Valuation is not an art or science, it is a craft — Aswath Damodaran
One of the most important metrics for any founder, business owner or a manager is the valuation of her firm. This is because valuation allows you to measure and baseline the fair value of the firm, and you can only manage what you can rightfully measure.
However, even though the fundamentals of valuation are straightforward, sometimes we are really off the mark, as we have seen in the case of wework, Casper, Uber just to name a few.
Most of the inaccuracies in valuation can be attributed to
– Lack of applying the right valuation framework
– Getting the right data for comparison
– Uncovering the hidden and implicit assumptions
Let’s look at each of these one by one:
Lack of application of the right valuation framework
Everything should be made as simple as possible, but not simpler — Albert Einstein
When confronted with countless ambiguities associated with a firm, especially a start-up, applying an EBITDA multiple is usually a faster way out, and it involves a leap of faith over blind spots that can be avoided. However, both investors and founders have much to lose by taking the EBITDA route. Moreover, it leaves a lot of fundable companies which are doing good from a unit economics perspective but currently might be in red.
With the rising number of companies in SaaS, DTC and subscription-based services, venture capitalists and investors increasingly think that estimating customer lifetime value is a better valuation strategy than using EBITDA multiples. Discounted cash flows are also making a way back in to measure a firm’s value as it helps understand the revenue, growth and profitability of a startup even though the historical data might not be present.
Getting the right data for comparison
Most people use statistics like a drunk man uses a lamppost; more for support than illumination” — Andrew Lang
From my personal experience in helping start ups raise capital both in US and India, the use of data for relative valuations is a mixed surprise. We all tend to go for data that is readily available and that even if that doesn’t give the complete picture.
There is a clear scope for investors to play their version of Moneyball, especially with the availability of data in the start-up industry in recent years. We have stalwarts like Professor Aswath Damodaran who industriously clean the raw market and accounting data on publicly traded companies and companies like Crunchbase, Tracxn, Owler which are working on the data space.
Uncovering the hidden and riskiest assumptions
In start-up parlance, assumptions are notions that need to be true or resolved in order for the idea to work. Typically, when we do a sales or a financial forecast, there are implicit and hidden assumptions that creep in. Are my growth projections an output from all the marketing channels or are they just a CAGR from where I should be? Do I have a sales reinvestment to account for the growth?
There is an increasing play of both AI and ML to bring out the implicit assumptions that get buried in the numbers.
Finally, the reason that too much capital is chasing too few startups is also that somewhere we are not able to fund companies that are actually fundable, because the anatomy of how to value a company has remained unchanged since past 25–30 years. Personal interactions and relationships based diligence coupled with valuations based on thin excel models create a propensity for bias.
I believe that a solution that allows entrepreneurs and investors to measure a company’s fair value would not only be empowering for the stakeholders, but also bring more financial efficiency into the system.
Today, software and AI are eating the world, and every industry is being transformed by the use of data, from health-tech to financial services to real-estate and beyond. If the fundamental question is whether early stage investment decisions and valuation can be made better with the use of data driven valuation techniques, the answer is most certainly yes.
While we have been helping companies use our MVP in a private beta, do drop us a line if you are raising capital or measuring a company in your portfolio. We are committed to demystify and democratise the use of data for valuation and capital raising.