Looking at Knowledge

I set out to surprise my husband with a new Xbox game for his birthday. Not being a gamer myself, I initially did a Google search on popular Xbox games, but this overwhelmed me with too many results. So, I narrowed my search to sites that had a large online community of gamers who I thought could help find something that my husband would like. One site stood out in my search. It asked me to enter some basic information up front--like his age, the types of gaming consoles he had, other games that he liked. By answering these questions, I got a clear listing of suitable games, ordered by price, and with embedded consumer ratings. The site even recommended the best game for me based on my husband's past purchase history. It also included links to a searchable discussion board where additional product information and peer reviews were posted. I read through all the material available, asked a couple of questions that were immediately answered, and I was able to quickly choose the perfect gift for him. I often think about this experience when I am at work--not because I have an interest in gaming, but because I work at a knowledge management company, and am frequently called to recommend best practices for the deployment of these products. Knowledge management (KM) products must be implemented in such a way as to be successful with this new generation of customers--customers who rely on online social networking and tribal knowledge of others instead of expert advice to guide them through their lives. They use customer ratings to purchase new products, and discussion groups, forums, or wikis for first-line customer service. One of our marquee customers recently called on us to modify a traditional customer service solution to address these exact issues. They used a knowledge base as a repository of all expert advice, and a traditional authoring workflow for submitting and approving new content for the knowledge base. However, the relevancy of knowledge customers had access to was lacking because content authoring was not being performed by those on the front lines, fielding questions from customers. As well, their linear authoring flow introduced a time delay between when solutions were written and when they were available to customers. We recommended they take several steps to create a sense of community between their customers, agents, and knowledge authors. We felt this approach would ultimately make their customers more trusting and more loyal. As a first step, we appended a feedback form to all their solutions, asking their customers whether the solutions helped solve their question. Knowledge solutions were then reworked as needed to make them more in line with user demand. We then opened up the knowledge base to help authors, enabling them to publish directly to it without content being routed through a review process. Information was made instantly available to the customer base. Call center agents and customers alike found this especially useful, but there were some questions for which answers did not yet exist in the knowledge base. Next, we recommended a just-in-time KM philosophy. If an agent is unable to find the right solution to a customer's question within a knowledge base, he can author a new solution on the fly. This allows the solution to be captured with the customer's point of view in mind, and in his exact vernacular. Agents are also able to modify existing solutions to correct mistakes or to make them more pertinent to their customer base. In this model solutions are not subjected to an arduous review process, but are reviewed as they are reused by other agents. This ultimately focuses the agent's energy in reviewing and perfecting only the solutions that are the most frequently used. Agents collectively take responsibility for the quality of solutions within their knowledge base. And, appending the name of the agent who last modified a solution helps recognize agents who contribute to the knowledge base. This adds an additional level of peer pressure to ensure that solutions are the best they can possibly be. This organization went a step farther in reaching out to its user community by integrating the knowledge base with a discussion forum. This allows users to recommend information to be added to the knowledge base, ensuring that it grows organically, with customer-recommended changes. The firm also realized that it has groups of expert users who know the product and the customer service agents, and the company now allows expert users to post content directly to the knowledge base, in effect turning each knowledge solution into a wiki. Expert user contributions are identified and can be rated so that poor contributors can be restricted from adding content, while star contributors are recognized. Knowledge management solutions like these are not suitable for all industries, but in many businesses, collaboration between users and agents helps perfect knowledge content in parallel with customer needs. It also helps build a sense of community around your brand, allows you to differentiate yourself from your competitors, and keeps customers loyal by providing accurate and on-topic answers to their questions. About the Author Kate Leggett is director of product management, knowledge management, at KANA. Please visit www.kana.com
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