A company with sustained profitability for nearly ten years in the enterprise semantic market space has credibility. Reactions from a maturing company to what users have to say are interesting and carry weight in any industry. My lines of inquiry and the commentary from the Linguamatics officers centered around their own view of the market and adoption experiences.
When asked about growth potential for the company outside of pharmaceuticals where Linguamatics already has high adoption and very enthusiastic users, Drs. Milward and Hastings asserted their ongoing principal focus in life sciences. They see a lot more potential in this market space, largely because of the vast amounts of unstructured content being generated, coupled with the very high-value problems that can be solved by text mining and semantically analyzing the data from those documents. Expanding their business further in the life sciences means that they will continue engaging in research projects with the academic community. It also means that Linguamatics semantic technology will be helping organizations solve problems related to healthcare and homeland security.
The wisdom of a measured and consistent approach comes through strongly when speaking with Linguamatics executives. They are highly focused and cite the pitfalls of trying to "do everything at once," which would be the case if they were to pursue all markets overburdened with tons of unstructured content. While pharmaceutical terminology, a critical component of I2E, is complex and extensive, there are many aids to support it. The language of life sciences is in a constant state of being enriched through refinements to published thesauri and ontologies. However, in other industries with less technical language, Linguamatics can still provide important support to analyze content in the detection of signals and patterns of importance to intelligence and planning.
Much of the remainder of the interview centered on what I refer to as the "team competencies" of individuals who identify the need for any semantic software application; those are the people who select, implement and maintain it. When asked if this presents a challenge for Linguamatics or the market in general, Milward and Hastings acknowledged a learning curve and the need for a larger pool of experts for adoption. This is a professional growth opportunity for informatics and library science people. These professionals are often the first group to identify Linguamatics as a potential solutions provider for semantically challenging problems, leading business stakeholders to the company. They are also good advocates for selling the concept to management and explaining the strong benefits of semantic technology when it is applied to elicit value from otherwise under-leveraged content.
One Linguamatics core operating principal came through clearly when talking about the personnel issues of using I2E, which is the necessity of working closely with their customers. This means making sure that expectations about system requirements are correct, examples of deployments and "what the footprint might look like" are given, and best practices for implementations are shared. They want to be sure that their customers have a sense of being in a community of adopters and are not alone in the use of this pioneering technology. Building and sustaining close customer relationships is very important to Linguamatics, and that means an emphasis on services co-equally with selling licenses.
Linguamatics has come a long way since 2001. Besides a steady effort to improve and enhance their technology through regular product releases of I2E, there have been a lot of "show me" and "prove it" moments to which they have responded. Now, as confidence in and understanding of the technology ramps up, they are getting more complex and sophisticated questions from their customers and prospects. This is the exciting part as they are able to sell I2E's ability to "synthesize new information from millions of sources in ways that humans cannot." This is done by using the technology to keep track of and processing the voluminous connections among information resources that exceed human mental limits.
At this stage of growth, with early successes and excellent customer adoption, it was encouraging to hear the enthusiasm of two executives for the evolution of the industry and their opportunities in it.
The Gilbane report and a deep dive on Linguamatics are available through this Press Release on their Web site.
When asked if they were surprised by anything in my coverage of the market, the simple answer was "not really, nothing we did not already know." The longer answer related to the presentation of our research illustrating the scope and depth of the marketplace. These two veterans of the semantic industry admitted that the number of players, applications and breadth of semantic software categories is impressive when viewed in one report. Mr. Scagliarini commented on the huge amount of potential still to be explored by vendors and users.
Our conversation then focused on where we think the industry is headed and they emphasized that this is still an early stage and evolving area. Both acknowledged the need for simplification of products to ease their adoption. It must be straightforward for buyers to understand what they are licensing, the value they can expect for the price they pay; implementation, packaging and complementary services need to be easily understood.
Along the lines of simplicity, they emphasized the specialized nature of most of the successful semantic software applications, noting that these are not coming from the largest software companies. State-of-the-art tools are being commercialized and deployed for highly refined applications out of companies with a small footprint of experienced experts.
Expert System knows about the need for expertise in such areas as ontologies, search, and computational linguistic applications. For years they have been cultivating a team of people for their development and support operations. It has not always been easy to find these competencies, especially right out of academia. Aker and Scagliarini pointed out the need for a lot of pragmatism, coupled with subject expertise, to apply semantic tools for optimal business outcomes. It was hard in the early years for them to find people who could leverage their academic research experiences for a corporate mission.
Human resource barriers have eased in recent years as younger people who have grown up with a variety of computing technologies seem to grasp and understand the potential for semantic software tools more quickly.
Expert System itself is gaining traction in large enterprises that have segmented groups within IT that are dedicated to "learning" applications, and formalized ways of experimenting with, testing and evaluating new technologies. When they become experts in tool use, they are much better at proving value and making the right decisions about how and when to apply the software.
Having made good strides in energy, life sciences, manufacturing and homeland security vertical markets, Expert System is expanding its presence with the Cogito product line in other government agencies and publishing. The executives reminded me that they have semantic nets built out in Italian, Arabic and German, as well as English. This is unique among the community of semantic search companies and will position them for some interesting opportunities where other companies cannot perform.
I enjoyed listening and exchanging commentary about the semantic software technology field. However, Expert System and Gilbane both know that the semantic space is complex and they are sharing a varied landscape with a lot of companies competing for a strong position in a young industry. They have a significant share already.
For more about Expert System and the release of this sponsored research you can view their recent Press Release.
Research for a forthcoming Gilbane report on semantic software technologies turned up numerous applications used in the life sciences and publishing. Neither semantic technologies nor text mining are mentioned in this recent article Rare Sharing of Data Leads to Progress on Alzheimer's in the New York Times but I am pretty certain that these technologies had some role in enabling scientists to discover new data relationships and synthesize new ideas about Alzheimer's biomarkers. The sheer volume of data from all the referenced data sources demands computational methods to distill and analyze.
One vertical industry poised for potential growth of semantic technologies is the energy field. It is a special interest of mine because it is a topical area in which I worked as a subject indexer and searcher early in my career. Beginning with the 1st energy crisis, oil embargo of the mid-1970s, I worked in research organizations that involved both fossil fuel exploration and production, and alternative energy development.
A hallmark of technical exploratory and discovery work is the time gaps between breakthroughs; there are often significant plateaus between major developments. This happens if research reaches a point that an enabling technology is not available or commercially viable to move to the next milestone of development. I observed that the starting point in the quest for innovative energy technologies often began with decades-old research that stopped before commercialization.
Building on what we have already discovered, invented or learned is one key to success for many "new" breakthroughs. Looking at old research from a new perspective to lower costs or improve efficiency for such things as photovoltaic materials or electrochemical cells (batteries) is what excellent companies do.
How does this relate to semantic software technologies and data mining? We need to begin with content that was generated by research in the last century; much of this is just now being made electronic. Even so, most of the conversion from paper, or micro formats like fîche, is to image formats. In order to make the full transition to enable data mining, content must be further enhanced through optical character recognition (OCR). This will put it into a form that can be semantically parsed, analyzed and explored for facts and new relationships among data elements.
Processing of old materials is neither easy nor inexpensive. There are government agencies, consortia, associations, and partnerships of various types of institutions that often serve as a springboard for making legacy knowledge assets electronically available. A great first step would be having DOE and some energy industry leaders collaborating on this activity.
A future of potential man-made disasters, even when knowledge exists to prevent them, is not a foregone conclusion. Intellectually, we know that energy independence is prudent, economically and socially mandatory for all types of stability. We have decades of information and knowledge assets in energy related fields (e.g. chemistry, materials science, geology, and engineering) that semantic technologies can leverage to move us toward a future of energy independence. Finding nuggets of old information in unexpected relationships to content from previously disconnected sources is a role for semantic search that can stimulate new ideas and technical research.
A beginning is a serious program of content conversion capped off with use of semantic search tools to aid the process of discovery and development. It is high time to put our knowledge to work with state-of-the-art semantic software tools and by committing human and collaborative resources to the effort. Coupling our knowledge assets of the past with the ingenuity of the present we can achieve energy advances using semantic technologies already embraced by the life sciences.
Yes, we have seen the demise of vinyl phonograph records, cassette tapes and probably soon musical CD albums, but those are explicit devices and formats. When you can't buy or play them any longer, except in a museum or collector's garage, they are pretty dead in the marketplace. This is not true of search in the enterprise, behind the firewall, or wherever it needs to function for business purposes. People have always needed to find "stuff" to do their work. KM methods and processes, special libraries and integrated library systems still exist, even as they were re-labeled for PR and marketing purposes.
What is happening to search in the enterprise is that it is finding its purpose, or more precisely its hundreds of purposes. It is not a monolithic software product, a one-size-fits-all. It comes in dozens of packages, models, and price ranges. It may be embedded in other software or standalone. It may be procured for a point solution to support retrieval of content for one business unit operating in a very narrow topical range, or it may be selected to give access to a broad range of documents that exist in numerous enterprise domains on many subjects.
Large enterprises typically have numerous search solutions in operation, implementation, and testing, all at the same time. They are discovering how to deploy and leverage search systems and they are refining their use cases based on what they learn incrementally through their many implementations. Teams of search experts are typically involved in selecting, deploying and maintaining these applications based on their subject expertise and growing understanding of what various search engines can do and how they operate.
After years of hearing about "the semantic Web," the long sought after "holy grail" of Web search, there is a serious ramping of technology solutions. Most of these applications can also make search more semantically relevant behind the firewall. These technologies have been evolving for decades beginning with so-called artificial intelligence, and now supported by some categories of computational linguistics such as specific algorithms for parsing content and disambiguating terms. A soon to-be released study featuring some of noteworthy applications reveals just how much is being done in enterprises for specific business purposes.
With this "teaser" on what is about to be published, I leave you with one important thought, meaningful search technologies depend on rich linguistically-based technologies. Without a cornucopia of software tools to build terminology maps and dictionaries, analyze content linguistically in context to elicit meaning, parse and evaluate unstructured text data sources, and manage vocabularies of ever more complex topical domains, semantic search could not exist.
Language complexities are challenging and even vexing. Enterprises will be finding solutions to leverage what they know only when they put human resources into play to work with the lingo of their most valuable domains.
]]>This analyst has praise for the industry players who continue to persevere, working to get the packaging, usability, usefulness and business purposes positioned effectively. Jean Ferré is absolutely correct; the nature of the deal underscores the importance of the industry and the vision of the acquirers.
As we segue from a number of conferences featuring search (Search Engines, Enterprise Search Summit, Gilbane) to broader enterprise technologies (Enterprise 2.0) and semantic technologies (SemTech), it is important for enterprises to examine the interplay among product offerings. Getting the mix of software tools just right is probably more important than any one industry-labeled class of software, or any one product. Everybody's software has to play nice in the sandbox to get us to the next level of adoption and productivity.
Here is one analyst cheering the champions of search and looking for continued growth in the industry...but not so big it fails.
The Gilbane Group focuses on content technologies. In its early history this included Web content management, document management, and CMS systems for publishers and enterprises. We now track related technologies expanding to areas including standards like DITA and XML, adoption of social tools, plus rapid growth in the drive to localize and globalize content; Gilbane has kept up with these trends.
My area, search and more specifically "enterprise search" or search "behind the firewall," was added just over three years ago. It seemed logical to give attention to the principal reason for creating, managing and manipulating content, namely finding it. When I pay attention to search engines, I am also thinking about adjoining content technologies. My recent interest is helping readers learn about how technology on both the search side and content management/manipulation side need better context; that means relating the two.
If one theme ran consistently through all the talks at Enterprise Search Meeting, it was the need to define search in relationship to so many other content technologies. The speakers, for the most part, did a fine job of making these connections.
Here are just some snippets:
Bipin Patel CIO of ProQuest, shared the technology challenges of maintaining a 24/7 service while driving improvements to the search usability interface. The goal is to deliver command line search precision to users who do not have the expertise to (or patience) to construct elaborate queries. Balancing the tension between expert searchers (usually librarians) with everyone else who seeks content underscores the importance of human factors. My take-away: underlying algorithms and architecture are worth little if usability is neglected.
Martin Baumgartel spoke on the Theseus project for the semantic search marketplace, a European collaborative initiative. An interesting point for me is their use of SMILA (SeMantic Information Logistics Architecture) from Eclipse. By following some links on the Eclipse site I found this interesting presentation from the International Theseus Convention in 2009. The application of this framework model underscores the interdependency of many semantically related technologies to improve search.
Tamas Doszkocs of the National Library of Medicine told a well-annotated story of the decades of search and content enhancement technologies that are evolving to contribute to semantically richer search experiences. His metaphors in the evolutionary process were fun and spot-on at a very practical level: Libraries as knowledge bases > Librarians as search engines > the Web as the knowledge base > Search engines as librarians > moving toward understanding, content, context, and people to bring us semantic search. A similar presentation is posted on the Web.
David Evans noted that there is currently no rigorous evaluation methodology yet for mobile search but is it very different than what we do with desktop search. One slide that I found most interesting was the Human Language Technologies (HLT) that contribute to a richer mobile search experience, essentially numerous semantic tools. Again, this underscores that the challenges of integrating sophisticated hardware, networking and search engine architectures for mobile search are just a piece of the solution. Adoption will depend on tools that enhance content findability and usability.
Jeff Fried of Microsoft/Fast talked about "social search" and put forth this important theme: that people like to connect to content through other people. He made me recognize how social tools are teaching us that the richness of this experience is a self-reinforcing mechanism toward "the best way to search." It has lessons for enterprises as they struggle to adopt social tools in mindful ways in tandem with improving search experiences.
Shekhar Pradhan of Docunexus shared this relevant thought about a failure of interface architecture and that is (to paraphrase): the ubiquitous search box fails because it does not demand context or mechanisms for resolving ambiguity. Obviously, this breaks down adoption for enterprise search when it is the only option offered.
Many more talks from this meeting will get rolled up in future reports and blogs.
I want to learn your experiences and observations about semantic search and semantic technologies, as well. Please note that we have posted a brief survey for a short time at: Semantic Technology Survey. If you have any involvement with semantic technologies, please take it.
Most technology buyers have a level of cynicism about such claims and commentary because we know that in each case there is a bias, with good reasons, for the praise. However, also for good reasons, language containing positive sentiment can have an effect - otherwise, it would not be so widespread. At the very least, sentiment analysis tools that are integrated with search engines will pick up on pervasive tones of praise, and from that create new content streams that compound the positive spin.
Being aware of marketing methods and influences on our psyche should arm us with caution but not to a point of being risk averse or frozen to indecisiveness. Instead, we need to find a way to prove the hype and claims through thoughtful, artful and strategic analytical processes. We need methods for testing claims that are appropriate for the solution sought.
First, we need to establish what is appropriate for our business need. Cost is often the primary qualifying factor when narrowing products that will be considered, but this may be short sighted. Business impact and benefits from applying the right solution need to be directly in our line of sight. If the solution you acquire can be evaluated to demonstrate a significant business benefit, the cost of a higher priced product may also be high-value to your business. Add to business impact the scope for the use of an enterprise search engine (how widely deployed and leveraged) and whether it can scale to include multiple searchable repositories across the organization; these attributes may enhance business impact.
Judging business impact, scope and scaling enterprise search products is a tricky proposition. You absolutely cannot do it by totaling the number of positive checks a vendor ticks off on a spreadsheet of requirements. While such a device can be useful for narrowing down a field of products to those you might select, it is only a beginning. All too often, this is where the selection process ends.
What needs to be done next? I recommend these three steps that can be concurrent:
If things are not going smoothly, how does a vendor react and respond, and what is their follow-up and follow-through in the pre-purchase stage. Never succumb to the excuse that because they are "going through growing pains," have "so much business demand" they are stretched thin, or that something else is more important to them than your product evaluation. If any of these creep in before you purchase, you have a major symptom conveying clearly that your business is not as important or valuable as someone else's.
The steps for selection will take a little longer than just sending out RFPs and reading responses, but it is really worth it over the long haul relationship you are about to engage.
While these 2010 releases of Fast ESP on UNIX and Linux will continue to be supported for ten years, and repositories are projected to be indexable on these two platforms by future Fast releases, some customers will opt out of continuing with Fast. As newer and more advanced search technologies support preferred operating systems, they will choose to move. Microsoft probably expects to retain most current customers for the time being - inertia and long evaluation and selection processes by enterprises are on their side.
This recent announcement did include a small aside questioning whether Microsoft would continue to offer a standalone search engine outside of its SharePoint environment where the Fast product has been embedded and leveraged first. It sounds like the short term plan is to continue with standalone ESP, but certainly no long term commitment is made.
So, whatever stasis/constancy pre-Microsoft Fast customers were feeling sanguine about, it is surely being shaken around. Let's take a look at some reasons that vendors abandon their acquisitions. First we need to consider why companies add products through acquisition in the first place. A simple list looks like this:
While item 1 probably was not a contributor to the Microsoft Fast acquisition, 2 and 3 certainly factored into their plan. Fast was "the" brand and had become synonymous in the marketplace with "enterprise search leader." Surely Microsoft considered the technology IP and key employees that they would be acquiring, and having a ready-made customer-base and maintenance revenue stream would be considerations, too.
Customers do have reasons to be nervous in any of these big acquisitions, however. Here is what often get exposed and revealed once the onion is peeled:
The Microsoft/Fast circumstance is just an illustration. You might take a look at what is also going on with SAP after its acquisition of Business Objects (BO) in this lengthy analysis at Information Week. In this unfortunate upheaval, BO's prior acquisition of Inxight has been a particular loss to those who had embraced that fine analytics and visualization engine.
The bottom line is that customers who depend on technology of any kind, for keeping their own businesses running effectively and efficiently, must be aware of what is transpiring with their most valued vendor/suppliers. When there is any changing of the guardians of best-of-breed software tools, be prepared by becoming knowledgeable about what is really under the skin of the newly harvested onion. Then, make your own plans accordingly.
]]>What buyers need to do first is to stop limiting their procurement selection choices based primarily on license prices. When enterprises begin their selection by considering prices first, many options are eliminated that may be functionally more appropriate and for which the total cost of ownership may be even less.
Product pricing correlates more to the market domain in which a vendor sells or aims to sell than to actual product value per installed user. Therefore, companies in the small to mid-range are particularly vulnerable to unreasonable licensing. I have written about this before but it bears repeating, the strength of the underlying technology has little to do with the price but can influence the total-cost-of-ownership (TCO) dramatically.
Buyers often believe high license price relates to top product value; in general you still need to add another 60-80% for services and support costs to get that value out. But let's look at the business reality and corporate context for sellers of high-priced enterprise search.
Net sales of any company that is large is a significant determinant of its reputation and potential staying power in its industry. However, when actual sales for a search product line are a tiny fraction of total company revenue, potential buyers of enterprise search need to know that and factor it into their decision-making for these reasons:
• The largest software companies are heavily vested in subscribing to analyst services that write about the industry. They are diligent in reporting their sales figures to those companies and publications that do annual surveys on various industry segments. The reporting is usually careful to note when revenues for a particular sector ( like search) are not broken out, but this often escapes the notice of buyers who only see that company X has enormous revenues compared to others. This leaves the impression that they are also a standout in the search sector.
• The fact that a company offers many software products, of which search is only one, has often resulted from acquisition of a lot of products. Search may only be in the mix because it complements other products. The company may or may not have actually retained the technology gurus who originally designed, developed and supported the software. A lot of software quickly becomes stale once acquired by a third-party.
• When a very large company offers many products, it focuses sales, account management, support and development on those with the largest revenue stream or growth potential. Marketing for marginal products may be sustained for a longer period to bring in "easy" business but unfortunately, for too long, search has been treated as a loss leader to attract revenues for other product lines. Where "search" fits into a mix of products, how well it will be serviced and supported over time may be difficult to discern.
• The final situation that happens for very large software companies is that competition is an ever-present cause for shifting agendas. The largest software firms will often abandon technologies whose architecture, unique functions and even their customers do not fit their changing market interests. They will abandon products for which they have paid huge sums once the initial value of the procurement has been realized, when a product's technology has been captured for embedding in other product suites, or if the product is no longer viewed as strategic.
In the next blog posting we'll take a look at some other reasons that vendors make and then abandon their acquisitions. But in the meantime, here is a recommendation to buying decision-makers:
When you see a very long list of customer logos on the web sites of major software vendors there is important context that is not provided. Large corporations can and do buy competing products all the time. Some products get into enterprise-wide use and adoption for the long term while others are used briefly or in smaller applications. You can't know whether a product is even in use in the company whose logo is displayed. Because it is almost impossible for an outsider to find the actual buyer/user of a product in a large enterprise; the posted logos tell you little. Inside an enterprise one may discover endless tales of when, why and how competing products were acquired, many as part of package deals or through a subsidiary acquisition. What is also true is that stories of successful implementations or brand loyalty do not abound.
For you who are new to enterprise search, take control of your own destiny by educating yourself using a lower priced product with a good reputation for a niche application. Invest your budget instead in human resources (internal or 3rd party) to craft the solution you really need. Start with a vision of appropriate scale, tackling a small domain of high value content that is currently hard to find in your organization.
Use the experience of implementing and leveraging this search product and engaging with the vendor to bring a deeper understanding of the technology and applications of search. Working with a vendor dedicated exclusively to search will have another cost benefit because of the focused attention you are more likely to receive. Delving deeply into planning and implementation for a targeted result will have a cost that brings multiple benefits moving forward to larger and more complex implementations - even if you move on to another product.
]]>I don't make forecasts or try to guess whether strategic changes will succeed or fail but a couple of years ago, I blogged on IBM's introduction of Yahoo OmniFind, a free offering and then followed up with these comments just a few months ago. IBM makes their competitors change, try to outsmart, outguess, or copy, just as Microsoft or Google changes cause ripples in the industry.
Meanwhile, OpenText, another large software company with search offerings, is not going to offer search outside of its other product suites. [More is likely to come out after the scheduled analyst meetings today but I'm not there and can't brief you on deeper intent.] We have recently seen an announcement about FAST being delivered with new SharePoint offerings, the first major release of FAST announced since Microsoft acquired them almost two years ago. While FAST is still available as a standalone product from MS, it and other search engines may be steadily moving into being embedded in suites by their acquirers.
Certainly IBM has a lot of search components that they have acquired, so continuing to bind with other content offerings is a probable strategy. Oracle and Autonomy may soon come up with similar suite offerings embedding search once again. Oracle SES (Secure Enterprise Search) does not appear to have a lot of traction and it's possible that supporting pure search offerings may be a burden for Autonomy with its stable of many acquired content products.
All of this leads me to think that, since enterprise search has gotten such a bad reputation as a failed technology, the big software houses are going to bury it in point solutions. Personally, I believe that enterprise search is a failed strategy and SMBs can still find search engines that will serve the majority of their enterprise needs for several years to come. The same holds true for divisions or groups within large corporations.
Guidance: select and adopt one or more search solutions that fit your budget for small scale needs, point solutions and enterprise content that everyone in the organization needs to access on a regular basis. Learn how these products work, what they can and cannot deliver, making incremental adjustments as needs change and evolve. Do not install and think you are done because you will never be done. Cultivate a few search experts to stick with the evolving landscape and give them the means to keep up with changes in the search landscape. It is going to keep morphing for a long time to come.
]]>As part of a panel on semantic search, moderated by Hadley Reynolds of IDC, with Jeff Fried of Microsoft and Chris Lamb of the OpenCalais Initiative at Thomson Reuters, I wanted to give a high level view of semantic technologies currently in the marketplace. I contacted about a dozen vendors and selected six to highlight for the variety of semantic search offerings and business models.
One case study involves three vendors, each with a piece of the ultimate, customer-facing, product. My research took me to one company that I had reviewed a couple of years ago, and they sent me to their "customer" and to the customer's customer. It took me a couple of conversations and emails to sort out the connections; in the end the relationships made perfect sense.
On one hand we have conglomerate software companies offering "solutions" to every imaginable enterprise business need. On the other, we see very unique, specialized point solutions to universal business problems with multiple dimensions and twists. Teaming by vendors, each with a solution to one dimension of a need, create compound product offerings that are adding up to a very large semantic search marketplace.
Consider an example of data gathering by a professional services firm. Let's assume that my company has tens of thousands of documents collected in the course of research for many clients over many years. Researchers may move on to greater responsibility or other firms, leaving content unorganized except around confidential work for individual clients. We now want to exploit this corpus of content to create new products or services for various vertical markets. To understand what we have, we need to mine the content for themes and concepts.
The product of the mining exercise may have multiple uses: help us create a taxonomy of controlled terms, preparing a navigation scheme for a content portal, providing a feed to some business or text analytics tools that will help us create visual objects reflecting various configurations of content. A text mining vendor may be great at the mining aspect while other firms have better tools for analyzing, organizing and re-shaping the output.
Doing business with two or three vendors, experts in their own niches, may help us reach a conclusion about what to do with our information-rich pile of documents much faster. A multi-faceted approach can be a good way to bring a product or service to market more quickly than if we struggle with generic products from just one company.
When partners each have something of value to contribute, together they offer the benefits of the best of all options. This results in a new problem for businesses looking for the best in each area, namely, vendor relationship management. But it also saves organizations from dealing with huge firms offering many acquired products that have to be managed through a single point of contact, a generalist in everything and a specialist in nothing. Either way, you have to manage the players and how the components are going to work for you.
I really like what I see, semantic technology companies partnering with each other to give good-to-great solutions for all kinds of innovative applications. By the way, at the conference I am doing a quick snapshot on each: Cogito, Connotate (with Cormine and WorldTech), Lexalytics, Linguamatics, Sinequa and TEMIS.
Frequently, enterprise stakeholders will reference a commercial web site they like or even search tools within social sites. These are a great starting point for a designer to explore. It makes a lot of sense to visit scores of sites that are publicly accessible or sites where you have an account and navigate around to see how they handle various design elements.
To start, look at:
The point of this list of questions is that you can use it to build a set of criteria for designing what your enterprise will use and adopt, enthusiastically. But this is only a beginning. By actually visiting many sites outside your enterprise, you will find features that you never thought to include or aggravations that you will surely want to avoid. From these experiences on external sites, you can build up a good list of what is important to include or banish from your design.
When you find sites that you think are exemplary, ask key stakeholders to visit them and give you their feedback, preferences and dislikes. Particularly, you want to note what confuses them or enthusiastic comments about what excites them.
This post originated because several press notices in the past month brought to my attention Web applications that have sophisticated and very specialized search applications. I think they can provide terrific ideas for the enterprise search design team and also be used to demonstrate to your internal users just what is possible.
Check out these applications and articles: on KNovel, particularly this KNovel page; ThomasNet; EBSCOHost mentioned in this article about the "deep Web.". All these applications reveal superior search capabilities, have long track records, and are already used by enterprises every day. Because they are already successful in the enterprise, some by subscription, they are worth a second look as examples of how to approach your enterprise's search interface design.
]]>First it explains why none of the articles I write for this blog about enterprise search appear in Google alerts for “enterprise search.” Besides being a personal annoyance, easily resolved if I invested in some Internet search optimization, it may explain why meta tagging is a hard sell behind the firewall.
I do know something about getting relevant content to show up in enterprise search systems and it does depend on a layer of what I call “value-added metadata” by someone who knows the subject matter in target content and the audience. Working with the language of the enterprise audience that relies on finding critical content to do their jobs, a meta tagger will bring out topical language known to be the lingua franca of the dominant searchers as well as the language that will be used by novice employee searchers. The key here is to recognize that in any specific piece of content its “aboutness” may never be explicitly spelled out in terminology by the author.
In one example, let’s consider some fundamental HR information about “holiday pay” or “compensation for holidays” or “compensation for time-off.” The strings in quotes were used throughout documents on the intranet of one organization where I consulted. When some complained about not being able to find this information using the company search system, my review of search logs showed a very large number of searches for “vacation pay” and almost no searches for “compensation” or “holidays” or “time off.” Thus, there was no way that using the search engine employees would stumble upon the useful information they are seeking – unless, meta tags make “vacation pay” a retrievable index pointer to these documents. The tagger would have analyzed the search logs, seen the high number of searches for that phrase and realized that it was needed as a meta tag.
Now, back to Google’s position on ignoring meta tags because writers and marketing managers were “gaming the system.” They were adding tags they thought would be popular to get people to look at content not related but for which they were seeking a huge audience.
I have heard the concern that people within enterprises might also hijack the usefulness of content they were posting in blogs or wikis to get more “eyeballs” in the organization. This is a foolish concern, in my opinion. First I have never seen evidence that this happens and don’t believe that any productive enterprise has people engaging in this obvious foolishness.
More importantly, professional growth and success depends on the perceptions of others, their belief in you and your work, and the value of your ideas. If an employee is so foolish as to misdirect fellow employees to useless or irrelevant content, he is not likely to gain or keep the respect of his peers and superiors. In the long run persistent, misleading or mischievous meta tagging will have just the opposite effect, creating a pathway to the door.
Conversely, the super meta tagger with astute insights into what people are looking for and how they are most likely to look for it, will be the valued expert we all need to care for and spoon feed us our daily content. Trusted resources rise to the top when they are appropriately tagged and become bedrock content when revealed through enterprise search on well-managed intranets.
]]>I wrote about the IBM launch of the OmniFind suite of search products a couple of years ago with positive comments. The reality ended up being quite different as I noted later. Among the negatives were three that stand out in my mind. First, free (as in the IBM OmniFind Yahoo no-charge edition) is rarely attractive to serious enterprises looking for a well-supported product. Second, the substantial computing overhead for the free product was significant enough that some SMBs I know of were turned off; the costs associated with the hardware and support it would require offset "free." Third, my understanding that the search architecture for the free product would provide seamless upgrades to IBM's other OmniFind products was wrong. Each subsequent product adoption would require the same "rip and replace" that Steve Arnold describes in his report, Beyond Search. It is hard to believe that IBM got much traction out of this offering from the enterprise search market at large. Does anyone know if there was really any head-to-head competition between IBM and other search vendors over this product?
On the other hand, does the Microsoft Express Search offering appeal to enterprises other than the traditional Microsoft shop? If Microsoft Express Search went away, it would probably be replaced by some other Microsoft search variation with inconvenience to the customer who needs to rip and replace and left on his own to grumble and gripe. What else is new? The same thing would happen with IBM Yahoo OmniFind users and they would adapt.
I've noticed that free and cheap products may become heavily entrenched in the marketplace but not among organizations likely to upgrade any time soon. Once enterprises get immersed in a complex implementation (and search done well does require that) they won't budge for a long, long time, even if the solution is less than optimal. By the time they are compelled to upgrade they are usually so wedded to their vendor that they will accept any reasonable offer to upgrade that the vendor offers. Seeking competitive options is really difficult for most enterprises to pursue without an overwhelmingly compelling reason.
This additional news item indicates that Microsoft is still trying to get their search strategy straightened out with another new acquisition, Applied Discovery Selects Microsoft FAST for Advanced E-Discovery Document Search. E-discovery is a hot market in legal, life sciences and financial verticals but firms like ISYS, Recommind, Temis, and ZyLab are already doing well in that arena. It will take a lot of effort to displace those leaders, even if Microsoft is the contender. Enterprises are looking for point solutions to business problems, not just large vendors with a boatload of poorly differentiated products. There is plenty of opportunity for specialized vendors without going toe-to-toe with the big folks.
]]>Like other topics in this blog this one requires a readjustment in thinking by technology users. One of the great things about digitizing text was the promise of ways in which it could be parsed, sorted and analyzed. With heavy adoption of databases that specialized in textual, as well as numeric and date data fields for business applications in the 1960s and 70s, it became much easier for non-technical workers to look at all kinds of data in new ways. Early database applications leveraged their data stores using command languages; the better ones featured statistical analysis and publication quality report builders. Three that I was familiar with were DRS from ADM, Inc., BASIS from Battelle Columbus Labs and INQUIRE from IBM.
Tools that accompanied database back-ends had the ability to extract, slice and dice the database content, including very large text fields to report: word counts, phrase counts (breaking on any delimiter), transaction counts, relationships among data elements across associated record types, ability to create relationships on the fly, report expert activity and working documents, and describe distribution of resources. These are just a few examples of how new content assets could be created for export in minutes. In particular, a sort command with DRS had histogram controls that were invaluable to my clients managing corporate document and records collections, news clippings files, photographs, patents, etc. They could evaluate their collections by topic, date ranges, distribution, source, and so on, at any time.
So, there existed years ago the ability to connect data structures and use a command language to formulate new data models that informed and elucidated how information was being used in the organization, or to illustrate where there were holes in topics related to business initiatives. What were the barriers to wide-spread adoption? Upon reflection, I came to realize that extracting meaningful content from database in new and innovative formats requires a level of abstract thinking for which most employees are not well-trained. Putting descriptive data into a database via a screen form, then performing a transaction on the object of that data on another form, and then adding more data about another similar but different object are isolated in the database user's experience and memory. The typical user is not trained to think about how the pieces of data might be connected in the database and therefore is not likely to form new ideas of how it can all be extracted in a report with new information about the content. There is a level of abstraction that eludes most workers whose jobs consist of a lot of compartmentalized tasks.
It was exciting to encounter prospects that really grasped the power of these tools and were excited to push the limits of the command language and reporting applications, but they were scarce. It turned out that our greatest use came in applying text analytics to the extraction of valuable information from our customer support database. A rigorously disciplined staff populated it after every support call with not only demographic information about the nature of the call, linked to a customer record that had been created back at the first contact during the sales process (with appropriate updates along the way in the procurement process) but also a textual description of the entire transaction. Over time this database was linked to a "wish list" database and another "fixes" database and the entire networked structure provided extremely valuable reports that guided both development work and documentation production. We also issued weekly summary reports to the entire staff so everyone was kept informed about product conditions and customer relationships. The reporting tools provided transparency to all staff about company activity and enabled an early version of "social search collaboration."
Current text analytics products have significantly more algorithmic horsepower than the old command languages. But making the most of their potential and transforming them into utilities that any knowledge worker can leverage will remain a challenge for vendors in the face of poor abstract reasoning among much of the work force. The tools have improved but maybe not in all the ways they need to for widespread adoption. Workers should not have to be dependent on IT folks to create that unique analysis report that reveals a pattern or uncovers product flaws described by multiple customers. We expect workers to multitask, have many aptitudes and skills, and be self-servicing in so many aspects of their work, but for them to flourish the tools fall short too often. I'm putting in a big plug for text analytics for the masses, soon, so that enterprise search begins to deliver more than personalized lists of results for one person at a time. Give more reporting power to the user.
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