I totally agree. I am new to investing and learned a lot. I agree that the Smile model presented could be applied elsewhere. Thank you for pulling the pieces together in a way a novice could follow, and take many valuable lessons with them.
Will we ever see regulators flatten the smile? There has been long rumours and debate about exchanges double dipping, and even more so the monopolies that index providers hold? Do you think we will see intervention?
Interesting thought. My personal view is that regulators shouldn’t be too bothered by value creation and capture mechanics, instead more on predatory and anti-competitive practices. So instead of flattening the curve (a socialist approach), they should be aiming to make more room under the curve for more participants. Which is what I think you imply in the second half of your comment.
Will we see strong enough intervention? Unlikely. But that is the way of financial markets.
This is a really well written article, well done Terminalist. Though I'm not much involved in finance anymore, this was an easy to read and follow article
a couple of things that popped to mind as i was reading it:
1/ i think using the "per Employee" metrics is not completely fair. if you have a low headcount company those metrics would look great compared to large headcount companies - even if they are not great otherwise.
2/ the fact that FactSet is operating so long in the less lucrative part of the value chain - and not trying to acquire businesses that help it venture into the more lucrative part - suggests that perhaps that sector is not a bad one to be in :) perhaps there's something else that is not captured in the metrics explored that makes it worthwhile to be in a business where you're being squeezed.
3/ one could argue that raw data creation is a byproduct of CME. 3.1/ i wonder how many employees are busy with this byproduct compared to the main business. i suspect that this byproduct is far more lucrative than you calculated. 3.2/ there's other sectors whose byproduct has high utility (e.g. oil refinement and cement - that needs the heat). i wonder if there's a bigger thing to understand about it.
4/ i think that those in activation might have work cut out for them too. no doubt that when market is booming - people are coming up with crazy indexes and are willing to pay for constant feed of those, but when some product loses all its consumers - they need to deprecate it. on a large scale - that means those businesses need to be in actively "trimming the garden" on a daily basis. as data product takes time to mature, i think that this trimming is not an easy decision to make. all that to say: maybe the high end of the value chain is not an easy place to be when the market dries up.
appreciate the detailed comment Daniel, lots to think about.
1 - per employee metrics certainly have their limitations, but serve as one of a group of relative comparisons available when comparing within the same industry. By itself I agree it may not give the full picture, but i've used it more to explain why it is high/low for certain companies, as a way to draw out insights on the business model.
2 - you are absolutely right. Factset is quite lucrative, in fact their stock has 140x since IPO. The margins aren't high when selectively compared to the other two, but are pretty attractive across the S&P500. I highlight that in my next post, would welcome your detailed commentary on that too!
3 - 3 & 3.1 again I cover this in my third post. Indeed, raw data production is a fire & forget operation, printing dollars from data as literally as possible. 3.2 The oil industry comparison has a bit more to reveal, hope to get to that in a future post.
4 - i like the 'trimming the garden' analogy. I unimaginatively called it the experimentation cost (third post) which index providers are happy to bear, given the power law returns of a successful index. I estimate S&P makes 300-350m a year from just the S&P500, a quarter of their index revenues
Thanks again for the thoughtful feedback. Really welcome your comments to my third post, it may help me land on the themes for my next one! :)
Really enjoyed your work on this; particularly appreciate the graph and underlying rationale. Dev Kantesaria (Valley Forge), an investor I highly respect, has owned SPGI and MCO for years (recently bought MSCI); he focuses on companies with pricing power and predictable growth. Your work helps one better understand the logic underpinning his approach.
I’m sure he has a deeper thesis on data businesses that I’d love to hear. Their largest position atm is FICO, which is another incredible Nof1 data monopoly. Diamond hands to hold it at 90+ PE. as the market wises up to the cash cow.
Glad you enjoyed this post. My third post looks at their pricing power in more detail. I’m sure Dev tuned into it way before I did.
Do you think AI benefits or hurts FS/other businesses in the distribution category relative to the others? On one hand, labor costs should be driven down dramatically as they are replaced with AI, relatively benefiting their margins compared to others. But they also may not be able to maintain that margin as AI lowers the barrier to entry/erodes process power.
To seed, build, and nurture timeless, intangible human capitals — such as resilience, trust, truth, evolution, fulfilment, quality, peace, patience, discipline, relationships and conviction — in order to elevate human judgment, deepen relationships, and restore sacred trusteeship and stewardship of long-term firm value across generations.
A refreshing take on our business world and capitalism.
A reflection on why today’s capital architectures—PE, VC, Hedge funds, SPAC, Alt funds, Rollups—mostly fail to build and nuture what time can trust.
“Built to Be Left.”
A quiet anatomy of extraction, abandonment, and the collapse of stewardship.
"Principal-Agent Risk is not a flaw in the system.
Tremendous read. Working for an upstart in the activation space, your breakdown of the different layers hit the nail on the head for why many legacy systems are entrenched for users.
Glad it was helpful Ross. Big fan of the Teegus story, tremendous potential. I only hope as it grows bigger within AS, they can keep the strong counter-positioning, founder-led DNA...
I think fewer than ten people in the world could have written this piece. My complements to the chef.
I totally agree. I am new to investing and learned a lot. I agree that the Smile model presented could be applied elsewhere. Thank you for pulling the pieces together in a way a novice could follow, and take many valuable lessons with them.
MOAR THE PPL NEED MOAR
working hard on the next one sire!
Will we ever see regulators flatten the smile? There has been long rumours and debate about exchanges double dipping, and even more so the monopolies that index providers hold? Do you think we will see intervention?
Interesting thought. My personal view is that regulators shouldn’t be too bothered by value creation and capture mechanics, instead more on predatory and anti-competitive practices. So instead of flattening the curve (a socialist approach), they should be aiming to make more room under the curve for more participants. Which is what I think you imply in the second half of your comment.
Will we see strong enough intervention? Unlikely. But that is the way of financial markets.
Amazing work!
Thanks Didier, your support means a lot!
This is a really well written article, well done Terminalist. Though I'm not much involved in finance anymore, this was an easy to read and follow article
Thanks DT, glad you appreciate the writing
Great write up, keep it up
Consumer credit data / credit bureau i.e. EXPN, EFX, TRU, FICO, etc.
Thanks Roobs, what would be of interest next?
This is the best Substack piece that I have read in a long time. Hats off to you sir!
Fantastic piece of work. A tour de force?
truly insightful.
a couple of things that popped to mind as i was reading it:
1/ i think using the "per Employee" metrics is not completely fair. if you have a low headcount company those metrics would look great compared to large headcount companies - even if they are not great otherwise.
2/ the fact that FactSet is operating so long in the less lucrative part of the value chain - and not trying to acquire businesses that help it venture into the more lucrative part - suggests that perhaps that sector is not a bad one to be in :) perhaps there's something else that is not captured in the metrics explored that makes it worthwhile to be in a business where you're being squeezed.
3/ one could argue that raw data creation is a byproduct of CME. 3.1/ i wonder how many employees are busy with this byproduct compared to the main business. i suspect that this byproduct is far more lucrative than you calculated. 3.2/ there's other sectors whose byproduct has high utility (e.g. oil refinement and cement - that needs the heat). i wonder if there's a bigger thing to understand about it.
4/ i think that those in activation might have work cut out for them too. no doubt that when market is booming - people are coming up with crazy indexes and are willing to pay for constant feed of those, but when some product loses all its consumers - they need to deprecate it. on a large scale - that means those businesses need to be in actively "trimming the garden" on a daily basis. as data product takes time to mature, i think that this trimming is not an easy decision to make. all that to say: maybe the high end of the value chain is not an easy place to be when the market dries up.
appreciate the detailed comment Daniel, lots to think about.
1 - per employee metrics certainly have their limitations, but serve as one of a group of relative comparisons available when comparing within the same industry. By itself I agree it may not give the full picture, but i've used it more to explain why it is high/low for certain companies, as a way to draw out insights on the business model.
2 - you are absolutely right. Factset is quite lucrative, in fact their stock has 140x since IPO. The margins aren't high when selectively compared to the other two, but are pretty attractive across the S&P500. I highlight that in my next post, would welcome your detailed commentary on that too!
3 - 3 & 3.1 again I cover this in my third post. Indeed, raw data production is a fire & forget operation, printing dollars from data as literally as possible. 3.2 The oil industry comparison has a bit more to reveal, hope to get to that in a future post.
4 - i like the 'trimming the garden' analogy. I unimaginatively called it the experimentation cost (third post) which index providers are happy to bear, given the power law returns of a successful index. I estimate S&P makes 300-350m a year from just the S&P500, a quarter of their index revenues
Thanks again for the thoughtful feedback. Really welcome your comments to my third post, it may help me land on the themes for my next one! :)
Really enjoyed your work on this; particularly appreciate the graph and underlying rationale. Dev Kantesaria (Valley Forge), an investor I highly respect, has owned SPGI and MCO for years (recently bought MSCI); he focuses on companies with pricing power and predictable growth. Your work helps one better understand the logic underpinning his approach.
I’m sure he has a deeper thesis on data businesses that I’d love to hear. Their largest position atm is FICO, which is another incredible Nof1 data monopoly. Diamond hands to hold it at 90+ PE. as the market wises up to the cash cow.
Glad you enjoyed this post. My third post looks at their pricing power in more detail. I’m sure Dev tuned into it way before I did.
Great work
Thanks for keeping this piece as free. hope for more high quality content like this
Do you think AI benefits or hurts FS/other businesses in the distribution category relative to the others? On one hand, labor costs should be driven down dramatically as they are replaced with AI, relatively benefiting their margins compared to others. But they also may not be able to maintain that margin as AI lowers the barrier to entry/erodes process power.
Prescient take into my next piece, Charlie.
Shhh, don’t let the cat out of the bag yet.
Hello there,
Huge Respect for your work!
New here. No huge reader base Yet.
But the work has waited long to be spoken.
Its truths have roots older than this platform.
My Sub-stack Purpose
To seed, build, and nurture timeless, intangible human capitals — such as resilience, trust, truth, evolution, fulfilment, quality, peace, patience, discipline, relationships and conviction — in order to elevate human judgment, deepen relationships, and restore sacred trusteeship and stewardship of long-term firm value across generations.
A refreshing take on our business world and capitalism.
A reflection on why today’s capital architectures—PE, VC, Hedge funds, SPAC, Alt funds, Rollups—mostly fail to build and nuture what time can trust.
“Built to Be Left.”
A quiet anatomy of extraction, abandonment, and the collapse of stewardship.
"Principal-Agent Risk is not a flaw in the system.
It is the system’s operating principle”
Experience first. Return if it speaks to you.
- The Silent Treasury
https://tinyurl.com/48m97w5e
Tremendous read. Working for an upstart in the activation space, your breakdown of the different layers hit the nail on the head for why many legacy systems are entrenched for users.
Glad it was helpful Ross. Big fan of the Teegus story, tremendous potential. I only hope as it grows bigger within AS, they can keep the strong counter-positioning, founder-led DNA...
This is a gem. I work in investing and didn't know this.
Thanks, do get the word out to the investor community.
Hoping to shed new perspective on this industry and everything related…
Of course. If you'd like to read about how Irish GDP is calculated, you can find my piece below.
https://substack.com/@notrealapa/note/p-153591436?r=1vxcgi