Now You Are Talking: Can a Company Make Money with Enterprise Search?

January 22, 2013

I have better things to do that capture my immediate thoughts about “Inside H-P’s Missed Chance to Avoid a Disastrous Deal.” You can find the article in a dead tree version of the Wall Street Journal on page 1 with a jump to Page 16, where the “would not comment” phrase appears with alarming frequency.

The most interesting point in the write up is the quote, allegedly crafted by a Hewlett Packard Big Dog:

Now you’re talking.

Like much of the chatter about search, content processing, and Big Data analytics, on the surface these information retrieval software companies are like Kentucky Derby hopefuls on a crisp spring morning. The big pay day is two minutes away. How can the sleek, groomed, documented thoroughbreds lose?

The reality, documented in the Wall Street Journal, is that some companies with sure fire winning strategies can win. Now you’re talking.

How did HP get itself into the headline making situation? How can smart folks spend so much money, reverse course, and appear to be so scattered? Beats me.

I have, however, seen this before. As I read the Wall Street Journal’s story, I wrote down some thoughts in the margin of the dead tree instance of the story at the breakfast table.


A happy quack to

Herewith are my notes to myself:

First, name one search vendor in the period from 1970 to the present which has generated more than $1 billion in revenue from search. Acquisitions like IBM’s purchase of iPhrase (er, what happened to that outfit), Vivisimo (now a Big Data company!), or SPSS’s Clementine (ah, you don’t know Clementine. Shame on you.) Don’t toss Google and its search appliance into the mix. Google only hints at the great success of the product. When was the last time you searched using a Google Search Appliance?

Second, didn’t Microsoft purchase Fast Search & Transfer for $1.2 billion in January 2008. How is that working out? The legions of search add in vendors for SharePoint are busy, but the core system has become a little bit like dear old Clementine. Fast Search was the subject of a couple of probes, but the big question which has not yet been answered as far as I know is, “How much revenue did Fast Search generate versus how much revenue Fast Search reported?” I heard that the revenues were, to some degree, inflated. I thought search was a sure fire way to make money.

Third, after more than a decade of top down marketing, why did Endeca need cash infusions from Intel and SAP venture units? How much did Oracle pay for Endeca? Some azure chip consultants have described Endeca as the leading vendor of enterprise search. Endeca added ecommerce and business intelligence to its line up of products. What was the firm’s revenue at the time of its sale to Oracle? I estimated about $150 million.

Fourth, Dassault, the company with the “system”, bought Exalead. What has happened to this promising technology? Is Exalead now a $200 million a year revenue producer for the prestigious French engineering firm? Perhaps the “system” has been so successful that Exalead is now infused into Dassault clients throughout the world? On the other hand, wouldn’t a solution with this type of impact make headlines every week even in the US. Is it more difficult to to cultivate information retrieval revenues than other types of software revenue? The good news is that Dassault paid a reasonable price for Exalead, avoiding the Autonomy, Endeca, and Fast Search purchase prices.

These examples reminded me that even if my estimates are wide of the mark by 20 or 30 percent, how could any company generate the astounding growth required to pay the $11 billion acquisition cost, invest in search technology, and market a product which is pretty much available for free as open source software today? Answer: Long shot. Exercise that horse and make sure you have what it takes to pay the jockey, the stable hands, the vet, and the transportation costs. Without that cash cushion, a Derby hopeful will put a person in a financial hole. Similar to search dreams of big acquirers? Yep. Maybe identical?

Two different points occurred to me.

On one hand, search and its bandwagon riders like Big Data analytics must seems to be a combination of the Klondike’s mother load and a must-have function no matter what a professional does for a living. The reality is that of the 65 search and related vendors I have written about in my books and confidential reports, only three managed to break the $100 million in search revenue ceiling. The companies were Autonomy, Endeca, and Fast Search. Of the three, only Endeca emerged relatively unscathed from the process. The other 62 companies either went out of business (Convera, Delphes, Entopia) or stalled at revenues in the millions of dollar. If one totals the investments in these 65 firms to generate their revenues, search is not a break even investment. Companies like Attivio and Coveo have captured tens of millions of venture dollars. Those investors want a return. What are the odds that these companies can generate more revenues than Autonomy? Interesting question.

On the other hand, search and its child disciplines remain the most complex of modern computing problems. Whether it is voice to text to search and then to predictive analytics for voice call intercepts or just figuring out what Buffy and Trent in the sales department need to understand a new competitor, software is just not up to the task. That means that money pumped into promising companies will pay big dividends. Now the logic may make sense to an MBA, but I have spent more than 35 years explaining that progress in search is tough to achieve, expensive to support, and disappointing to most system users. The notion that a big company could buy software that is essentially customized to each customer’s use cases (notice the plural of “cases”) and make big money is a characteristic of many firms and managers. The reality is that even governments lack the money to make search work.

Don’t get me wrong.

There are small firms which because they focus on quite specific problems can deliver value to a licensee. However, big money assumes that search technology will be a universal, easily applied to many situations. Even Google, with its paid search model, is now facing innovation challenges. With lots of smart people, Google is hiring the aging wizards of search in an attempt to find something that works better than the voting methods in use today.

What do my jottings suggest? Search is a tough business. Assumptions about how much money one can make from search in an era of open source options and cost cutting need to be looked at in a different way. The current approach, as the Wall Street Journal write up makes clear, is not working particularly well. Does this search revenue track record suggest that the azure chip consultants, former middle school teachers, and real journalists miss the larger message of search, content processing, and Big Data analytics? My tentative answer is, “Yep.”

Stephen E Arnold, January 22, 2013


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