Consumption software Modelling
Started my learning / recruiting for pod HF recently (currently PE asso) and trying to develop coverage / ideas in consumption software - given I'm trying to recruit for a software pod. One area, I find a bit more challenging has been modelling and thinking about consumption SaaS i.e. businesses with upfront commitments and trade on bookings / RPO like SNOW, DDOG, DT, MDB
Questions below from the work I'm doing and apologies in advance if the questions are somewhat naive. Some additional questions are below un-related to the specific modeling.
1. Given that revenue and current period top-line is often a lagging indicator do you typically aim to model billings / bookings and think about how changes here inform the forecasted revenue, deferred, etc. (i.e. drive everything from bill / book)
2. If so, how do you get granular on your modelling - often RPO / booking / billing data isn't granular and if I have a particular view on some of the segmentation it seems challenging to model without a numerical basis. Is it generally not a fruitful exercise to try to estimate and get more granular here?
4. Less modelling and thinking and more research-related: A basic starting point of research involves channel checks and digging for data - I have access to expert networks, but feel weird about using firm resources to do more HF style expert calls - curious if and how people at PE firms who have recruited to HF leveraged expert networks or built their own channels.
5. Am I digging a grave by trying to cover names that are mid / slightly mid/large cap and develop ideas given the intense coverage? I.e. it will be likely incredibly challenging to know comparable (10b+ market cap) names in the coverage universe better than the analysts / PMs who interview me. Curious if this is a generally poor approach when recruiting.
I'm in learning mode, so highly appreciate any and all honest advice or negative feedback on my thought process.
To tackle your questions effectively:
Modeling Billings/Bookings to Forecast Revenue: Based on the most helpful WSO content, modeling billings/bookings is a common approach for SaaS businesses, especially those with upfront commitments. Revenue is indeed a lagging indicator, so driving forecasts from billings/bookings and deferred revenue is a logical method. For example, billings can be calculated as the sum of current revenue and the QoQ change in deferred revenue, while bookings might include current revenue and QoQ changes in RPOs. This approach helps align your model with the operational realities of consumption-based SaaS businesses.
Granularity in Modeling: When RPO/booking/billing data lacks granularity, it can be challenging to segment effectively. However, as noted in SaaS modeling discussions, the level of granularity often depends on the company and available disclosures. If segmentation is critical to your thesis, you might need to rely on management commentary, industry benchmarks, or alternative data sources. While it can be fruitful to estimate and segment, ensure your assumptions are defensible and aligned with the company's reporting practices.
Leveraging Expert Networks for Research: Transitioning from PE to HF often involves a shift in research methodology. While using expert networks is common in hedge funds, it’s understandable to feel cautious about utilizing firm resources for HF-style calls. Many PE professionals transitioning to HFs build their own networks by reaching out to industry contacts, attending conferences, or leveraging public data sources. If you do use expert networks, ensure compliance with your firm's policies.
Covering Mid/Large-Cap Names: Covering mid/large-cap names can be challenging due to intense sell-side and buy-side coverage. However, as highlighted in WSO threads, the key is to develop a differentiated perspective. This could involve identifying underappreciated growth drivers, mispriced risks, or unique insights from alternative data. While it’s tough to out-analyze seasoned analysts/PMs, demonstrating a unique angle or deep understanding of a niche within the sector can set you apart.
General Advice: Your approach to learning and asking thoughtful questions is commendable. To further strengthen your preparation, consider diving into SaaS-specific metrics like net retention rates, LTV/CAC ratios, and ARR growth. Resources like TheSaaSCFO (www.thesaascfo.com) and Andreessen Horowitz's SaaS metrics guides (https://a16z.com/2015/08/21/16-metrics/ and https://a16z.com/2015/09/23/16-more-metrics/) can provide valuable insights.
Your thought process is solid, and with continued learning and refinement, you'll be well-prepared for your HF recruiting journey.
Sources: L/S SaaS Modeling, An Overview of Technology Media and Telecom (TMT) - Part 2 of 2, PE recruiting technical questions (software specific), An Overview of Technology Media and Telecom (TMT) - Part 2 of 2, Q&A: Technology IB Analyst
Illo aut veritatis nemo et reprehenderit quod. Velit quibusdam fugit omnis fugit et aut accusamus.
Beatae officiis rerum iusto reprehenderit sunt. Reprehenderit deleniti et molestias voluptas molestiae. Assumenda occaecati fugit aliquid sit facilis. Consectetur excepturi laboriosam labore aperiam accusamus aut non.
Voluptatum voluptatum velit ratione ut. Voluptatibus hic quia assumenda qui ipsum. Id omnis consequuntur nulla maxime.
See All Comments - 100% Free
WSO depends on everyone being able to pitch in when they know something. Unlock with your email and get bonus: 6 financial modeling lessons free ($199 value)
or Unlock with your social account...