A business’s MIS department can be most beneficial in using HR Data to reduce costs in many ways that enhance the effective application of technology. MIS department use of HR data creates a central point of data collection and analysis that minimizes the cost of information management (Nocker, 2019). Central data integration enables the MIS department to acquire accurate and consistent decision-making and implementation of management ideals. The use of HR Data in management helps reduce the cost of hiring interdisciplinary experts to analyze and evaluate the data for improvement in the company. HR data provides essential information on resource utilization that enables the management to improve services.
HR Data enables the MIS department to develop decisions from the analytics and reports that cover key performance indicators, which reveal the insights and contributions of the employees. The management department system articulates information to keep track of metrics that help in the retention of employees and boosting their performance through training and changes to better compensation, which cuts the cost of recruitment for replacement (Jabir, 2019). HR Data also provides predictive analysis that MIS departments utilize to prevent problems that are likely to occur, saving the cost incurred in solving the challenges. MIS department can engage the employees to make strategic plans, which enhances the sense of belonging and performance.
Business’s HR departments can encourage objective decision-making through data in various ways that improve and implement strategic plans for achievement. The HR department can promote decision-making based on data through accuracy and transparency in the collection and analysis of data on performance, recruitment, and allocation of resources (Park, 2020). Accuracy and consistency in data in the HR department encourage objective decision-making by keeping track of various metrics for management and other executives’ performance measurements. Data governance in the HR department can encourage objective decision-making due to the assurance of personal data privacy that enhances quality and compliance.
The HR department can encourage objective decision-making through data by investing in training and career development for the HR professionals to gain skills in analysis and improvement in data evaluation that enhance efficiency and effective communication for productivity (Jabir, 2019). The department can be improved by integrating and assessing external data, which involves exhaustive analysis that influences decision-making on high standards and quality improvement. Eliminating biases in data collection and analysis could encourage making decisions based on decisions and implementing objectives in business.
Problems can arise in using HR data in decision-making for various reasons that compromise data analysis and evaluation. Overdependence on data can affect the contribution of human knowledge and experience, which limits the sense of belonging and hinders humanity’s perception in decision-making on matters affecting the stakeholders (Park, 2020). The cost of developing and maintenance of high-quality data is high, which is challenging for companies during instability and low output. Some companies strain to meet the demands of analysis and collection of data due to the high cost of hiring experts to ensure the smooth running of events.
Data-driven practices in organizations are restrained by resistance to change. Using HR data can be problematic in management that resists changes, which hinders the adoption of the new system. Processing of HR data requires digitalization and application of various technology techniques to manage large sets of data for accuracy and reliability, which is expensive and requires computing resources (Jain, 2020). Interpretation of data is another challenge that affects performance due to the influence on decision-making. Erroneous interpretation hinders the achievement of success of the initiatives in the organization since the practices will bear different outputs from the analysis. HR data faces problems with data security that lead to cyberattacks and system hacking, which threaten the safety of data, putting the organization at risk.
References
Jain, P., & Jain, P. (2020). Understanding the concept of HR analytics. International Journal on Emerging Technologies, 11(2), 644-652. https://www.researchgate.net/profile/Pooja-Jain-30/publication/340950833_Understanding_the_Concept_of_HR_Analytics_-_The_Theory_of_HR_Quantification/links/5ea70d21299bf1125612f3b9/Understanding-the-Concept-of-HR-Analytics-The-Theory-of-HR-Quantification.pdf
Jabir, B., Falih, N., & Rahmani, K. (2019). HR analytics a roadmap for decision making: Case study. Indonesian Journal of Electrical Engineering and Computer Science, 15(2), 979-990.https://pdfs.semanticscholar.org/f5b9/e4c4d3a3a42aa5ebab2e9b3003d97508ee10.pdf
Nocker, M., & Sena, V. (2019). Big data and human resources management: The rise of talent analytics. Social Sciences, 8(10), 273. https://www.mdpi.com/2076-0760/8/10/273
Park, Y., & Mithas, S. (2020). Organized Complexity of Digital Business Strategy: A Configurational Perspective. MIS Quarterly, 44(1). https://www.researchgate.net/profile/Youngki-Park-2/publication/339703982_Organized_Complexity_of_Digital_Business_Strategy_A_Configurational_Perspective/links/5e7d09c092851caef4a1ef6f/Organized-Complexity-of-Digital-Business-Strategy-A-Configurational-Perspective.pdf
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