THE USE OF MCKINSEY’S 7S FRAMEWORK AS A STRATEGIC PLANNING AND ECONOMIC ASSESTMENT TOOL IN THE PROCESS OF DIGITAL TRANSFORMATION

Year 2019, Volume: 9 Issue: 1, 114 - 119, 30.07.2019

Ezgi Demir , Batuhan Kocaoglu

https://doi.org/10.17261/Pressacademia.2019.1078

Abstract

Purpose- It is aimed to evaluate the maturity of the business through the
transition to digital transformation under McKinsey’s criteria.

Methodology- The aim of this study is to make an
organizational structure and economic assessment of enterprises in the digital
transformation process and to contribute to the literature. In this evaluation,
the criteria and sub-criteria of the 7S's framework will be modelled in accordance
with the Multi-Criteria-Decision-Making methodology. In this study,  McKinsey’s 7S’s dimensions have been clustered with the
digital transformation criteria. In this clustering, the weights of the
criteria have been determined by using AHP method and the maturity assessment
of the business for digital transformation has been reached.  In the study, 5 expert managers were asked to
evaluate the criteria among themselves. Afterwards, a survey of company
employees has been conducted to evaluate the maturity for business. The questions
through the survey about the stages they carried out during the company's
digital transformation process have been asked to the business employees.

Findings- In the model digital transformation criteria were defined for
business according to McKinsey’s 7S. The weights of the criteria have been determined during the
digital transformation stage in the enterprises. Finally, the maturity of
digital transformation of the enterprise has been determined.

Conclusion- The study provides a maturity assessment methodology which is an
important part of digital transformation process. It is planned to provide
benefits both for the practitioners and academics focusing on maturity
assesstment in business for the digital transformation.

Keywords

Digital transformation, maturity assesstment, McKinsey’s 7S, ahp

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