For a long time revenue per employee was a good approximation for the profitability of a company. For instance, in the US for a SaaS company to be profitable generally meant it had revenues of at least $200K/employee. Wages were the bulk of a software company’s operating expenses. As we are entering the age of AI the biggest factor will be electricity. Data center capital expenditures are massive right now, but eventually the infrastructure will be deployed. Operating cost in the future will be dominated by electricity. And hence the new metric to look for is revenue per MWh.
The idea for this new metric comes from my friend Sara Menker. She has pulled together data from public filings on Microsoft, Google, Meta and Amazon. Here is the key chart from her analysis
At the moment it looks like Google is the champ of wringing dollars out of electricity and conversely that Microsoft has a lot of catching up to do. On a relative value basis this suggests that Google trading at 6.4x times revenues could be a steal compared to Microsoft at 14.1x times. If you want to play around with Sara’s data yourself, you can do so here.
The comparable metric for nations will be GDP per GWh (instead of GDP per capita). The price and availability of electricity will play a crucial role in this. The cheaper it is the more AI use cases can be sustained profitably i.e. the lower the viable revenue/MWh threshold. And a lower threshold will correspond to higher GDP.
This spells trouble for many parts of the world where energy is too expensive, in particular for Europe (and especially for my native Germany). Sadly the current administration is also needlessly handicapping the US in this regard, to the point where Anthropic has put out a blog post about the need for a better energy policy.
Energy enables progress, in the age of AI more so than ever.
Cover image source: ABB.
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Blog post: $ / MWh -- the metric for the AI age https://continuations.com/the-ai-metric-dollar-mwh
I enjoyed reading this. Short and sweet, but also bold!
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