Well, maybe “dumb” is the wrong word; “repetitive” is probably more accurate. How many times do you have to explain how you acquire users, how big your market is, or what the competitive response will be to your product? It can get pretty frustrating, especially if you’re actually turning poop into gold.
I think conference panels exacerbate this frustration, especially those “lightning pitches” wherein a number of judges has to instantly critique a business plan they know almost nothing about. I’d estimate that 90% of the questions judges ask on these things are the same 10 questions. And, the one that is always included is:
How do you scale?
This question is almost never answered properly. I think it’s because “scale” is not well-defined in common discourse. Here’s my attempt to put a framework around it.
For me, scale has a very specific meaning. It has nothing to do with your back-end technology. Product scalability is an entirely different topic, and one best covered by other authors.
Businesses that scale are businesses with operating leverage. Put simply, if you add operating costs (sales, marketing, administrators, R&D, etc) at the same rate you grow revenue, then your business does not scale. Alternatively, if additional revenue requires relatively smaller and smaller additions to operating costs, then congratulations…your business scales!
Let’s make one thing clear: just because a business doesn’t scale, doesn’t mean it’s not a wonderful business. McKinsey & Co is one of the greatest consulting firms and brands in corporate America. But, it doesn’t scale. Ignoring its publishing business, McKinsey needs to add consultants, almost on a one-to-one basis, to grow its revenue. Its financials aren’t public, but they probably look something like this:
(Note that I’ve put gross margin in the above plot instead of revenue. You should actually be scaling gross margin, not just revenue, so we’ll stick with the former from here on.)
Technology businesses, on the other hand, tend to have a core set of assets that are developed early on, which can then be monetized at very low marginal cost going forward. Along with viral user acquisition or another low cost method of acquiring customers, scalable technology businesses tend to look like this:
While both companies exhibit linear operating cost growth, McKinsey’s top-line growth is linear, while our hypothetical tech company has an exponentially growing top-line. This is why venture capital firms prefer to invest in technology companies: we get a lot of bang for our buck. We can spend the difference between the blue and red lines to create a rocketship. Businesses like McKinsey, on the other hand, don’t need any capital to get started, and also don’t grow as fast.
The nice thing about exponential growth is that public markets reward it with big revenue multiples. Take OpenTable (NASDAQ:OPEN), for instance, which trades at an astounding 18x trailing revenues:
Real life is never quite as nice as theory, but I think you’ll agree directionally. In fact, it appears that the business was managed on a break-even basis until the IPO in mid-2009. That said, when management decided to “go for it,” OpenTable’s business model certainly supported significant operating leverage and top-line growth.
Google took this principle to the extreme after its IPO in 2004, as shown below:
It’s no coincidence that the best venture-backed companies in history did a great job scaling. It’s how you turn small amounts of invested capital into extremely valuable equity in a short period of time.
So next time a VC asks you a dumb question about how you scale your business, tell him how you make a chart that looks like one of these, and you’ll be all set!