in both,” said FT’s CEO John Ridding at a conference last year.
A word about these somewhat imprecise statements: Nikkei Inc., the corporate owner of the FT, is employee-owned so doesn’t publish financial reports. There isn’t therefore a perfect way to reconstitutes this data, but I can confidently say that at the percentage of paid traffic the FT generates, there isn’t a realistic way to generate advertising revenue that would compare.
So we have two companies with very mature direct consumer revenue strategies on digital whose advertising revenue is comparatively becoming less important. But for the NYT, this is a cake still split toward the middle and with continued diversification pursuits that lean on advertising.
And to be sure, these are more than two-sided strategies: Events, print, and other ancillaries are a significant play at both the FT and the NYT — and Axios, too (for the events business).
But for our purposes, let’s consider advertising and product as the two main consumers and drivers of data for these companies.
- At The Times, there is a more even split between the various goals of the companies, and data would be in a tricky spot if it was run under product.
- At Axios (well, speaking about its activities prior to its recent acquisition by Cox), there is (or was) no ambivalence that the revenue play was direct consumer revenue, too. Axios’ traffic, while impressive for a young company, was never going to sustain its large newsroom via advertising.
And so the NYT put data under general leadership. But for the FT and Axios, where data has a clear “dominant” partner or customer, data falls under these umbrellas.
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