Identifying and evaluating disruptive technologies using technology scanning

The identification of disruptive technologies and the evaluation of their impact on the own business is a major challenge for technology intelligence. Technology trends such as additive manufacturing (""3D printing"") and the Internet of Things with its applications such as Industrie 4.0 in production technology are seen by companies as both major opportunities and threats to their business models on an abstract level, yet the identification and especially evaluation of specific technologies impacting a company's business in the future is still difficult. Disruptive technologies threaten market incumbents as these technologies enable addressing new or latent customer requirements or evaluation dimensions in a given market rather than improving on the fulfillment of existing evaluation criteria. When the value customers place on requirements and evaluation criteria (i.e. the evaluation context) changes, this can lead to rapid devaluation of products or services using traditional technologies. Technology Scanning is the technology intelligence sub-discipline responsible for finding weak signals of technological trends, and as we conjecture also for finding signals on technology-driven impeding changes in evaluation contexts in relevant markets. To do so, Technology Scanning uses a toolbox of methods including forecasting, scenario analysis, and trend analysis methods. We have previously stated the need for practitioners to have a framework of design recommendations for technology scanning based on the specific company's strategic goals on the identification of disruptive technologies, and outlined a research agenda on providing such a framework. As part of this research agenda, in this paper we present an overview of requirements for identifying and evaluating disruptive technologies in a company's context, and give an analysis of existing methods and design options (processes, organizations etc.) for technology scanning regarding these requirements. We proceed to outline a method to systematically detect possible changes in evaluation contexts to assist identifying and evaluating disruptive technologies using cross-industry analogies. We find that concepts from technology intelligence need to be complemented with concepts from market intelligence and environmental scanning to properly evaluate upcoming disruptive changes.