Private Equity (PE) investors often ask us who will turn out to be the best performing businesses in the TMT (Technology, Media, Telecoms) sector following COVID-19. As always, the answer is ‘it depends’.
From a bird’s eye view, it is easy to conclude that anything digital is ‘in’, and anything physical is ‘out’. Current stock market valuations seem to reflect this view with big tech already trading at pre-COVID-19 levels while corporates that operate exhibitions, conferences and live events are trading well below pre-COVID-19 levels.
However, this binary approach is unlikely to maximise returns for investors. Not all participants in a sector with tailwinds are guaranteed to succeed and not all those operating in more challenging markets are inescapably compromised. More sophisticated analytical frameworks are required to identify the right deals and deliver the next wave of super-returns. Within reason, an element of contrarian thesis is likely to reward investors that take this path more handsomely than those that pile their capital into a narrower pool of ‘in vogue’ asset classes overcrowded with aspiring buyers.
Therefore, in testing the investment thesis for a post-COVID-19 world, we assess the quality of a business and the potential for value creation from multiple angles, such as (non-exhaustive list):
- How was the business performing pre-crisis?
- How robust are its P&L, unit economics, and cash conversion?
- How do its unit economics change in a social distancing environment?
- Does the business sell must-have or discretionary products?
- How integrated are they in the workflow of its users?
- How are they rated vs competing solutions?
- Can they be consumed online or do they depend on physical interaction/delivery?
- Is there a robust product development roadmap to increase the number of use cases and expand the total addressable market over time?
- Does the business derive revenues from yearly subscriptions, transactional sales, sponsorships, or other?
- What drives volume and value?
- Is the industry vertical served likely to experience growth or consolidation?
- Does the business serve large enterprises, SMEs, government or individuals?
- What’s the risk of any customers’ financial distress leading to bad debt?
- How flexible is the operating model of the business?
- Does it make full use of digital technologies to maximise and diversify sales, engage customers, speed up product development, and optimise the cost structure?
- Can it withstand workplace and workflow disruptions?
Doing this homework requires deep analytics and extensive access to company data and market information. The additional complication in a Covid-19 context is that all market forecasts produced by third-party research firms only a few months ago are completely out of date. Therefore, we advocate the use of ‘alternative, high-frequency data’ to uncover more recent trends and lead-indicators of performance in the new-normal. Often these consist of real-time data sets accessible through online application programming interface (APIs), mobile apps and other raw primary sources (for example, satellite imagery, Twitter feeds, mobile searches, online bookings data, web scraping of retail prices on e-commerce sites, etc).
Using this integrated framework shows that SaaS platforms (Software-as-a-Service), underpinned by sticky, tech-enabled use cases and recurring revenue streams, score well on many of the Level 1 to Level 5 criteria – therefore, they will continue to be in favour with PE investors. This methodology also shows that not all SaaS businesses are created equal. A platform serving SMEs may be less well positioned than one serving corporates. One that operates in the oil & gas sectors should fare less well in the immediate future than another serving the health & pharma or government sectors. A Business 2 Business (B2B) provider that is not SaaS and serves oil & gas should be under significant pressure; but not necessarily, if the data provided are must-have ‘price analytics’ used in financial derivatives and other commercial contracts, for example.
Businesses that score highly on all of Level 1 to Level 5 criteria are likely to be highly coveted and therefore very expensive. Will they deliver the expected returns? It will really depend on the interplay between entry price, post-deal business performance and exit valuation. 20x Earnings before interest, taxes, depreciation, and amortization (EBITDA) had become the norm for PE investing in top performing subscription-based / tech-enabled companies pre-COVID-19, up from 10-12x a decade ago. Can we perhaps look forward to 30x EBITDA deals down the line, once the new liquidity created by central banks and the imbalance between abundant dry powder and the shortage of good assets fully plays out.
On the opposite end of the spectrum, trade exhibitions and conferences are likely to be out of favour for some time, in spite of EBITDA multiples reaching highs of 14-15x not long ago. The argument being that humanity and business life are inescapably heading online and executives are unlikely to travel to trade shows. Or at least not in the same numbers. As a result, valuations have already fallen sharply and are likely to stay low for a while. Nevertheless, therein lies the opportunity (for the contrarians). While webinars are likely to effectively complement or even replace conferences where the purpose of the gathering is ‘information download’, trade shows and exhibitions are face-to-face platforms for convening buyers and sellers. In the B2B world, trade shows enable the discovery and furthering of commercial relationships and long term partnerships in a way that no digital business has been able to replicate online so far. At the right entry price, this asset class could deliver quite attractive returns on the 2023-2025 horizon, without necessarily requiring a 100 percent recovery of revenues to pre-COVID-19 levels.
So, who will turn out to be the best performing businesses from an investment perspective? Clearly, it depends.
Investors that will do their own homework on commercial, operational and financial due diligence using differentiated tools and high-frequency datasets are likely to outperform those that rely too heavily on Seller’s pre-packaged information and on traditional commercial and financial diligence methods.