The things you need to think about when setting yourVenture fund target

Follow me @samirkaji for my thoughts on the venture market, with a focus on the continued growth with the emerging manager landscape.

A common question I get when speaking with newer venture emerging managers is about how to go about fund sizing.

Most of the managers I speak with compute fund targets based on a few common factors:

1) How much they think they can reasonably raise using their available market intelligence and line of sight to prospective capital (this is hard, inexact, and often wrong).

2) A bottom-up approach toward how much they want to invest in companies, # of portfolio companies they’d like in the fund, and contemplated reserve model.

3) What they and their partners need to support themselves financially.

For many managers, this sets a path of a linear progression of fund sizing. I.e., a manager may raise a $15MM fund 1, jump to $30MM-$40MM for Fund 2, and perhaps $50MM-$100MM (or more) for Fund III.

Generally speaking, there are very rational explanations for fund size growth, including increased capital available for initial checks and reserves and the ability to accommodate institutional investors’ allocation requirements. This type of thinking often makes excellent sense and can work very well; however, it’s critical for managers not to limit themselves to any linear or pre-ordained mindset on fund sizing. An example of this type of thinking is “Fund 1 will be a proof of concept at $20MM, Fund II will be $35MM, and Fund III will be $50MM-$75MM”.

While that fund growth progression may end up being the optimal path for the fund manager, it still requires another dimension to the mental model. As Mike Maples has said repeatedly, “Your fund size is your business model.”

While this is a concept that is relatively easy to understand, it does require fund managers to ask themselves some crucial questions, including:

• Do I have any definable edge for the business model that relates to my contemplated fund size?
• How does my product value to founders and co-investors differ across fund sizes? At larger check sizes, % ownership, and % allocation of a round, the height of the product bar you need to clear changes dramatically. Going from small non-lead positions to lead positions requires an entirely different product profile, business model, and operational mindset.
• Who are my competitors at different fund size bands, and within which cohort is my product and offering the most competitive and why?
• Is the strenght of my brand aligned with fund size? Often, I see fund managers look to upsize significantly from fund to fund well in advance of establishing the type of brand equity that enables them to be consistently competitive with the new cohort of competitors.
• Does the fund size optimize returns for my LPs (and for my partnership)? From experience, I’ve seen managers produce exceptional returns within a fund size band and then poorly perform when going too far above that band. VC is undoubtedly the consummate long game, and it’s vital to align fund size to where your highest competitive edge lies at that given point in time. The difference between a 5X on a $15MM fund vs. a 2X on a $35MM is 4.2X Net for LPs and $12MM in Carry for the GP vs. a 1.8X Net for LP’s and $7MM in carry for the GP. Optimize fund size for what best aligns with competitive edge.

To be clear, this isn’t my call to keep fund sizes small (albeit I do think small fund sizes do allow much more nimbleness in investing behavior), but rather a call to managers to ask these critical questions while setting fund targets.

In truth, there are plenty of managers that have thrived despite growing fund sizes significantly — DCVC, Forerunner, and Felicis are firms that have grown fund sizes, but not at the expense of the risk/return profiles they offer LP’s. In contrast, others such as IA Ventures and Founder Collective have determined that staying within a specific fund size range is optimal for their ability to produce the highest returns.

Fund sizing doesn’t have to be overly complicated and isn’t an exact science but does require thinking across several macro and micro dimensions.