The Key to Millions: Enterprise Search?

November 11, 2019

I thought the world was crazier than ever when enterprise search became the focal point of a multi-billion dollar deal and a multi-year lawsuit. The open source search movement picked up steam as companies shifted their attention from proprietary search and retrieval solutions to those maintained by a “community.” Search became a utility which many information technology professionals found a Bermuda Triangle for careers.

Why?

Our research prior to the publication of the three volumes of the Enterprise Search Report I wrote and our subsequent work on next generation search solutions revealed these problems:

  1. Enterprise search implies one size fits all. Information retrieval needs vary by business unit, department, and individuals. When one pokes around a large organization, one finds numerous search and information access systems. One size? Nope.
  2. Users look for information in the enterprise search system and cannot locate it. The reasons vary, but the universal gripe is, “I can’t locate the document I just saved.” The notion of real time is not one that fits into more organization’s information infrastructure. Cost is one big reason. What looks good in a demo does not work in the “real world” of a company.
  3. Silos. The implications of “enterprise” suggest that a significant amount of information will be available to a user of the search system. Nothing could be further from the reality. Legal keeps some documents under lock and key. Personnel? The same approach. Research? No data goes out of the lab or the researcher’s workstation. On and on.
  4. Changes that are not captured. The top sales professional changes his presentation right before giving a talk to seal a big deal. The changes are not indexed because the sales professional has to do the contract. Missing info? Yes.
  5. Untracked digital information. Enterprise search has not been either quick nor adept at handling social media posts (authorized or unauthorized), interviews, videos produced in lieu of a written report, and similar information objects. Try to find key facts from these content collections. Give up yet.

I could extend this list, but I don’t have the energy. Few are interested in what caused Entopia to go out of business. No one I have spoken with in the last five years cares about why Fast Search & Transfer self destructed. No one cares.

I read “Want to Earn Millions? Launch an AI Based Enterprise Search Startup.” That’s a path to fame and riches. The write up states:

Enterprise search engines based on artificial intelligence systems are taking off fast. Cognitive search systems using NLP can include structured data contained in databases and even nontraditional enterprise information like pictures, video, sound, and machine information, for example, from the internet of things (IoT) gadgets, to bring contextual results in the actual business context.

Sounds good. How about this?

For startups and venture investing, the trend is clear. One prime example of this trend is the world’s leading space agency- NASA has enormous data ever since it was created in 1958. Now, the agency is working to make its data increasingly accessible for rocket designers and researchers. It is redesigning search and analytics abilities utilizing AI and natural language processing (NLP) systems created by a company known as Sinequa which is collaborating with the agency to deploy a worldwide knowledge management ability.

Amazing. Technologies like RECON’s which NASA helped move forward because engineers could not locate key documents is looking at technology which has wobbled from search to intelligence and back again.

A quick reality check, gentle reader, please.

One can download open source search and retrieval software and get decent results. But there are firms which have goosed the “money” in enterprise search to astronomical levels:

  • Algolia, $100 million
  • Coveo, $200 million
  • LucidWorks, $150 million
  • ThoughtSpot, $248 million.

Now let’s think about Autonomy. At its height, the company reported revenues of about $800 million. HP paid $10.3 billion. After a short period of time, HP realized its massive sales and marketing system could not generate enough new sales and sustainable revenue to keep the Autonomy business an alleged winner.

How will these companies pitching enterprise search generate sufficient revenue to pay back their investors, fund research and development, add filters and other components needed to deal with today’s content flows, and support their existing systems as licensees try to make search work like investigative software?

The answer is, “The odds are quite unappealing.”

  • Enterprise search has been available for half a century with some of the old school systems still available from OpenText in the guise of BRS Search
  • Dissatisfaction with enterprise search systems generally runs about 50 to 70 percent in most organizations with such a system
  • Costs of keeping an enterprise search and retrieval system continue to creep up despite the advent of managed services like those available from Amazon and others

Where are the customers?

That’s the question the article ignores.

Customers are likely to be just as tough to convince to use an enterprise solution as they have been for decades.

Net net: Enterprise search may not be the spring chicken the write up describes. Enterprise search has a history. And history is about to repeat itself. When the Autonomy matter is resolved, there may be be a new search drama to follow.

Keep in mind that Google couldn’t make enterprise search work. But these cash stuffed outfits can? Maybe? Well, probably not.

Stephen E Arnold, November 11, 2019

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