What are the common pitfalls and biases when comparing VC multiples and IRR?

1 Multiple definitions

Multiples are ratios that measure the value of a company relative to some financial metric, such as revenue, earnings, or cash flow. They are often used to compare companies within the same industry or stage, or to estimate exit values. However, there is no standard definition or calculation of multiples, and different sources may use different methodologies, assumptions, and adjustments. For example, some may use trailing or forward metrics, gross or net revenue, adjusted or reported earnings, or enterprise or equity value. To avoid misleading comparisons, you should always check the underlying data and formulas of the multiples you use, and adjust them if necessary to match your criteria and context.

2 IRR limitations

IRR is the annualized rate of return that equates the present value of a series of cash flows to the initial investment. It is often used to measure the profitability and efficiency of a VC investment, and to compare it with other investments or benchmarks. However, IRR has some limitations that can distort its accuracy and usefulness. For example, IRR assumes that all cash flows are reinvested at the same rate, which may not be realistic in VC. IRR also ignores the size and timing of the cash flows, which can affect the risk and value of the investment. Furthermore, IRR can have multiple or negative values, or no value at all, depending on the cash flow pattern. To overcome these limitations, you should complement IRR with other metrics, such as net present value (NPV), cash-on-cash return, or payback period.

3 Benchmark biases

Benchmarks are reference points that help you assess the performance and potential of your portfolio companies and your fund. They can be based on multiples or IRR, and derived from various sources, such as public markets, peer funds, industry averages, or historical data. However, benchmarks can also introduce biases that can affect your comparisons and decisions. For example, benchmarks can suffer from selection bias, survivorship bias, reporting bias, or recency bias, depending on the sample and methodology used to create them. Benchmarks can also create anchoring bias, confirmation bias, or overconfidence bias, depending on how you interpret and use them. To avoid these biases, you should always question the validity and relevance of the benchmarks you use, and seek alternative perspectives and evidence.

4 Context matters

One of the most important factors to consider when comparing multiples and IRR is the context of the companies and the investments. Context can include aspects such as industry, stage, growth rate, profitability, capital structure, competitive advantage, market dynamics, exit opportunities, and risk factors. These aspects can have a significant impact on the value and return of a company, and explain why some companies may have higher or lower multiples or IRR than others. Therefore, you should always adjust your comparisons for the differences in context, and avoid simplistic or superficial analysis.

5 Value drivers

Another key factor to consider when comparing multiples and IRR is the value drivers of the companies and the investments. Value drivers are the factors that influence the growth, profitability, and sustainability of a company, and determine its potential to generate value for its shareholders. Value drivers can include aspects such as customer acquisition, retention, and monetization, product innovation and differentiation, operational efficiency and scalability, team quality and culture, strategic partnerships and alliances, and social and environmental impact. These aspects can have a positive or negative effect on the value and return of a company, and explain why some companies may deserve higher or lower multiples or IRR than others. Therefore, you should always identify and evaluate the value drivers of the companies and the investments you compare, and avoid relying solely on quantitative metrics.

6 Sensitivity analysis

Finally, one of the best practices to follow when comparing multiples and IRR is to conduct sensitivity analysis. Sensitivity analysis is a technique that allows you to test how changes in one or more variables affect the outcome of a calculation or a model. For example, you can use sensitivity analysis to see how changes in revenue growth, margin expansion, exit multiple, or discount rate affect the value or return of a company or an investment. Sensitivity analysis can help you understand the range and distribution of possible outcomes, the key assumptions and drivers of value and return, and the risks and uncertainties involved. Therefore, you should always perform sensitivity analysis to enhance your comparisons and decisions.