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Investigating an alternative approach to SaaS company valuation : using ‘Rule of 40’ metrics as indicators of Enterprise Value

Hottenhuis, Bas (2020) Investigating an alternative approach to SaaS company valuation : using ‘Rule of 40’ metrics as indicators of Enterprise Value.

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Abstract:Company valuation has always been highly difficult and a reason for discussion. Especially the valuation of Tech companies and 'Software as a Service'-companies (SaaS) is challenging as the most-used valuation methods are mainly focused on traditional companies with a higher amount of fixed assets. Conventional valuation methods are often based on discounted cash flows (DCFs). These are not in the same way applicable for Tech/SaaS companies since they typically have different company characteristics (e.g. hardly any fixed assets) which lead to unreliable DCF results. We introduce an alternative point of view: the ‘Rule of 40’. Conceptually, this rule of thumb states that there is a direct trade-off between a company’s growth and margin, which can therefore be added together to give an indication of a firm’s performance. The sum of the growth and margin is in the case of this research used as an indicator for the level of the firm’s valuation multiple. To find the most significant indicator, we compare 20 different combinations of Rule of 40 indicators and valuation multiples. This analysis is carried out using linear regression, in which we focus on the results of the slope and R-squared. Tech companies are retrieved using S&P's General Industry Classification Standards (GICS), and SaaS companies are selected based on a list of the 50 largest SaaS companies in America. The Tech company analysis does not result in any significant relations. Therefore we decided to focus on SaaS companies. The most significant relationship is found to be Rule of 40 indicator 'Free Cash Flow Margin + Revenue Growth', in combination with the valuation multiple 'TEV/Revenue'. Based on our literature review, we extended the applicability of the Rule of 40 by looking at different sectors with similar characteristics. E-commerce companies are also selected using GICS. The regressions for E-commerce also result in 'FCF margin + Revenue growth' as the most significant indicator in combination with 'TEV/Revenue'. From this, we conclude that the trade-off principle is applicable to both SaaS as well as E-commerce. The regressions for SaaS and E-commerce both do not result in a relationship that is significant enough to use for company valuation. Since the concept cannot be applied to valuation we test the robustness of our analyses in two different ways. We reconsider the growth + margin concept by checking the relationships using Spearman ranked correlation. The results suggest the same indicators to be most significant, which confirms earlier findings. For the second robustness check, we use winsorizing, which adjusts our data to decrease the effect of outliers. The check shows that the results for SaaS are more robust than for E-commerce. Possible reasons for this are sticky demand, customer loyalty, and customer base-scalability, which all have a positive effect for SaaS. The final conclusion is that there is a significant relationship, but that it cannot directly be used for company valuation since the relationship is not significant enough. This research adds to the existing literature with a comprehensive evaluation of the predictive powers of Rule of 40-based indicators for company valuation multiples. Another addition to the literature is the extension towards a different industry, which had not been done before. For further research, we advise using the most significant indicator from this report as a starting point for more elaborate regression research in which more variables are added such as company size, age, the percentage in recurring customers or industry subcategory within SaaS. This will lead to a more reliable source for SaaS company valuation. A point of discussion remains to which extent the conclusions are applicable to smaller companies since the current research is focused on large companies.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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