Digital Transformation of Talent Acquisition

Rafique, Mofasshara Binte, 2017

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Gatziu Grivas, Stella
Keywords
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In the era of digitalization, organizations are facing increasingly challenging business environment where they must redefine their business strategy, activities, and processes to adapt themselves with the fast evolving technology trends. To keep up with the pace, organizations need talents with special skills and capabilities who can help them through the transformation. Talent acquisition faces tremendous pressure to find and hire great talents especially in a volatile economy where there is a widespread shortage of skills. Nevertheless, there is no existing generic framework or guidance tool to support digital transformation of the talent acquisition. This research paper has developed a systematic guidance tool that aligns business strategy and talent strategy with the present TA technologies and platforms.Based on a framework for digital business models called eVISOR, a talent acquisition maturity model, with four levels of maturity, has been developed which acts as a roadmap for improving organizations’ talent acquisition approach, and help TA leaders and professionals assess their current capabilities on the continuum and decide how they would like to progress in the future. A motivation analysis has been performed based on which the subcategories of the maturity model were developed and prioritised. To provide an overview of the key practices involved in talent acquisition a reference model has been developed, and a stakeholder map has been created that can enable the TA professionals maintain a sound relationship with the key stakeholders in order to deliver an effective and efficient service. Expert interviews were conducted to evaluate the quality of the artefacts developed and assess whether the artefacts align with the real life business scenario.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Rafique, Mofasshara Binte
Betreuende Dozierende
Gatziu Grivas, Stella
Publikationsjahr
2017
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten