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Scalability 2.0

Scalability is the question that plagues everything in business.  Do the operations scale?  Do the systems scale?  Does the organizational structure scale?  Better phrased: What does it take to scale this business?

Scale is often cited as a major determining factor in the output of various business models.  Consulting, law, and accounting are examples of businesses that scale as a factor of people.  As in, the company's production is directly governed by the number of employees.  Since the only physical products of these industries are documents, it's fair to say that output is entirely contingent on people.  Therefore, to produce more you must hire more people, which is difficult and expensive.

Contrast that with Google, the epitomy of hosted services.  The company essentially provides hosted software, which is monetized through ads.  It employs roughly 10,000 people, mostly developers, and serves hundreds of millions of users.  That's a massive scale, although they have their own problems based on maintaining sufficient revenue per user.

Here's one way to think about scale: 

Say you have a web company, XYZ.com.  XYZ.com earns $1 per user per month and has 100,000 regular users.  That means they're making $1.2 million per year.  That's enough to support a staff of 15 at an average salary of $80,000 (assuming no other costs), or really a staff of 12 at that salary with $240,000 in annual web hosting costs.

What's the incremental cost of scaling to support 1,000,000 users?  You'll have to add a couple more servers at your hosting facility, say doubling the cost to $480,000.  Will you need to add more employees? 

Possibly, but you won't really need more programmers, and if you run a service like Google's, you won't need more customer support staff because there's almost no tech support.  Therefore, your hosted solution virtually eliminates your scaling costs. Incredible, isn't it?

Scalability is the question that plagues everything in business.  Do the operations scale?  Do the systems scale?  Does the organizational structure scale?  Better phrased: What does it take to scale this business?

Scale is often cited as a major determining factor in the output of various business models.  Consulting, law, and accounting are examples of businesses that scale as a factor of people.  As in, the company's production is directly governed by the number of employees.  Since the only physical products of these industries are documents, it's fair to say that output is entirely contingent on people.  Therefore, to produce more you must hire more people, which is difficult and expensive.

Contrast that with Google, the epitomy of hosted services.  The company essentially provides hosted software, which is monetized through ads.  It employs roughly 10,000 people, mostly developers, and serves hundreds of millions of users.  That's a massive scale, although they have their own problems based on maintaining sufficient revenue per user.

Here's one way to think about scale: 

Say you have a web company, XYZ.com.  XYZ.com earns $1 per user per month and has 100,000 regular users.  That means they're making $1.2 million per year.  That's enough to support a staff of 15 at an average salary of $80,000 (assuming no other costs), or really a staff of 12 at that salary with $240,000 in annual web hosting costs.

What's the incremental cost of scaling to support 1,000,000 users?  You'll have to add a couple more servers at your hosting facility, say doubling the cost to $480,000.  Will you need to add more employees? 

Possibly, but you won't really need more programmers, and if you run a service like Google's, you won't need more customer support staff because there's almost no tech support.  Therefore, your hosted solution virtually eliminates your scaling costs. Incredible, isn't it?

How do you evaluate scaling opportunities?

I've just shown you what a business that doesn't require significant inputs for scaling looks like.  But how do you figure out what does or doesn't scale before starting your business?  And, more importantly, how do you figure out if the revenue stream will scale to where it makes sense? 

Well, that's the great question.  I think the exercise I just used in the example is the quickest way to understand how business costs scale:

  1. Take a piece of paper.  Draw a box in the middle of it.  This box represents your business.
  2. Make a list of each of the things your business needs to operate (people, office space, equipment, server space, etc.).  Cross off what's secondary or minimal.
  3. Finally, ask yourself, "If my sales grow by an order of magnitude (10 times), which inputs will have to be increased to support it?"  

The answers to this exercsise should show you what the major cost factors are to scaling your startup.

What about revenue scalability?

This question is probably more interesting to most readers.  The scalability of the revenue stream is the crux of debate in most startup circles.  And the truth is that it's pretty hard to tell.  I've heard a number of top-tier VCs say, "I strike out enough that I can't afford to do anything but swing for the fences."  What they mean is that their job is to understand business risks and market opportunity and they, as seasoned professionals, have a difficult time predicting the winners.

I would start with a couple of tasks (use spreadsheets!):

  1. Determine the size of your market.  Start by summing up the applicable revenues of your competitors (GE and IBM have many divisions but only 1 or 2 probably compete in your industry).  Then add in any additional market segments for which you have a credible value proposition.  For example, Clearwire (a WiMAX vendor) might sum the revenue of the mobile data products (Aircards, etc) of the major cellular carriers and then add to it a portion of the broadband revenue of major cable and wireline carriers, adjusting for the number of markets Clearwire serves.  Clearwire might also include some of the voice revenue from the wireless carriers, as well.
  2. Predict your achievable market share.  Try to dig up some research reports on the markets you're targeting.  It helps if you can get deeper than just newspaper articles (perhaps you have access to market research databases, etc).  Use these reports to determine how your value proposition compares to the market drivers and restraints for each of your target market segments.  These determinations should create a set of sensitivity factors that you can average to determine an overall market segment sensitivity.  Multiply the market segment size by its sensitivity factor and sum the results.
  3. The last two steps have generated an estimate of your end-state revenue size.  Now, use milestones from your marketing plan to define the growth of your marketshare from start to end-state.  It's helpful to graph the results.

If you're interested, you can overlay the graph you created in the last step with a cost estimate for your business, taking into account how costs scale to your customer base.  The resulting graph will show how your revenues scale compared to your costs.  It will be helpful both for understanding your business and for raising capital.

The point at which your revenue surpasses your expenses is your break-even, and it will determine both the amount of investment required and the risk associated with that investment. Take, for example, Sprint's Xohm service that's now in question after Carl Icahn forced out Sprint's CEO.  Their scaling proposition was: "We're going to build a new network that covers 100 million people, of which we expect to take X percent as subscribers, but it's going to cost us $3Bn."  Icahn was able to force out the CEO because investors felt the amount of investment required to build the network as too risky. 

This graph also is a good credibility check.  If you think your product or service is going to change the world, but you're an untested entrepreneur and you need one million users to break even, then you might want to rethink your business strategy to increase your revenue or reduce your expenses.  After all, if it looks too good to be true, it probably is.

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