Starting Greatness
I’ve been digging Mike Maples’ podcast Starting Greatness. Podcast hosts generally like to hear themselves talk, but Mike doesn’t succumb to that temptation. The focus is on the learning, and the founders who found gold.
Each episode packs a punch: a rare mix of brevity, clarity and potency. If you appreciate high signal:noise, you’ll love this podcast.
Find your wave before your market
In the above episode Mike emphasizes the importance of waves (and catching them!). Waves are a popular metaphor to describe change. Mike suggests there are three types of waves:
Technology: new hardware or software capabilities.
Adoption: changes in consumer preference due to affordability, desirability, beliefs, etc.
Regulatory: government mandates that remove barriers or compel action.
If a founder can catch one—or more—of these waves, their startup will have an increased likelihood of 1) discovering a new market, and 2) creating a category.
Lyft, Salesforce, Okta, AirBnb
Lyft, as the episode mentions, caught two powerful waves: improved GPS (technology) and increased smartphone users (adoption).
Salesforce and Okta both rode the cloud wave to create categories in CRM and identity management, respectively. [Okta’s founder Todd McKinnon is a Salesforce alumni so he had a good vantage point for wave spotting].
If you skip wave hunting, you risk looking for white space in an industry—as it exists today, i.e. the present. This is one way founders limit their potential and iterate to a local maximum.
Back from the future
The best companies are never present-focused. They are time-travelers who have escaped the present to discover a vastly different future.
Think how crazy AirBnB must have sounded to people in 2008. The idea of renting out your personal space was fraught with suspicion. This year AirBnB is on pace to do $3.5-4 billion in revenue.
Most founders haven’t found their wave. That’s okay. The important thing is 1) don’t settle, and 2) don’t be in denial if you can’t find it.
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If you enjoyed this topic, I also recommend reading Chris Dixon’s article Inside-out vs. Outside-in: The Adoption of New Technologies in which he analyzes the different ways technologies are created and proliferated, e.g. machine learning (inside-out) with open-source (outside-in).