AI Enabled Dynamic Capabilities

Helping Large Organisations to Overcome Disruptions with a Capability Orchestration Framework

Master Thesis (2020)
Author(s)

K.L. Smith (TU Delft - Industrial Design Engineering)

Contributor(s)

Sicco Santema – Mentor (TU Delft - Responsible Marketing and Consumer Behavior)

E.Y. Kim – Mentor (TU Delft - Responsible Marketing and Consumer Behavior)

AG Plugge – Mentor (TU Delft - Responsible Marketing and Consumer Behavior)

Faculty
Industrial Design Engineering
Copyright
© 2020 K.L. Smith
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 K.L. Smith
Graduation Date
26-08-2020
Awarding Institution
Delft University of Technology
Programme
Strategic Product Design
Faculty
Industrial Design Engineering
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Abstract

Due to globalisation and technological advancements, the world is becoming increasingly complex. Volatile, uncertain, complex and ambiguous (VUCA) environments have called for organisations to become more agile in order to survive and compete in such changing environments. Large organisations are at particular risk for becoming stagnant due to operational inertia. In order to combat this and achieve agility, dynamic capabilities are developed. These capabilities allow an organisation to more effectively and efficiently change to incoming threats or opportunities. Such changes create uncertainty and insecurity amongst employees which translates into higher employee turnover and decreased performance. Stability therefore needs to be provided for individuals, while achieving dynamacy for organisations. This paradox of dynamic stability drives research into understanding relationships and effects caused by
disruptions. Covid-19 is used as an extreme use case in order to create these understandings. After primary and secondary research conclusions were developed, a conceptual framework was developed in order to orchestrate capabilities. This aims to help speed up the time taken for opportunities/threats to be translated into outcomes. This also aims to help improve the depth, diversity and accuracy of these outcomes.

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