Better customer service via knowledge management. (Customer Relationship Management).

Amidst the sizeable investments companies are making in CRM systems, knowledge management systems, workforce management software and other technologies in the quest to deliver superior customer service and support, there's some irony that shouting over the wall of the cubicle, calling around the organization or e-mailing others for assistance is a key component of the customer support process.

This ad hoc collaboration, which is repeated daily by support analysts seeking assistance with complex questions, has become an accepted component of the support process. In fact, informal collaboration occurs on over 80 percent of all requests, according to a January 2002 study conducted by the Service & Support Professionals Association (SSPA). Unfortunately, this informal collaboration happens outside of the standard support processes and systems, which means that the information exchanged isn't captured in any CRM sysrem or knowledge base. Therefore, that incredibly valuable knowledge is lost for reuse unless that same support analyst recalls it during another interaction. The bottom line is that when a similar question arises, the same time-consuming, inefficient, ad hoc process takes place all over again.

The Costs Of Informal Collaboration

Consider the typical scenario in the life of a complex support request. The issue comes into the support department and the support analyst, who takes primary responsibility for getting the issue resolved, most likely doesn't have the entire set of knowledge or skills to answer it since the level of complexity is so high. Once the analyst has exhausted all existing sources of research and knowledge, he or she needs to tap other experts to help find a resolution.

Typically, when a support analyst needs additional assistance with a complex question, he or she will simply ask a colleague for help. However, that person isn't necessarily the "best" person to help solve the problem. If that person can't help, then the support analyst embarks on a search via e-mail or phone for other assistance, This inefficient searching for the right resources has a negative impact on the performance of both the support analyst and the support organization, impacting service levels and other key performance metrics.

Once the right team for the problem at hand is finally located, it is probable that the team does nor have a formal, structured place in which to work together, forcing informal collaboration. Trying to work together without a shared workspace consumes a lot of time and energy because the problem must be continually explained each time a new participant is contacted. When finally all the communication has occurred and the support analyst has the information required to respond to the customer, all the preceding interactions, which are arguably as important as the final resolution, are never recorded for future use.

Now add to the mix a complex issue that requires participation from outside the support department, such as the development organization, or from outside the company, such as a channel partner, other vendors or outsourcers. The SSPA study reported that up to 80 percent of requests requiring collaboration received help from outside the support department.

The inefficiencies and costs of informal collaboration quickly get magnified, resulting in an increased backlog of requests, reduced service levels, lost information and, most important, unhappy customers. In fact, SSPA estimates that 75 percent of companies feel their current ad hoc collaboration negatively impacts customer satisfaction.

The large volume of information exchanged through informal collaboration is certainly very hard to measure, track and capture. But don't throw our the baby with the bath water. Collaboration is not only required for resolving complex issues, it can be a very strategic process for the entire company -- when done correctly. By putting a formal, structured process and targeted technologies around that collaboration, complex issues can get resolved more quickly and accurately. Knowledge can be harnessed and reused, and customer satisfaction will soar, resulting in the ultimate measure of a company's success: customer retention.

The True Value Of Structured Collaboration -- Rich, Reusable Knowledge

The value of collaboration goes well beyond just allowing two or more people to communicate. By its very nature, the collaborative process itself contains an enormous amount of valuable information -- the process that occurs throughout the resolution contains very rich knowledge. Obviously, the resolution itself is critical information to capture. But so are the roles of the people involved, as well as how they worked together to best achieve successful closure of the issue, To maximize the value of knowledge, you must first broaden the definition of knowledge. Knowledge is not limited to "what" was the answer to a specific problem, but also includes "who" participated in the resolution and "how" the resolution was achieved.

Most people think only about capturing the end result -- the ultimate solution to a specific question -- as content to add to the knowledge base. For simple issues, this is probably sufficient, However, when collaboration between multiple people is required to arrive at a resolution, it is also very valuable to capture the dialog that took place throughout the interactions. The complete transcript contains not only the final answer, but also the path that led there, often revealing critical aspects of the context for which the solution is valid.

In addition to the "what," the content people contribute while resolving an issue, it's important to know who said it. By knowing who has worked on certain types of problems, and contributed to their solutions, those same individuals can quickly be identified in the future when related problems arise. This is particularly crucial with complex problems, where subtle differences between situations may make it impossible to apply the precise solution from one problem to a similar, but not identical, new problem. In those cases, quickly locating the right expertise may make the difference between making or missing service-level targets.

Frequently, more important than the actual names of the contributors are their characteristics, such as their skills, qualifications, department or company. For example, one of your major customers has a performance problem with your company's enterprise financial software when it interfaces with their ERP system from another vendor. While resolving the issue, it is discovered that the root cause of the problem was lack of an index in the database table -- something not immediately obvious. However, until the primary support analyst invited a database administrator to participate as a member of the problem-solving team, the problem could not be properly diagnosed.

If all of this trial and error, on-the-job learning could get captured in a knowledge base, the next time any support analyst had a performance problem with that particular application, they would know to invite a database administrator into the collaborative team to expedite problem resolution.

Equally important in the collaboration process is the "how" -- the process by which a timely resolution was reached. What steps were tried before the right answer was found? How many people did it take, and at which point in the resolution cycle were they brought in?

For example, a company may find that, after analyzing past collaborative issues for certain customers or issues, their most effective approach has been to involve a broad set of people and skills up front in the support process. Other companies may discover that, for one of their major customers, the most effective way to resolve issues is to include the customer only at the end of the process. Learning how to best approach the resolution process for each situation can become key to most effectively deploying valuable personnel and resources.

By capturing this information in a knowledge base, a company can develop a more effective support process going forward. By capturing and analyzing the complete interaction, trends emerge which can lead to improvement not only in the customer support process, but also for the rest of the company. For instance, it may be discovered that there are new product enhancements that would reduce a persistent issue or opportunities for the sales force to sell new service and training offerings to the customer. Knowledge about the entire process can be valuable because it enables management to tune the whole company's performance.

Improving Your Knowledge Base For Better Customer Service

A company's knowledge base is its brain trust. Support analysts may come and go, but a knowledge base containing their interactions remains. Herein lies the information that can help expedite complex customer issue resolution, the goal of every company and the hope of every customer.

But a knowledge base is only as good as the information it contains. Capturing all the interactions, the "who," "what" and "how," from all participants involved in the resolution of a complex issue is imperative for improving customer service and support. Knowing when people joined and left the interaction, the order in which things happened, when critical insight occurred, when the transition took place between understanding and solving the problem, and the final resolution - is all valuable knowledge.

This wealth of knowledge enables not only the reuse of solutions to sets of similar problems, but also the identification of the people and skills that are most effective at solving new problems when they arise. By capturing and examining the successes and shortcomings of the support processes, this broader perspective of knowledge can be the basis for continuous, companywide improvement and, ultimately, better customer service.

Chris Derossi is founder and chief technical officer of ePeople (www.epeople.com), a provider of Internet-based, collaborative CRM solutions. Prior to founding ePeople, Derossi served as director of the Magic Cap products division for General Magic, where he led the team that built the operating system and applications for personal communicators shipped by Sony and Motorola. He spent six years at Apple Computer, where he was chief architect of Macintosh system software.