A sharp entrepreneur can solve for just about anything with enough time and money. But how much time and money is it worth? Some of the best qualities of an entrepreneur (relentless optimism, resiliency, and determination) can also cloud judgment on effort of implementation and execution. This makes it challenging for the entrepreneur and prospective investors to sufficiently evaluate the technology and the supporting ecosystem required to realize the technology’s potential. Here are NINE questions to ask first before diving into a technology.

1. Are you inventing something completely novel, or piecing together a proven technology in a new way?

First of all, most technologies are not unique. Those rare and disruptive technologies may come with great reward but also great risk. One of these risks and inevitable challenges is timing; the concept of right tech, wrong timing.

Start with REX to get the health vitals of the technology and more information about the technology landscape. Our natural language processing and machine learning technology filters through unstructured data and returns the most relevant information. All datasets are broken into major categories, representing the various phases in the technology’s product lifecycle: research funding, patent filings, science and research news, technology news, and business and investment news. Datasets are weighted and time is relevant. What does this mean? Patents that were issued 30 years ago, are weighted less. Trends over time within each category capture the momentum of the technology and allow users to make general assumptions about the position in the technology lifecycle. For instance, a recent and rapid increase in grant funding and science and research news could indicate a very early stage opportunity. Using variables such as the volume of documents within each category and trends over time, our algorithm will score your search parameter between 0-99 for uniqueness, commercial viability, license potential, patent potential, and rising competitive risk.

2. Is the technology patentable? Is it infringing on other patents?

Patents can be the foundation of a business’ value. And in many cases can help build stronger opposition to any new competing technologies or companies. However, patents are not the end all be all. What is more important than a good patent portfolio is the ability to execute and effectively leverage the intellectual property. Either way, you must familiarize yourself with patents that might be overlapping with your technology in any way.

3. What is the stage of the technology? Do you have a proven or established technology in the desired market?

There is a learning curve for introducing new technologies that can prolong the adoption rate significantly—keep this in mind.
4. Are there potential obsoleting technologies on the horizon?
To best defend against disruptive challengers you must pay attention to competitive advantages of the whole product, not just technical features. The ecosystem of the technology and the peripheral market can play a critical role in the success of new technologies–just consider the story of Betamax. How dependent is the technology on other innovations? Although HDTV was invented in the early 80’s it took nearly 30 years for supporting elements (from high-def cameras to broadcast standards) to emerge and enable HDTV technology.
You can start to gather a general idea of the technology landscape by running a search on your technology. Leverage artificial intelligence to make better innovation decisions. Our content engineering platform continuously crawls and ingests vast amounts of unstructured data that are used by our artificial intelligence based algorithms.

5. Are others doing something similar?

It’s not necessarily a good OR bad thing that something is completely unique and disruptive. If you are risk averse, you may find it reassuring that there have been other players and other attempts. On the other hand, if a technology market is completely saturated, it may be a good time to reevaluate commercial viability for new end markets of the technology.

6. Do you have domain expertise?

…Or can you acquire it?

7. What is the addressable market?

Who are the consumers? What is the underlying technology? What is the current industry application?

The best way to answer these questions is to review the top relevant documents in that sector. How recent are the publications?
When you run a search on REX you the “composition” of your search input by technology sectors.

Breaking into a new market/application of a technology can be exciting and risky. On one hand you have a solid/proven technology in an unproven market. Plan on increased rate of adoption for new markets that may require changes in behaviors and education.

8. What is the size of the addressable market?

9. What is the sentiment or attitude toward of the technology?

We can’t discredit the importance of qualitative evaluation of a technology. Sentiment analysis. Expert opinion.

In our attempt to include these qualitative measures in our algorithm, we measure the volume, relevancy and trends over time in the “Technology News” category. Technology News represents a unique vertical of datasets that are tech and science publications for non-experts. Datasets in this vertical are most often supported by advertising so the publishers’ goal is to deliver content that is going to drive the most traffic (and revenues). In this sense, Technology News acts as a barometer of public interest and opinion of technology topics. We are able to draw unique conclusions about the interest and attitude of the technology based on overall volume and publishing trends over time.

It’s all about risk versus reward. Not every opportunity is going to pay off overnight (or at all). You don’t have to be an expert, you just have to ask the questions.

Venture capital is the oxygen almost all startup companies need to survive the “Valley of Death”.  The price paid by the entrepreneur for this essential ingredient to his fledgling company’s success is, like the price in any arms-length transaction, the result of a negotiation based on facts, emotions, and circumstances unique to each negotiation.  Is the price paid by the entrepreneur really based on the “value” of his project?  Finance professors in academia are likely to argue that the “value” of a startup project can be determined empirically, if only the necessary information can be gathered.   Then does “value” exist apart from a market-determined price derived from a specific negotiation?

 

In this post I will cover briefly the techniques academics would use to calculate what they might call true value, and in the process illuminate the practical problems that make these tools only marginally useful to venture capital investors.  This realization leads to my central point: what some people call “value” is more properly a “price” set by a marketplace under a specific set of conditions and circumstances.  Very few things have true intrinsic “value” that can be established so precisely that there would be no disagreements among participants in an open marketplace so that there would be complete agreement on the price at which a transaction could be done.  Even the broadest markets for common commodities with complete information sometimes trade with a wide spread between bid and offering prices.

 

So, the search for a true value for a startup company is probably a fool’s errand.  What needs to be developed is a price at which investors are willing to risk capital, and at which an entrepreneur is willing to share the rewards of his great idea with those investors.  Whether or not this price is anywhere near true value (even if such a thing could be determined) is completely irrelevant.  If there is no agreement on price, there is no investment, and thus, no new company.  This leads to my personal opinion of the bottom line of new venture pricing that I will flesh-out in more detail later:

 

Venture Capital Pricing =       60% Negotiation

20% Personal Evaluation of the entrepreneur

20% Numerical Analysis

 

Almost all of the factors in venture pricing are based on experience, intuition, domain knowledge, and unique circumstances.  Most are qualitative assessments.  The two parties to the negotiation, the investor and the entrepreneur, often come into the discussions with very different levels of bargaining power.  Marketplace conditions will very likely change markedly both during and after discussions.  But, in order for a deal to be struck, both sides will need to be comfortable that whatever price is set will allow each to meet his financial objectives.  That is the art of the deal.

 

The Science of Establishing True Value: Classical Finance Theory

 

One of the most accepted facts of investment finance is that the value of an asset is the sum of all future cash flows from that asset adjusted for the time value of money and the risks associated with those uncertain future cash flows.  In math terminology:

 

Where:

 

V = Value of an Asset or Company

n = Year

CF_n = The amount of cash flow available to equity owners in Year n

R = Discount rate

8  = Forever

 

In order to use this formula to value a startup, we would need to make the following estimates:

• Annual earnings available to equity holders for every year that the new company exists, forever ….
• If the company is acquired at some point in the future, the acquisition price
• Market interest rates for each year in the future that the company exists
• Some rational method for adjusting for the following risks:
  • Estimation risk for all those future numbers
  • The risk of company failure; timing of failure
  • Dilution risks from required future capital infusions

 

Right …..

 

I won’t go through all the problems associated with coming up with reasonable estimates of these numbers.  Most would agree that forecasting even 3 to 5 years into the future at this detail level is extremely difficult, even for an established company, but for a startup?  Just the process of developing these estimates might actually lower the confidence of a potential investor with any humility.  If you want more details on the advantages and disadvantages of this approach, refer to this, this, or this.

 

The Science of Establishing True Value: Practical Approximations

 

Recognizing the futility of deriving the necessary estimates to apply the classical finance valuation tools, some investors fall back to what is often referred to as the “comparable multiples approach”.  This approach takes advantage of the fact that capital markets exist to allow investors to trade securities, and that the prices set in these free markets are the best approximation of true value at any point in time.  This means that simple multiples (ratios) such as price/earnings or revenue/price are available for a wide variety of publicly traded companies.  All one needs to do to value a non-public company is to find a comparable publicly traded company, and then apply the public company multiples to the earnings or revenues of the non-public company to derive the estimate of the non-public company price.   Practitioners look for young public companies in the same industry, with similar capital structures, as the startups they are trying to value.

 

Of course, the problems with this approach in valuing startup companies should be obvious.  Startups are unlike publicly traded companies in many important ways: they are much more fragile in that they typically rely on a single product and a small management team, they are often breaking new technological or business model ground, and are far less liquid than public companies.  For these reasons alone, despite the fact that this approach appears far more reasonable than the classical finance valuation approach, it will, at best, provide only a gross approximation of the true value, or even the appropriate market price, of a startup company.

 

So, where does this leave the valuation issue, art or science?  I think it’s clear that almost all company valuations, and especially valuations of startups, are solidly in the art, or more correctly, negotiation camp.  But, investors and company owners can’t just pull numbers out of thin air and hope to reach some sort of agreement on price, so valuation theory must play a role, albeit as a check on reality rather than as the definitive method of reaching agreement.  Practitioners in venture capital, and to a lesser extent private equity, have developed techniques that bridge the art versus science valuation gap to assist the negotiations between themselves and entrepreneurs to set startup company valuations.

 

 Practical Valuation: The Venture Capital Model

 

It is worth reiterating a central concept at the heart of the so-called venture capital valuation model: the “value” of a startup company is nothing more or less than the “price” agreed by the entrepreneur and the investor team.  The price is decided through negotiations educated by valuation parameters and the experience of the investor team.  The venture capital model valuation process has four essential parts:

 

1. Work with the entrepreneur to develop reasonable financial projections for the next 3 to 5 years or until expected profitability. These projections focus on the essential ingredients for success for the particular company being evaluated.  In some cases, the essential factors will be market penetration and share, in other cases the factors might be profit margins or cash burn required to sustain the expected growth.
2. The investor team then translates the numbers from the financial business plan in step 1 into an expected “market value” that could occur from a public offering or a trade sale of the company at the point of profitability estimated in step 1. This translation typically uses the more simplistic comparable multiples approach described above rather than a full-blown discounted cash flow model.  There is also typically much back and forth between the entrepreneur and investor teams about this projected value, with the entrepreneur usually trying to demonstrate why the investor numbers are too low.
3. Throughout steps 1 and 2, the investor team assesses the quality of the entrepreneur team to determine if additional talent will need to be added immediately at some additional expense, and how much help and guidance will be required from the investor. An important purpose of this assessment is to gauge a key element of the overall risk to the investment.  It is only fair to point out that, at some level, this becomes a binary assessment.  That is, there is an absolute minimum level of perceived entrepreneur team quality below which no deal can be done no matter how attractive the project.  This level is, obviously, different for each investor team.  Some investors may try to work with the entrepreneur to shore up the team; others will just walk away.  In any event, it is in the investor’s best interests to get to this assessment as quickly as possible so that there is no wasted team time on a project that just is not going to get financed.
4. The final step is to translate the future “maybe” value of the company to a price the investor is willing to pay today in the form of a capital investment. Mathematically, this is a simple process:

 

Where:

CV₀ = Today’s Value

FV_n = Expected future value at year n

n = Year at which future value is calculated

R = Investor’s required annual rate of return

 

Perhaps the most important variable in this formula is R, the required return to the investor to finance the project.  The investor’s required return is a complex function of expected time to payout, confidence in the numbers from the financial business plan, confidence in the entrepreneur team, competition from other investor teams for the deal, the negotiating skills of the entrepreneur, general capital market conditions, and often, factors unique to the investor team such as how performance has tracked on other investments the team has made from the fund that would be making this investment.

 

Typically, an investor team would work from a basic pricing matrix similar to the one below as a starting point (this matrix is for example only and may not be indicative of current market conditions) and then make adjustments based on the factors listed above:

 

 

Defining each column in the matrix:

 

State of Company Development:  As a practical way of consolidating several risk factors, investors typically categorize the development level of an investment prospect company.  In this example, the diagram below illustrates how a venture investor might define a set of such categories:

(R) Required Annual Rate of Return: This is the discount rate at which the future expected value of the startup company will be discounted to compensate for the time value of money and for the risks associated with the investment, including the possibility of total loss, to determine the price the entrepreneur pays today to obtain the capital he needs to build the company.  This is the annual return the investor would receive if the future worked out exactly as planned.  In fact, that would be a rare event.  Some investments do better than expected; some do far worse.  The returns venture investors actually have received, on average, are far lower than the numbers shown in the table.  Total losses do occur, and investors must assume that they will.  So, they naturally build a bit of a cushion into the prices they pay for investments to make up for the disappointments.   On the other hand, the entrepreneur tries to keep the cost of capital as low as possible so that he can enjoy the rewards of his idea.  This is the area where give and take (typically hard negotiations) occurs to get the point where both sides are satisfied with the price to be paid.  The numbers in this table are definitely not static, either across time or across venture investors.  They are subject to a wide range of situations and market conditions, and are very difficult to “observe” without actually being in a negotiation.

 

Implied MOIC:  MOIC is an abbreviation for “Multiple of Invested Capital”, which is simply the total value of an investment at some future date divided by the original investment amount.  This return measure is preferred by some investors because it captures the effects of both annual return and the time period over which the return was earned.  An investment capable of delivering a 100% annual return over 5 years (MOIC = 32.0 times) would obviously be preferable to an investment capable of delivering the same 100% annual return, but only for 3 years, not 5 (MOIC = 8.0 times).  Since 100% annual return investments are very rare, almost every investor would prefer the 5 year investment to the 3 year investment.  The MOIC columns in the matrix translate the annual return expectations to MOIC expectations over a 3 year and a 5 year time horizon.

 

With all the pieces in place for a Venture Capital Method Valuation, take a look at the example below:

 

Characteristics:

• “Pre-seed” development level company
• Expect to make a trade sale (through acquisition) of the company when it becomes profitable in 3 years
• Confidence level in projections is average
• Entrepreneur team is good, but not great, and will require some hands-on assistance from the venture team

 

With these assumptions, the investor team is likely to require pricing so that it can achieve an annual return at the upper end of the return range, for a “pre-seed” company, say 70%, leading to the valuation for today of $61 million as shown below. This is known as the “Pre Money Valuation”.

 

Note that if the entrepreneur is able to convince the investor to accept a mid-range required return for this investment through effective negotiations, the today valuation would increase to more than $73 million.

 

The final calculations to be done are “Post Money Valuation” and the amount of equity the entrepreneur must give up to raise various levels of venture financing:

 

Post Money Valuation = Pre Money Valuation + Capital Provided by Investor

 

% of Equity Acquired by Investor = Capital Provided by Investor / Post Money Valuation

 

The table below provides examples of these measures for various levels of venture investment:

 

 

This table clearly indicates that while it is very important for the entrepreneur to negotiate the best deal he can with the investor regarding valuation, it is far more important that the entrepreneur limit the amount of capital he accepts to the amount he actually needs to reach the three-year milestone.  Frugality here will pay off handsomely three years down the road!

 

One of the most important tools in REX^tm to accelerate the development of new products and companies from scientific research is the Launch Money^tmportal created to help entrepreneurs raise pre-seed investment funds for their projects.   Within Launch Money^tm, there are guidelines to assist entrepreneurs in setting the prices at which equity shares can be offered to investors.  These guidelines are based on the Venture Capital Model described above.  However, since entrepreneurs using our Launch Money^tm portal will not be negotiating one on one with an experienced venture investor, but will instead be posting offering prices for investors to take or leave, we will provide current readings of the marketplace to assist entrepreneurs much like the “Required Rate of Return” matrix shown above.  By providing this information to entrepreneurs we hope to assure investors that the offering prices on Launch Money^tm are fair and reflective of current market conditions.

 

The most widely cited problem for startup failure is lack of market need.  It’s easy to blame the market.  What this more often means is that the founders built a product to their grand vision was not in alignment with a validated market need, or there was a disconnect between the product and the addressable market.

Growing a startup is an iterative process, and it’s my observation that most are almost certain to fail in their first attempt.  I am often reminded of a quotation by Thomas Edison after many unsuccessful attempts to create an incandescent light bulb “I have not failed.  I’ve just found 10,000 ways that won’t work”.

The sentiment is similar among VC’s.  Experienced venture capitalists will point out, you have to kiss a lot of frogs to find a prince.

(source: https://list25.com/25-most-useless-inventions-ever/)

Ultimately finding out what can’t work will sooner lead you to finding out what can work.   The question becomes, how can we fail (and hopefully ultimately succeed) as quickly as possible with the least investment of time and money?

You might have the best idea in the world, but you need to first consider whether there’s a market. Here are a couple of things to consider when determining whether your great idea is feasible:

 

1. A strong understanding of customer problems and validation of the idea will help clarify the addressable markets (or potential markets). Just because the solution to a problem is interesting to you, does not mean it is driven by a validated market need.  

(source: http://famepace.com/weird-silly-inventions-32-photos/weird-and-silly-inventions-3/)

 

One of the main causes of failure is untested assumptions.   Bottom line: a full understanding of the problems is crucial in the discovery of potential target markets.

 

 

2. Do your homework. Start with Google.  Interview prospective users/customers.   Research competing IP and solutions. A patent attorney can perform a patent search to make sure there are no existing patents or inventions similar to your own. Or let REX help you develop a data driven strategy.  Search on existing patent number(s), blocks of text, keywords, URLs or PDF documents to find semantically similar academic literature, research grants, and patents, and IP within minutes.

For disruptive technologies and companies, it can be very difficult to identify an addressable market in the first place.  Perhaps you have not (and should not) ruled out the possibility of new applications/markets for an existing technology.   The REX radar chart will dynamically analyze and build a natural clustering of content based on technology taxonomy.  Here is a sample rendering for a specific technology in the cryptocurrency space that is broken down into three major categories: 25% electronic sciences, 24% computing sciences, 17% energy sciences.  Clicking on any of these major categories on the left side will display a radar chart that is dynamically organized into sub-categories.  Color gradients indicate relevancy for each of the segments with in a sub-category.  You may click on any segment in the radar chart to drill down into correlated and/or competing technologies (semantically similar documents) in that technology space.

Identify a technology in a highly developed form, and see where there might be an opportunity to reposition for new applications (in new sectors and new markets).   So say you have two technologies, a therapeutic and a very specific type of delivery agent that on their own may have a commercialization gap, but together they are much more viable.   How can research be “combined” to create a more compelling and viable commercialization opportunity?   We want to improve the ability to take great ideas to market.  We can help you with this step.

 

One final thing to note is that validating a problem is one thing, identifying a solution that people will pay for (and determining how much?) is another.  Research where people are investing their money in the orbit of your technology/IP.  Take cues from the best and brightest innovators on REX and track what types of projects are listed on the GetFunded portal.   What types of projects are getting launched?  Who is investing now?  How much?

 

And don’t forget: Kiss a lot of frogs, but never date a frog.

If you’re an entrepreneur in search of your “prince”, click here to develop your data-driven strategy.