Moving from Collecting to Leveraging Knowledge:
When talking about knowledge management, most companies think in terms of rich and complicated repositories of documents containing information on customers, employees and operations. However, more important than having all information stored is the proper management of all strategic knowledge assets: core competences, areas of expertise and intellectual property , and enabling employees to have fast and easy access to these assets. As mentioned in the HBR article Managing Your Mission-Critical Knowledge: “in the absence of a clear understanding of the knowledge drivers of an organization’s success, the real value of big data will never materialize”. This becomes even more critical in the modern workplace where documents are dispersed, employees can work remotely, and careers paths change fast.
Traditional knowledge management systems organize all company files using a strong metadata structure and are intended to facilitate the capture and transfer of company expertise to spur learning and innovation. Nevertheless, research by Wharton professor Martine Hass indicates that knowledge sharing efforts often fail to result in improved task outcomes due to a lack of supportive context: employees cannot work at their best if they do not have easy and fast access to the exact information they need. In this sense, the Search Functionality of your KM tool becomes the key to its success and explains why many KM systems implementations have fallen short of their promises.
Introducing ChatBot technology to refine Search Functionalities
Search functionalities often provide multiple results based on keyword matches, metadata refiners and past popularity of files. When tags and dependencies are installed manually by Knowledge experts, they quickly become obsolete. Matt Wade explained that even pinned search results (e.g. promoted results in SharePoint) are poor since it “gives administrators a little wiggle room to force a result, but usually only one item per search term can be pinned. Generally, the predictability and dependability of search in this situation is bad because what shows up in today’s may not be what will be there next week”. Moreover, employees are most of the time not provided with direct answers to their queries but with supporting documents that they have to digest to find the specific answer they needed. Clicking though folders, views and filters is still a chore and can dissuade an employee from looking further for a file they need. The result? They either accept not finding the information which will ultimately affect the quality of their work or contact someone else for help, thereby using that employee´s valuable time on a task that was most likely already shared with someone else in the past.
Elqano has introduced a ChatBot powered technology to overcome the shortcomings of Search Functionalities. In a nutshell, coversation becomes the new way of sharing, the new interface. This innovative mechanism works as follows:
Daily, Elqano connects to all existing systems (SharePoint, Microsoft Teams, Circuit,...) and automatically tags all employee documents to know who has worked on what.
The identification of knowledge is called expertise mapping and is used to train Elqano ChatBot in identifying critical knowledge and engaging key stakeholders.
By using Q&A interactions as knowledge extraction, Elqano ChatBot streamlines the interaction between employees and experts, resulting in an improved customer engagement process and employee experience.
The combination of continuous semantic analysis with expertise mapping self-updates the ChatBot specific taxonomy.
Providing the answer instead of the source of information
Elqano ChatBot lets the employee skip straight to the answer while pointing him/her to the source for reference, saving both the expert and the employee time. It provides what is needed when it is needed, nothing more. Employees will no longer have to deal with extraneous results, from keywords that overlap to outdated information, or having to read, digest and further search for information after finding the source they wanted.
The above screenshot shows three extra benefits of Elqano:
It avoids duplicated work. Experts no longer need to reply several times to the same question. Elqano collects all Q&A past interactions and will redirect the information seeker to the best answer to their querie. By providing only curated responses to what employees are looking for, Elqano dramatically increases the efficiency of knowledge sharing across the company.
It points the information seeker to complementary sources should they need additional information. Elqano will recommend complementary experts and Q&A to complete the requests. For example, in the case of a new launch in an emerging country, a precise and complete answer will contain both the input of the local execution team leader and the supply chain coordinator.
It requires minimal user training. Employees do not really enjoy having to take a training course on another new entreprise tool to learn about folder structures and search. Elqano ChatBot requires no training: employees only need to type a question and the bot will provide them with the answer and the right expert.
Looking for a way to improve the flow of knowledge in your organization? Contact us today!