Optimizing Data Driven Recruitment Strategies in a Disruptive Era Through Digital Workload Analysis

Summary To emerge as a leading global energy company, an agile structure that facilitates business acceleration and operational excellence is necessary. However, following a recent subholding restructuring, the organization faces a 23% vacancy rate. This situation is compounded by the dynamic business landscape, which makes additional challenges to recruiting efforts. To address these issues and ensure an effective recruitment strategy to maintain productivity while adapting to the changes, a comprehensive organizational evaluation and processes is essential. A digitalized Workload Analysis (WLA) application was implemented to comprehensively assess staffing needs of 6,200 positions across the organization, including structural and contracted positions. This approach addressed limitations of conventional WLA methods such as data validity and extended timeline. Pre-filled questionnaires based on standardized job descriptions ensured data accuracy, and sharing sessions for high-level management, Subject Matter Experts (SMEs), and all respondents, further enhanced completion quality. Additionally, technical guidance and support were offered in various forms, including online/offline assistance, instructional videos, and interactive communication channels. This streamlined WLA process was completed within two months. The analysis resulted in some critical insights: among the 23% vacancy rate, 15% were identified as high-priority roles within core operational teams. Another 3% could be eliminated, while recruitment for another 5% could be deferred based on anticipated business developments. These findings informed targeted recruitment strategies, timelines, and resource allocation, ensuring efficient workforce management. Emphasizing a data-driven approach, it optimizes the recruitment process and identifies opportunities to enhance efficiency by eliminating redundant positions, supporting the company to swiftly adapt to evolving talent demands and ensuring readiness in the dynamic business landscape.

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Publication Details

Published
2024-11-04
DOI
https://doi.org/10.2118/222976-ms
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.64
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article

Optimizing Data Driven Recruitment Strategies in a Disruptive Era Through Digital Workload Analysis

Sri Handayani, Ratna Dewi Kusumaningtyas, Danang Wahyu Wicaksono, Novita Eka Putri et al.
1 citations
Human-Automation Interaction and Safety
0.64
article

Optimizing Data Driven Recruitment Strategies in a Disruptive Era Through Digital Workload Analysis

Sri Handayani, Ratna Dewi Kusumaningtyas, Danang Wahyu Wicaksono, Novita Eka Putri, C. Triasnita
article en
1 citations

Abstract

Summary To emerge as a leading global energy company, an agile structure that facilitates business acceleration and operational excellence is necessary. However, following a recent subholding restructuring, the organization faces a 23% vacancy rate. This situation is compounded by the dynamic business landscape, which makes additional challenges to recruiting efforts. To address these issues and ensure an effective recruitment strategy to maintain productivity while adapting to the changes, a comprehensive organizational evaluation and processes is essential. A digitalized Workload Analysis (WLA) application was implemented to comprehensively assess staffing needs of 6,200 positions across the organization, including structural and contracted positions. This approach addressed limitations of conventional WLA methods such as data validity and extended timeline. Pre-filled questionnaires based on standardized job descriptions ensured data accuracy, and sharing sessions for high-level management, Subject Matter Experts (SMEs), and all respondents, further enhanced completion quality. Additionally, technical guidance and support were offered in various forms, including online/offline assistance, instructional videos, and interactive communication channels. This streamlined WLA process was completed within two months. The analysis resulted in some critical insights: among the 23% vacancy rate, 15% were identified as high-priority roles within core operational teams. Another 3% could be eliminated, while recruitment for another 5% could be deferred based on anticipated business developments. These findings informed targeted recruitment strategies, timelines, and resource allocation, ensuring efficient workforce management. Emphasizing a data-driven approach, it optimizes the recruitment process and identifies opportunities to enhance efficiency by eliminating redundant positions, supporting the company to swiftly adapt to evolving talent demands and ensuring readiness in the dynamic business landscape.

Pertamina (Indonesia) (ID)
Decent work and economic growth
Openalex Percentile: Top 26%
Human-Automation Interaction and Safety
0.64
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Optimizing Data Driven Recruitment Strategies in a Disruptive Era Through Digital Workload Analysis — Sri Handayani, Ratna Dewi Kusumaningtyas, et al. · (2024) | TGRS Research Map | TGRS