As a former Wall St. analyst, it’s easy to spot really bad research reports marketed as “investment research”. The problem is that it’s not as easy for the non-investment layman to recognize bad investment research. As an entrepreneur, you know your own market niche, but what do you know of industries and market niches where you are not involved?
Ten years after Eliot Spitzer demanded changes from the investment banking industry, it would appear that very little has changed. That’s an opportunity lost. Among the most odious reports were those that were produced by the analyst at the firm which was the lead underwriter of the issuer of the Initial Public Offering (IPO). We recently received a report published by a very large bulge bracket investment bank that exhibits many of the worst characteristics of bad research.
Everyone likes a bullish report as it most directly impacts personal wealth through stock option programs. However, intellectual honesty requires that inflated balloons need to be identified, and discussed. We have often written up a company as a “Sell”, and we can tell you that it significantly impacted our relationships with company management and impacted our relationship with institutional accounts that owned the stock. The best book we’ve read on the perils of shorting a stock, and being right, was written by hedge fund manager David Einhorn called Fooling Some of the People All Of the Time.
The lessons for a startup company from this bad research are simple. When you put together an investor presentation, don’t do what the author of the bad research report is doing: Don’t misrepresent the truth and don’t spin the truth. It looks obvious, crass, and most importantly, investors can see through the crapola. Very frequently, you will take a meeting with a VC where you are educating them about your space. Since they don’t know anything about it, they will ask other VCs who do know. When the truth comes out, your opportunity with that VC is over.
Here is a small sampling of the items from the bad “research” we recently received.
We will keep the name of the issuer and the lead underwriter of this “research” confidential. We don’t have a short position in the name, but we are evaluating the best time to short the stock. The best time will probably occur sometime over the next 3 months.
First, an investment research report is supposed to have a section devoted to analyzing the competition, and the report will typically fit the subject into a 2-D competitive landscape. In a “Buy” recommendation report, you “expect” that the subject will be favorably reviewed in comparison to the competition. However, when the competition is not reviewed, AT ALL, one should be suspicious. When the subject is positioned at the top right of the competitive landscape chart, and positioned equally on the functionality scale against some of the largest software companies on the planet – one should be suspicious.
Second, when the marketing pitch of the subject is the ONLY information presented in this “independent” “research” report – one should be very suspicious. Not only does it look bad, it looks like the work of an inexperienced amateur. When you know that the analyst is not an inexperienced amateur, but is an experienced analyst earning $1mm per year, then there is really very little room to go on the ethics spectrum.
Third, when the word “disruptive” is used in reference to a software market niche that is almost 20 years old, one should be suspicious. Making the job easier and more productive is the goal of well-designed software. This is not disruptive and revolutionary.
Fourth, when the marketing message of the company uses key words that are also used by its competitors; you can no longer describe the company’s technology as unique. In fact, if a competitive review had been accomplished, the analyst would probably have noticed those marketing key words were being used by the competitors. Alas, he didn’t.
Fifth, as a Canadian, we’re all about hockey sticks. Unfortunately, hockey sticks and revenue or earnings profiles don’t make for a happy ending. The revenue and earnings profile of any company is typically monotonically linear; lowest in Q1, and strongest in Q4. Non-SaaS enterprise software companies follow this trend very nicely. In fact, everyone knows that the bulk of the revenues typically occur in the last two weeks of any quarter. We also know that every company tries to smooth out the transactions in a quarter by attempting to close deals earlier in the quarter. However, once a software company goes public, every customer understands that their large transaction, at the margin, could represent whether the company does really well in a quarter, just makes the quarter, or completely misses the quarter. Although this is less true for a very large company like Oracle with multiple products, multiple divisions, and multiple groups, it is true of a one product company – like the subject company.
Therefore, when you see the revenue/earnings profile of a non-SaaS enterprise software company look relatively flat over Q1, Q2, and Q3, and then spike up into Q4, so that Q4 is equal to the sum of the other quarters – times 2 or 3, then one should be suspicious. In other words, when the expected revenue in Q4 is double the amount in Q3, but the earnings in Q4 is 7x the earnings in Q3, you should be suspicious. Moreover, we don’t know of ANY enterprise software company that can produce this kind of result – consistently over many years. If you see this, you should be suspicious.
Sixth, we have it on good authority that the subject company reported a loss in Q4 of 2008. Imagine our surprise when we saw the research report that showed a substantial positive Q4FY08 earning margin – meaning profit. As my French colleagues used to say, “Quelle surprise!”
Seventh, we have it on good authority that the CEO of this software company was determined to get a $1billion valuation at the IPO. Software companies that take on a $1b valuation target as an end unto itself have a very, very bad history. It’s similar to a startup thinking that if you get funded you’ve achieved the goal. It almost always leads to self-destructive behavior and extremely bad executive management decision making. We can provide numerous examples in the technology world.
Eighth, we have it on good authority that the average sale by the company to a client is 50% higher than reported in the research. Company management may be setting the expectations bar low, as does another well-known tech company named after a fruit. In any enterprise software company, the much larger follow-on sales occur after the initial sale. However, when the service and support organization only does “service and support”, rather than additional product sales, like any company should be doing, then it’s very difficult to generate follow-on sales at the same customer. Note to Startup: ensure that every individual team member in your service and support org is always selling. Live the letters: ABS – Always Be Selling. Compensate the sales and service team on finding new sales opportunities. Only part of the job of the salesperson is to find new opportunities. The other part is to close on those opportunities. The closing part is far more important than the finding part since the finding part should be generated by the marketing dept. (I know, we’ve hit a nerve, so let’s discuss this at a later date).
Ninth, doubling your sales force does NOT mean that you will double your sales. Moreover, if you begin to add sales people in Q1, then it will take them a minimum of 6 months to ramp up and begin selling. After 12 months, the rule of thumb is that 25% of those new sales people will not be able to meet quota, so they will be gone or close to being gone – which is why you found them in the first place – they left their previous company because they saw the writing on the wall. The next 50% are a toss up – some ramping up while others are waning. The top 25% are getting the job done. In other words, doubling your sales force does NOT mean that you can double sales.
Tenth, a small IPO means a small float. The float is the number of shares available for sale on any given day. The float does not include stock held by insiders, or those groups holding in excess of 5 percent. We’ll use some made up numbers as a heuristic device. If the total number of shares outstanding after the IPO is 100 million, and the company sold 10 million shares in the IPO, then most of that stock has been placed in institutional accounts. (The best customers get the “best” stock). If any institutional owner was allocated 100,000 shares in the IPO, that stock is also removed from the effective float since the reason that they got 100,000 shares was because they agreed to hold the stock for at least 30-60 days. Therefore, if the total stock traded on any day is 100,000 shares, then the stock has no liquidity because there is no float. Institutional accounts trade stock in blocks of 10,000 shares or more. In order to build a position of 100,000 shares, the institutional account trader must buy blocks of 10,000 shares over the next 10 trading days, and must try to do so without moving the market. This is really hard to do. As an analyst, valuation metrics take over – but that is another lesson.
Bonus. If there is ANY sign that the revenue of sales growth is slowing – then watch out. If the analyst at an institutional account finds that competition actually does exist, that the software technology is not disruptive, that key marketing words are not unique, but also used by competitors, and that the revenue/earnings profile looks really hard to achieve, then it becomes more likely that institutional accounts will try to shed that stock, and lock in a profit. If all of those institutional accounts try to unload the stock at the same time, then the lack of a float predicts that the fire on the Hindenburg will look like a tea party at Satan’s picnic. As one of our friends has put it, “IT WILL BE A DISASTER.”
As a startup, you want to generate excitement about your product/company to prospective investors. But, as Austin Powers would say:”Behave Yourself!”