Post-launch, a fund manager’s focus shifts from portfolio construction to active portfolio management — and a frequent pain point is follow-on reserve sizing on active deals. Most managers grapple with optimal follow-on reserve for a deal and oftentimes struggle to determine how follow-on reserves should change over time. We’ve surveyed the best practices of hundreds of emerging managers and in this post, we shed light on the quantitative frameworks used to answer both of these questions.
Before we begin, let’s address a few misconceptions we’ve seen regarding follow-on strategies:
Most managers take a balanced approach — they’ll follow on in deals where the managers continue to have conviction while passing on a few where the exit expectations have drastically reduced. We’ve noticed that the decision to follow on is frequently sentiment-driven. Managers may “fall in love” with a deal, fall prey to the sunk cost fallacy, or make follow-on investments based on their relationships with founders.
To avoid these pitfalls, we’ve noticed most successful data-driven managers follow a quantitative workflow that periodically takes into account a company’s expected performance to size reserves, rebalance reserves, and eventually deploy reserves. This is what the workflow looks like:
Executing the above workflow in action requires a bit of math. This is where Tactyc Venture Manager comes in — a portfolio scenario-planning platform that automatically executes this workflow.
The Workflow in Action
Let’s say we’ve made a $1M seed investment in Company X — and our underwrite case expects the company to exit at a $100M valuation. We’ve built the underwrite case in Venture Manager as follows:
Step 1: Estimate Initial Reserves
What is the optimal reserve amount for the future Series A round? Venture Manager helps answer this by summarizing impacts to Exit MOICs, Return the Fund, Exit FMV at various reserve levels:
Picking the right reserve level here is a balancing act. We don’t want the Return the Fund metric to increase beyond reasonable valuations — but also want to reduce depression on Exit MOIC. We also want to compare this deal’s reserve ratio with our overall fund reserve ratio to ensure we aren’t significantly over or under-allocating reserves for this investment vs. our overall fund’s reserve ratio.
Step 2: Building Performance Cases
Next, we build multiple performance cases for this investment at various exit values (e.g. a “downside” and “upside” case with 20% probability each). Venture Manager automatically summarizes the Exit MOICs, MOIC on Initial Investment, and MOIC on Follow-on Investment across each case:
Based on the above, Venture Manager’s recommended reserve level is $900K for a future follow-on investment in Company X’s Series A round.
It’s worth pointing out the Follow-On MOIC metric of 3.98x — this is the key. The Follow-On MOIC is the expected return on follow-on investments only.
Many fund managers miss calculating this essential metric (as the math can become somewhat cumbersome), but as will become evident shortly, this is a powerful metric to compare expected returns on reserves across deals in the rest of this workflow.
Step 3: Periodically Rebalance Reserves
Over time our view on each investment’s potential exit values and probabilities may change as we track the company’s actual performance to projected — this is an opportunity to re-balance deal reserves. Let’s say our current reserve levels are as follows:
And after 6 months, we review Company X’s operating performance and compare it to our projection built at the time we made the first investment — and realize that the company is falling short of our expectations.
We decide to revisit our downside case for Company X and increase its probability to align exit expectations with actual performance data.
Our expected Follow-On MOIC has now drastically reduced from the original 3.98x to only 1.65x. Are there other companies in our portfolio where this follow-on reserve may be better spent? To answer, we take a look at the Follow-On MOIC metric across our entire portfolio to compare investments on an apples-to-apples basis.
Company H, A, and B all have higher Follow-on MOICs than Company X. We want to maximize reserves in H, A, and B (subject to available pro-rata rights in those companies) and should consider shifting reserves from Company X to Company H, A, or B instead.
The point here is that by taking expected performance into consideration across deals, we can allocate the greatest reserves to the highest yielding deals — and continuously rebalance as our performance expectations change.
Closing Thoughts: Data-Driven Workflows = Crucial
Reserve planning and deployment can become more art than science. This workflow removes emotions and avoids sunk cost fallacies to creep into the decision-making process. Tactyc Venture Manager makes scenario-planning workflows easy and readily available — without having to update or manage complicated spreadsheet models. We’ve crystalized this specific follow-on workflow into our software by computing Follow-On MOICs for every deal automatically. We want to empower every emerging manager with these strategies from day one.
Upcoming Webinar on Follow-On Strategies
Join us on Thursday, March 24 at 1 pm Eastern for a live webinar on follow-on strategies. We’ll be joined by Michael Palank, Partner at MaC Venture Capital, and Anubhav Srivastava, Founder of Tactyc, to discuss follow-on strategies in detail and the quantitative methods used for follow-on reserve allocation and deployment. Join us by registering here!
Authored By: Anubhav Srivastava
Tactyc Venture Manager (vc.tactyc.io) is a portfolio construction and scenario planning software for venture funds. If you’d like to onboard your fund’s model into Venture Manager, please contact email@example.com or schedule a demo.