Competitor intelligence: information or intelligence?

Freeman, Olivia

doi:10.1177/0266382994237126

Cited by 10 publications

(4 citation statements)

References 2 publications

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“…Critics of the above proposal may claim that active investigation of primary sources of risk information is best left to the area of fuzzy overlap between the competitive intelligence, business intelligence and marketing intelligence functions which already have wellestablished competency in this area (Freeman, 1999;Wright and Calof, 2006;Calof and Wright, 2008;Smith and Lindsay, 2012). Nonetheless, we suggest risk management can take a leadership and coordination role, linking these functions to the rest of the organisation through a guiding theoretical concern with the purposeful cross-functional co-development of risk forecasting knowledge.…”

Section: A Dangerous High Stakes Activity?mentioning

confidence: 99%

Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation

Marshall

Ojiako

Wang

et al. 2019

International Journal of Forecasting

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This theoretical perspective paper interprets (un) known-(un) known risk quadrants as formed from abstract and concrete risk knowledge. It presents these quadrants as useful, both for categorising risk forecasting challenges against levels of abstract and concrete risk knowledge typically available, and for psychometric research measuring perceived levels of abstract and concrete risk knowledge available for forecasting. Drawing on some cybersecurity risk examples, a case is made for refocusing risk management forecasting effort towards raising unknown-unknowns into known-knowns. We propose achieving this by developing the 'boosted risk radar' as organisational practice where suitably 'risk intelligent' managers gather 'risk intelligence information', such that the 'risk intelligent organisation' can purposefully co-develop both abstract and concrete risk forecasting knowledge. We illustrate what this can entail in simple practice terms within organisations.

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Section: A Dangerous High Stakes Activity?mentioning

confidence: 99%

Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation

Marshall

Ojiako

Wang

et al. 2019

International Journal of Forecasting

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“…A cultura da empresa não é orientada para uso dos sinais fracos. Lesca (1994); Rouibah e Bessam (2001); Freeman (1999). Uso de informação antecipatória é considerado muito dificil (embora altamente útil).…”

Section: Dificuldades Na Gestão De Sinais Fracosunclassified

“…El Sawy e Pauchant (1988); Gelb et al, (1991); Lesca (1994); Rouibah e Lesca (1996); Attaway (1998); Freeman (1999); Rouibah e Ould-Ali (2002); ); Rouibah (2002); Rouibah (2003). Gestores tem frequentemente pouca tolerancia à ambiguidade e podem ser relutantes em dedicar tempo adicional para a conjectura de hipóteses alternativas.…”

Section: Processamentounclassified

Weak Signals Management, Entrepreneurship and Uncertainty: A Relational Theoretical Essay Under the Perspective of Intelligence

Janissek-Muniz

Blanck

2014

Proceedings of the 11th CONTECSI International Conference on Information Systems and Technology Management

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The more one recognizes the strategic importance of information for organizations, the harder it is the perception about the difficulties associated with the search and productive use of information. This research investigate two points: is there an association between the difficulties perceived by managers in the management of weaksignal and the level of entrepreneurial orientation of organizations? And is there is an association between the perceived difficulties and the dimensions of uncertainty perceived by organizations? We conduct this research from the perspective of Intelligence, given that it covers the steps involved in the search, identification, classification, storage, dissemination and use of information. This structure will make it possible to associate the main difficulties in the management of weak signals (identified in previous studies), according to their nature with the Intelligence process. In turn, this will enable an analysis of the relationship between the most significant difficulties perceived by organizations with the degree of entrepreneurship they employ, as well as with the dimensions of uncertainty perceived.

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“…However, it has drawbacks because more information requires more processing to understand its reliability, relevance, and recency (Hanratty, Newcomb, Hammell, Richardson, & Mittrick, 2016), and with limits in human cognition, more information can decrease decision-making performance (Marusich et al, 2016). In our current state of technology, a trained intelligence analyst will provide greater decision-making capability than will software (see Freeman, 1999), but increased information will also stress an analyst’s working memory capacity (Pirolli & Card, 2005; Stasko, Görg, & Liu, 2008) or the amount of information that may be processed at once.…”

Section: Introductionmentioning

confidence: 99%