Marketers, Big Data and Intuition – Implications for Strategy and Decision-Making



Krishnan, Gopal
(2018) Marketers, Big Data and Intuition – Implications for Strategy and Decision-Making. Doctor of Business Administration thesis, University of Liverpool.

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Abstract

Marketers worldwide are grappling with issues relating to effective decision-making in context of the opportunities and challenges created by the emergence of Big Data. Marketing executives are challenged by the impact of advances in technology, measurement and Big Data in making decisions regarding delivering short-term business results and creating a long term future. Traditional marketing analytics rely more on propositional knowledge as opposed to Big Data marketing analytics that depend more on automated procedural knowledge. It has been observed in the workplace that marketers operating in the world of Big Data are challenged with how to adapt their decision making styles to these advancements. This need for change has created some amount of confusion and lack of clarity in marketing teams as has been observed in the author’s own workplace. Rather than let the operators in “the trenches” figure a way out through trial and error, this thesis and accompanying research aim to provide an actionable framework for guiding marketers as they make critical decisions. Based on theory-generating expert interviews with senior marketing leaders, this thesis proposes a novel application framework for decision-makers in Marketing, which connects the cadence of strategic, operational and tactical decisions in the business with Big Data, analytics, and intuition. The application of the framework is subsequently illustrated in a workplace setting through Action Research that seeks to improve the decision-making styles within a marketing team. The application of the framework helped the action research group to transform their quality and efficiency of insight collection, analysis and decision-making. This research thesis demonstrates the evolution of the problem, creates a novel and actionable framework that can be used by marketers, demonstrates the efficacy of the model in a workplace action research setting and finally provides a guide to implementation of this framework in the service of marketing executives in other organizations.

Item Type: Thesis (Doctor of Business Administration)
Uncontrolled Keywords: Big data, Intuition, Decision making, Judgment, Marketing, Strategy, Digital Marketing, Chief Marketing Officer, CMO, Analytics, Global marketing, Management, Organizational development, Theory Generating Expert Interview, Action research, Management theory, Insight, Knowledge, Leadership
Divisions: Fac of Humanities & Social Sci > School of Management
Depositing User: Symplectic Admin
Date Deposited: 27 Nov 2018 16:09
Last Modified: 09 Jan 2021 04:58
DOI: 10.17638/03027868
Supervisors:
  • Mastorakis, George
URI: https://livrepository.liverpool.ac.uk/id/eprint/3027868