<p>Real-Time Talent Liquidity Dashboards for Adaptive Workforce Allocation in Global Financial Institutions</p>

Business requirements, regulations, cyber threats, and technology initiatives can evolve rapidly, making it even more critical for large financial institutions to have workforce planning in place. A lot of banks have information regarding employee skills, project demand, time tracking, training records, and compliance information in various systems. As a result, managers might know they have talent within the organization but may not have the ability to identify and recruit the right person at the right time. This paper focuses on how a real-time talent liquidity dashboard can help improve workforce allocation. The dashboard compiles employee skills, availability, project requirements, cost, and compliance limits in one place. It assists managers in identifying potential candidates, assessing their skills, determining whether they are suitable for the job, and understanding what factors may limit the staffing choice. The study uses a mixed-method approach. It includes a proposed dashboard design, simulated evaluation results, and stakeholder feedback. The results indicate that such a dashboard can help decrease staffing delays and enhance staffing decisions. For the pilot-style results, the median time-to-first-acceptance was reduced from 9.2 days to 6.8 days, the internal fill rate increased from 54.0% to 63.5%, and contractor spend was cut by 11%. The findings indicate that real-time visibility, predictive matching, and compliance filtering could be useful tools for managers to make quicker and more accurate staffing decisions. At the same time, the dashboard does not make staffing decisions on its own. It gathers the evidence, ranks the options, and flags the constraints, while the final judgment stays with the manager who reviews each recommendation. Meanwhile, the dashboard itself will only be of any use if the data that underlies it is accurate, up-to-date, and properly controlled. This paper makes the case for viewing a talent liquidity dashboard not as another human resources report. It should be viewed as a decision-making tool that enables financial institutions to make faster, more transparent, and responsible decisions about their workforce. The paper also stresses the importance of having robust data quality, well-defined skills, human oversight, privacy safeguards, fairness checks, and audit trails before adopting such a system in a regulated setting.

Authors

Publication Details

Journal
Cureus Journal of Computer Science.
Published
2026-07-24
DOI
https://doi.org/10.7759/s44389-026-00180-1
Primary Topic
Human Resource and Talent Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

<p>Real-Time Talent Liquidity Dashboards for Adaptive Workforce Allocation in Global Financial Institutions</p>

Pratik Pravin Mahajan
Cureus Journal of Computer Science.
Human Resource and Talent Management
article

<p>Real-Time Talent Liquidity Dashboards for Adaptive Workforce Allocation in Global Financial Institutions</p>

Pratik Pravin Mahajan
article en

Abstract

Business requirements, regulations, cyber threats, and technology initiatives can evolve rapidly, making it even more critical for large financial institutions to have workforce planning in place. A lot of banks have information regarding employee skills, project demand, time tracking, training records, and compliance information in various systems. As a result, managers might know they have talent within the organization but may not have the ability to identify and recruit the right person at the right time. This paper focuses on how a real-time talent liquidity dashboard can help improve workforce allocation. The dashboard compiles employee skills, availability, project requirements, cost, and compliance limits in one place. It assists managers in identifying potential candidates, assessing their skills, determining whether they are suitable for the job, and understanding what factors may limit the staffing choice. The study uses a mixed-method approach. It includes a proposed dashboard design, simulated evaluation results, and stakeholder feedback. The results indicate that such a dashboard can help decrease staffing delays and enhance staffing decisions. For the pilot-style results, the median time-to-first-acceptance was reduced from 9.2 days to 6.8 days, the internal fill rate increased from 54.0% to 63.5%, and contractor spend was cut by 11%. The findings indicate that real-time visibility, predictive matching, and compliance filtering could be useful tools for managers to make quicker and more accurate staffing decisions. At the same time, the dashboard does not make staffing decisions on its own. It gathers the evidence, ranks the options, and flags the constraints, while the final judgment stays with the manager who reviews each recommendation. Meanwhile, the dashboard itself will only be of any use if the data that underlies it is accurate, up-to-date, and properly controlled. This paper makes the case for viewing a talent liquidity dashboard not as another human resources report. It should be viewed as a decision-making tool that enables financial institutions to make faster, more transparent, and responsible decisions about their workforce. The paper also stresses the importance of having robust data quality, well-defined skills, human oversight, privacy safeguards, fairness checks, and audit trails before adopting such a system in a regulated setting.

Cureus Journal of Computer Science.
Decent work and economic growth
Openalex Percentile: Top 4%
Human Resource and Talent Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.