Developing a knowledge management strategy for data analytics and intellectual capital

Purpose - This paper aims to build on current analytics and Big Data definitions and strategies from the literature to develop an overall strategic model connecting knowledge management strategy (KMS) for intellectual capital (IC) acquisition and business use. It also extends the IC research stages to a fifth stage of IC research including IC strategic intent. Design/methodology/approach - A literature review highlights the connections among strategic intent, firm strategy, KMS and a data analytics strategy aligned with firm and KMS strategic intent. An extended model of the interrelationships is developed from the prior research. Findings - A model framework was developed from the literature that connects Big Data to achieve the goals of a firm KMS and demonstrates how Big Data analytics (BDA) needs to shift from being a tactical tool to a strategic knowledge management tool directed by the overall strategy and strategic intent of the firm. Research limitations/implications - The model presented needs to be empirically tested over a sample of companies and periods to determine if performance improves using this model. Practical implications - Use of this model proposes that strategic intent will be enhanced and improve the capture of intellectual property derived from advanced analytics and increase sustainable advantages at firm. Social implications - The social implications of lack of strong privacy laws coupled with the possible elimination of millions of knowledge worker jobs creates a pressing need for more research into and identification of firm’s and government’s Big Data strategic use for both good and perhaps evil. Originality/value - The research in this paper extends current models of IC development and adds strategic intent and collective intelligence as the fifth stage of IC research and presents an overall KMS/BDA model.