Remember those terrible word association problems from your SAT? (A is to B as C is to D) I do, and this is the first time I’ll be using them again almost 15 years later. But they serve an important purpose in this post as the framework for equating a few common pitfalls of large companies to the high-growth startup.
Two of the biggest inflection points for a growing startup happen when headcounts go from 10 to 20 people and subsequently 20 to 50 people. During the former, employees begin to transition from generalists to specialists. For example, the engineer who was also serving as a PM moves focus to just one of those roles and a startup hires the remaining position. Yet after this phase, every employee in the company still has knowledge of most decisions that are being made.
As your company continues to grow, roles become even more generalized and senior leadership is brought in to help scale the company. Key decisions are now made by the exec team, and often those early employees begin to feel left out of the process. It’s crucial to avoid the temptation to save “culture” and include everyone as often as possible. Don’t get me wrong, I believe in transparency and communication from leadership but when everyone has a vote in key decisions your progress is bound to slow to a screeching halt. Stick to the Jeff Bezos meeting size, if it takes more than two pizzas to feed everyone it’s too large.
We now live in a world of almost unlimited data, and the best data any startup can capture is proprietarily customer-centric. The only way to capture it is to get your product to market. Entrepreneurs by nature are often visionary, and see the long-term possibilities of the product they are creating. Therefore, it’s often counterintuitive for them to release something that is not up to their personal standards. I’ve seen products that took over 6 months of development fail, not because they weren’t well thought out, but because the customer wanted something we didn’t see. The cruel joke of entrepreneurship is that most of the time, no matter how great you are, certain aspects of your product will be rejected by the market and that’s okay.
“If you cannot fail, you cannot learn.” – Eric Reis, Author – The Lean Startup
Large companies use data to become proficient and knowledgeable. However, the returns on data analytics are marginal (at least when done by humans) and often lead to a blind spot where large firms are unable to see the unrealized potential of what lies ahead, preventing them from developing new products that grow market share. The best early-stage companies are able to get a viable product to market quickly, and thanks to a myriad of new tools, collect as much data as possible including how customers use their product, customer acquisition costs, and customer value. Combining these types of data with a vision for the future of an industry can be a powerful pairing.
When I decided to go back to school in order to get my MBA I knew I was adding a checkbox to my resume for certain positions within large companies. Little did I know, my passion for startups would prevent that from becoming useful. Yet, my intentions highlighted an issue with many large firms, they hire exclusively based on things like titles and advanced degrees. While it’s true that these things can be an indication of effectiveness and leadership, it is certainly no guarantee. Large companies often neglect things chemistry and creativity.
If large companies neglect culture fit, startups can often do an exact 180 and over-value it. While I still immensely value culture, I’ve also learned that results (good or bad) are part of the culture and often what is seen as good culture is actually vanity perks masquerading as such. What does this look like in hiring? It means doing things like having subordinates interview their potential new boss for “buy-in” or expecting someone to adhere to the “work hard, play hard” schedule. I’ve fallen into that latter bucket with people we hired only to be proven completely wrong about the person’s work-ethic and capability.
Remember, while many of us are working to disrupt the incumbents in large industries, we’d still be served to look to them for examples, both good and bad. After all, we’re working toward being as large as them someday.
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