Recording Analysing and Using HR Information

HR data is an incredibly valuable asset for both the organization and the HR team. HR data is vital in the decision making process regarding the employees' welfare and as a result optimize processes in the organization Marler and Boudreau, 2017). HR sits on valuable data including training data, recruitment data, personal development and career progression, all of which is very important to the organization. In today's' era of big data and analytics, data is turned into insights useful for predictions such as when and where to recruit suitable candidates, how to attract, identify and retain suitable candidates, when employees will leave and how to keep a happy workforce De (Romree, Fecheyr-Lippens, and Schaninger, 2016). If you are delving into HRM dissertation help, understanding all the intricacies of HR data along with its implications could form a significant aspect of your research. HR does not only collect data valuable to the HR team but rather metrics revealed by HR data provide critical insights that have a significant impact on business performance. Therefore an organization needs to collect HR data because a data-driven HR uses data to evaluate and understand the impact of people on business, make better HR decisions, improve the effectiveness of the employees and thus make business operations more effective and efficient (Shah, Irani and Sharif, 2017).

HR collects a range of data mainly to support the HR role in the organization. Data is collected on both the employer and the employee to help serve the employees more efficiently and to support the HR meet the needs of its workforce (Van den Heuvel and Bondarouk, 2017). Examples of this data include recruitment and retention data, employee count data, contractual agreements and training needs data. Recruitment and retention data comprise of details such as the number of applicants, number of interviews conducted and the outcomes of the hiring process. This data is important to HR as it is used to measure the effectiveness of a company's selection and recruitment processes. Retention data shows the number of employees who stay with the organization and is important for measuring the cost-per-hire metrics. The employee count data is important to the HR practices as it tracks the number of workers at any given time. It determines important metrics such as the ratio of HR staff to employees and to plan on health insurance for the employees. A company should keep this data to determine the best health insurance plans and to determine the number of HR staff to employ. Data on contractual agreements comprise of details such as the pay rates and changes in contractual agreements. This data is mainly a legal requirement and is important to the HR especially when the organization is required by the Regulating Bodies to send information showing compliance such as the National Minimum (Wage Shah, Irani and Sharif, 2017).

HR data is stored in different forms which include electronically as soft copies and manually as papers and documents. In modern times, the electronic form has become more effective and efficient for storage and retrieval of data (Min Shin et al., 2018). Electronically data is stored in soft copy in computerized files. Storing electronic records has more benefits which include increased flexibility, less storage space is required, the information in electronic form is easily searchable, and it is easier to update information and to share it (Sharma and Sharma, 2017). The other method of data storage is manual or paper form. Data is recorded and stored as a paper file and while this method is slowly being abandoned because of its shortcomings, it is beneficial in that files are easily accessible to the users, is not affected in case of technical issues such as a blackout or system crashing.

In the UK, there are legal requirements that relate to the recording, storage and accessibility of data. The following are some of these legal requirements explained. The Data Protection Act 2018 provides and controls the processing of personal data requiring that the competent authorities must implement the Law Enforcement Directives when processing personal data (Carey, 2018). This Act makes it an offence to recklessly or knowingly obtain, disclose, procure or retain personal data with an obtained consent. The second legal requirement is the Freedom of Information Act which provides for how to obtain and access data held by the government or an entity. This Act provides that public authorities must publish certain information concerning their activities (Wallace et al., 2014). Also, it provides that the members of the public may request certain information from any public authorities. People are by this Act allowed access to their data held by a public authority.

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References

Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1-11.

Carey, P. (2018). Data protection: a practical guide to UK and EU law. Oxford University Press, Inc.

De Romree, H., Fecheyr-Lippens, B., & Schaninger, B. (2016). People analytics reveals three things HR may be getting wrong. McKinsey Quarterly.

Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. The International Journal of Human Resource Management, 28(1), 3-26.

Min Shin, D., Shin, B. K., Cheong, H. H., Kong, J. J., Son, H. R., Song, Y. G., & Lim, S. J. (2018). U.S. Patent Application No. 10/164,663.

Shah, N., Irani, Z., & Sharif, A. M. (2017). Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviours. Journal of Business Research, 70, 366-378.

Sharma, A., & Sharma, T. (2017). HR analytics and performance appraisal system: A conceptual framework for employee performance improvement. Management Research Review, 40(6), 684-697.

Van den Heuvel, S., & Bondarouk, T. (2017). The rise (and fall?) of HR analytics: A study into the future application, value, structure, and system support. Journal of Organizational Effectiveness: People and Performance, 4(2), 157-178.

Wallace, S. E., Gaye, A., Shoush, O., & Burton, P. R. (2014). Protecting personal data in epidemiological research: DataSHIELD and UK law. Public Health Genomics, 17(3), 149-157.

Analyses of Data

After the data analysis, the following was observed; the average turnover percentage for the three years is 8%. The highest turnover percentage was in the current year at 14%, the other two years; an average of 5% was recorded. For the past two years, data analysis shows that the company experienced a retention/ stability rate of 118%. The mode for staff leaving was identified as 5 meaning that the mode reason for leaving the company was employee retirement and employees failure to enjoy working for a line manager, or both. This means that the highest number of employees leaving the company left because they retired or, they did not enjoy working for their line manager, or both of these reasons. 6% of the employees left the company because they did not enjoy working for the company. In the last three years, the average number of joiners was 47 employees.

In addition to this data, further information would be useful to ad meaning to the analysed data. For instance, in relation to data about the reason and number of employees leaving, additional data about the sections of the company are leaving. This data would be used to determine the effectiveness of the selection and recruitment method in the different sectors of the company.

Based on the data analysed and information available, this report makes several conclusions about the staffing situation in the company. First, it is clear that the company has a high retention/stability rate, 118% for the period under consideration. Also, the company has a low turnover rate averaging at about 8% in the three years. Lastly, out of the 250 employees in the current years, only about 25 would leave the company for any reasons. In conclusions, therefore, at BlueChip, the staffing situation is healthy but requires improvement.