Regardless of the approach, an entrepreneur\u2019s initial idea is invariably incorrect.<\/p>\n\n\n\n
Since the initial attempt is bound to fail, the audacious ones have the right idea to quickly release products without wasting time over-analyzing. They toss s*%@ against a wall and see if it sticks.<\/p>\n\n\n\n
Chemistry ultimately determines the success or failure of a startup. Do the founder and executive team possess chutzpah and humility in equal measures? If so, the team is probably nimble enough to dispassionately recognize failure, pivot, and keep going without losing confidence. Teams lacking this alchemy will either doggedly stick with a losing proposition or cry wolf and give up.<\/p>\n\n\n\n
I help teams accomplish their goals without becoming dispirited. I\u2019m not an entrepreneur, but I advise plenty of them. I counsel many young founders who started with a \u201cFire, Aim, Ready\u201d approach to retool their products for people willing to pay. A CEO recently told me, \u201cI view you as my Eric Schmidt,\u201d flattering both of us. It went without saying he viewed himself as the enigmatic Sergey\/Larry and saw me as the boring but steady adult who ruins the fun. I give entrepreneurs enough rope to jump from the ledge and I\u2019m there to yank them back up.<\/p>\n\n\n\n
I\u2019ve observed these 10 Sins of the Founders that often prevent success:<\/p>\n\n\n\n
There\u2019s nothing inherently wrong with platforms. In fact, platforms are great because they enable multi-constituent revenue streams. But in the words of a venture capitalist I spoke to recently, \u201cYou have to earn the right to build a platform.\u201d He meant that before one attempts to build a multi-sided platform, it\u2019s necessary to first nail the needs of at least one group of potential customers.<\/p>\n\n\n\n
Even technically-minded founders get caught in the application trap, believing a slick user interface is the key to success. This is often not the case. To illustrate: A team of data scientists builds a machine learning-based predictive algorithm that replaces a long-in-the-tooth heuristic solution. They shouldn\u2019t waste their time building it into an application. Instead, they should write a kick-ass GraphQL interface for their APIs and sell prediction-as-a-service.<\/p>\n\n\n\n
Buyer beware unless the preexisting mousetrap is truly ineffective. Suppose a founder has a brilliant idea about adding structure to video calls. This doesn\u2019t mean the team should waste time recreating all the plumbing Zoom has already perfected. For one, it\u2019s unlikely a startup will ever equal Zoom\u2019s speed and robustness. Secondly, rock-solid performance is merely the table stakes now that everyone\u2019s accustomed to Zoom. Better to integrate with Zoom than rebuild it.<\/p>\n\n\n\n
I know, I know, we\u2019re all tired of hearing about the Eric Ries Lean Startup<\/a> concept of failing fast because it seldom happens. More commonly, failure is slow, agonizing, and difficult to recognize. A team in the throes of a death spiral should not keep their heads down and try to muscle it out. They\u2019re better off gathering their wits and finding a new path to survival.<\/p>\n\n\n\n