Dealing with the deluge of Pipeline
Pipeline counter: 50-60 a week. 15-20 of them referred from VCs, angels, LPs, Blume founders, non-Blume founders et al and that’s suddenly a job by itself for a small army of analysts. Some big VCs have small teams dedicated to sift through this overload. Companies like Tracxn and LetsVenture were first born in the US out of this need and replicated here (don’t think the job is getting any simpler though). I don’t think startup success rates are surging in portfolio selection basis tools. Elsewhere, Salesforce and other CRM hacks and products like Gust help manage the process for VCs and angel groups respectively. We’ve struggled with this growing deluge, given the team size, the budgets of a small fund, and the continuous frenzy of a large portfolio.
While we can’t speak for other VCs’ pipeline processes, we thought it was only fair to founders who pitch to us for capital to know how we think about pipeline and what maybe the reasons that most mails and approaches may yet draw a blank from Blume. We do try and send back as courteous / encouraging a reply as we possibly can. We are trying to get better in that department as well.
The selection rates are below 1% and even there, the bias is severe towards referrals (selection rates are likely higher in the referral category – hope to have far better data to present once 2016 is done – will describe this referral bias more in Part 4 of this series). So, cold pipeline (approaches) at early stage are almost impossible to devote time to.
Let me state it here once and for all: we have nothing but respect for every entrepreneur out there who writes into us. It takes a rare courage to even startup – 9 out of 10 people can barely muster that courage in the first place. And our rejection by any means shouldn’t shake your conviction in the idea. Someone who can spend time with you and whom you trust should be the ones who help shape or shake your conviction, if at all. That’s the mark of a great founder – to surround themselves with the right advisors and mentors but also be mindful of what to disregard (which is a large % of the “gyaan” you will get from everyone around you – gyaan loosely translates to “wisdom/knowledge” in the Indian context for our overseas readers). So, if your conviction holds, keep pushing yourself, till you don’t feel the same conviction for more than a few mornings at a stretch (you have to budget for tough stretches 🙂).
As you can well figure out, there is only so much capital and so much bandwidth available at each firm and that automatically dictates a typical size of portfolio over an investing period. It’s surprising how many founders think VCs raising third party capital is such a breeze and that we always have more than enough money to throw around (this seeming lack of knowledge at the founders’ end on what it takes folks like us to build a VC fund ground up may prompt a series called the Fund Raising Chronicles!).
To give you an illustration of how things work in an investment cycle:
At Blume, the investing timeframe for a Fund II would be 30-36 months i.e. all our seed/pre-Series A investments (basically Blume’s first cheque into a company) would be made in this period. We are already 6+ months into the Fund II cycle => Meaning we would be tracking at 20-25% of total # of investments to be made already (most funds, including us, are guilty of a front-ended bias in terms of number of companies – this happens because a) there is a backlog usually when between funds – lack of capital towards the end of the last fund, and before the new fund falls into place nicely, means that a lot of interesting pipeline spills over into new fund and b) riskier, smaller bets tend to be taken in the early years given that you want to give a longer runway for some companies to be built over 8-10 years)
Here’s a snapshot of what the projected cashflows and phases of our Fund II cycle look like (for easy reference, this suggests a total investment of $X starting mid-2015):
These little nuances explain selection rates / selection biases. And then you would add back the structural problems with Venture Capital funnels (sketched briefly in part 2 of this series) – as you can see in those funnels, no amount of additional capital at seed is useful if acquirers or Series A’s are missing in sufficient proportions. This feeling of despair continues down the value chain i.e. Series A folks feel the same way about potential acquirers and Series B players missing in the ecosystem etc.
Cut to Fund II strategy shifts: Even though we are amongst the most prolific investors in the country, we are choosing to broadly abandon the 50-100K ‘optionality strategy’ in most part in this Fund – which means we either lead/co-lead most of our investments with co-investors we like, or we stay out. Our cheque sizes, therefore, will likely be in the range of 200-500K in round sizes of 300K-$1 million. We employed the syndicate strategy very effectively in Fund I. It has its pluses (we got to work with some great founders we would’ve missed otherwise and learnt immensely with very little risk capital) but the negatives seem to outweigh the positives. Tactical entry-level cheques would be limited to companies we missed at seed and we are catching at A rounds or thereabout OR if there’s a very large seed round of >1.5-2 million (which is becoming fairly common too for, say, 10-15 startups in a year where founding teams are deemed great or accomplished). So, this will slow our 2011/12/13 pace of 20-23 investments a year since we plan to go deeper than broader now. We are likely to make 35-40 core strategy investments in Fund II. And add a few tactical cheques to the tally.
Early examples in Fund II (these were all announced in Q3 and Q4 of 2015)
Lead / Co-Lead (core strategy): Mockbank, MechMocha, Road Runnr, Zenatix
Syndicate / Tactical: Chillr
To reiterate, even at our higher-than-market-average levels, where Blume is making 15-18 fresh investments in a year, this is out of a pipeline that’s easily now at an annualized rate of about 2,500-3,000 (and this is direct email/twitter/linkedin inbound + referrals, not just a blind total from some external database).
So, if one applies the compounding of probabilities of:
‘Does it fit our Conviction Criteria’ (part 1 of this series) x
‘Is it a fit with our macro-thesis areas’ (part 2 of this series) x
‘Do we have Competing or multiple/similar early bets made in the space’ x
‘Does it fit our internal frameworks around stakes/valuations etc’ x
‘The sheer volume that potentially leads to alpha/beta errors around selection’;
it seems almost a zero probability event that we actually invest in anything at all!