Improving the Applicability of Environmental Scanning Systems: State of the Art and Future Research

Abstract

Abstract. The 2008/2009 economic crisis provided a sustainable impulse for improving environmental scanning systems (ESS). Although a rich body of know-ledge exists, concepts are not often used in practice. This article contributes a literature review addressing six findings for ESS design to become more applicable than the state of the art. They are structured by the elements of information systems (IS) design theories. Addressing the lack of a sound requirements analysis, our first finding proposes 360-degree ESS for executives' "managing a company" task and presents how to select just the most important scanning areas to keep focus. Three other findings cover the IS model perspective focusing on a better "grasp" of weak signals: define concrete indicators and use IT to identify relevant cause-effective-chains, leverage IT to automate dayto-day routines and monitor the variety of indicators' movements, and-as a fourth finding-leverage expert experience with an impact matrix and translate indicators' impact into a balanced opportunity-and-threat portfolio. From the methods perspective on ESS, we propose to more closely incorporate scanning results into executives' decision-making process by generating scenarios from a set of environment assumptions as well as to use retrospective controls to continuously update the ESS and collaborate to share the scanning findings day-to-day.

Compensating for perceptual filters in weak signal assessments

“…Recent field studies have recognized the existence of a special managerial process for weak signals, as well as the limiting role of perceptual filters (Ansoff, 1979;Hahn et al, 2014;Hambrick & Mason, 1984;Ilmola & Kuusi, 2006;Nadkarni & Barr, 2008;Weick, 1995), but the process itself has rarely been reinvestigated. Instead, research focused on methodologies to reduce the limiting effects of perceptual filters (Kayser & Bierwisch, 2016;MacKay & McKiernan, 2004;Mayer, Steinecke, & Quick, 2011;Rossel, 2011;Rossel, 2012;Schoemaker, Day, & Snyder, 2013;Thorleuchter & Van den Poel, 2015), the correct assessment of emerging signals (Battistella & De Toni, 2011;Carbonell, Sánchez-Esguevillas, & Carro, 2015;Derbyshire, 2017;Kuosa, 2011;Kuosa, 2010;von Groddeck & Schwarz, 2013;Warnke & Schirrmeister, 2016), and the adequacy of strategic response (Buyl, Boone, & Matthyssens, 2011;Haasnoot, Kwakkel, Walker, & ter Maat, 2013;Reeves & Deimler, 2011).…”

“…Online information proliferated exponentially, as well as data mining software packages and artificial intelligence to interpret its findings. The first studies into the new information and automated analysis have been published already (Kayser & Bierwisch, 2016;Kim & Lee, 2017;Mayer et al, 2011;Yoon, 2012). However, the possible effects of digitalization on the process are unknown.…”

Improving Environmental Scanning Systems Using Bayesian Networks

“…Furthermore, the annual report must contain an assessment of the effectiveness of these control structures and procedures, which the management must attest to and auditors have to comment on in the audit report (Krishnan, Rama, and Zhang 2008;Sherman and Chambers 2009 Webster and Watson (2002), a literature review should be concept-centric. Elements of IS design theories -(user) requirements, models, and methods -combined with the research approach applied offer a rigorous framework for structuring the literature (Mayer, Steinecke, and Quick 2011). Figure 1 illustrates the following research gaps: Sound requirements analysis is missing (Figure 1, first column left): Most of the publications, for example Frolick, Parzinger, Rainer Jr., and Ramarapu (1997) (Chen, Chau, and Li 2011) or scenarios based on opportunity and threat analysis are not specified (Fontela 1976).…”