Venture Outcome: The Search and Content Processing Angle
August 14, 2014
I suggest you read “Venture Outcomes Are Even More Skewed Than You Think.” The write up contains several factoids. I highlighted one and added a couple of exclamation points. I suggest you print out the article, grab a writing instrument, and do your own filtering.
The main point of the write up is buried in the paragraph that begins “This really underscores the challenge of crating a venture portfolio that produces reasonable returns.” The factoid I honored with exclamation points is:
In my hypothetical $100M fund with 20 investments, the total number of financings producing a return above 5x was 0.8 – producing almost $100M of proceeds. My theoretical fund actually didn’t find their purple unicorn, they found 4/5ths of that company. If they had missed it, they would have failed to return capital after fees. Even if we doubled the number of portfolio companies in the hypothetical portfolio, a full quarter of the fund’s return comes from the roughly ½ of a company they invested in that generated 10x or above. Had they missed it, they would have produced a return that roughly approximated investing in bonds – not the kind of risk adjusted return they or their investors were looking for.
I know this is a hypothetical. Assume that the analysis is off by plus or minimum 10 percent. What do we get? Lousy returns; that is, returns comparable to dumping cash into bonds. I think about the banking and venture firm meetings in which I have participated. I cannot recall any of the smiling MBAs considering that their best ideas could perform on a par with bonds. My hunch is that the people who pushed money into venture funds and bank VP-inspired investments are not thinking bond-type yield.
If the number is accurate, I wonder if those folks who have pumped tens of millions of dollars into outfits promising a money ball from search and content processing will get their money back. Forget an upside. Break even may be tough. Search and content processing makes headlines like this one every day:
To get similar results, navigate to Google News and enter the query Autonomy HP or Autonomy CFO.
The second item I circled with my pink marker was a diagram:
The important part is the small number of “winners” graphically embodied in the miniscule 0.4% column. This is a broad swath of investments. For search and content processing, the payoffs have to be measured in what money flows via revenues or a sell off like Fast Search to Microsoft, Exalead to Dassault, or Autonomy to HP. The number of folks who made big bucks and are really happy may be modest. In fact, judging from the legal hassles with regard to Fast Search and the recent HP Autonomy headlines, even those who were MBA winners may have headaches. Information retrieval seems to deliver a number of headaches for stakeholders.
The third item is the factoid that makes clear the failure rate of start ups. Search and content processing poses similar challenges. There is a twist. Once a search and content processing sells to a larger firm, how many have become major money pumps to the acquiring companies? The question is very difficult to answer. The absence of information tells me that there are not too many feel good stories to tell. The pleas on LinkedIn enterprise search discussion threads for positive case studies about search are easy to ignore. Good news with regard to search and content processing is not sloshing around the Big Data bucket in which we exist.
How long with companies that have been in business for many years promising a money ball from search be able to survive? How long will the old soft shoe about search and content processing open checkbooks? How many years will it take some information retrieval companies to replace red ink with the blank ink of hefty after tax profits? How long will it take those seeking answers to information retrieval problems to wake up to the fact that consultant saucisson, Star Trek fantasies, and marketing hyperbole are unlikely to deliver a Disneyland-like “win”?
The data set for the Seth Levine write up is large enough to warrant a tentative answer, “Probably never.” Search and content processing are different. The algorithms and methods are decades old. Talk does not change what can be accomplished with affordable computational resources. Pumping money into search, therefore, may be painful when the actual financial data are reviewed by investors and stakeholders.
Why aren’t their abundant “good news” cases for search and content processing? There just aren’t that many. Think a power curve of implementation successes. There are more examples of search going off the rails than home runs. This is surprising when so many profess to be experts in search and so much money has been injected into information retrieval start ups. The business strategy of search and content processing companies may be raising money. Any other work may be of little interest.
Stephen E Arnold, August 14, 2014
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