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O’Mahony, Juanita (2024) To what extent does strategic talent measurement impact talent management strategies in STEM industries. Masters thesis, Dublin, National College of Ireland.
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Abstract
Technology is driving change in the global talent management industry which is projected to grow from its estimated value of USD 8.6 billion to USD 15.29 billion by 2028 (PR Newswire 2023). Talent Measurement is a crucial component of talent management given that it enables companies to determine both the short and long-term human capital requirements for their business, in order to remain innovative and competitive.
This study has been conducted to determine to what extent strategic Talent Measurement impacts talent management strategies in STEM industries. Specifically, who measures what, and how. The currently available literature on Talent Measurement is limited and one-dimensional and does not provide sufficient evidence of what, or how, talent is measured in practice (Yogalakshmi and Supriya 2020; Thunnissen, Boselie and Fruytier 2013; Guthridge, Komm and Lawson 2008).
Primary data was collected from a sampling selection of HR professionals and Hiring Managers working within enterprises in STEM Industries. Quantitative data was obtained through cross-sectional research, a questionnaire was constructed and self-administered online, and the data analysis was completed using SPSS software, applying regression and correlation techniques (Field 2018). The reliability of the constructs was assessed by Cronbach’s alpha.
The evidence revealed a significant finding that users' interest in strategic outcomes appears to be influenced by their use of predictive techniques, such as AI and machine learning. The results revealed that the more technology-savvy HR professionals are, the increased likelihood they will use predictive techniques when measuring talent. The findings confirm that not a single participant “Always” employed predictive analysis in skill assessments, implying that current measuring methodologies are not rooted in facts, but instead based on “gut” and influenced by bias.
This study highlights the acute necessity for disruption in the Talent Management industry. Most HR users are not using predictive techniques, and companies may have unknowingly contributed to perceived skill shortages by declining suitably qualified candidates, due to inexperienced HR professionals and Hiring Manager's bias. This study adds to the field of Strategic Measurement by identifying a link between manual selection and strategic measurement, which offers support to HR policies and encourages investments in HR users' analytical skills, as a means to expedite knowledge and growth.
The researcher would hope that the core finding regarding users' interest in strategic outcomes, which appears to be influenced by their use of predictive techniques and AI, will provide the basis for future research into skill combination and strategic performance.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Loughnane, Gerard UNSPECIFIED |
| Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Talent Management |
| Divisions: | School of Business > Master of Science in International Business |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 11 Aug 2025 14:30 |
| Last Modified: | 11 Aug 2025 14:30 |
| URI: | https://norma.ncirl.ie/id/eprint/8487 |
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