Innovation strategy, culture, and funding aside, one of the greatest challenges facing the innovation worker – those folks in your organization tasked with developing new products, finding new markets, and improving existing products – is accessing the information they need in order to solve problems and make decisions.
But accessing knowledge – even internal corporate knowledge – is time-consuming and tedious.
Product development information is scattered across different departments and geographies. Intranets and shared drives do little to solve the knowledge retrieval challenge. And traditional keyword search is ill-suited for research across the incredible volume of unstructured data that makes up the vast majority of R&D content. Because traditional search technologies are unable to process the meaning of queries and of the content they are searching, traditional searches generally return lots of irrelevant ‘results’. Even if an engineer or researcher is able to locate a potential document of interest, they then need to read the document to determine if it is truly relevant to the problem at hand.
All this time-intensive research is especially frustrating when you consider that up to 80% of research time (according to market research studies) is spent doing work that is similar to, if not the same, as work that has previously been done (often in one’s own organization), while only 2% of a researcher’s time is spent performing novel research.