The purpose of a startup is not to make a lot of money. The purpose of a startup is to find a repeatable, scalable, and profitable way to make a lot of money.

I talk to entrepreneurs for a living. One concept I repeat very often is the concept of the Sales Learning Curve. The author, Mark Leslie, ”retired” to Stanford after a stellar career as an entrepreneur and executive and continued to impact the lives of budding entrepreneurs.

Around 2003, Mark talked to me — and many other entrepreneurs — about the concept of a Sales Learning Curve. The concept is similar to that of a manufacturing yield learning curve, but for new product market launches. I think most of us who had previous built companies where blown away by Mark's crystalization of what was previously haphazard activities that startups would go through to converge on scaleable businesses. Mark wrote:

"The concept of a learning curve is well understood in manufacturing. Employees transfer knowledge and experience back and forth between a production line and the purchasing, manufacturing, engineering, planning, and operations departments. Over time, the entire process becomes more effective: The more times a process is repeated, the more efficient it becomes and the lower its cost.

Startups and existing companies launching new products follow a sales learning curve that’s analogous to the manufacturing learning curve but one that unfolds through the give-and-take between the company and its customers. As customers adopt and use the product, the organization modifies both the offering and the processes associated with making and selling it."

The Sales Learning Curve basically captures the idea that when you first create a product and bring it to market, there are many things you don't know about how to make your unit economic model repeatable and scaleable. Imagine when the first McDonald's stores was being built: Where do you locate it? What prices do you charge for what's on the menu? What's on the menu? How much can you afford to pay for the workers? Where do you buy the potatoes, buns, hamburger patties, napkins, ....? How profitable should the store be at steady state? And so on. Before you can decide to roll out thousands of stores, you need to first have answers to these and other questions. Whatever the unit economics of your startup, you need to figure out (i.e. learn) the metrics that allow you to grow your business before investing money in growing it. You need to discover the controls to your rocketship before you launch.

Non-enterprise businesses.
Although Mark initially called the concept the "Enterprise Sales Learning Curve" and wrote about the Sales Learning Curve from the perspective of an enterprise software company, I find the concept is also applicable to all types of consumer and social network businesses. For example, before you spend large amounts of money acquiring users for a mobile game, you minimally need to understand your CAC (customer acquisition cost) and recovery rate, ARPU, retention, life-time value of a user, virality, etc.... so that you have predictability of the cost/profit of cranking up your user base.

Other models.
The process suggested by the Sales Learning Curve is similar to Steve Blank's Customer Development Methodology (in The Four Steps to the Epiphany) and The Lean Startup processes suggested by Eric Ries, but more from a much stronger perspective of developing predictable revenues. Startup models that depend on building marketplaces or social networks at scale might want to initially substitute engagement and user count metrics in the earlier part of growth.... but even then, at some time sooner than later, revenues become a matter of survival! (Duh!)

Angel investing.
If you are an angel investor, looking at deals from the lens of the Sales Learning Curve helps you understand how well your founders appreciate the task ahead of them.... and will help you guide your portfolio companies. By the way, your investment buys optionality ... and it is for the purpose of proving the founder's thesis. It might turn out that the thesis is proven wrong — in which case your investment, though possibly well spent, will not return value to you. But if the thesis is in the ballpark of being right, you have just bought yourself a chunk of what might be a valuable entity. Of course, the worst result you could get from an angel investment is that no thesis was proved or disproved — the team just wondered around playing with ideas and features — that's more of an R&D investment, as opposed to an angel investment.

Series A, Series B.
From the time an entrepreneur raises seed/angel financing till the startup's institutional rounds, the entrepreneur and the startup team need to experiment and learn.... and create a unit economic model (around a consumer/user, or a target customer, or an "outlet" as in the case of McDonald's) of the business. The closer the team is to a repeatable, scalable, and (highly) profitable model before the entrepreneur attempts to raise Series A or B financing, the easier his/her life will be in fund-raising. At the very latest, the team should have the workings of a repeatable model when it goes out to raise Series B — Series B is traditionally the financing round for funding the scaling out of revenue generation capability; although, these days, many entrepreneurs have enough information to start scaling out with Series A funding.

Early stage investing.
If you are an early-stage (Series A, B) investor, one of your key points of evaluation of a company is: Is it ready to scale out? I've actually seen entrepreneurs scale out businesses with unit economics that have negative gross margins! — a sure indication that the board oversight (if it existed) did not include individuals who understand the Sales Learning Curve. For Series A, you should expect that the team will use the new funds to finish out the Sales Learning Curve process and start scaling. For Series B, the team should be ready to crank. (Of course, "Series A" and "Series B" are just terms used as rough markers for you to think about the stages of company development, and are not used to be absolute guideposts — please use them as such.)

Thesis and experiments.
The purpose of a startup is to prove a thesis... that the product, server, and/or business model, as construed by the entrepreneur, can become an on-going concern in the near future. The assignment for the entrepreneur is to "prove”, in a series of market place experiments, that what he/she told the angel investors is indeed a reflection of reality. Of course not all the details of the original thesis will be correct — pricing, value proposition, distribution channels, minimum viable product feature set, etc. will all change as you run experiments with early adopters in the market place. That is part of the learning of the Sales Learning Curve.

Good ideas are powerful things. They can save you countless hours of grief and millions of dollars of wasted effort. The Sales Learning Curve is one such idea. If you are anywhere near a startup, you should understand this concept well. It should be an integral part of anyone who hopes to disrupt the world with a new idea.

This article was initially published in Tech in Asia on July 7, 2014.


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