December 15, 2014
When enterprise search vendors say their systems index “all” of the information an organization has, the statement is silly, if not downright crazy. A good example of why one does not index “all” information on an organization’s computers appears in “13 Revelations from the Sony Hack.” The next time a search vendor runs the “all” spiel, point them to this write up. In addition to salary information that alleges my former neightbor Jennifer Lawrence gets less dough than some others in her recent film, do I need to know a Sony employee has a drinking problem and nuked his liver? Search works if the content is vetted. That means someone has to do an information inventory and make some decisions about what gets indexed and who may view what. “All”—one more reason why enterprise search has found that open source solutions are “good enough” for many prospects.
Stephen E Arnold, December 15, 2014
December 9, 2014
The article titled To Bing and Beyond on IDM provides an interview with Dave Hawking, an award-winner in the field of information retrieval and currently a Partner Architect for Bing. In the somewhat lengthy interview, Hawking answers questions on his own history, his work at Bing, natural language search, Watson, and Enterprise Search, among other things. At one point he describes how he arrived in the field of information retrieval after studying computer science at the Australian National University, where he the first search engine he encountered was the library’s card catalogue. He says,
“I worked in a number of computer infrastructure support roles at ANU and by 1991 I was in charge of a couple of supercomputers…In order to do a good job of managing a large-scale parallel machine I thought I needed to write a parallel program so I built a kind of parallel grep… I wrote some papers about parallelising text retrieval on supercomputers but I pretty soon decided that text retrieval was more interesting.”
When asked about the challenges of Enterprise Search, Hawking went into detail about the complications that arise due to the “diversity of repositories” as well as issues with access controls. Hawking’s work in search technology can’t be overstated, from his contributions to the Text Retrieval Conferences, CSIRO, FunnelBack in addition to his academic achievements.
Chelsea Kerwin, December 09, 2014
December 8, 2014
The protestations of the enterprise search vendors in hock for tens of millions to venture funders will get louder. The argument is that proprietary search solutions are just better.
Navigate to “Postgres Full-Text Search Is Good Enough!” This has been the mantra of some of the European Community academics for a number of years. I gave a talk at CeBIT a couple of years ago and noted that the proprietary vendors were struggling to deliver a coherent and compelling argument. Examples of too-much-chest-beating came from speakers representing and Exalead and a handful of consultants. See, for example, http://bit.ly/1zicaGw.
The point of the “Postgres Good Enough” article strikes me as:
Search has became an important feature and we’ve seen a big increase in the popularity of tools like Elasticsearch and SOLR which are both based on Lucent. They are great tools but before going down the road of Weapons of Mass Search, maybe what you need is something a bit lighter which is simply good enough! What do you I mean by ‘good enough’? I mean a search engine with the following features: stemming, ranking/boost, multiple languages, fuzzy search, accent support. Luckily PostgreSQL supports all these features.
So not only are the proprietary systems dismissed, so are the open source solutions that are at the core of a number of commercialization ventures.
I don’t want to argue with the premise. What is important is that companies trying to market enterprise search solutions now have to convince a buyer why good enough is not good enough.
For decades, enterprise search vendors have been engaged in a Cold War style escalation. With each feature addition from one vendor (Autonomy), other vendors pile on more features (Endeca).
The result is that enterprise search tries to push value on customers, not delivering solutions that are valued by customers.
The “good enough” argument is one more example of a push back against the wild and crazy jumbles of code that most enterprise search vendors offer.
The good news is that good enough search is available, and it should be used. In fact, next generation information access solution vendors are including “good enough” search in robust enterprise applications.
What is interesting is that the venture funding firms seem content to move executives in and out of companies not hitting their numbers. Examples include Attivio and LucidWorks (really?). Other vendors are either really quiet or out of business like Dieselpoint and Hakia. I pointed out that the wild and crazy revenue targets for HP Autonomy and IBM Watson are examples of what happens when marketing takes precedent over what a system can do and how many customers are available to generate billions for these big outfits.
Attention needs to shift to “good enough” and to NGIA (next generation information access) vendors able to make sales, generate sustainable revenue, and solve problems that matter.
Displaying a results list is not high on the list of priorities for many organizations. And when search becomes job one, that is a signal the company may not have diagnosed its technological needs accurately. I know there are many mid tier consultants and unemployed webmasters who wish my statements were not accurate. Alas, reality can be a harsh task master or mistress.
Stephen E Arnold, December 8, 2014
November 30, 2014
I seem to run into references to the write up by a “expert”. I know the person is an expert because the author says:
As an Enterprise Search expert, I get a lot of questions about Search and Information Architecture (IA).
The source of this remarkable personal characterization is “Prevent Enterprise Search from going to the Weeds.” Spoiler alert: I am on record as documenting that enterprise search is at a dead end, unpainted, unloved, and stuck on the margins of big time enterprise information applications. For details, read the free vendor profiles at www.xenky.com/vendor-profiles or, if you can find them, read one of my books such as The New Landscape of Search.
Okay. Let’s assume the person writing the Weeds’ article is an “expert”. The write up is about misconcepts [sic]; specifically, crazy ideas about what a 50 year plus old technology can do. The solution to misconceptions is “information architecture.” Now I am not sure what “search” means. But I have no solid hooks on which to hang the notion of “information architecture” in this era of cloud based services. Well, the explanation of information architecture is presented via a metaphor:
The key is to understand: IA and search are business processes, rather than one-time IT projects. They’re like gardening: It’s up to you if you want a nice and tidy garden — or an overgrown jungle.
Gentle reader, the fact that enterprise search has been confused with search engine optimization is one thing. The fact that there are a number of companies happily leapfrogging the purveyors of utilities to make SharePoint better or improve automatic indexing is another.
Let’s look at each of the “misconceptions” and ask, “Is search going to the weeds or is search itself weeds?”
The starting line for the write up is that no one needs to worry about information architecture because search “will do everything for us.” How are thoughts about plumbing and a utility function equivalent. The issue is not whether a system runs on premises, from the cloud, or in some hybrid set up. The question is, “What has to be provided to allow a person to do his or her job?” In most cases, delivering something that addresses the employee’s need is overlooked. The reason is that the problem is one that requires the attention of individuals who know budgets, know goals, and know technology options. The confluence of these three characteristics is quite rare in my experience. Many of the “experts” working enterprise search are either frustrated and somewhat insecure academics or individuals who bounced into a niche where the barriers to entry are a millimeter or two high.
Next there is a perception, asserts the “expert”, that search and information architecture are one time jobs. If one wants to win the confidence of a potential customer, explaining that the bills will just keep on coming is a tactic I have not used. I suppose it works, but the incredible turnover in organizations makes it easy for an unscrupulous person to just keep on billing. The high levels of dissatisfaction result from a number of problems. Pumping money into a failure is what prompted one French engineering company to buy a search system and sideline the incumbent. Endless meetings about how to set up enterprise systems are ones to which search “experts” are not invited. The information technology professionals have learned that search is not exactly a career building discipline. Furthermore, search “experts” are left out of meetings because information technology professionals have learned that a search system will consume every available resource and produce a steady flow of calls to the help desk. Figuring out what to build still occupies Google and Amazon. Few organizations are able to do much more that embrace the status quo and wait until a mid tier consultant, a cost consultant, or a competitor provides the stimulus to move. Search “experts” are, in my experience, on the outside of serious engineering work at many information access challenged organizations. That’s a good thing in my view.
The middle example is what the expert calls “one size fits all.” Yep, that was the pitch of some of the early search vendors. These folks packaged keyword search and promised that it would slice, dice, and chop. The reality of information, even for the next generation information access companies with which I work, focus on making customization as painless as possible. In fact, these outfits provide some ready-to-roll components, but where the rubber meets the road is providing information tailored to each team or individual user. At Target last night, my wife and I bought Christmas gifts for needy people. One of the gifts was a 3X sweater. We had a heck of a time figuring out if the store offered such a product. Customization is necessary for more and more every day situations. In organizations, customization is the name of the game. The companies pitching enterprise search today lag behind next generation information access providers in this very important functionality. The reason is that the companies lack the resources and insight needed to deliver. But what about information architecture? How does one cloud based search service differ from another? Can you explain the technical and cost and performance differences between SearchBlox and Datastax?
The penultimate point is just plain humorous: Search is easy. I agree that search is a difficult task. The point is that no one cares how hard it is. What users want are systems that facilitate their decision making or work. In this blog I reproduced a diagram showing one firm’s vision for indexing. Suffice it to say that few organizations know why that complexity is important. The vendor has to deliver a solution that fits the technical profile, the budget, and the needs of an organization. Here is the diagram. Draw your own conclusion:
The final point is poignant. Search, the “expert” says, can be a security leak. No, people are the security link. There are systems that process open source intelligence and take predictive, automatic action to secure networks. If an individual wants to leak information, even today’s most robust predictive systems struggle to prevent that action. The most advanced systems from Centripetal Networks and Zerofox offer robust systems, but a determined individual can allow information to escape. What is wrong with search has to do with the way in which provided security components are implemented. Again we are back to people. Information architecture can play a role, but it is unlikely that an organization will treat search differently from legal information or employee pay data. There are classes of information to which individuals have access. The notion that a search system provides access to “all information” is laughable.
I want to step back from this “expert’s” analysis. Search has a long history. If we go back and look at what Fulcrum Technologies or Verity set out to do, the journeys of the two companies are quite instructive. Both moved quickly to wrap keyword search with a wide range of other functions. The reason for this was that customers needed more than search. Fulcrum is now part of OpenText, and you can buy nubbins of Fulcrum’s 30 year old technology today, but it is wrapped in huge wads of wool that comprise OpenText’s products and services. Verity offered some nifty security features and what happened? The company chewed through CEOs, became hugely bloated, struggled for revenues, and end up as part of Autonomy. And what about Autonomy? HP is trying to answer that question.
Net net: This weeds write up seems to have a life of its own. For me, search is just weeds, clogging the garden of 21st century information access. The challenges are beyond search. Experts who conflate odd bits of jargon are the folks who contribute to confusion about why Lucene is just good enough so those in an organization concerned with results can focus on next generation information access providers.
Stephen E Arnold, November 30, 2014
November 29, 2014
Several years ago, an ArnoldIT team tackled a content management search system that had three characteristics:  The system could not locate content a writer saved to the system.  The search results lacked relevance that made sense to the user; that is, time sequences for versions of the article were neither in ascending or descending order.  Response time was sluggish. Let’s look at each of these obvious problems.
The user wanted to access a document that required final touch ups. The article was not in a result that even when the writer entered the full title of the article. Examination of the system revealed that it lacked keyword search, relying on a training set of documents that did not contain some of the words in the title. The fix was to teach the user to search for articles using words and concepts that appeared in the body of the article. We also identified an indexing latency problem. The system lacked sufficient resources so recent material was not in an index until the indexing system caught up. The organization did not have the money to add additional resources, so the writers were told, “Live with it.”
What is that vendor doing amidst the prospects? A happy quack to http://bit.ly/1CrUc81
The chaos in the relevance function was a result of a configuration error during an upgrade and subsequent reindexing. The fix was to reconfigure the system and reindex the content. Keep in mind that indexing required more than two weeks. The attitude of the client was, “It is what it is.”
The third problem was the response time. This particular system used a product from a Canadian vendor of search and content management systems. The firm acquires companies and then “milks” the system. The idea is that updating and bug fixing are expensive. The problem was exacerbated because the search system was a stub provided by another vendor. The result was that in order to get more robust performance, the client had to upgrade the OEM search system AND add computers, memory, and network infrastructure. The client lacked the money to take these actions.
What were the hidden limitations of this enterprise search system?
On the client side, there was a lack of understanding of the interdependencies of a complex system. The client lacked expertise and, more importantly, money to address the problems of an “as is” infrastructure. Moving the operation to the cloud was not possible due to security concerns, knowledge of what to do and how to do it, and initiative on the management team. The conclusion was, “The system is good enough.”
On the vendor side, the marketing team closing the deal did not disclose that the OEM search system was a stub designed to upsell the licensee the seven figure “fix”. The vendor also did not reveal that funds were not being invested in the system due to the vendor’s “milk the cow” philosophy.
I point out this situation because it applies to many vendors of enterprise search systems. The object of the game on the client side is to get a good enough system at the best possible price. Senior managers are rarely experts in search and often search Google anyway.
The vendor has zero incentive to change its business practices. Even with low cost options available, once a prospect becomes a customer, lock in usually keeps the account alive. When a switch is in the wind, the search vendor plays the “legacy” card, pointing out that there are some people who need the older system. As a result, the licensing organization ends up with multiple search systems. The demand for money just goes up and findability remains a bit of a challenge for employees.
I do not see a fix under the present enterprise search business model. Education does not work. Search conferences dodge the tough issues, preferring to pander to vendors who buy exhibit stands and sponsor lunch.
Something different is needed: Different vendors, different approaches, and different assemblies of technology.
That’s why next generation information access is going to pose a threat to companies that pitch enterprise search disguised as customer support, business intelligence, analysis systems, and eDiscovery tools.
At some point, the NGIA vendors will emerge as the go-to vendors. Like the promising but now quiet outfits like Hakia and Autonomy, search as it has been practiced for decades is rapidly becoming a digital Antikythera mechanism.
Stephen E Arnold, November 29, 2014
November 25, 2014
I read a pretty darned amazing article “Is Free Enterprise Search a Game Changer?” My initial reaction was, “Didn’t the game change with the failures of flagship enterprise search systems?” And “Didn’t the cost and complexity of many enterprise search deployments fuel the emergence of the free and open source information retrieval systems?”
Many proprietary vendors are struggling to generate sustainable revenues and pay back increasingly impatient stakeholders. The reality is that the proprietary enterprise search “survivors” fear meeting the fate of Convera, Delphes, Entopia, Perfect Search, Siderean Software, TREX, and other proprietary vendors. These outfits went away.
Many vendors of proprietary enterprise search systems have left behind an environment in which revenues are simply not sustainable. Customers learned some painful lessons after licensing brand name enterprise search systems and discovering the reality of their costs and functionality. A happy quack to http://bit.ly/1AMHBL6 for this image of desolation.
Other vendors, faced with mounting costs and zero growth in revenues, sold their enterprise search companies. The spate of sell outs that began in the mid 2000s were stark evidence that delivering information retrieval systems to commercial and governmental organizations was difficult to make work.
Consider these milestones:
Autonomy sold to Hewlett Packard. HP promptly wrote off billions of dollars and launched a fascinating lawsuit that blamed Autonomy for the deal. HP quickly discovered that Autonomy, like other complex content processing companies, was difficult to sell, difficult to support, and difficult to turn into a billion dollar baby.
Convera, the product of Excalibur’s scanning legacy and ConQuest Software, captured some big deals in the US government and with outfits like the NBA. When the system did not perform like a circus dog, the company wound down. One upside for Convera alums was that they were able to set up a consulting firm to keep other companies from making the Convera-type mistakes. The losses were measured in the tens of millions.
November 19, 2014
The Arnold IT team is working on a new report that focuses on what my team is calling Next Generation Information Access or NGIA. The Information Today column for the next issue (maybe January 2015) addresses one of the several hurdles that enterprise search vendors will have to get over in order to close some of the larger information access deals available today.
In this write up, I want to identify five other issues that bedevil enterprise search. Please, understand that I am not talking about Web search, which is essentially a different application of string matching and online advertising.
Here’s the partial list with a short comment:
- A suite of components, not a one shot system like a download of Lucene
- An architecture that allows the licensee flexibility when integrating, scaling, or modifying certain operations of the system. The black box is an intriguing notion, just unsuited to today’s working environment.
- A suite of components that have been designed to inter-operate without extensive custom scripting or silly explanations about the difficulty of making Component A work with Component B of the same vendor’s software. Incompatible Lego blocks don’t fly in kindergarten, and they certainly don’t work in high risk information settings.
- Connectors that work and support the file types commonly in use in fast moving, flexible work situations. The notion that the licensee can just code up a widget makes sense only when the vendor lacks the expertise or the resources to do this job before selling an information access system.
- Native support for languages in which the licensee’s content resides. Again, telling the licensee that he or she can just connect a system to a third party translation system is a limp wristed solution to today’s global content environment.
There are other hurdles as well. I will be identifying more and mapping out the specific differences between some of the aggressively marketed “charade” information access systems and solutions from vendors who have been operating at a different level in today’s three dimensional information chess game.
Playing checkers is not the same as 3D chess in my view.
Stephen E Arnold, November 19, 2014
November 11, 2014
Three or four days ago I received a LinkedIn message that a new thread had been started on the Enterprise Search Engine Professionals group. You will need to be a member of LinkedIn and do some good old fashioned brute force search to locate the thread with this headline, “Enterprise Search with Chinese, Spanish, and English Content.”
The question concerned a LinkedIn user information vacuum job. A member of the search group wanted recommendations for a search system that would deliver “great results with content outside of English.” Most of the intelligence agencies have had this question in play for many years.
The job hunters, consultants, and search experts who populate the forum do not step forth with intelligence agency type responses. In a decision making environment when inputs in a range of language are the norm for risk averse, the suggestions offered to the LinkedIn member struck me as wide of the mark. I wouldn’t characterize the answers as incorrect. Uninformed or misinformed are candidate adjectives, however.
One suggestion offered to the questioner was a request to define “great.” Like love and trust, great is fuzzy and subjective. The definition of “great”, according the expert asking the question, boils down to “precision, mainly that the first few results strike the user as correct.” Okay, the user must perceive results as “correct.” But as ambiguous as this answer remains, the operative term is precision.
In search, precision is not fuzzy. Precision has a definition that many students of information retrieval commit to memory and then include in various tests, papers, and public presentations. For a workable definition, see Wikipedia’s take on the concept or L. Egghe’s “The Measures Precision, Recall, Fallout, and Miss As a function of the Number of Retrieved Documents and Their Mutual Interrelations, Universiiteit Antwerp, 2000.
In simple terms, the system matches the user’s query. The results are those that the system determines containing identical or statistically close results to the user’s query. Old school brute force engines relied on string matching. Think RECON. More modern search systems toss in term matching after truncation, nearness of the terms used in the user query to the occurrence of terms in the documents, and dozens of other methods to determine likely relevant matches between the user’s query and the document set’s index.
With a known corpus like ABI/INFORM in the early 1980s, a trained searcher testing search systems can craft queries for that known result set. Then as the test queries are fed to the search system, the results can be inspected and analyzed. Running test queries was an important part of our analysis of a candidate search system; for example, the long-gone DIALCOM system or a new incarnation of the European Space Agency’s system. Rigorous testing and analysis makes it easy to spot dropped updates or screw ups that routinely find their way into bulk file loads.
Our rule of thumb was that if an ABI/INFORM index contained a term, a high precision result set on SDC ORBIT would include a hit with that term in the respective hit. If the result set did not contain a match, it was pretty easy to pinpoint where the indexing process started dropping files.
However, when one does not know what’s been indexed, precision drifts into murkier areas. After all, how can one know if a result is on point if one does not know what’s been indexed? One can assume that a result set is relevant via inspection and analysis, but who has time for that today. That’s the danger in the definition of precision in what the user perceives. The user may not know what he or she is looking for. The user may not know the subject area or the entities associated consistently with the subject area. Should anyone be surprised when the user of a system has no clue what a system output “means”, whether the results are accurate, or whether the content is germane to the user’s understanding of the information needed.
Against this somewhat drab backdrop, the suggestions offered to the LinkedIn person looking for a search engine that delivers precision over non-English content or more accurately content that is not the primary language of the person doing a search are revelatory.
Here are some responses I noted:
- Hire an integrator (Artirix, in this case) and let that person use the open source Lucene based Elasticsearch system to deliver search and retrieval. Sounds simplistic. Yep, it is a simple answer that ignores source language translation, connectors, index updates, and methods for handling the pesky issues related to how language is used. Figuring out what a source document in an language with which the user is not fluent is fraught with challenges. Forget dictionaries. Think about the content processing pipeline. Search is almost the caboose at the end of a very long train.
- Use technology from LinguaSys. This is a semantic system that is probably not well known outside of a narrow circle of customers. This is a system with some visibility within the defense sector. Keep in mind that it performs some of the content processing functions. The technology has to be integrated into a suitable information retrieval system. LinguaSys is the equivalent of adding a component to a more comprehensive system. Another person mentioned BASIS Technologies, another company providing multi language components.
- Rely on LucidWorks. This is an open source search system based on SOLR. The company has spun the management revolving door a number of times.
- License Dassault’s Exalead system. The idea is wroth considering, but how many organizations are familiar with Exalead or willing to embrace the cultural approach of France’s premier engineering firm. After years of effort, Exalead is not widely known in some pretty savvy markets. But the Exalead technology is not 100 percent Exalead. Third party software delivers the goods, so Exalead is an integrator in my view.
- Embrace the Fast Search & Transfer technology, now incorporated into Microsoft SharePoint. Unmentioned is the fact that Fast Search relied on a herd of human linguists in Germany and elsewhere to keep its 1990s multi lingual system alive and well. Fast Search, like many other allegedly multi lingual systems, rely on rules and these have to be written, tweaked, and maintained.
So what did the LinkedIn member learn? The advice offers one popular approach: Hire an integrator and let that company deliver a “solution.” One can always fire an integrator, sue the integrator, or go to work for the integrator when the CFO tries to cap the cost of system that must please a user who may not know the meaning of nus in Japanese from a now almost forgotten unit of Halliburton.
The other approach is to go open source. Okay. Do it. But as my analysis of the Danish Library’s open source search initiative in Online suggested, the work is essentially never done. Only a tolerant government and lax budget oversight makes this avenue feasible for many organizations with a search “problem.”
The most startling recommendation was to use Fast Search technology. My goodness. Are there not other multi lingual capable search systems dating from the 1990s available? Autonomy, anyone?
Net net: The LinkedIn enterprise search threads often underscore one simple fact:
Enterprise search is assumed to be one system, an app if you will.
One reason for the frequent disappointment with enterprise search is this desire to buy an iPad app, not engineer a constellation of systems that solve quite specific problems.
Stephen E Arnold,November 11, 2014
November 9, 2014
I use Google Trends to see what’s hot and what’s not in the world of information retrieval. If you want to use the free version of Google Trends, navigate to http://www.google.com/trends/ and explore. That’s some of what Google does to make decisions about how much of Larry Page’s “wood” to put behind the Google Search Appliance eight ball.
I plugged in “enterprise search.” When one allows Google to output its version of the popularity of the term, you get this graph. It shows a downward trend but the graph is without much context. The pale lettering does not help. Obviously Googlers do not view the world through trifocals with 70 year old eyes. Here’s the Trends’ output for “enterprise search”:
Now let’s add some context. From the “enterprise search” Trends’ output, click the pale blue plus and add this with quotes: “big data.” Here’s the output for this two factor analysis:
One does not have to be an Ivy League data scientist to see the difference between the hackneyed “enterprise search” and more zippy but meaningless “Big Data.” I am not saying Big Data solutions actually work. What’s clear is that pushing enterprise search is not particularly helpful when the Trends’ reveal a flat line for years, not hours, not days, not months–years.
I think it is pretty clear why I can assert with confidence that “enterprise search” appears to be a non starter. I know why search vendors persist in telling me what “enterprise search” is. The vendors are desperate to find the grip that a Tupinambis lizard possesses. Instead of clinging to a wall in the sun at 317 R. Dr. Emílio Ribas (Cambui) (where I used to live in Campinas, SP), the search vendors are clinging to chimera. The goal is to make sales, but if the Google data are even sort of correct, enterprise search is flat lining.
Little wonder that consultant reports like those from the mid tier crowd try to come up with verbiage that will create sales leads for the research sponsors; case in point, knowledge quotient. See Meme of the Moment for a fun look at IDC’s and search “expert” Dave Schubmehl’s most recent attempt to pump up the music.
The question is, “What is generating revenue?” In a sense, excitement surrounds vendors who deliver solutions. These include search, increasingly supplied by open source software. Elasticsearch is zipping along, but search is not the main dish. Search is more like broccoli or carrots.
The good news is that there is a group of companies, numbering about 30, which have approached search differently. As a result, many of these companies are growing and charting what I call “next generation search.”
Want to know more? Well, that’s good. Watch for my coverage of this sector in the weeks and months ahead. I will toss a small part of our research into my November Information Today column. A tiny chunk. Keep that in mind.
In the meantime, think critically about the craziness flowing from many mid tier or azure chip consulting firms. Those “outputs” are marketing, self aggrandizing, and, for me, downright silly. What’s that term for doing trivial actions again and again?
Stephen E Arnold, November 9, 2014
November 5, 2014
I read “Enterprise Search: Despite Benefits, Few Organizations Use Enterprise Search.” The headline caught my attention. In my experience, most organizations have information access systems. Let me give you several recent examples:
- US government agency. This agency licenses technology from a start up called Red Owl Analytics. That system automatically gathers and makes available information pertinent to the licensing agency. One of the options available to the licensee is to process information that is available within the agency. The system generates outputs and there are functions that allow a user to look for information. I am reasonably confident that the phrase “enterprise search” would not be applied to this company’s information access system. Because Red Owl fits into a process for solving a business problem, the notion of “enterprise search” would be inappropriate.
- Small accounting firm. This company uses Microsoft Windows 7. The six person staff uses a “workgroup” method that is easy to set up and maintain. The Windows 7 user can browse the drives to which access has been granted by the part time system administrator. When a person needs to locate a document, the built in search function is used. The solution is good enough. I know that when Windows-centric, third party solutions were made known to the owner, the response was, “Windows 7 search is good enough.”
- Large health care company with dozens of operating units. The company has been working to integrate certain key systems. The largest on-going project is deploying a electronic health care system. Each of the units has legacy search technology. The most popular search systems are those built into applications used every day. Database access is provided by these applications. One unit experimented with a Google Appliance and found that it was useful to the marketing department. Another unit has a RedDot content management system and has an Autonomy stub. The company has no plans, as I understand it, to make federated enterprise search a priority. There is no single reason. Other projects have higher priority and include a search function.
If my experience is representative (and I am not suggesting what I have encountered is what you will encounter), enterprise search is a tough sell. When I read this snippet, I was a bit surprised:
Enterprise search tools are expected to improve and that may improve uptake of the technology. Steven Nicolaou, Principal Consultant at Microsoft, commented that “enterprise search products will become increasingly and more deeply integrated with existing platforms, allowing more types of content to be searchable and in more meaningful ways. It will also become increasingly commoditized, making it less of a dark art and more of a platform for discovery and analysis.”
What this means is that the company that provides “good enough” search baked into an operating system (think Windows) or an application (think about the search function in an electronic health record), there will be little room for a third party to land a deal in most cases.
The focus in enterprise search has been off the mark for many years. In fact, today’s vendors are recycling the benefits and features hawked 30 years ago. I posted a series of enterprise search vendor profiles at www.xenky.com/vendor-profiles. If you work through that information, you will find that the marketing approaches today are little more than demonstrations of recycling.
The opportunity in information access has shifted. The companies making sales and delivering solid utility to licensees are NOT the companies that beat the drum for customer support, indexing, and federated search.
The future belongs to information access systems that fit into mission critical business processes. Until the enterprise search vendors embrace a more innovative approach to information access, their future looks a bit cloudy.
In cooperation with Telestrategies, we may offer a seminar that talks about new directions in information access. The key is automation, analytics, and outputs that alert, not the old model of fiddling with a query until the index is unlocked and potentially useful information is available.
If you want more information about this invitation only seminar, write me at seaky2000 at yahoo dot com, and I will provide more information.
Stephen E Arnold, November 5, 2014