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Category: Collaboration and workplace (Page 33 of 97)

This category is focused on enterprise / workplace collaboration tools and strategies, including office suites, intranets, knowledge management, and enterprise adoption of social networking tools and approaches.

Coherence and Augmentation: KM-Search Connection

This space is not normally used to comment on knowledge management (KM), one of my areas of consulting, but a recent conference gives me an opening to connect the dots between KM and search. Dave Snowden and Tom Stewart always have worthy commentary on KM and as keynote speakers they did not disappoint at KMWorld. It may seem a stretch but by taking a few of their thoughts out of context, I can synthesize a relationship between KM and search.

KMWorld, Enterprise Search Summit, SharePoint Symposium and Taxonomy Boot Camp moved to Washington D.C. for the 2010 Fall Conference earlier this month. I attended to teach a workshop on building a semantic platform, and to participate in a panel discussion to wrap up the conference with two other analysts, Leslie Owen and Tony Byrne with Jane Dysart moderating.

Comments from the first and last keynote speakers of the conference inspired my final panel comments, counseling attendees to lead by thoughtfully leveraging technology only to enhance knowledge. But there were other snippets that prompt me to link search and KM.

Tom Stewart’s talk was entitled, Knowledge Driven Enterprises: Strategies & Future Focus, which he couched in the context of achieving a “coherent” winning organization. He explained that to reach the coherence destination requires understanding of different types of knowledge and how we need to behave for attaining each type (e.g. “knowable complicated “knowledge calls for experts and research; “emergent complex” knowledge calls for leadership and “sense-making.”).

Stewart describes successful organizations as those in which “the opportunities outside line up with the capabilities inside.” He explains that those “companies who do manage to reestablish focus around an aligned set of key capabilities” use their “intellectual capital” to identify their intangible assets,” human capability, structural capital, and customer capital. They build relationship capital from among these capabilities to create a coherent company. Although Stewart does not mention “search,” it is important to note that one means to identify intangible assets is well-executed enterprise search with associated analytical tools.

Dave Snowden also referenced “coherence,” (messy coherence), even as he spoke about how failures tend to be more teachable (memorable) than successes. If you follow Snowden, you know that he founded the Cognitive Edge and has developed a model for applying cognitive learning to help build resilient organizations. He has taught complexity analysis and sense-making for many years and his interest in human learning behaviors is deep.

To follow the entire thread of Snowden’s presentation on the “The Resilient Organization” follow this link. I was particularly impressed with his statement about the talk, “one of the most heart-felt I have given in recent years.” It was one of his best but two particular comments bring me to the connection between KM and search.

Dave talked about technology as “cognitive augmentation,” its only truly useful function. He also puts forth what he calls the “three Golden rules: Use of distributed cognition, wisdom but not foolishness of crowds; finely grained objects, information and organizational; and disintermediation, putting decision makers in direct contact with raw data.”

Taking these fragments of Snowden’s talk, a technique he seems to encourage, I put forth a synthesized view of how knowledge and search technologies need to be married for consequential gain.

We live and work in a highly chaotic information soup, one in which we are fed a steady diet of fragments (links, tweets, analyzed content) from which we are challenged as thinkers to derive coherence. The best knowledge practitioners will leverage this messiness by detecting weak signals and seek out more fragments, coupling them thoughtfully with “raw data” to synthesize new innovations, whether they be practices, inventions or policies. Managing shifting technologies, changing information inputs, and learning from failures (our own, our institution’s and others) contributes to building a resilient organization.

So where does “search” come in? Search is a human operation and begins with the workforce. Going back to Stewart who commented on the need to recognize different kinds of knowledge, I posit that different kinds of knowledge demand different kinds of search. This is precisely what so many “enterprise search” initiatives fail to deliver. Implementers fail to account for all the different kinds of search, search for facts, search for expertise, search for specific artifacts, search for trends, search for missing data, etc.

When Dave Snowden states that “all of your workforce is a human scanner,” this could also imply the need for multiple, co-occurring search initiatives. Just as each workforce member brings a different perspective and capability to sensory information gathering, so too must enterprise search be set up to accommodate all the different kinds of knowledge gathering. And when Snowden notes that “There are limits to semantic technologies: Language is constantly changing so there is a requirement for constant tuning to sustain the same level of good results,” he is reminding us that technology is only good for cognitive augmentation. Technology is not a “plug ‘n play,” install and reap magical cognitive insights. It requires constant tuning to adapt to new kinds of knowledge.

The point is one I have made before; it is the human connection, human scanner and human understanding of all the kinds of knowledge we need in order to bring coherence to an organization. The better we balance these human capabilities, the more resilient we’ll be and the better skilled at figuring out what kinds of search technologies really make sense for today, and tomorrow we had better be ready for another tool for new fragments and new knowledge synthesis.

Understanding the Smart Content Technology Landscape

If you have been following recent XML Technologies blog entries, you will notice we have been talking a lot lately about XML Smart Content, what it is and the benefits it can bring to an organization. These include flexible, dynamic assembly for delivery to different audiences, search optimization to improve customer experience, and improvements for distributed collaboration. Great targets to aim for, but you may ask are we ready to pursue these opportunities? It might help to better understand the technology landscape involved in creating and delivering smart content.

The figure below illustrates the content technology landscape for smart content. At the center are fundamental XML technologies for creating modular content, managing it as discrete chunks (with or without a formal content management system), and publishing it in an organized fashion. These are the basic technologies for “one source, one output” applications, sometimes referred to as Single Source Publishing (SSP) systems.

smart technology landscape

The innermost ring contains capabilities that are needed even when using a dedicated word processor or layout tool, including editing, rendering, and some limited content storage capabilities. In the middle ring are the technologies that enable single-sourcing content components for reuse in multiple outputs. They include a more robust content management environment, often with workflow management tools, as well as multi-channel formatting and delivery capabilities and structured editing tools. The outermost ring includes the technologies for smart content applications, which are described below in more detail.

It is good to note that smart content solutions rely on structured editing, component management, and multi-channel delivery as foundational capabilities, augmented with content enrichment, topic component assembly, and social publishing capabilities across a distributed network. Descriptions of the additional capabilities needed for smart content applications follow.

Content Enrichment / Metadata Management: Once a descriptive metadata taxonomy is created or adopted, its use for content enrichment will depend on tools for analyzing and/or applying the metadata. These can be manual dialogs, automated scripts and crawlers, or a combination of approaches. Automated scripts can be created to interrogate the content to determine what it is about and to extract key information for use as metadata. Automated tools are efficient and scalable, but generally do not apply metadata with the same accuracy as manual processes. Manual processes, while ensuring better enrichment, are labor intensive and not scalable for large volumes of content. A combination of manual and automated processes and tools is the most likely approach in a smart content environment. Taxonomies may be extensible over time and can require administrative tools for editorial control and term management.

Component Discovery / Assembly: Once data has been enriched, tools for searching and selecting content based on the enrichment criteria will enable more precise discovery and access. Search mechanisms can use metadata to improve search results compared to full text searching. Information architects and organizers of content can use smart searching to discover what content exists, and what still needs to be developed to proactively manage and curate the content. These same discovery and searching capabilities can be used to automatically create delivery maps and dynamically assemble content organized using them.

Distributed Collaboration / Social Publishing: Componentized information lends itself to a more granular update and maintenance process, enabling several users to simultaneously access topics that may appear in a single deliverable form to reduce schedules. Subject matter experts, both remote and local, may be included in review and content creation processes at key steps. Users of the information may want to “self-organize” the content of greatest interest to them, and even augment or comment upon specific topics. A distributed social publishing capability will enable a broader range of contributors to participate in the creation, review and updating of content in new ways.

Federated Content Management / Access: Smart content solutions can integrate content without duplicating it in multiple places, rather accessing it across the network in the original storage repository. This federated content approach requires the repositories to have integration capabilities to access content stored in other systems, platforms, and environments. A federated system architecture will rely on interoperability standards (such as CMIS), system agnostic expressions of data models (such as XML Schemas), and a robust network infrastructure (such as the Internet).

These capabilities address a broader range of business activity and, therefore, fulfill more business requirements than single-source content solutions. Assessing your ability to implement these capabilities is essential in evaluating your organizations readiness for a smart content solution.

You Are Your Organization’s Chief Collaboration Officer

There have been a couple of interesting blog posts about organizational collaboration leadership penned recently by respected, influential thinkers. Last week, Morten Hansen and Scott Tapp published Who Should Be Your Chief Collaboration Officer? on the Harvard Business Review site. Yesterday, Dion Hinchcliffe posted Who should be in charge of Enterprise 2.0? on Enterprise Irregulars.

It is logical that the question of the proper seat of ownership for enterprise collaboration efforts is being raised frequently at this moment. Many organizations are starting the process of rationalizing numerous, small collaboration projects supported by enterprise social software. Those social pilots not only need to be reconciled with each other, but with legacy collaboration efforts as well. That effort requires leadership and accountability.

Both of the posts cited above – as well as the comments made on them – add valuable ideas to the debate about who should be responsible for stimulating and guiding collaboration efforts within organizations. However, both discussions miss a critical conclusion, which I will make below. First, allow me to share my thoughts on the leadership models suggested in the posts and comments.

While it is critical to have collaboration leadership articulated and demonstrated at the senior executive level, the responsibility for enterprise collaboration cannot rest on one person, especially one who is already extremely busy and most likely does not have the nurturing and coaching skills needed for the job. Besides, any function that is so widely distributed as collaboration cannot be owned by one individual; organizations proved that long ago when they unsuccessfully appointed Chief Knowledge Officers.

Governance of enterprise collaboration can (and should) be provided by a Collaboration Board. That body can offer and prescribe tools, and establish and communicate policy, as well as good practices. However, they cannot compel others in the organization to collaborate more or better. Yes, Human Resources can measure and reward collaboration efforts of individuals, but they can only dangle the carrot; I have never seen an organization punish an employee for not collaborating when they are meeting other goals and objectives that are given higher value by the organization.

There is only one person (or many, depending on your perspective) for the job of actively collaborating – YOU! Ultimately, each individual in the organization is responsible for collaboration. He can be encouraged and incented to collaborate, but the will to work with others must come from the individual.

Collaboration in the enterprise is similar in this regard to knowledge management, where the notion of Personal Knowledge Management (PKM) has been gaining acceptance. PKM advocates believe that having each member of the organization capture, share, and reuse knowledge, in ways that benefit them personally, is far more effective than corporate mandated knowledge management efforts, which generally produce benefits for the enterprise, but not the individuals of which it is comprised.

So it is with collaboration. If an individual does not see any direct benefit from working with others, they will not do so. Conversely, if every employee is empowered to collaborate and rewarded in ways that make their job easier, they will.

The Enterprise 2.0 movement has correctly emphasized the emergent nature of collaboration. Individuals must be given collaboration tools and guidance by the organization, but then must be trusted to work together to meet personal goals that roll-up into measures of organizational success. The only individual that can “own” collaboration is each of us.

LinkedIn Signal Demonstrates The Power of Role-Based Activity Stream Filters

LinkedIn today announced Signal, a new feature (currently in beta) that lets members see an activity stream that combines LinkedIn status updates and Twitter posts from other members who have opted-in to the feature. LinkedIn has licensed the Twitter firehose to incorporate all of its members’ tweets into the site, not just tweets with the #in hashtag embedded, as is current practice.

While it is hard to imagine anyone other than corporate and independent talent recruiters will make LinkedIn their primary Twitter client, Signal does have an element that is worthy of emulation by other social networks and enterprise social software providers that incorporate an activity stream (and which of those does not these days!) That feature is role-specific filters.

I wrote previously in this post about the importance of providing filters with which individuals can narrow their activity stream. I also noted that the key is to understand which filters are needed by which roles in an organization. LinkedIn apparently gets this, judging by the screenshot pictured below.

LinkedIn Signal screenshot courtesty of TechCrunch

Notice the left-hand column, labeled “Filter by”. LinkedIn has most likely researched a sample of its members to determine which filters would be most useful to them. Given that recruiters are the most frequent users of LinkedIn, the set of filters displayed in the screenshot makes sense. They allow recruiters to see tweets and LinkedIn status updates pertaining to LinkedIn members in specific industries, companies, and geographic regions. Additionally, the Signal stream can be filtered by strength of connection in the LinkedIn network and by post date.

The activity stream of every enterprise social software suite (ESS) should offer such role-based filters, instead of the generic ones they currently employ. Typical ESS filtering parameters include individuals, groups or communities, and workspaces. Some vendors offer the ability to filter by status as a collaborator on an object, such as a specific document or sales opportunity. A few ESS providers allow individuals to create custom filters for their activity stream. While all of these filters are helpful, they do not go far enough in helping individuals narrow the activity stream to view updates needed in a specific work context.

The next logical step will be to create standard sets of role-based filters that can be further customized by the individuals using them. Just as LinkedIn has created a filter set that is useful to recruiters, ESS providers and deploying organizations must work together to create valuable filter sets for employees performing specific jobs and tasks. Doing so will result in increased productivity from, and effectiveness of, any organization’s greatest asset – it’s people.

How Smart Content Aids Distributed Collaboration

Authoring in a structured text environment has traditionally been done with dedicated structured editors. These tools enable validation and user assisted markup features that help the user create complete and valid content. But these structured editors are somewhat complicated and unusual and require training in their use for the user to become proficient. The learning curve is not very steep but it does exist.

Many organizations have come to see documentation departments as a process bottleneck and try to engage others throughout the enterprise in the content creation and review processes. Engineers and developers can contribute to documentation and have a unique technical perspective. Installation and support personnel are on the front lines and have unique insight into how the product and related documentation is used. Telephone operators not only need the information at their fingertips, but can also augment it with comments and ides that occur while supporting users. Third-party partners and reviewers may also have a unique perspective and role to play in a distributed, collaborative content creation, management, review, and delivery ecosystem.

Our recently completed research on XML Smart Content in the Enterprise indicates that as we strive to move content creation and management out of the documentation department silo, we will also need to consider how the data is encoded and the usefulness of the data model in meeting our expanded business requirements. Smart content is multipurpose content designed with several uses in mind. Smart content is modular to support being assembled in a variety of forms. And smart content is structured content that has been enriched with semantic information to better identify it’s topic and role to aide processing and searching. For these reasons, smart content also improves distributed collaboration. Let me elaborate.

One of the challenges for distributed collaboration is the infrequency of user participation and therefore, unfamiliarity with structured editing tools. It makes sense to simplify the editing process and tools for infrequent users. They can’t always take a refresher course in the editor and it’s features. They may be working remotely, even on a customer site installing equipment or software. These infrequent users need structured editing tools that are designed for them. These collaboration tools need to be intuitive and easy to figure out, easily accessible from just about anywhere, and should be affordable and have flexible licensing to allow a larger number of users to participate in the management of the content. This usually means one of two things: either the editor will be a plug in to another popular word processing system (e.g., MS Word), or it will be accessed though a thin-client browser, like a Wiki editor. In some environments, it is possible that both may be need in addition to traditional structured editing tools. Smart content modularity and enrichment allows flexibility in editing tools and process design. This allows the  use of a variety of editing tools and flexibility in process design, and therefore expanding who can collaborate from throughout the enterprise.

Also, infrequent contributors may not be able to master navigating and operating within a  complex repository and workflow environment either for the same familiarity reasons. Serving up information to a remote collaborator might be enhanced with keywords and other metadata that is designed to optimize searching and access to the content. Even a little metadata can provide a lot of simplicity to an infrequent user. Product codes, version information, and a couple of dates would allow a user to hone in on the likely content topics and select content to edit from a well targeted list of search results. Relationships between content modules that are indicated in metadata can alert a user that when one object is updated, other related objects may need to be reviewed for potential update as well.

It is becoming increasingly clear that there is no one model for XML or smart content creation and editing. Just as a carpenter may have several saws, each designed for a particular type of cut, a robust smart content structured content environment may have more than one editor in use. It behooves us to design our systems and tools to meet the desired business processes and user functionality, rather than limit our processes to the features of one tool.

Revenge of the ECM nerds

cats

For those of you who aren’t familiar with who I am, I am the Marketing Specialist for Gilbane, more specifically the man behind the various social media curtains. One of my favorite parts of social media is memes, defined as, “a unit of cultural ideas, symbols or practices, which can be transmitted from one mind to another through writing, speech, gestures, rituals or other imitable phenomena.” The most famous example of a meme, almost synonymous with the internet now, is Lolcatz. One of the great pleasures I have managing the Gilbane accounts is the unique community. Defying stereotypes of computer geeks, the online CMS community has proven to be composed of a plethora of creative, witty, clever, and simply funny individuals spanning timezones, continents, and native languages. Earlier this year, we were treated with CMSHaikus, which I was happy to preserve in an ebook (the .pdf originally had Youtube videos embedded in it, but these have since been blocked due to a security patch). This time around, @Adriaanbloem took another meme and spun it with his own angle.

Adriaan bloem

The tweets that followed were a mixture of angst, disappointment, frustration, front-line experience, but most importantly humor! The sarcasm runs rampant here, but the jabs are taken at brands, vendors, scripting languages, developers, each other, and consulting agencies (although the “Godfather” and the agency in his name still seems to command respect as of this writing ).

The engine seems to have plenty of meme steam left in it, but when it’s gone you can read the #CMSRetraction Archive, or better yet follow the participants and become part of the quirky CMS Twitterrati. If I missed you on the list, drop me a line (@gilbane or @tallbonez) and I will be sure to add you!

Focusing on Smart Content

This summer, Dale Waldt, Mary Laplante, and I have been busy wrapping up our multi-vendor report about “Smart Content in the Enterprise: How Next Generation XML Applications Deliver New Value to Multiple Stakeholders.” We’ll be publishing the report in it’s entirely in a few weeks. We are grateful to our sponsors – IBM, JustSystems, MarkLogic, Mindtouch, Ovitas, Quark, and SDL – for supporting our research and enabling us to make headway on this important trend for the future of content technologies on the web. Here’s the link to access some of the case studies that are part of this report.

XML as a tagging standard for content is almost as old as the web itself. XML applications have long proven their significant value—reducing costs, growing revenue, expediting business processes, mitigating risk, improving customer service, and increasing customer satisfaction. But for all the benefits, managers of successful XML implementations have struggled with attempts to bring XML content and applications out of their documentation departments and into their larger enterprises.

So much XML content value remains untapped. What does it take to break out of the XML application silo? What is the magic formula for an enterprise business case that captures and keeps the attention of senior management? These are the issues we set out to address.

We believe that the solution needs to be based on “smart content.” When we tag content with extensive semantic and/or formatting information, we make it “smart” enough for applications and systems to use the content in interesting, innovative, and often unexpected ways. Organizing, searching, processing, discovery, and presentation are greatly improved, which in turn increases the underlying value of the information that customers access and use.

We started this discussion late last year.  We now have the solution-oriented case studies and the additional analysis to reinforce our perspective about the drivers for the digital revolution at hand. We look forward to the continuing conversations with all of you who are seeking to transform the content-related capabilities of your business operations by championing XML applications.

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