Valuing technology companies by historical and projected financial performance requires different methods. Selecting the best method for your company depends on its stage of growth, profitability and many other factors.
One size does not fit all. Further, there are many non-financial factors that can be used in very early tech company valuations. These factors can be used even before they generate revenue. Valuing pre-revenue tech companies is explored in depth in the companion articles in the Early Exits 2.0 series.
This article focuses only on the popular financial methodologies for valuing tech companies:
- Discounted Cash Flow
- EBITDA times Multiple
- Revenue times Multiple
Discounted Cash Flow (DCF) approach
DCF is the time-honoured approach which you can find in every textbook on valuation. It is the first method taught in MBA programs. It is the most credible for mature companies because it uses the historical actual cashflows as a predictor for the future. Here is the process:
- Forecast the cash flow or Adjusted EBITDA for as many years as it can be reasonably estimated into the future; i.e. CF1, CF2, CF3, … CFn;
- Calculate a terminal value (TV) of the company in year n based on the formula:
TV = CFn * (1+g) / (r – g) where:
- CFn is the cash flow in year n
- r is the discount rate
- g is the company growth rate in cash flow
- Calculate the Net Present Value (NPV) of the forecast earnings stream and Terminal Value using r as the discount rate; i.e. CF1, CF2, CF3, … (CFn+TV)
- The Net Present Value is the value of the company.
While DCF delivers reasonable valuations for mature companies with predictable earnings and comparables to benchmark the variables, it very quickly breaks down for growing technology companies. Here’s why: DCF requires the estimation of:
- future cashflows: CF1, CF2, CF3, … CFn
- growth rate (g)
- discount rate (r)
The uncertainty of DCF calculation is the compound of the risk of all three of these estimates, each with a range of uncertainty. For a growing tech company, compounding the three uncertainties leads to a range of possible NPV calculations so wide as to be meaningless. For this reason, DCF is not used in valuing growing tech companies.
The methods based on multiples described below are more appropriate.
Calculating a valuation by using a multiple of EBITDA is more popular for companies with a history of positive earnings. EBITDA is defined as Earnings before Interest, Taxes, Depreciation, Amortization and other non-cash charges to the income statement. EBITDA is normalized to remove income or expenses not related to the business for sale. The EBITDA method strips out the balance sheet items and taxes to generate the company’s actual cashflow.
To use this method, the company calculates its normalized historical EBITDA for the most recent several years by quarter. If the company has had a predictable EBITDA for several quarters, it then calculates the EBITDA for the trailing twelve months (TTM). It then multiplies TTM EBITDA by a multiple appropriate for that business.
This method works well for companies with a history of growing or predictable earnings because it avoids estimating future performance. For tech companies this is often not reliable. But by the same token, it penalizes companies which are investing to grow at the expense of earnings. The EBITDA multiple approach only works for later stage companies where the past is prologue for the future.
That said, in hot M&A markets, acquirers become more aggressive. Often, they may use current or run-rate EBITDA or even projected EBITDA for the forward 12 months. These are used despite the inherent uncertainty.
The EBITDA multiple is not set in stone in the technology industry. Generally, the market suggests a range of values reflecting the buoyancy or misery of the M&A market at that time. For example, multiples can soar to 20x when markets are confident but settle into a historical pattern of 3x – 5x. The position within the range is subject to intense negotiation between the buyer and vendor.
Revenue Multiples for Enterprise Software
The revenue multiple method is popular in the technology industry because it is applicable to the largest number of companies. The revenue multiple method described here is applicable to enterprise, or on-premise software. In addition to these considerations, there are others which apply to subscription-based or Software as a Service (SaaS) companies, as discussed below.
To use the revenue multiple model the company first calculates its trailing 12-month (TTM) revenue. The TTM is multiplied by a revenue multiple reflecting the overall performance of the company.
Using revenues as a base of valuation solves many problems. Revenues are the most reliable number at the top of the income statement. They are unaffected by expenses and allocations that affect EBITDA, or balance sheet charges which affect earnings. It measures the performance factor that early-stage technology companies are most focussed on: revenue growth.
Companies investing heavily to build their technology and expand their sales are rewarded for achieving growth. They are not penalized for the resulting low or negative earnings. Lastly, revenue multiples can be applied to virtually any technology company which has begun selling and as a result, is the most widely applicable.
That said, not all revenues are equal. The revenue multiple is adjusted for a myriad of factors that are different for different kinds of companies. The most important variable, as noted, is the growth rate. A higher growth rate generates more value for a tech company than any other factor as it has the greatest impact on the revenue multiple. However, the revenue multiple is affected by many factors other than the growth rate, including:
- Gross Margin: for a software company, a gross margin of 80% or better is expected. Lower than that will penalize the multiple.
- Predictability of revenue and earnings: If customers are dependent on your software for critical operations, then valuators are reassured that the customers will renew and the revenue stream will continue. Lower risk earns a larger multiple. Revenue from customers locked into subscription services are also predictable. Software as a Service (SaaS) companies are discussed in further detail below.
- Sustainable competitive advantages: As is the case with any company, if you have an advantage which you can protect from your competitors through:
- unique well-developed technology that cannot be easily replicated,
- products that are deeply imbedded and difficult to switch away from,
- regulations that require your services to be in compliance,
- or other “moats”, as Warren Buffett describes them,
then, your revenues are more predictable, leading to a higher multiple.
- Customer concentration: If your revenue is dependent on a few large customers, then you are vulnerable if they leave or extract concessions to remain. Usually, you want no customer to represent more than 10% of your revenue stream.
- Partner reliance: On the supply side, if your business is dependent on partners continuing to provide critical technology or access to channels, then you are highly vulnerable. The risk is that partners will leverage you and this will negatively impact your multiple.
- Market size and structure: The larger the total available market (TAM) the more opportunity for growth and the higher the revenue multiple. But if your software targets a niche or vertical market then the market may be limited. Similarly, if the market is well-served already, your growth depends on stealing share. This means revenues are less predictable, or less profitable, and the lower the multiple.
- Capital intensity: if growth requires heavy investment in sales, marketing, infrastructure, etc., then your software business generates less return on investment which reflects in a lower multiple. Alternatively, a new breed of fully remote companies are agile, easily scaled, with minimal facilities and overhead costs. As described in our Fully Remote Company posts, fully remote companies earn much higher multiples for these and other reasons.
- Strength of the team: A motivated, experienced team is better able to react to unforeseen events and opportunities. This increases the predictability of results which would be reflected in a higher multiple.
These factors are discussed in greater depth in the companion article: “Revenue Multiples are Hard to Use” (to be published in Q2 2022).
Revenue Multiples for SaaS Companies
Software as a Service companies entered the software industry in the 2000s. The advent of wide bandwidth internet allowed software companies to deliver their products online. They charge a monthly or annual fee to rent the software to customers on a continuous basis.
Customers could pay monthly and continuously receive software updates while providers were less concerned about maintenance, especially version control. Everyone wins.
The challenge for SaaS providers is that they bear the upfront sales and marketing costs. They plan to recover these upfront costs through repeat predictable sales, as shown in this graph:
A challenge for valuators occurs when young SaaS companies are in the trough and losing money prior to revenue growth. A new practice has evolved to evaluate SaaS operations in the trough. This practice is to determine whether the business is in fact healthy despite their current losses. Their performance across several parameters determines their long-run profitability which is then reflected in the SaaS revenue multiple.
Considerations specific to SaaS are:
- Customer Acquisition Costs (CAC) – total sales and marketing expenditures divided by the number of new customers – the cost of acquiring a customer
- Payback (CAC / MRR) – the number of months of revenue or gross margin required to recoup the cost of acquiring the customer
- Churn rate – the percentage of customers or revenue lost, per month or per annum
- Long Term Value (LTV) of a customer – Revenue * Gross Margin % / Churn rate)
Industry practice has developed these rules of thumb:
- LTV / CAC >3. LTV measures the average length of time that a customer generates gross margin dollars before leaving. e.g. if the ARR is $1200 and the gross margin is 80%, the annual gross margin dollars is 1200 * 0.8 = $960. If the annual churn rate is 20%, then the average lifetime of a customer is 1/(0.20) = 5 years. LTV = 960*5 = $4800. If the cost of customer acquisition is $1600, then LTV / CAC = 4800/1600 = 3. The company just meets this threshold.
- Payback < 12 months. Monthly gross margin = 960/12 = $80. CAC is $1600. Payback = 1600/80 = 20 months. The payback period is too long.
In terms of valuation, this company would be penalized with a lower revenue multiple because it takes longer to recoup the cost of acquiring customers. To lower the payback period, the company needs to reduce the acquisition costs or improve the gross margin. If the ARR could increase to $1500 and the CAC could decrease to $1200 then payback would be exactly 12 months.
In summation, there are 3 main methods to value technology companies using financial methodology:
- Discounted Cash Flow – almost never used
- EBITDA Multiple – good for companies with a track record of positive earnings
- Revenue Multiple – good for all technology companies which have begun sales, with specific parameters for SaaS companies.