We at M25 are very proud of our Midwest roots. It is core to our investment thesis, as well as who we are individually.
In the same way that the Midwest is core to us, agriculture is core to the Midwest. Ever drive from Chicago to St. Louis? How about Kansas City to Lincoln, or Columbus to Indianapolis? If you’ve ever driven anywhere across the region, odds are you’ve passed fields on fields on fields filled with anything from corn, to soybeans, to cows. It is hard to miss, and forms a regional historical economic core going back into history.
In the heart of college football season, desperate fans will look to anything to stoke a rivalry. US News & World Report rankings, party schools, “colleges that pay you back” — so what about best collegetown tech hubs? So I decided to dig into the Best of the Midwest rankings by MidwestStartups.com to see where Midwest collegetowns stack up, sprinkling in Pitchbook’s 2017 University Report rankings as well. Spoiler alert: Gridiron success and startup greatness are only loosely correlated.
The day before Valentine’s Day (coincidence? I don’t think so) of this year I wrote a post following up our first ever M25 Summit — a semi-annual event we hold exclusively to pour into our portfolio companies, a.k.a. Club M25. Last week we took our second swing at it, bringing roughly 30 founders across 25 startups in from 5 different states across the Midwest.
After working on this for months, M25 finally released our first official ranking of the top startup cities in the Midwest. After making the announcement and releasing the rankings publicly last week, I figured it would only be prudent to add some color from someone who’s stared at the data longer than most.
Here are my 5 takeaways from Midwest Startups Cities: Best of the Midwest.
Since launching M25 two years ago, we’ve become experts on the Midwest startup ecosystem. We are one of the most active investors in the region, with nearly 50 portfolio companies spanning 9 states. We have deep roots in this region and regularly cover a ton of ground — hopping from city to city and digging into each local community to understand their unique challenges and opportunities. While there, startup leaders and community champions who understand the importance of a tech economy regularly ask us how they are doing — the good, the bad and the ugly. They know they are far away from Silicon Valley but see the opportunity all around them. They want to know what their community can do to improve the odds of startup success — and attract talented entrepreneurs to build their companies there. And, perhaps most interestingly, they want to know where they stack upagainst other cities we’ve visited.
Welcome back to our final post in the Smaller, Earlier VCs Should Invest Differently series. If you’re just joining us now, you can learn about portfolio variance here or dilution here. This week I’m wrapping up by demonstrating the huge effect seemingly small changes in valuations have at earlier-stages — and why a micro-VC should be the exact opposite of “valuation insensitive.”
This is part three of a four-part blog series that I began two weeks ago. The first post outlines why micro-VCs investing in early-stage startups should notfollow the best practices of their larger, more traditional VC peers. Last week in the second post, I discussed a little-discussed metric — portfolio variance — and how that significantly impacts a smaller, earlier fund’s risk. The big takeaway? A larger portfolio size of 70 companies both increases the median fund return and decreases portfolio variance (i.e. risk) to match that of a 20-company-portfolio Series A fund. This week I’m bringing up a metric that is touted as a chief concern for investing in smaller, earlier VCs but I find it completely over-hyped: dilution. Turns out, it really doesn’t matter that much…
Last week I began a blog series on how the growing array of micro-VCs investing in early-stage rounds should think differently. You should read that now before diving into this post, but TL;DR is that these VCs (including us at M25) should not utilize some of the best practices in portfolio theory that have worked well for the larger, traditional VC. These strategies, transferred to our stage and AUM, don’t take account of the vast differences in risk and reward. Today, I’ll first dig into a little-talked-about metric: portfolio variance.
Like any industry, VC can be resistant to change and disruption, and we’ve now begun to see a myriad array of new strategies in this growing asset class: accelerators & their follow-on funds, geo- or thesis- focused strategies, “index” portfolios and miniature versions of traditional firms abound. If you read much about this space, you’ve probably already read a bit about “the rise of micro-VC.” Most of these smaller firms focus on earlier-stages than their larger counterparts, as they generally need to make smaller investments.
Data science is here, and it’s growing fast. No one’s questioning that. Which is core to our thesis behind one of our most recent investments, Astronomer. But it wasn’t too long ago that explaining the value of data science to folks wasn’t that easy.