Strategies for Optimal Follow-On Investments

Anubhav Srivastava
Founder
Strategies for Optimal Follow-On Investments

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 comes in — a portfolio scenario-planning platform that automatically executes this workflow.

The Workflow in Action

Let’s say we’ve made a $1.5M seed investment in Company X — and our underwrite case expects the company to exit at a $150mm valuation. We’ve built the underwrite case in Tactyc as follows:

Estimate Initial Reserves

What is the optimal reserve amount for the future Series A round? Tactyc 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.

Building Performance Cases

Next, we build multiple performance cases for this investment at various exit values (e.g. a “bear” and “bull” case with probability for each). Tactyc automatically summarizes the risk weighted returns and reserves across all the performance cases.

Based on the above, Tactyc recommended reserve level is $702K for a future follow-on investment in Company X’s Series A round.

The Follow-on MOIC and rebalancing reserves

The Follow-on MOIC is the expected return on the next $1 into the company. Specifically it’s the return on the reserve dollars to be invested.

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. Based on our current expectations, Company X stands to return $2.45 for every new $1 of 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. For example, let’s say 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 from 30% to 50% to align exit expectations with actual performance data.

Our expected Follow-On MOIC has now drastically reduced from the original 2.45x to only 1.80x. We may consider optimizing our reserves to allocate more to companies with higher Follow-On MOICs.

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 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.