The correlation between the most innovative companies and those that embrace knowledge management (KM) systems has been documented by academics for 15 years. Knowledge management is vital because, among other things, innovation-driven organizations recognize the need to facilitate collaboration within and between their strategy, R&D, product management, sales and marketing teams.
Collecting, interpreting and acting on large data was something that companies with an innovation strategy excelled at. This was likely due to their sophisticated knowledge management systems. Being able to work with large amounts of data allows knowledge to be shared throughout the company, creating better products, services and outcomes for customers.”
The ability to collect, organize, and readily share unstructured data is just as important, both for reviewing relevant literature – from primary and secondary market research studies, journals, conference abstracts and posters, industry and government databases, and media reports – and for mining field intelligence provided by an organization’s sales, service, and support personnel.
Aggregating all relevant textual information in one integrated repository, and making it readily searchable, is not a trivial task, which is why many companies – even the largest global enterprises – partner with an outside specialist to do it. A user’s ability to find meaningful content within their organization’s knowledge management system is largely a function of how documents have been indexed, and the search engine within the system. When all documents are deeply and consistently tagged according to relevant industry-specific taxonomies, text analytics can be applied, enabling users to discover relationships between the concept areas revealed in search results and uncover relevant business issues hidden in content.
Significantly, today’s advanced knowledge management systems also enable “subject matter experts” (SMEs) within an organization who have expertise relevant to a user’s topic of interest to be displayed along with documents in search results. Such capability facilitates collaboration among colleagues in ways that previously were not practical because, especially in a large enterprise, you can’t know everyone who may be knowledgeable on a given subject. Now, an advanced KM system can show the user a SME’s areas of expertise, professional biography, relevant documents they have authored, and their contact information, without even being asked.
Some KM systems are utilizing artificial intelligence (AI)-based machine learning to synthesize information to make it easier for people to digest quickly. This may take the form of machine-generated summaries of the most salient points within a document, or automated referrals to other documents in a content collection that pertain to a user’s specific area of interest.
Finally, the most valuable knowledge management systems facilitate sharing and distribution of information in a variety of ways. An AI-enabled insight distribution ecosystem is an infrastructure that directs relevant content and insights to the individuals who need it, in a timely manner, via whatever medium or mechanism those individuals prefer, automatically. Options may include strategic dashboards, search results, newsletters, machine learning-driven recommendations and insights reports, email alerts, RSS, and more.
A knowledge management system with these capabilities deployed by a well-organized and resourced organization may well give it a leg up over its competitors. As the authors of the latest innovation strategy research write: “All innovation strategy elements — leadership, resources, knowledge management and processes — were found to increase the likelihood of new discoveries.”