KNOWLEDGE management (KM) applications have been on the market for more than 40 years, but this category is still not fully understood. Perhaps it’s because KM applications are similar to other categories—enterprise search, content management systems, collaborative platforms like SharePoint—and it’s been easy for vendors to obfuscate the differences. Nevertheless, they’re valuable applications that have a six- to 12-month return on investment (ROI), can be implemented in three to six months, and can benefit an entire enterprise, not just the contact center.
DMG defines KM as “a structured methodology and technology framework used to capture and curate the collective information of their organization, industry, clients and employees, transform the data into knowledge assets, and systemically distribute the knowledge assets for the achievement of organizational objectives.”
THE PANDEMIC RAISED INTEREST IN KM
COVID-19 drove employees home to work, and it also brought home the need for an effective knowledge base. Agents could no longer simply turn around and ask a colleague a question about a product or how to handle an inquiry; they needed an easy-to-use and accessible source for enterprise information. In turn, companies need a standard source of information and answers to respond to the growing volume of self-service inquiries, which have become the preferred method of service for customers. And, of course, it’s essential for the answers and information delivered by live agents to be the same as what customers receive from self-service solutions—interactive voice response (IVR) systems, intelligent virtual agents (IVAs), and the like—although the answers have to be delivered in a manner that is consumable and appropriate for each channel and constituent.
A well-designed KM solution uses an optimized search capability to find and deliver the right answers to their audience of users—internal agents, back-office staff, or customers—in an appropriate format. The better KM solutions are designed to optimize delivery of knowledge in a manner that minimizes the user’s investment of time. With each subsequent look-up, the KM system gets better at narrowing the options to be delivered. Users of a KM solution don’t want to be bothered with how (or why) it works; they simply want to receive the right answer or information in the shortest time possible.
AI AND MACHINE LEARNING NEED INSTITUTIONAL KNOWLEDGE
For an artificial intelligence (AI) solution to work well, it requires a large repository of data in which to find patterns. Machine learning algorithms are designed to analyze a massive data repository and identify new issues, approaches, answers, and more.
Companies have been using their KM solutions as these repositories or sources of information and knowledge to feed their AI- and machine learning-based applications. This is fine as long as the information a KM application contains is up to date and as complete as can be. Making the same institutional knowledge available to AI and machine learning systems as well as all internal and external-facing employees is a great way to standardize the dissemination of company information.
The age-old challenge for KM solutions is to load them with data and keep the information accurate and timely. This is an area where there are substantial differences among solutions, and also another way in which KM solutions are different from search applications. The better KM solutions know when their information is out of date and can automate much of the process of updating it. This is a necessity—given the volume and diversity of information these solutions hold, automation is the only viable way to keep them current. It’s also an area where AI and machine learning can make major contributions, and something companies should examine during the buying process.
SO TO ANSWER THE ORIGINAL QUESTION…
Yes, the time has come to invest in a KM solution, preferably one with a highly flexible search capability. It should notify its users when data/information/processes/policies have become stale. It should come with automated recommendation and updating enabled by AI and machine learning. It should be able to access internal and external information as it looks for the right answers. It should render information in the ideal format and presentation vehicle for each inquiry, and it should be easy to use. This all sounds like a big ask, and it is. But good KM solutions can do all this today, so it’s time for companies to leverage them for the benefit of agents, customers, and the bottom line.
Donna Fluss is president of DMG Consulting. For more than two decades she has helped emerging and established companies develop and deliver outstanding customer experiences. A recognized visionary author and speaker, Fluss drives strategic transformation and innovation throughout the service industry. She provides strategic and practical counsel for enterprises, solution providers, and the investment community.
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