So now you know we’re in the Social Age! We explored some of the trends and innovations that got us here, and you’ve begun to get a flavor for the incredible power of wikis, blogs, and other Social Age tools in the enterprise. We think you’re probably ready for a trip into the clouds.
Social Age clouds are not big, puffy things in the sky from which rain falls. Social Age clouds are really “clouds of knowledge,” which incorporate services and information, making both easily accessible from anywhere. These clouds are a key enabler for our smaller, smarter, and more social world. These clouds are why people in the Social Age generation can take for granted that the web page they’re looking at is “smart.” That is, we now expect the web page we look at to know who we are, what we want to read, and to suggest other web pages, services, or products in which we might be interested. We expect that when information or events change on our favorite site, we’ll be aware of it immediately, including receiving proactive notification, depending on our profile.
Early clouds are with us today, and more clouds are rapidly forming to take advantage of the global transformation now underway. Clouds will become even more pervasive and encompass ever-increasing knowledge as more people commit to this medium and increasingly engage in social networking activities.
Social Age clouds are available worldwide and include collective knowledge unimaginable just a few years ago. They can be either “tag clouds” that aggregate social behavior and community interests or “computer clouds” (better known as cloud computing), which we discuss in detail in Chapter 6, “Cloud Computing Paradigm.”
At least for now there’s not a lot of interaction between various services in these clouds. In other words, open standards are still evolving that ultimately will facilitate the integration or exchange of information with other social tools. For example, perhaps you use a social networking site, and during registration, you were asked to invite your friends from your Gmail or Yahoo distribution lists. Soon these questions will be unnecessary as new standards for data exchange emerge and the maturation of cloud computing accelerates. Driven by market pressures, these open standards and web services protocols will dramatically increase the collective information available in the cloud.
Of the two categories—tag clouds and cloud computing—tag clouds are perhaps the most interesting to the average Internet user. Tag clouds are an aggregation of personally created keywords that can be applied to either content or people. You can tag a web page, a document, a video, some new music, a friend’s blog, some wiki comments, a book, a collection of bookmarks, or even a person.
Tagging is the action or process by which an individual can label and classify an item. Social networking communities share an enthusiasm for the pastime of tagging, making it the primary driver for the collection and availability of tags. Tag clouds are virtual entities in the Social Age that are aware of community preferences and behavior through the aggregation and analysis of tags.
In the Social Age, the practice of tagging is an organic process usually referred to as folksonomy.[1] Previously the classification of information and objects (whether people or things) was the exclusive domain of the highly specialized science of taxonomy. Now through the folksonomy of social networking, everyone is getting into the act! The primary advantage of communities and especially businesses participating in the exercise of tagging is that it generates a group preference or classification that specifically reflects the needs and desires of the collective.
Folksonomies create a powerful bridge between the individual and the collective, and they differ fundamentally from formal taxonomies. Typical IT taxonomies are carefully structured by specialists to define data dictionaries for databases. IT taxonomies define data structures and data relationships that are central to achieving a good data definition about relatively static data relationships, supporting well-defined transactions. Examples of such well-defined transactions include financial and accounting data.
Folksonomies, on the other hand, are created organically by individuals who classify items within specific communities of interest, based on personal opinions and value systems. Unlike taxonomies, folksonomies evolve dynamically and constantly as the interests and composition of the community changes. The process of creating a folksonomy is highly efficient because it leverages the collective knowledge of a community, a business, or an entire society.
A wealth of information and objects can be tagged on the Web and inside an organization’s firewall that are of great value to your business. These community-created tag clouds are the latest, most accurate representations of what’s important to that community. These tag clouds are often represented visually on a Web site, with various font sizes or other attributes to distinguish relative popularity, as illustrated in Figure 5.1.
Figure 5.1. The virtuous cycle of tagging produces an increasingly valuable tag cloud that can be used by other web applications and services to examine buying behaviors and community preferences.
For your business, the intelligence contained in tag clouds—inside and outside your organization—is incredibly valuable; and most surprisingly, in the Social Age, such intelligence is available to you at little or no cost!
Tagging empowers people within a community to build relationships and associations as they share their thoughts and opinions. A sense of community identity develops as each member contributes to the team through the shared classification, evaluation, and ranking of people and objects.
Amazon.com is an excellent example of the power of tagging. Have you found yourself checking the star ranking before buying something on Amazon? Do you read the opinions of other buyers before you click “Add to Cart?” Most of us do!
For Amazon.com and thousands of other savvy retailers, tag clouds can easily be leveraged to create “cash clouds” that drive revenue and quickly enhance the reputation of a product. In addition to opinions and stars rankings, Amazon.com also offers the opportunity to tag items, making them easier to find later or to highlight in a social networking community. Perhaps you’re considering a new watch. You can tag the watches you like and then use that tag category any time to compare them side by side. Or maybe you think there should be a category of watch called “diver.” You’re free to create that category for your benefit or for the benefit of other visitors to Amazon. All this and more is possible only through the power of tagging!
Visitors to Amazon.com and other retailer Web sites depend on tags and reviews to get the real word on products. They trust what they read because it is the opinion of other consumers who have actually used the products, rather than a review or biased opinion of the manufacturer. Every review, categorized by reviewer, is available at any time, allowing a visitor to confirm the credibility and review the record of each reviewer. Tags and reviews help drive the sales of the best products, and more quickly eliminate weak products.
Basic human curiosity and a need for affirmation are the reasons we reach out to others to get their opinions, or to get the comfort that the opinion of a community provides. This basic social instinct is why people seek recommendations from others, spend time tagging, and enjoy spreading the word about what’s considered cool.
The tag cloud is an entirely new method of communication that reveals ever-evolving characteristics of a community—what’s important to them, what motivates them, what problems they’re confronting, what they need, and of course what they’re buying now and might be willing to buy in the future. As Amazon.com has happily discovered, tag clouds offer your business a powerful new way to market products.
As always, community opinion is important, but now it carries even greater weight because it is not just immediate and close friends providing recommendations. Now a long tail of loosely connected people you barely know can offer incredible insights on topics that interest you. As discussed in Chapter 4, “Blogs: Your Personal News Outlet,” this long tail of loose connections is a powerful aspect of blogs.
In a world of information overload, tags offer a welcome relief. Tag clouds quickly highlight topics, activities, conferences, people, or any other items of interest to an individual or a business that have been recommended and highly ranked by a community through the aggregation of tags. Popular topics and themes tend to bubble to the top of tag clouds quickly. Tags create a ranking process, separating good content from bad, identifying best values, and saving substantial time and frustration for community members. Tags create associations and correlations that can be used to understand group preferences and relationships between different items.
Perhaps the most surprising aspect of the tag clouds is that the same relevant content surfaces regardless of web application or tag tool experience. The extraordinary consistency of community behavior on tag cloud content, regardless of the tool used for the tagging, reveals profound unity, almost as if the community had a “mind of its own.” To succeed today, your business must focus as much on the community as on the individual.
Tag clouds consist of tags that are essentially “social fragments” that reflect the interests and preferences of a community. As such, they tend to foster greater understanding of social behavior, inclinations, and interactions within communities. In addition, two key advantages of aggregating individual tags into a tag cloud are the statistical elimination of individual biases and providing a context for tagged objects.
For example, if you’re a tennis player and belong to one of the many social networking groups for tennis fans, you’ll probably get relatively unbiased recommendations of top tennis rackets that fit your expectations and needs. The tag cloud contains ratings from thousands of tennis players and is the collective wisdom of the people who have researched the topic and have actually used the rackets. Even if a couple of tennis racket sales reps slip into the cloud, no worries! Their glowing—and obviously biased—recommendations of a particular racket are going to be tempered by the unbiased statistical majority of others in the cloud. In fact, the longer a community has been tagging, the more effective its cloud becomes. Essentially, every click in the tag cloud is a vote; together the cloud expresses precisely the preferences of the community within a particular context and without individual biases.
Context is everything in the quality of a web search. The tag cloud offers incredible insight regarding community members’ interests and opinions. As a result, when you search tag clouds, you generate results vastly superior to regular search methodologies, offering a clear, competitive advantage for your business.
Today more than 250 million people worldwide engage in social networking activities.[2] As a result, tagging is becoming the trusted reference and preferred way to classify objects. Tagging is an organic, dynamic process rather than a static, structured process. Your business must leverage the power of social networking because a community evaluation or ranking can quickly make or break a product. In this context, social networking is essentially a new marketing channel for your products and company reputation.
We also urge you to seriously evaluate the value of the tag cloud to improve the social spaces you create for your customers—forums, blogs, wikis, customer satisfaction survey pages, among others. As tagging becomes more pervasive, evaluation and tagging mechanisms will simultaneously become more sophisticated. New mechanisms will make web applications and services smarter and more capable of interacting and responding in ways unimaginable today. Creating a smart social environment to empower your customers to tag your products and provide feedback might be one of the smartest things you can do to improve your direct channel.
Tags are like fingerprints or an audit trail in social spaces that can provide a way for you to understand your customers’ preferences. What do your customers like? Well, you could call each of them on the phone and ask them; or you could just check online customer ratings of your products. While you’re at it, you can check tags, wiki comments, network traffic, lists, bookmarks, and other “taggable” events wherever they appear, whether on your product web page or out in the external tag cloud. Using the power of the tag cloud, you’ll know what your customers like—for sure! (Keep in mind you might not always like the results you see. But when would you rather find out about a problem? Now, through the tag cloud? Or when the monthly sales report tells you a particular product is one of your worst sellers? This, coincidentally, might be the day after you place a big order for that item with your supplier!)
In addition to the many benefits previously mentioned, the tagging process also enables a virtuous cycle of social networking—virtuous because with each discrete piece of community input, the social network becomes more reliable, trustworthy, and important to its members (see Figure 5.2). Tags enable the virtuous cycle of social networking by surfacing content that is made available to the social networking spaces. In turn, these virtual spaces provide a conduit for more tagging that keeps the community vibrant and accurately reflecting the interests of the collective.
Keep in mind that because of the interconnectedness of the smart web pages created through tags, a networking space can consist of many different social networking tools that share the same community interest within a single tag cloud. As the community changes its preferences, the tags will change and the tag cloud will surface other documents and items, making the social space an accurate reflection of common interests and values of the community. The tag cloud allows us to see the relationship among the individual, the collective, and the shared social spaces, as illustrated in Figure 5.2.
By now, you have probably realized the significant value and incredible power of tag clouds for your business. So what is the most effective way to apply a tag cloud to the enterprise? How can tags help improve your business search engine? What tag cloud services are applicable to corporations?
One of the key benefits of implementing a tag cloud service within the enterprise is the cultural transformation that occurs through tagging. Properly implemented, tagging can make the corporation increasingly people-centric and unleash the collective knowledge and experience of its employees. Just as public tag clouds foster greater understanding through shared interests and mutually beneficial folksonomies, tagging within the enterprise helps build stronger corporate communities and teams. In the enterprise, you can tag documents and internal Web sites to more easily highlight content of interest to specific business communities.
The tag cloud empowers businesses to tune their search engines to reflect the interests and values of the corporation and their communities. This tuning creates efficiencies in information identification that can significantly improve employee morale and customer satisfaction. In addition, as previously discussed, the virtuous cycle is accelerated in your business through a well-established tag system. The tag system helps people find the information most relevant to them and this, in turn, has an effect on the overall web traffic on the most popular pages.
Two years ago at IBM, we designed a cross-business-unit solution called the Enterprise Tagging Service (ETS), which provided common services accessible to IT internal applications to ensure every tag generated was collected in a common data repository. These tags were correlated and made available in many different ways to satisfy specific application needs, regional and local requirements, and the business needs of other internal communities. The ETS team designed a tag aggregation service for applications to publish and consume tag data and a tag analytics program to define how to apply tags in multiple contexts. The ETS framework was well documented and several example widgets were created to enable easy access and attachment of these artifacts to web pages everywhere within the firewall.
Note that tag widgets were created to facilitate adoption of the technology. Again we return to the importance of proper planning and implementation to ensure the success of your tag cloud. The tag widgets should have simple interfaces to make it easy to integrate them into Web sites.
The IBM tag widgets illustrated in Figure 5.3 are easy to implement and can be attached to web documents and applications in just a few steps. We created these tag widgets by leveraging Web 2.0 technologies and then made them easily available to IBMers to customize and attach everywhere within the internal firewall.
Figure 5.3. (Left to right) (1)“Tagger” widget listing tags based on configurable categories; (2) tag cloud, represented by relative font size, the popularity of the tag, or particular application; (3) tag cloud widget rendering the tags associated with a particular web page or web application.
The result of implementing a companywide tagging system was an avalanche of participants eagerly tagging all kinds of information. Technical and nontechnical employees participated equally in the creation of new, simple tagging widgets, which they attached to many of their favorite sites and applications. It seemed everyone was jumping into the tagging frenzy. After the establishment of the tagging service, the internal Web site traffic pattern was actually altered by the new tag cloud—nearly 70 percent of the site traffic was related in some way to the ETS redirects. This was a perfect example of the influence a community can have on employee behavior.
Alexander Graham Bell, Library and Archives Canada
“Great discoveries and improvements invariably involve the cooperation of many minds.”
Alexander Graham Bell
For your business, finding information through tagging might not be as significant as identifying someone with the right skills or expertise for a particular job. Tags can help people find each other, and they can help you find just the right person for a job. Because of the large number of participants, the tag cloud serves as a trustworthy source of information about a person’s abilities and experience. The tagging process is an excellent way to locate people who have a vote of confidence from the community and recognition for earlier accomplishments. Because this can be such a valuable resource for your business, we spend a few pages discussing some of the Social Age strategies and tools for expertise location. The minds you attach to your environment determine success or failure, since human resources are the most valuable business asset. As Alexander Graham Bell said, “Great discoveries and improvements invariably involve the cooperation of many minds.” To get the best outcomes, you want the best minds to be part of your community.
With the incredible volume of easy-to-access information on the Internet, it would seem that finding an expert should be simple enough, right? Unfortunately, because of the complex nature of such a search, standard Internet searches just aren’t going to get it done. Unlike other information, expertise location—whether searching for an expert or for an expert answer—remains a vexing challenge, existing as it does at the odd intersection of machine learning and individual identity. Fortunately, traditional communication channels for expertise location—including standard Internet searches—are giving way to dynamic social solutions such as wikis, blogs, and forums, quickly identifying the right person for the job, or the right answer to a problem.
Current corporate structures usually lead to dispersing information and expertise within silos of specialization, and employees working in this structure recognize the limits of their knowledge and experience. So how do we uncover the diversity of perspectives, approaches, and experience that invariably produce higher quality results?
Expertise location often begins with a basic search for the answer to a specialized question. The answer leads to more research, which often leads to the need to consult with subject experts. Among the most frequently mentioned needs for expertise location are
• Quick, accurate answers—Perhaps the most popular need, when traditional search techniques have yielded few or conflicting answers.
• Decision support—Management needs rapid and deep understanding of an issue or business challenge. Prior experience—tacit knowledge—is invaluable. Collective intelligence can be important here and a consensus might be sought.
• Team augmentation—An appropriate person is needed to fill a performance or skill gap.
• Collaborative innovation—For accelerated refinement or adoption of an innovation by experienced collaborators.
• Campaigning or sales—Influencing business results inside and outside the enterprise with expert opinion.
Because expertise location is either for answers or for experts, many organizations focus first on the simpler of these—answer services—and use this as a first step in the full development of enterprise search services.
What’s the total energy used by our building site? Who knows how to buy replacement toner cartridges? How do I hire a contract developer? What’s the average return on direct-mail marketing for apparel?
Organization-specific research questions like these have a locality and often confidentiality that point employees to an enterprise search, but the questions are often general enough to make searching difficult. So where to begin? The enterprise intranet? The employee directory? Or maybe you should just do what you always do: start calling the usual colleagues for suggestions. Typically an employee will first do just that—ask colleagues. If that doesn’t yield a good answer, a broad intranet search is next, with incremental refinements as clues and related information are discovered, leading—it is hoped—to the answer or the expert. Many IT organizations have observed this process and sought to automate the query process and to capture the resulting answers for reuse. This approach has the benefit of building an enterprise-specific knowledge base while gaining a better understanding of the needs of employees. Figure 5.4 illustrates the process flow for answer services that interact with an expertise network.
Figure 5.4. The Answer Service process. A user queries the database and either the answer is provided or the query gets sent to the Expertise Network for an answer. If the answer is approved by the user, it can be added to the database permanently.
Automated answer systems typically include a data repository of known answers—product support problems and solutions, frequently asked questions, process documentation, and so on. This data repository is coupled with a search engine and an application that connects acceptable answers to queries. Mature answer systems go one step further—they capture the quality and relevance of answers through user surveys and rerank the search result accordingly.
As might be expected, these automated answer systems work best in contained environments such as on-line product support or for process support in complex enterprise applications. When deployed as part of an enterprise help desk or a business support function, these answer systems can be effective for answering common questions quickly and online. More difficult questions can then be referred for human assistance and, in turn, documented and managed in the automated database.
Several public “answer services” have been created on the Web. General search services such as Ask.com and About.com blend proprietary documentation with web search, whereas on-call web-based human researchers are available through Google Answers, Experts Exchange, and others. Many enterprises adopted similar intranet-based service desks to help remote practitioners or high-need employees.
As powerful as all these techniques can be for you and your business, social networking takes them to the next level. For example, instant messaging can be paired with an enterprise answer system in which employees volunteer to affiliate with communities or topic groups. When a query is received by the system that can’t be answered with the database, the query is broadcast with an unobtrusive notice to the affiliated community. If they have an answer, or just a pointer, they can instant-message the seeker directly. An accepted answer is stored in the database.
A lightweight example of a broadcast answer product is the Lotus Sametime® Skill Tap feature. Similar solutions use an intranet web page coupled with e-mail notification to solicit answers. Social networking also helps identify individuals within the communities to which queries are directed. User profiles in social networking communities are more easily updated through the beneficial synergy created by the answer system. This synergy also enables deeper collaboration and capability discovery.
Studies have shown that we rarely collaborate casually more than 150 feet (50 meters) from our office.[3] It is, therefore, highly unlikely that we will stumble upon the expertise we need through casual contact, especially when deep expertise or extended collaboration with a trusted source is called for. The challenge is to find experts outside your existing network or local environment.
As we said previously, using corporate intranet search tools or directories is an obvious first choice. However, these tools often do not have the content needed to identify the right expert, nor the indexed data repositories that allow us to easily tease out more insight and information. Researchers have found the average enterprise worker spends more than 12 hours per week searching for information.[4]
Fortunately, in the Social Age, finding answers no longer needs to be so difficult—or time-consuming! In the Social Age, automated profiling is increasingly used to provide an incredibly detailed picture of each employee. Unlike a few years ago, when corporate profiles were not much more than electronic business cards, automated profiling today provides an up-to-date, detailed snapshot of each employee’s specialized areas of expertise.
In the Information Age, time was perhaps the primary impediment to maintaining current employee profiles. After all, updating an employee profile is a lot like updating a resume. And unless you’re looking for a job, why do it? Likewise, what’s in it for an employee, who has a million other things to do, to manually update his or her profile? Automated profiling essentially eliminates the burden on the employee for updates.
Automated profiling begins with the collection of as much published content as possible for an employee. The content or an abstract of the content is included with the profile, along with a full text search index. The results are ranked based on frequency, linked citations, and timeliness. This step works if employees produce a constant stream of published intranet documents. Unfortunately, this is rarely the case.
The second step is to consider indexing an employee’s e-mail and other private content, while cloaking specific details. Linguistic tools can extract relevant keywords while cloaking the context of the private communication. Keywords are then stored in a hidden, indexed portion of the profile, or they can be clustered and placed in the profile. Searches for these keywords or related topics (using the technique of expanded search term with a thesaurus) results in a hit on the target’s profile.
Although this technique works well, it has one drawback. Although most companies have a policy that all e-mail and other employee communications are not private, some sensitivity should be exercised with regard to the perception of employee privacy. At a minimum, the employee should have the opportunity to edit the keywords to filter out anything they consider nonbusiness-related.
This review of keyword topics, however, places the burden back on the employees to interact with their profiles. One solution is to use subject taxonomies. These are terms relevant to the enterprise, which are used to cluster topics. Based on document or e-mail scanning, a small set of higher-level categories can then be suggested to an employee using these terms. When accepted, the terms would help identify employees with the strongest affinities to a category and would be displayed when browsing or searching for similar content.
Another solution to both the privacy and the efficiency issues is to use a “broker” to gain access to a potential expert. Tacit Software’s KnowledgeMail system used text mining of e-mail to determine a user’s interests. Then, rather than expose the expert in search results, the system used e-mail to notify the experts of the request. The experts had an opportunity to respond or ignore the request, with the option of revealing their identity only after knowing the identity of the requestor. The KnowledgeMail system solved many of the privacy and control issues but sacrificed the immediacy often required for expertise location. Oracle recently bought the KnowledgeMail intellectual property from Tacit Software and is planning to integrate this technology into the Oracle Beehive for a more robust and secure enterprise expertise location solution.
Early Knowledge Management systems were developed during the Internet expansion of the late 1990s when these solutions seemed not just possible, but inevitable. Although the bursting of the Internet bubble delayed Knowledge Management development, the dawn of the Social Age reinvigorated it in unexpected ways. In the Social Age, it seemed everyone was becoming comfortable with writing publicly. Blogging tools were free and accessible. Wikipedia clearly demonstrated the social value and mechanics of simple collaborative authoring. It was natural that social networking tools began to include shared profile information, initially offered for purely social reasons, but which ultimately extended into business relationships as well.
Having such a rich trove of information available through social networking tools was an exciting turn of events for expertise location within the enterprise. Seemingly overnight, public social networking tools have become commonplace, accompanied by a profound shift in attitude—one’s identity, relationships, interests, activities, and passions are no longer private matters but are essentially open to the world. Many businesses leverage this change in attitude and have developed proprietary social tools, using them to gather core information about business and technical expertise.
So does this mean we have finally the answer for quick, efficient expertise location? Not exactly, but we’re building the tools that get us a lot closer. Perhaps the biggest challenge is generational. People in the Social Age generation have used social tools throughout their academic careers and are, therefore, comfortable with the personal transparency of this medium. Although this demographic continues to stream into the workforce, and thus expand the use of social tools in the enterprise, mid-career and older professionals are increasingly getting into the act with business-oriented platforms such as LinkedIn.com. Naturally it will take some time to create the most-efficient solutions for expertise location using this wealth of information. But the content is there, and it will continue to grow at a blinding pace as more people join the Social Age revolution.
To access the wealth of data on social tools, new Web 2.0 tools are continually emerging, often with direct enterprise value. Del.ico.us[5] is a well-known example of one of these tools, which leverages the concept of “social bookmarking.” Bookmarking creates a browser bookmark on a web page and applies a tag to the URL. Social bookmarking in the enterprise is a lightweight method of improving “findability” of content and for sharing one’s intranet discoveries. Integrated browser extensions make this process unobtrusive and simple. Even when only a small percentage of the enterprise is engaged in tagging, the results are powerful.
At IBM, a small set of early adopters of an internal tagging service called Dogear[6] quickly tagged the majority of important intranet documents.[7] These tags—created by less than one percent of the workforce—proved so valuable that they were immediately integrated into the IBM corporate search engine, improving the company’s search by more than 60 percent.
Given the success of document tagging at IBM, the obvious extension—tagging people—was tested. Would employees feel comfortable tagging colleagues? Would the system be abused? What types of tags would be generated? A test version of the popular IBM Bluepages employee directory was the basis of a research pilot called “Fringe,” which was used to answer these and other questions. To eliminate potential abuse, person tagging was cleverly designed to reveal the tag author and to allow tag removal by either the tag author or the profile owner. (No abuse has ever been reported to the Fringe team.)
The results of Fringe were a pleasant surprise. Employees used tags for a host of purposes, some expected, some completely unexpected. Tags were used as reminders, as skill labels, and to create quick ad hoc collections of people. In addition to including tags as key search terms, the system was used to create mailing lists, geographic maps of member locations, and a visual relationship map of tag groups. At the conclusion of the pilot, person tagging was included as a feature of the Lotus Connections profile component and has been shown to be an effective social tool.[8] For the adoption and success of people tagging, the process must be seamless and the results must be relevant and easily accessible.
Another social innovation that supports expertise location is friending, the explicit and usually confirmed assertion of a person-to-person relationship. Friending is useful in an enterprise to understand the relative strength and diversity of relationships. Although not always conclusive, these factors can indicate influence, working style, and openness to contact, and provide a snapshot of an employee’s topical network. Most friending network features focus on relationships, their quantity and structure, together with some measure of strength.
Text mining tools are emerging as a vital tool to suggest topical relationships. For example, e-mail or other collaboration sources are used to correlate communication with the subject of the communication. The result of this correlation is a network map of someone’s interest groups and specifics about frequency of contact. Privacy issues have limited these tools to personal use to reveal one’s own network, but they have still proven to be incredibly valuable in many businesses. In time, these topical relationship maps will likely support automated listings of communities of interest on employee profiles. Uncovering informal groups with automated community listings is a valuable extension of the employee profile.
A collection of relationships is referred to as someone’s social graph. Vendors are eagerly anticipating the day when the details of these graphs can be leveraged to provide targeted service and products. As we discussed in Chapter 1, “Dawn of the Social Age,” standardization will accelerate adoption of this technology as it has done to many others. Having an open, standard social graph allows competitors to combat the “lock in” enjoyed today by most current social network solutions providers. Open social graphs can also be a powerful tool for finding expertise, especially if the graph contains specific subjects and strength of the relationship. The graph can reflect the breadth of expertise, as well as relationships within the network. The opinion of someone’s resume is one thing. The opinion of someone’s peers is something else indeed!
As the use of expertise location goes beyond the corporate firewall, this idea of a topical social graph will gain increasing importance. Ideally the social graph will be built with the same structure that allows Google to predict the best site for any query. The Google Page Rank algorithm correlates a graph of links that others have created using the same search criteria, speeding up the search, and providing the best results. With a similar approach, a verified social graph will quickly and reliably identify the best experts for a given topic query, providing your business with an incredibly powerful competitive tool.
Exposing capabilities is a further challenge in the area of expertise location. The context has now shifted, and the question is somewhat different: How can I find a potential vendor of services with the skills needed to complete the task at hand?
This is an organization-to-organization challenge, not specifically a question of finding an expert. This challenge is about finding a partner that can ensure success. In the past, vendors met with you in person to demonstrate both the competence and the scale of their capabilities. Today, to be competitive, these activities must take place online. Evidence of the vendor’s experience and the dynamics of the proposed team are important differentiators today and are increasingly available through online tools.
Building a relationship of trust is primary in any business engagement, but as business relationships become increasingly virtual, it is perhaps even more critical. Social networking plays a crucial role here; it is a powerful mechanism for establishing trust based on the accumulated evidence of competence, shared values, and reputation.
As an Internet provider of a product or service, the capability of your offerings must first be discoverable. Although advertising can drive traffic to your site, it’s your reputation and evidence of accomplishment that keeps you on vendor lists. Showing signs of open collaboration or availability to vendor expertise during the presale period is often a differentiator, especially in markets that cannot sustain direct sales contact. After the sale is made, the customer’s ability to get responsive service and support and build a relationship with vendor personnel can powerfully enhance your company’s reputation.
Business relationships deepen further when internal expertise location tools, such as employee profiles and communities of interest, are open to your customers. Although the thought of opening your enterprise up for internal inspection might seem radical, we believe this level of transparency is inevitable and vital to success in the Social Age. It is certainly possible to be selective about the clients or partners who have access and the extent of this transparency. Serena Software uses a third-party social network as the basis of its intranet,[9] precisely to achieve an increased transparency in operations. Service providers such as TopCoder.com[10] have embraced transparency as their core business model; they reveal almost all aspects of their business processes, current work, and results online as a means to secure the best contract developers.
Although this cycle of building a reputation on responsive customer service is a well-known and obvious business model, the migration to an effective and profitable online model is still maturing. Social networking features, including people tagging, topical connections, and explicit communities, can provide a powerful vehicle for marketing your organization’s capabilities.
Participation in social networking activities is also a powerful way for savvy employees to create proof points for their expertise. Tags empower individuals to contribute to their community and at the same time to enhance their own reputation.
At IBM we have a self-branding tool called IBMer that enables the creation of a professional identity and reputation. A participant in IBMer builds a personal brand based on a list of skills and experiences, but the corporate community ranks and evaluates each person’s skills. Tags are used in this case to create the reputation of IBMers in a completely transparent way. These reputation tags help identify people with appropriate skills and simultaneously serve as implicit community recognition.
An employee tag cloud can also help surface key companywide concerns, differences between divisions, and new company trends and ideas. IBM has a strong business tag cloud of more than 600,000 tags that have helped accelerate innovation by enabling better communication and collaboration across the company. The growth of this tag cloud is illustrated in Figure 5.5.
Another view of the tag cloud, as shown in Figure 5.6, uses different size boxes depending on the popularity of the discussion subjects. Within each subject box, the document status is shown with color-coded bars. There is virtually no limit to the ways you can display and get business insight from the data contained in the tag cloud.
Figure 5.6. IBM researcher Martin Wattenberg’s Tag Cloud visualization represents by the size of each square the relative popularity of a tag assigned to a discussion subject.[11]
Every business has different needs and priorities. Tag tools might need to be customized for your situation, but by instrumenting your Web site with a tag tool, you can gain valuable business insights from the tag cloud created by your corporate community.
• In the Social Age everything is about the “clouds of knowledge” that incorporate services and information, making them easily accessible everywhere.
• Tag clouds encapsulate social behavior and community interests. These tags are user-generated keywords applied to content or people.
• Tag clouds represent the preferences, values, and associations of a community. Tag clouds build bridges between the individual and the collective.
• Expertise location is much more effective through the use of social networking tools.