Digital Transformation of Talent Acquisition

Rafique, Mofasshara Binte, 2017

Type of Thesis Master Thesis
Client
Supervisor Gatziu Grivas, Stella
Views: 24 - Downloads: 2
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.
Studyprogram: Business Information Systems (Master)
Keywords
Confidentiality: öffentlich
Type of Thesis
Master Thesis
Authors
Rafique, Mofasshara Binte
Supervisor
Gatziu Grivas, Stella
Publication Year
2017
Thesis Language
English
Confidentiality
Public
Studyprogram
Business Information Systems (Master)
Location
Olten