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Category: Enterprise search & search technology (Page 18 of 60)

Research, analysis, and news about enterprise search and search markets, technologies, practices, and strategies, such as semantic search, intranet collaboration and workplace, ecommerce and other applications.

Before we consolidated our blogs, industry veteran Lynda Moulton authored our popular enterprise search blog. This category includes all her posts and other enterprise search news and analysis. Lynda’s loyal readers can find all of Lynda’s posts collected here.

For older, long form reports, papers, and research on these topics see our Resources page.

Findability Issues Impact Everything Work Related

This should have been the last post of 2013 but you know how the holidays and weather (snow removal) get in the way of real work. However, throughout the month of December emails and messages, meetings, and reading peppered me with reminders that search surrounds everything we do. In my modest enterprise, findability issues occupy a major portion of my day and probably yours, too.

Deciding how important search is for workers in any enterprise is easy to determine if we think about how so many of us go about our daily work routines:

  • Receiving and sending emails, text messages, voice mail,
  • Documenting and disseminating work results,
  • Attending meetings where we listen, contribute, view presentations and take notes,
  • Researching and studying new topics or legacy content to begin or execute a project

As content accrues, information of value that will be needed for future work activities, finding mechanisms come into play, or should. That is why I probably expend 50% of my day consuming content, determining relevance and importance, deciding where and how it needs to be preserved, and clearing out debris. The other 50% of the time is devoted to retrieving, digesting and creating new content, new formulations of found material. The most common outputs are the result of:

  • Evaluation of professionals who would be candidates for speaking at programs I help organize,
  • Studying for an understanding of client needs, challenges and work environments,
  • Evaluation of technology solutions and tools for clients and my own enterprise,
  • Responding to inquiries for information, introductions, how-to solve a problem, opinions about products, people or processes,
  • Preparing deliverables to clients related to projects

Without the means and methods of my finding systems, those used by my clients, and those in the public domain, no work would get done. It is just that simple.

So, what came at me in December that made the cut of information to be made findable? A lot, but here are just three examples.

Commentary on metadata and taxonomy governance was a major topic in one session I moderated at the Gilbane Conference in Boston, Dec. 3-4, 2013. All of the panelists shared terrific observations about how and why governance of metadata and taxonomies is enterprise-critical; from one came this post-conference blog post. It, Taxonomy Governance, was written by Heather Hedden, author of The Accidental Taxonomist and a frequent speaker on taxonomy topics. The point here: when you engage in any work activity to consistently organize and manage the professional content in your possession, you are governing that material for findability. Anything that improves the process in the enterprise, is going to be a findability plus, just as it is for your own content.

Also in December, the Boston KM Forum hosted Allan Lewis, an “informaticist” at Lahey Health in Massachusetts; he is responsible for an initiative that will support healthcare professionals’ sharing of information via social business software tools. As a healthcare informatics professional, working with electronic clinical data sets to better codify diagnostic information, Allan is engaging in an enterprise-wide project. It is based on the need for a common view of medical conditions, how to diagnose them, and assign accurate classification to ensure the best records. Here is an issue where the quality of governing rules will be reached through consensus among medical experts. Again, findability is a major goal of this effort for everyone in a system, from the clinicians who need to retrieve information to the business units who must track cases and outcomes for accountability.

Last, from among the hundreds of information resources crossing my desk last month came one, a “Thank you for donating to the Wikimedia Foundation. You are wonderful!” You might ask why this did not simply get filed away for my tax return preparation; it almost did but read on.

Throughout the year I have been involved in numerous projects that rely on my ability to find definitions or explanations of hundreds of topics outside my areas of expertise. Sometimes I use known resources, such as government agency web sites that specialize in a field, or those of professional associations and publications with content by experts in a domain. I depend on finding tools at those sites to get what I am looking for. You can be certain that I know which ones have quality findability and those with difficult to use search functions.

When all else fails, my Google search is usually formatted as “define: xxx yyy” to include a phrase or name I seek to better understand. A simple term or acronym will usually net a glossary definition but for more complex topics Wikipedia is the most prominent resource showing up in results. Sometimes it is just a “stub” with notations that the entry needs updating, but more often it is very complete with scores of links and citations to help further my research. During one period when I had been beating a path to its site on a frequent basis, a banner requesting a donation appeared and persisted. As a professional benefiting from its work, I contributed a very modest sum. When the thank you came, I found the entire correspondence compelling enough to share parts of it with my readers. The last paragraph is one I hope you will read because you are interested in “search” and probably have the knowledge to contribute content that others might search for. Contributions of money and your knowledge are both important.

It’s easy to ignore our fundraising banners, and I’m really glad you didn’t. This is how Wikipedia pays its bills — people like you giving us money, so we can keep the site freely available for everyone around the world.

People tell me they donate to Wikipedia because they find it useful, and they trust it because even though it’s not perfect, they know it’s written for them. Wikipedia isn’t meant to advance somebody’s PR agenda or push a particular ideology, or to persuade you to believe something that’s not true. …

You should know: your donation isn’t just covering your own costs. The average donor is paying for his or her own use of Wikipedia, plus the costs of hundreds of other people. …

Most people don’t know Wikipedia’s run by a non-profit. Please consider sharing this e-mail with a few of your friends to encourage them to donate too. And if you’re interested, you should try adding some new information to Wikipedia. If you see a typo or other small mistake, please fix it, and if you find something missing, please add it. There are resources here that can help you get started. Don’t worry about making a mistake: that’s normal when people first start editing and if it happens, other Wikipedians will be happy to fix it for you.

So, this is my opening for 2014, a reflection on what it means to be able to find what we need to do our work and keep it all straight. The plug for Wikipedia is not a shameless endorsement for any personal gain, just an acknowledgement that I respect and have benefitted from the collaborative spirit under which it operates. I am thanking them by sharing my experience with you.

Can Human Sensors Contribute to Improving Search Technology?

Information Today fall meetings usually have me in the Enterprise Search Summit sessions but this year KM World was my focus. Social networking, social media and tools are clearly entering the mainstream of the enterprise domain as important means of intra-company communication, as many corporate case presentations revealed. But it was Dave Snowden’s Thursday keynote, Big Data vs. Human Data, which encouraged me because he conveyed a message of how we must synthesize good knowledge management practices out of both human and machine-based information. Set aside 52+ minutes and be prepared to be highly stimulated by his talk .

Snowden does the deep thinking and research on these topics; at present, my best option is to try to figure out how to apply concepts that he puts forth to my current work.

Having long tried to get enterprises to focus on what people need to do to make search work meaningfully in an organization, instead of a list of technology specifications, I welcome messages like Snowden’s. Martin White called for information specialists for search management roles earlier this year in a CMSWire piece. While it may be a stretch to call for “search specialists” to act as “human sensors,” it does merit consideration. Search specialists have a critical role to play in any enterprise where knowledge assets (content and human expertise), data retrieval and analysis , and understanding user needs must fit cohesively together to deliver a searchable corpus that really works for an organization. This is not typically an assignment for a single IT professional focused on installing software, hardware and network oversight.

One of the intangible capital assets defined by a recent start-up, Smarter-Companies, Inc., is human capital. Founder Mary Adams has devised a methodology to be used by a person she calls an Icountant. An Icountant establishes values for intangible capital and optimizing its use. Adam’s method is a new way of thinking about establishing asset value for organizations whose real worth has more to do with people and other intangibles than fixed assets like buildings and equipment.

Let’s consider the merit of assigning value to search specialists, those experts who can really make search technology work optimally for any given enterprise. How should we value them? For what competencies will we be assigning jobs to individuals who will own or manage search technology selection, implementation/tuning and administration?

Rather than defaulting to outside experts for an evaluation process, installation and basic training for a particular technology, we need internal people who are more astute about characteristics of and human needs of an organization. High value human sensors have deep experience in and knowledge of an enterprise; this knowledge would take the consultant off-the-street months or years to accrue. People with experience as searchers and researchers supporting the knowledge intensive units of a company, with library and information science training in electronic information retrieval methods must be on the front lines of search teams.

Knowledge of users, what searchable content is essential across all business units, and what is needed just for special cases is a human attribute that search teams must have. Consider the points in White’s article and the wisdom of placing humans in charge of algorithm-based solutions. What aptitudes and understanding will move the adoption of any technology forward? Then pick the humans with highly tuned sensitivity to what will or will not work for the technology selection and deployment situation at hand. Let them place search technology in the role of augmenting human work instead of making human workers slaves to technology adaptation.

If you are at the Gilbane Conference next week, and want to further this discussion, please look for me and let me know what you think. Session E7 will have a special focus on search, Strategic Imperatives for Enterprise Search to Succeed, a Panel Discussion. I will be moderating.

Healthcare e-Commerce Search Lessons for the Enterprise

Search Tools Wanting on Many Exchanges: This headline was too good to pass up even though stories about the failures of the Affordable Care Act web site are wearing a little thin right now. For those of us long involved in developing, delivering and supporting large software solutions, we can only imagine all the project places that have brought about this massive melt-down. Seeing this result: “many who get through the log-in process on the new health insurance exchanges then have trouble determining whether the offered policies will provide the coverage they need”, we who spend hours on external and internal web sites know the frustrations very well. It is not the “search tools” that are lacking but the approach to design and development.

This current event serves as a cautionary tale to any enterprise attempting its own self-service web-site, for employees’ in-house use, customer service extranets or direct sales on public facing sites.

Here are the basic necessary requirements, for anyone launching large-scale site search, internally or externally.

Leadership in an endeavor of this scale requires deep understanding of the scope of the goals. All the goals must be met in the short term (enrollment of both the neediest without insurance AND enrollment of the young procrastinators), and scalable for the long term. What this requires is a single authority with:

  • Experience on major projects, global in reach, size and complexity
  • Knowledge of how all the entities in the healthcare industry work and inter-relate
  • Maturity, enough to understand and manage software engineers (designers), coders, business operations managers, writers, user interface specialists and business analysts with their myriad of personality types that will be doing the work to bring millions of computing elements into synch
  • The authority and control to hire, fire, and prioritize project elements.

Simplicity of site design to begin a proof of concept, or several proofs of concept, rolled out to real prospects using a minimalist approach with small teams. This a surer path to understanding what works and what doesn’t. Think of the approach to the Manhattan Project where multiple parallel efforts were employed to get to the quickest and most practical deployment of an atomic weapon. Groves had the leadership authority to shift initiative priorities as each group progressed and made a case for its approach. This more technically complex endeavor was achieved over a 4 year period, only one year more than this government healthcare site development. Because the ability to find information is the first step for almost every shopper, it makes sense to get search and navigation working smoothly first, even as content targets and partner sites are being readied for access. Again, deep understanding of the audience, what it wants to know first and how that audience will go about finding it is imperative. Usability experts with knowledge of the healthcare industry would be critical in such an effort. The priority is to enable a search before requiring identity. Forcing enrollment of multitudes of people who just want to search, many of whom will never become buyers (e.g. counselors, children helping elderly parents find information, insurers wanting to verify their own linkages and site flow from the main site) is madness. No successful e-commerce site demands this from a new visitor and the government healthcare site has no business harvesting a huge amount of personal data that it has no use for (i.e. marketing).

Hundreds of major enterprises have failed at massive search implementations because the focus was on the technology instead of the business need, the user need and content preparation. Good to excellent search will always depend on an excellent level of organization and categorization for the audience and use intended. That is how excellent e-commerce sites flourish. Uniformity, normalization, and consistency models take time to build and maintain. They need smart people with time to think through logical paths to information to do this work. It is not a task for programmers or business managers. Content specialists and taxonomists who have dealt with content in healthcare areas for years are needed.

How a public project could fail so badly will eventually be examined and the results made known. I will wager that these three basic elements were missing from day one: a single strong leader, a simple, multi-track development approach with prototyping and attention to preparing searchable content for the target audience. Here is a lesson learned for your enterprise.

What Experts Say about Enterprise Search: Content, Interface Design and User Needs

This recap might have the ring of an old news story but these clips are worth repeating until more enterprises get serious about making search work for them, instead of allowing search to become an expensive venture in frustration. Enterprise Search Europe, May 14-16, 2013, was a small meeting with a large punch. My only regret is that the audience did not include enough business and content managers. I can only imagine that the predominant audience members, IT folks, are frustrated that the people whose support they need for search to succeed were not in attendance to hear the messages.

Here are just a few of the key points that business managers and those who “own” search budgets need to hear.

On Day 1 I attended a workshop presented by Tony Russell-Rose [Managing Director, UXLabs and co-author of Designing the Search Experience, also at City University London], Search Interface Design. While many experts talk about the two top priorities for search success, recall (all relevant results returned) and precision (all results returned are relevant), they usually fail to acknowledge a hard truth. We all want “the whole truth and nothing but the truth,” but as Tony pointed out, we can’t have both. He went on to offer this general guidance on the subject; recall in highly regulated or risk intensive business is most important but in e-commerce we tend to favor precision. I would add that in enterprises that have to manage risk and sell products, there is a place for two types of search where priorities vary depending on the business purpose. My takeaway: universal, all-in-one search implementations across an enterprise will leave most users disappointed. It’s time to acknowledge the need for different types of implementations, depending on need and audience.

Ed Dale [Digital Platforms Product Manager, Ernst & Young (USA)] gave a highly pragmatic keynote at the meeting opening, The Six Drivers for Search Quality. The overarching theme was that search rests on content. He went on to describe the Ernst & Young drivers: the right content, optimized for search, constant tuning for optimal results, attention to a user interface that is effective for a user-type, attention to user needs, consistency in function and design. Ed closed with this guidance: develop your own business drivers based on issues that are important to users. Based on these and the company’s drivers, focus your efforts, remembering that you are not your users.

The Language of Discovery: A Toolkit for Designing Big Data Interfaces and Interactions was presented by Joseph Lamantia, [UX Lead: Discovery Products and Services, Oracle Endeca]. He shared the idea that discovery is the ability to understand data, and the importance of not treating data, by itself, as having value without achieving discovery. Discovery was defined as something you have seen, found, and made sense of in order to derive insight. It is achieved by grasping or understanding meaning and significance. What I found most interesting was the discussion of modes of searching that have grown out of a number of research efforts. Begin with slide 44, “Mediated Sense making” to learn the precursors that lead into his “modes” description. When considering search for the needy user, this discussion is especially important. We all discover and learn in different ways and the “mode” topic highlights the multitude of options to contemplate. [NOTE: Don’t overlook Joe’s commentary that accompanies the slides at the bottom of the SlideShare.]

Joe was followed by Tyler Tate, [Cofounder, TwigKit] on Information Wayfinding: A New Era of Discovery. He asked the audience to consider this question, “Are you facilitating the end-user throughout all stages of the information seeking process?” The stages are: initiation > selection > exploration > formulation > collection > action. This is a key point for those most involved in user interface design and content managers thinking about facet vocabulary and sorting results.

Steve Arnold [Arnold IT], always brings a “call to reality” aspect to his presentations and Big Data vs. Search was no different. On “Big Data” a couple of key points stick out, “More Data” is not just more data; it is different. As soon as we begin trying to “manage” it we have to apply methods and technologies to reduce it to dimensions that search systems can deal with. Search data processing has changed very little for the last 50 years and processing constraints limit indexing capabilities across these super large sets. There are great opportunities for creating management tools (e.g. analytics) for big data in order to optimize search algorithms, and make the systems more affordable and usable. Among Arnold’s observations was the incessant push to eliminate humans, getting away from techniques and methods [to enhance content] that work and replacing them with technology. He noted that all the camera and surveillance systems in Boston did not work to stop the Marathon bombers but people in the situation did limit casualties through quick medical intervention and providing descriptions of suspicious people who turned out to be the principal suspects. People must still be closely involved for search to succeed, regardless of the technology.

SharePoint lurks in every session at information technology conferences and this meeting was no exception. Although I was not in the room to hear the presentation, I found these slides from Agnes Molnar [International SharePoint Consultant, ECM & Search Expert, MVP] Search Based Applications with SharePoint 2013 to be among the most direct and succinct explanation of when SharePoint makes sense. It nicely explains where SharePoint fits in the enterprise search eco-landscape. Thanks to Agnes for the clarity of her presentation.

A rapid fire panel on “Trends and Opportunities” moderated by Allen Peltz-Sharpe [Research Director for Content Management & Collaboration, 451 Research] included Charlie Hull [Founder of Flax], Dan Lee of Artirix, Kristian Norling of Findwise (see Findwise survey results), Eric Pugh of OpenSource Connections and Rene Kreigler an independent search consultant. Among the key points offered by the panelists were:

  • There is a lot to accomplish to make enterprise search work after installing the search engine. When it comes to implementation and tuning there are often significant gaps in products and available tools to make search work well with other technologies.
  • Search can be leveraged to find signals of what is needed to improve the search experience.
  • Search as an enterprise application is “not sexy” and does not inspire business managers to support it enthusiastically. Its potential value and sustainability is not well understood, so managers do not view it as something that will increase their own importance.
  • Open source adoption is growing but does face challenges. VC backed companies in that arena will have a struggle to generate enough revenue to make VCs happy. The committer community is dominated by a single firm and that may weaken the staying power of other search (Lucene, Solr) open source committers.

A presentation late in the program by Kara Pernice, Managing Director of NN/g, Nielsen Norman Group, positioned the design of an intranet as a key element in making search compelling. Her insights reflect two decades of “Eyetracking Web Usability” done with Jakob Nielsen, and how that research applies for an intranet. Intranet Search Usability was the theme and Kara’s observations were keenly relevant to the audience.

Not the least of my three days at the meeting were side discussions with Valentin Richter CEO of Raytion, Iain Fletcher of Search Technologies, Martin Rugfelt of Expertmaker, Benoit Leclerc of Coveo, and Steve Andrews an advisor to Q-Sensei. These contributed many ideas on the state of enterprise search. I left the meeting with the overarching sense that enterprise leadership needs to be sold on the benefits for sustaining a search team as part of the information ecosystem. Bringing an understanding of search as not just being a technological, plug & play product and a “one-off” project is the challenge. Messaging is not getting through effectively. We need strong and clear business voices to make the case; the signals are too diffuse and that makes them weak. My take is that messages from search vendors all have valid points-of-view but when they are combined with too many other topics (e.g. “big data,” “analytics,” “open source,” SharePoint, “cloud computing”) basic concepts of what search is and where it belongs in the enterprise gets lost.

Search: a Term for the Long Haul, But…

There is no question that language influences marketing success; positioning software products has been a game of out-shining competitors with clever slogans and crafty coined terminology. Having been engaged with search technologies since 1974, and as the architect of a software application for enterprise content indexing and retrieval, I’ve observed how product positioning has played out in the enterprise search market over the years. When there is a new call for re-labeling “search,” the noun defining software designed for retrieving electronic content, I reflect on why and whether a different term would suffice.

Here is why a new term is not needed and the reasons why. For the definition of software algorithms that are the underpinning of finding and retrieving electronic content, regardless of native format, the noun search is efficient, to-the-point, unambiguous and direct.

We need a term that covers this category of software that will stand the test of time, as has automobile, which originated after terms too numerous to fully list had been tested: horseless buggy, self-contained power plant, car, motor vehicle, motor buggy, road engine, steam-powered wheeled vehicles, electric carriage, and motor wagon to name a few. Finally a term defined as a self-powered vehicle, was coined, “automobile.” It covered all types of self-powered “cars,” not just those pulled by another form of locomotive as is a rail car. Like the term “search,” automobiles are often qualified by modifiers, such as “electric,” “hybrid” or “sedan” versus “station wagon.” Search may be coupled with “Web” versus “Enterprise,” or “embedded” versus “stand-alone.” In the field of software technology we need and generally understand the distinctions.

So, I continue to be mystified by rhetoric that demands a new label but I am willing to concede where we need to be more precise, and that may be what the crowd is really saying. When and where the term is applied deserves reconsideration. Technologists who build and customize search software should be able to continue with the long established lingo, but marketers and conferences or meetings to educate a great variety of search users could probably do a better job of expressing what is available to non-techies. As one speaker at Enterprise Search Europe 2013 (ESEu2013) stated and others affirmed, “search” is not a project and to that I will add, nor is it a single product. Instead it is core to a very large and diverse range of products.

Packaging Software that includes Search Technology

Vendors are obviously aware of where they need to be marketing and the need to package for their target audience. There are three key elements that have contributed to ambiguity and resulted in a lethargic reaction in the so-called enterprise search marketplace in recent years: overly complex and diffuse categorization, poor product labeling and definition, and usability and product interface design that does not reflect an understanding of the true audience for a product. What can be done to mitigate confusion?

  1. Categorizing what is being offered has to speak to the buyer and potential user. When a single product is pitched to a dozen different market categories (text mining, analytics, content management, metadata management, enterprise search, big data management, etc.) buyers are skeptical and wary of all-in-one claims. While there are software packages that incorporate many or elements of a variety of software applications, diffusion ends up fracturing the buying audience into such minute numbers that a vendor does not gain real traction across the different types of needs. Recommendation: a product must be categorized to its greatest technical strengths and the largest audience to which it will appeal. The goal is to be a strong presence in the specific marketplaces where those buyers go to seek products. When a product has outstanding capabilities for that audience, buyers will be delighted to also find additional ancillary functions and features that are already built in.
  2. Software that is built on search algorithms or that embeds search must be packaged with labeling that pays attention to a functional domain and the target audience. Clear messaging that speaks to the defined audience is the wrapper for the product. It must state what and why you have a presence in this marketplace, the role the product plays and the professional functions that will benefit from its use. Messaging is how you let the audience know that you have created tools for them.
  3. Product design requires a deep understanding of professional users and their modes of pursuing business goals. At ESEu2013 several presentations and one workshop focused on usability and design; speakers all shared a deep understanding of differences across professional users. They recognized behavioral, cultural, geographic and mode preferences as key considerations without stating explicitly that different professional groups each work in unique ways. I assert that this is where so many applications break-down in design and implementation. Workflow design, look-and-feel, and product features must be very different for someone in accounting or finance versus an engineer or attorney. Highly successful software applications are generally initiated and development is sustained by professionals who need these tools to do their work, their way. Without deep professional knowledge embedded in product design teams, products often miss the market’s demands. Professionals bring know-how, methods and practices to their jobs and it is not the role of software developers to change the way they go about their business by forcing new models that are counter to what is intuitive in a market segment.

Attention to better software definition leads to the next topic.

Conference and meeting themes: Search technology versus business problems to be solved

Attention to conference and meeting content was the reason for this post. Having given an argument for keeping the noun search in our vocabulary, I have also acknowledged that it is probably a failed market strategy to label and attach messaging to every software product with search as either, enterprise search or web search. Because search is everywhere in almost every software application, we need conferences with exhibits that target more differentiated (and selective) audiences.

The days of generic all-in-one meetings like AIIM, the former National Online Meeting (Information Today’s original conference), E2, and so on may have run their course. As a failed conference attendee, my attention span lasts for about one hour maximum, and results in me listening to no more than a half dozen exhibitor pitches before I become a wandering zombie, interested in nothing in particular because there is nothing specific to be drawn to at these mega-conferences.

I am proposing a return to professionally oriented programs that focus on audience and business needs. ESEu2013 had among its largest cohort, developers and software implementers. There were few potential users, buyers, content or metadata managers, or professional search experts but these groups seek a place to learn about products without slides showing snippets of programming code. There is still a need for meetings that include the technologists but it is difficult to attract them to a meeting that only offers programming sessions for users, the people for whom they will develop products. How do we get them into a dialogue with the very people for whom they are developing and designing products? How can vendors exhibit and communicate their capabilities for solving a professional problem when their target professional audience is not in the room.

At Enterprise Search Europe 2013, the sessions were both diverse and enlightening but, as I noted at the conference wrap-up, each track spoke to a unique set of enterprise needs and variety of professional interests. The underlying technology, search, was the common thread and yet each track might have been presented in a totally different meeting environment. One topic, Big Data, presents challenges that need explaining and information seekers come to learn about products for effectively leveraging it in a number of enterprise environments. These cases need to be understood as business problems, which call for unique software applications not just some generic search technology. Big data can and is already being offered as a theme for an entire conference where the emphasis on aspects of search technology is included. As previously noted topics related to big data problems vary: data and text mining, analytics, semantic processing aka natural language processing, and federation. However, data and text mining for finance has a totally different contextual relevance than for scientists engaged in genomics or targeted drug therapy research, and each audience looks for solutions in its field.

So, let’s rethink what each meeting is about, who needs to be in the room for each business category, what products are clearly packaged for the audience and the need, and schedule programs that bring developers, implementers, buyers and users into a forum around specially packaged software applications for meaningful dialogue. All of this is said with sincere respect for my colleagues who have suggested terms that range from “beyond search” to “discovery” and “findability” as alternative to “search. Maybe the predominant theme of the next Enterprise Search conference should be Information Seeking: Needs, Behaviors and Applications with tracks organized accordingly.

[NOTE: Enterprise Search Europe had excellent sessions and practical guidance. Having given a “top of mind” reaction to what we need to gain a more diverse audience in the future, my next post will be a litany of the best observations, recommendations and insights from the speakers.]

Leveraging Search in Small Enterprises

A mantra for a small firm or start-up in the 1970s when “Big Blue” was the standard for top notch sales and selling was we need to out-IBM the IBMers.

Search is just one aspect of being able to find what you need to leverage knowledge assets in your work, whether you are in a small firm, a part of a small group in a large organization or an individual consultant seeking to maximize the masses of content and information surrounding you in work.

My thoughts are inspired by the question asked by Andreas Gruber of Informations und Wissensmanagement in this recent post on Enterprise Search Engine Professionals, LinkedIn group. He posed a request for information stating: For enterprise search solutions for (very) small enterprises (10 to 200 employees), I find it hard to define success factors and it seems, that there are not many examples available. If you follow e.g. the critical success factors from the Martin White’s Enterprise Search book, most of them doesn’t seem to work for a small company – simply because none of them can/will investment in a search team etc.

The upcoming Enterprise Search Europe meeting (May 14-16, 2013) in London is one focus of my attention at present. Since Martin White is the Chairman and principal organizer, Andreas’ comments resonated immediately. Concurrently, I am working on a project for a university department, which probably falls in the category of “small enterprise”. The other relevant project on my desk is a book I am co-authoring on “practical KM” and we certainly aim to appeal to the individual practitioner or groups limited by capital resources. These areas of focus challenge me to respond to Andreas’ comments because I am certain they are top of mind for many and the excellent comments already at the posting show that others have good ideas about the topic, as well.

Intangible capital is particularly significant in many small firms, academia, and for independent consultants, like me. Intensive leveraging of knowledge in the form of expertise, relationships, and processes is imperative in these domains. Intangible capital, as a percent of most businesses currently surpasses tangible capital in value, according to Mary Adams founder of Smarter-Companies. Because intangible capital takes more thought and effort to identify, find or aggregate than hard assets, tools are needed to uncover, discover and pinpoint it.

Let’s take the example of expertise, an indisputable intangible asset of any professional services. For any firm, asking expert staff to put an explicit value on their knowledge, competencies or acumen for tackling the type of problem that you need to have solved may give you a sense of value but you need more. The firm or professional you want to hire must be able to back up its value by providing explicit evidence that they “know their stuff” and can produce. For you, search is a tool to lead you to public or published evidence. For the firm being asked to bid on your work, you want them to be able to produce additional evidence. Top quality firms do put both human and technology search resources to work to service existing projects and clients, and to provide evidence of their qualifications, when being asked to retrieve relevant work or references. Search tools and content management methods are diverse and range from modest to very expensive in scope but no firm can exist for long without technology to support the findability of its intangible capital.

To summarize, there are three principal ways that search pays off in the small-medium business (SMB) sector. Citing a few examples of each they are:

  • Finding expertise (people): potential client engagement principal or team member, answers to questions to fulfill a clients engagement, spurring development or an innovation initiative
  • Retrieving prior work: reuse of know-how in new engagements, discovery of ideas previously tabled, learning, documentation of products and processes, building a proposal, starting point for new work, protecting intellectual property for leverage, when patenting, or participating in mergers and acquisitions.
  • Creating the framework for efficiency: time and speed, reinforcing what you know, supporting PR, communications, knowledge base, portraying the scope of intellectual capital (if you are a target for acquisition), the extent of your partnerships that can expand your ability to deliver, creating new offerings (services) or products.

So, to conclude my comment on Andreas’ posting, I would assert that you can “out-IBM the IBMers” or any other large organization by employing search to leverage your knowledge, people and relationships in smart and efficient ways. Excellent content and search practices can probably reduce your total human overhead because even one or two content and search specialists plus the right technology can deliver significant efficiency in intangible asset utilization.

I hope to see conference attendees who come from that SMB community so we can continue this excellent discussion in London, next month. Ask me about how we “ate our own dog-food” (search tools) when I owned a small software firm in the early 1980s. The overhead was minimal compared to the savings in support headcount.

Launching Your Search for Enterprise Search Fundamentals

It’s the beginning of a new year and you are tasked with responsibility for your enterprise to get top value from the organization’s information and knowledge assets. You are the IT applications specialist assigned to support individual business units with their technology requests. You might encounter situations similar to these:

  • Marketing has a major initiative to re-write all product marketing pieces.
  • Finance is grappling with two newly acquired companies whose financial reports, financial analyses, and forecasts are scattered across a number of repositories.
  • Your Legal department has a need to categorize and analyze several thousand “idea records” that came from the acquired companies in order to be prepared for future work, patenting new products.
  • Research and development is attempting to categorize, and integrate into a single system, R&D reports from an existing repository with those from the acquisitions.
  • Manufacturing requires access to all schematics for eight new products in order to refine and retool manufacturing processes and equipment in their production area.
  • Customer support demands just-in-time retrieval and accuracy to meet their contractual obligations to tier-one customers, often from field operations, or while in transit to customer sites. The latter case often requires retrieval of a single, unique piece of documentation.

All of these groups have needs, which if not met present high risk or even exposure to lawsuits from clients or investors. You have only one specialist on staff who has had two years of experience with a single search engine, but who is currently deployed to field service operations.

Looking at just these few examples we can see that a number of search related technologies plus human activities may be required to meet the needs of these diverse constituents. From finding and assembling all financial materials across a five-year time period for all business units, to recovering scattered and unclassified emails and memos that contain potential product ideas, the initiative may be huge. A sizable quantity of content and business structural complexity may require a large scale effort just to identify all possible repositories to search for. This repository identifying exercise is a problem to be solved before even thinking about the search technologies to adopt for the “finding” activity.

Beginning the development of a categorizing method and terminology to support possible “auto-categorization” might require text mining and text analysis applications to assess the topical nomenclature and entity attributes that would make a good starting point. These tools can be employed before the adoption of enterprise search applications.

Understanding all the “use-cases” for which engineers may seek schematics in their re-design and re-engineering of a manufacturing plant is essential to selecting the best search technology for them and testing it for deployment.

The bottom line is there is a lot more to know about content and supporting its accessibility with search technology than acquiring the search application. Furthermore, the situations that demand search solutions within the enterprise are far different, and their successful application requires far greater understanding of user search expectations than Web searching for a product or general research on a new topic.

To meet the full challenge of providing the technologies and infrastructure that will deliver reliable and high value information and knowledge when and where required, you must become conversant with a boatload of search related topics. So, where do you begin?

A new primer, manageable in length and logical in order has just been published. It contains the basics you will need to understand the enterprise context for search. A substantive list of reading resources, a glossary and vendor URL list round out the book. As the author suggests, and I concur, you should probably begin with Chapter 12, two pages that will ground you quickly in the key elements of your prospective undertaking.

What is the book? Enterprise Search (of course) by Martin White, O’Reilly Media, Inc., Sebastopol, CA. © 2013 Martin White. 192p. ISBN: 978-1-449-33044-6. Also available as an online edition at: http://my.safaribooksonline.com/book/databases/data-warehouses/9781449330439

Enterprise Search Strategies: Cultivating High Value Domains

At the recent Gilbane Boston Conference I was happy to hear many remarks positioning and defining “Big Data” and the variety of comments. Like so much in the marketing sphere of high tech, answers begin with technology vendors but get refined and parsed by analysts and consultants, who need to set clear expectations about the actual problem domain. It’s a good thing that we have humans to do that defining because even the most advanced semantics would be hard pressed to give you a single useful answer.

I heard Sue Feldman of IDC give a pretty good “working definition” of big data at the Enterprise Search Summit in May, 2012. To paraphrase is was:

  • > 100 TB up to petabytes, OR
  • > 60% growth a year of unstructured and unpredictable content, OR
  • Ultra high streaming content

But we then get into debates about differentiating data from unstructured content when using a phrase like “big data” and applying it to unstructured content, which knowledge strategists like me tend to put into a category of packaged information. But never mind, technology solution providers will continue to come up with catchy buzz phrases to codify the problem they are solving, whether it makes semantic sense or not.

What does this have to do with enterprise search? In short, “findability” is an increasingly heavy lift due to the size and number of content repositories. We want to define quality findability as optimal relevance and recall.

A search technology era ago, publishers, libraries, content management solution providers were focused on human curation of non-database content, and applying controlled vocabulary categories derived from decades of human managed terminology lists. Automated search provided highly structured access interfaces to what we now call unstructured content. Once this model was supplanted by full text retrieval, and new content originated in electronic formats, the proportion of human categorized content to un-categorized content ballooned.

Hundreds of models for automatic categorization have been rolled out to try to stay ahead of the electronic onslaught. The ones that succeed do so mostly because of continued human intervention at some point in the process of making content available to be searched. From human invented search algorithms, to terminology structuring and mapping (taxonomies, thesauri, ontologies, grammar rule bases, etc.), to hybrid machine-human indexing processes, institutions seek ways to find, extract, and deliver value from mountains of content.

This brings me to a pervasive theme from the conferences I have attended this year, the synergies among text mining, text analytics, extractor/transformer/loader (ETL), and search technologies. These are being sought, employed and applied to specific findability issues in select content domains. It appears that the best results are delivered only when these criteria are first met:

  • The business need is well defined, refined and narrowed to a manageable scope. Narrowing scope of information initiatives is the only way to understand results, and gain real insights into what technologies work and don’t work.
  • The domain of content that has high value content is carefully selected. I have long maintained that a significant issue is the amount of redundant information that we pile up across every repository. By demanding that our search tools crawl and index all of it, we are placing an unrealistic burden on search technologies to rank relevance and importance.
  • Apply pre-processing solutions such as text-mining and text analytics to ferret out primary source content and eliminate re-packaged variations that lack added value.
  • Apply pre-processing solutions such as ETL with text mining to assist with content enhancement, by applying consistent metadata that does not have a high semantic threshold but will suffice to answer a large percentage of non-topical inquiries. An example would be to find the “paper” that “Jerry Howe” presented to the “AMA” last year.

Business managers together with IT need to focus on eliminating redundancy by utilizing automation tools to enhance unique and high-value content with consistent metadata, thus creating solutions for special audiences needing information to solve specific business problems. By doing this we save the searcher the most time, while delivering the best answers to make the right business decisions and innovative advances. We need to stop thinking of enterprise search as a “big data,” single engine effort and instead parse it into “right data” solutions for each need.

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