Temporary Labor Intensive Efforts are Fine in Startups

One area I find entrepreneurs constantly talking about, especially tech savvy entrepreneurs, is that of automating everything and having a “touchless” process whereby humans aren’t involved. A common example of this is having a web app with a self-service sign up and provisioning process complete with payment processing via credit card. Now, as awesome as this sounds, it’s incredibly rare in reality. Most startups are working on innovative, non-replicative ideas that are in their first or second generation — generations that require extensive handholding and education.

Temporary labor intensive efforts are fine in startups as long as the economics eventually make sense. Here are a few examples:

  • Cold calling is labor intensive and not nearly as elegant as online marketing, but it often makes sense if the gross margins, lifetime value of the customer, and cost of customer acquisition are all inline (cold calling doesn’t have to be a temporary effort as some startups do it indefinitely)
  • Manually parsing of data, even large quantities of data, can be done with Amazon Mechanical Turk via Smartsheet.com such that a core amount is handled in a crowd-sourced manner, before investing the effort to fully automate it
  • Billing always starts out as a manual process, and there’s a desire to spend engineering time to automate it or use a SaaS billing tool, but it’s easy to do by hand so that engineering can work on higher value projects

The goal isn’t to do labor intensive efforts indefinitely if there are better solutions, rather the goal is to focus on the most high value work at the time, especially if a manual workaround is possible. It’s also important to pay attention to what enables economies of scale vs what doesn’t (e.g. lots of consulting work that is labor intensive).

What else? What are your thoughts on temporary labor intensive efforts in startups?

One thought on “Temporary Labor Intensive Efforts are Fine in Startups

  1. Another reason why temporary labor intensive efforts are actually desirable (rather than merely tolerable): You learn *how* to automate them. Almost always, our preconceptions about how we should bill, how we should parse data, etc were incorrect. To automate things too early is to guarantee that you will head down the wrong path.

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