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Название: Strategic intelligence of an organization amid uncertainty
Авторы: Gitelman, L. D.
Kozhevnikov, M. V.
Chebotareva, G. S.
Дата публикации: 2021
Издатель: WITPress
Библиографическое описание: Gitelman L. D. Strategic intelligence of an organization amid uncertainty / L. D. Gitelman, M. V. Kozhevnikov, G. S. Chebotareva // International Journal of Energy Production and Management. — 2021. — Vol. 6. — Iss. 3. — P. 294-305.
Аннотация: The paper deals with the formation and development of strategic intelligence, a fundamentally new management mechanism in organizations that provides information and analytical support for making anticipatory decisions and the company’s preparedness for unpredictable challenges of the future. The paper systematizes academic approaches in terms of distinctive features and classification criteria of strategic intelligence, formulates its key objectives in the course of digital transformation, and gives the criteria for assessing its level in companies. It is shown that the establishment of strategic intelligence requires the introduction of specialized management systems, such as anticipatory management, and the formation of relevant competencies based on anticipatory learning. An anticipatory management model is proposed that takes into account weak signals for timely and adequate response to emerging threats. The power engineering industry has been used as an example for demonstrating the given model’s capabilities to create standard algorithms for making anticipatory decisions in difficult situations. The paper also defines the role of strategic intelligence in the process of digital transformation and the transformation of organizations into self-learning ones. © 2021 WIT Press, www.witpress.com
Ключевые слова: DIGITAL TRANSFORMATION
PROACTIVE MANAGEMENT
PROACTIVE TRAINING
SELF-LEARNING ORGANIZATION
STRATEGIC INTELLIGENCE
UNCERTAINTY
WEAK SIGNALS
URI: http://elar.urfu.ru/handle/10995/118368
Условия доступа: info:eu-repo/semantics/openAccess
Идентификатор РИНЦ: 47182662
Идентификатор SCOPUS: 85116780465
Идентификатор PURE: 23894659
ISSN: 20563272
DOI: 10.2495/EQ-V6-N3-294-305
Сведения о поддержке: Government Council on Grants, Russian Federation
ACKNOWLEDGMENT The work was supported by Act 211 Government of the Russian Federation, contract No. 02.A03.21.0006.
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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