Do you accept guest posts? Sorry, I don’t. May I use one of your charts? Yes, if you link back. Thanks! How do you make your charts? With R and ggplot2. There are instructions here. May I advertise on your site? Sorry, I don’t run ads. May I copy your content? Feel free to use the first 2-3 sentences of a post, but please do not copy the entirety.
You’re walking down the hallway at work from one meeting to the next. A colleague or report stops you en route, asks for a minute and presents an important problem. It’s easy to respond with “let me think about it” and duck into the meeting. In that half-second, all the responsibility of the decision has been transferred. Unlike a minute ago, you have the monkey on your back. The challenge with these situations is two-fold.
One way of measuring the efficiency of a company’s revenue model is to benchmark revenue per employee. Google and Facebook, the two most efficient companies, generate $1M per revenue per employee per year. Setting aside those exceptional cases and focusing instead on SaaS companies, the typical average revenue per employee is about $190k to $210k per year. The histogram above shows the ranges for publicly traded SaaS companies. In the scatterplot above, which compares revenue per employee to revenues (in log10 scale), the outliers pop out.
Financial statements are a Rosetta Stone for startups. They reveal the strategies and the tactics of how to bring a product to market. These are the ten metrics I look at when sifting through a startup’s operational model, whether when considering an investment or in a board meeting. Revenue growth indicates how quickly a company can grow under the current way of doing business. The top line shows whether the market affords steady growth (SaaS) or lumpy revenue growth created by the long sales cycles of big customers (Telecom) and whether the company must sell one product or a collection of complementary products.
On January 8, 1966, the New Yorker profiled Buckminster Fuller for the first time. During a trip to a Maine island with the journalist Calvin Tomkins, Fuller said something tremendously prescient: Fuller proposed a worldwide technological revolution…[that] would take place quite independently of politics or ideology; it would be carried out by what he calls “comprehensive designers” who would coordinate resources and technology on a world scale for the benefit of all mankind, and would constantly anticipate future needs while they found ever-better ways of providing more and more from less and less.
The traditional theoretical price demand curve is often drawn like this. The chart makes two points: there is some relationship between price and demand / revenue opportunity, and customer segments underpin that relationship. Each segment demands different products to satisfy different needs and presents a different revenue/profit opportunity. Even if the details are very hazy, price demand curves are useful tools to inform product strategy and prioritization. To make PD curves useful requires marketing research.
Raising money for a startup is expensive. The typical legal fees for a Series A are about 1% of the total money raised: roughly $40k on $4M. Of course, this doesn’t factor in the time for the process and the dilution of the investment. But if your startup is considering an IPO be prepared to pay eight times as much in fees. Across 360 venture backed technology IPOs in the last 10+ years which on average raised $107M, 8.
When startups are acquired, there are many considerations in accepting an offer. Does the vision of the acquirer fit the startup? Will the startup operate independently or be integrated? What is the price and structure of the transaction? Most of these questions have to be answered through extensive conversations with suitors. As for the structure of the acquisition, there’s data that can be used for benchmarking. I’ve assembled about 2400 M&A events of venture-backed technology companies since 2000 to compare the fraction of the total consideration which is stock and cash.
Bitcoin has captivated the imaginations of many with its quasi-anonymous, hyper cost-efficient payment network. The potential for Bitcoin to change foreign exchange is hard to overstate. In the same vein, the technologies that enable the internet of things (IoT) like Bluetooth Low Energy and Apple’s Beacons and Electric Imp’s infrastructure will transform the way we interact with the physical world to something akin to the mall in Minority Report. The startups that bring Bitcoin and IoT to the mass-market won’t declare themselves Bitcoin companies or connected devices companies.
Credit: National Geographic I was lucky enough to spend some time with Monica Adractas, a former McKinsey partner who is now Churn Czar at Box. She and I chatted about the challenges in managing churn and her view on how to handle it. I thought she had some terrific insights and a clear understanding of the methods to reduce churn from her experiences. These are my notes from that conversation: