Tomasz Tunguz is partner at Redpoint
. I write daily, data-driven blog posts about key questions facing startups. I co-authored the
book, Winning with Data
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In software, we've moved from a world where a customer buys a piece of software to run on their own infrastructure, to a world where a customer pays a vendor to run software on the vendor's infrastructure. With machine learning, we may see another evolution of this. Machine learning startups create models based on data provided by customers. Should customers be compensated for their contribution?
Amazon's acquisition of Whole Foods is notable for many reasons. Of course, there's the magnitude $13.7B. The second is the shockwaves reverberating through the grocery industry. Costco fell 10% and Kroger almost 25% on the news. Third, the acquisition underscores the importance of physical retail even to the largest American ecommerce giant. Those are all remarkable in their own right.
I've been reading Fred Kofman's book, Conscious Business. Written in 2006, the book summarizes Kofman's experiences as a management consultant to some of the great leaders in technology and other industries. In the book, Kofman lists 12 questions Gallup used to identify great managers in one of the largest management surveys conducted.
Earlier this week, I spoke at 2U's annual employee conference. We partnered with 2U at the Series A, and they are now a $2B publicly traded education company that powers online degree programs for Georgetown, USC, Syracuse, Berkeley, and Yale, among others. It was an inspirational moment for me because I observed the intense power of developing strong company culture.
When I analyzed the SaaS fundraising market in 2016, three trends emerged. The number of SaaS companies raising rounds had stalled, while the total number of dollars plateaued. Meanwhile, round sizes swelled. In other words, there was a concentration of capital in an increasingly small number of names. A year later, those trends have continued to converge, and SaaS valuations have resurged, reaching their highs of the 2014-2015 boom.
I am most grateful for my work experiences that were apprenticeships. Whether it was Philip who taught me how to write a proper Java function (10 lines or less), or Kim and Scott who are great managers, or the partners at Redpoint who invested a huge amount of time to educate me, those collections of experiences have taught me far more than I could've expected.
The New Zealand All Blacks are the most successful athletic team perhaps of all time. A rugby outfit whose name originates from the solid black uniforms, they have won 79% of their international matches spanning 68 years. James Kerr followed the All Blacks, interviewed them and distilled his learnings into a book, Legacy. Kerr organizes the book into 15 life lessons, three of which stood out to me.
What could be more natural than a marketer selling a product to other marketers? Or an engineer pushing a new devops tool to other developers? Or a customer success person pitching CS tools? After all, they both speak the same language, come from the same domain, will develop trust quickly. Consequently, they will sell faster and more efficiently. This might seem like a very logical argument for differentiating on sales processes, but it's a fallacy.
We've entered an era when computers can understand speech, computers can synthesize speech, computers can develop music, author encryption algorithms, create novel art, respond to customer support questions, and even generate new summaries and reports from data. Increasingly, humans will struggle to distinguish between computer-generated and human generated. Consequently, here's an opportunity for startups to lead, not just technologically, but more broadly.
When I was taught Michael Porter's value chain analysis, I learned to analyze at the industry level. A beer supplier sells to wholesaler sells to distributor sales to retailers sells to customer. But as I went back last night and reread Porter's Competitive Strategy, I was surprised to learn that Porter's intended value chain analysis to be used also at the business unit and at the company level.