Filter-first think-later model of (traditional) accelerators
I had once wondered if an accelerator could actually miss a potential startup if that startup idea is somewhat bold but carries characterizations of uncertainty such as one founder, or other characterizations that does not look like traction, or characterizations that sets them a part from what appears to be the market reality? Well, just writing this I am already inclined to reject that potential startup team.
Disclaimer — This is a technical research note, documented, from annotations I made on September 3th, 2019; where I were collecting evidence to explain a potential phenomenon, a characterization, where accelerators, in general (consider an average accelerator) could exercise a selection process highly based in market-driven biases while letting qualitative criterias to a later stage.
Initial motivation — a complication with a “top“ idea which I didn’t like
I had considered that possibility from an experience of being part of a ‘Silicon-Valley-based’ accelerator program that landed in my city in Brazil in 2016. I was in. And then, right at the beginning, they required me to come up with 3 ideas, and present them to mentors and program directors. However, for me, it turned out that the “top idea,” to their eyes, happened to be the one I had less connection with. At the time I sensed trouble in the air. But you know, how confusing things can be, when we are there, in the arena. I wasn’t sure about things going, things with the program or things with me. I may have wondered — from that not so clear space of confusion— if I had to be passionated with that idea, that 3rd one nice to their eyes but not cool for me.
Anyway, I moved on, with courage. I moved on with the one I liked more, what would be perhaps the boring one to the eyes of the market and one which I referred to it as “yet another slides platform.” As you may guess, not so far and later, my next pitch didn’t do well. Fast-forward to the after chapter, when I was already a drop out from the program, I kept that question alive: What happened there? At the time, watching some of teams that passed to the next chapter, I sensed what would seem to be the best situation: Value to the eyes of advisor/mentors, on one hand. An also value in terms of connection, to the team.
The research quest
A period of research followed from that initial motivation — not only related to that specific line of inquiry. Anyway and in this context, I later in 2019 I found a research paper which helped me to make sense of some of the characterizations of accelerators:
[a] Yin, B., & Luo, J. (2018). How do accelerators select startups? Shifting decision criteria across stages. IEEE Transactions on Engineering Management, PP(99), 1–16. https://doi.org/10.1109/TEM.2018.2791501
The following are some thoughts I had annotated at the time.
More consciousness to accelerator managers
According to the paper authors, one manager of the accelerator that was the study case, acknowledged that the findings would help them to be more conscious about “the shift in key factors at different stage of the selection.”
They also point, from their conclusion, that “For practice, our findings may help accelerator managers to be more conscious of their own subconscious preferences, rationales and biases and thus improve the decision process.”
Awaress of lack of criteria prior to the process
The paper points to how some of the decision making processes are in fact somewhat driven by decision-making pressures, like “having to decide.”
“As suggested by the psychological studies of decision making [16], decision makers often do not make a decision with clearly ranked preferences because of the complexity of choices but instead determine the preferences as a result of having to decide.” [a]
Refect-first, select later — suggesting qualitative or subjective later
They present interesting conclusions where many accelerator may actually engage into rejecting first which for me makes sense (from their views) due what would appear to be an impossibility or paradox. Note that the variability of start-ups could anyway let a good case escape — traction, data (first) followed by vision and values.
“ Using the identified critical criteria to predict the results of additional startups, we demonstrate preliminary evidence that the critical criteria in the initial stage are more explanatory on “rejection” decisions, and the critical criteria in the final stage are more explanatory on “selection” decisions.” [a]
This note is now documented as part of the process of completing the book entitled Slow Down to Start Up. I am considering some characterizations of this pain-problem in the foreword.
