This paper continues a research program designed to better understand the connections between different types of intangible assets, from data/information to knowledge to intelligence. As a consequence, theory and data are presented from different disciplines, allowing us to identify, by industry, where big data and explicit knowledge are applied as well as those where more tacit knowledge and analytical insights can be found. By better understanding the range of intangibles that can add value and their conditions of use, we can better advise decision-makers on when and how to invest in knowledge management systems, big data systems, intelligence systems, and related installations. The paper will have a substantial theoretical component, focusing on Ackoff’s (1989) DIKW (data/information/knowledge/wisdom) hierarchy and a more contemporary version initiated by Kurtz & Snowden (2003). Given the objective of bringing together different disciplines, scholarship from knowledge management (KM), intellectual capital, big data, and competitive intelligence will be reviewed and conceptualized. Data from financial statements (five years, almost 2,000 firms), a competitive intelligence survey (five years, almost 1,000 individuals), and a McKinsey big data research report will provide support for the analysis. By means of the databases and conceptualization, we can identify industries within which the different intangibles are more or less exploited (Erickson & Rothberg 2012). Industries with extensive use of big data can be uncovered. Industries emphasizing knowledge management installations (especially explicit-focused IT systems) can also be found, as can those more focused on individual tacit knowledge or insight managed through analytics and intelligence. These findings can be analysed through what we know about theory and practice in each of the identified industries. By outlining conditions in an industry–what intangibles lead to competitive advantage, where and how they are applied (operations? R&D? marketing?), what current best practices are—we can offer better advice to decision-makers looking at potential investments in big data and business analytics systems, KM systems (explicit- or tacit-oriented), competitive intelligence operations or other related activities. If monitoring and reacting to operational or transactional information is the key to success in an industry, that is one thing. If it is discerning deep strategic or tactical insights from analysing knowledge and information, that is quite another and calls for a different approach. Helping decision-makers assess their intangibles environment, take sensible intangibles management actions and make appropriate investments would help move the entire knowledge field forward.