Data attempts to explain concept of data management

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Data collection within organization is vital especially in supporting Human Resource Management Systems. Data management is the science of collecting, analyzing, and properly storing data in line with the laws and regulations controlling data monitoring. Thus, this analytical treatise attempts to explain concept of data management especially on the facets of data collection, storage and accessibility in the department of Human Resources Management (HR).

Scientifically, the process involves modeling unified data to provide accurate and single view of activities within the HR such as training, recruitment, compensation, performance, and employment management. For instance, ‘oracle leverage optimal workflow circles’ in multinational companies ensure easy and accurate accessibility of stored records within the shortest time possible.

However, the major reasons for collecting HR data are to meet stringent legal requirements such as personal details of workers, number of workers, salaries, hours of service, and medical condition. Often, companies are obliged to give accurate details to governmental departments whenever there is a need. Besides, data stored in the HR server is essential for protection of company against claims in court of law. Since details of each employee are kept intact, proper documentation would paint a clear picture for every complaint registered. [1]

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The two types of data collected by HR department include the Operational Information Data and Tactical Information Data. Under Operational Information Data, HR management team should be conscious of it arrangement and storage medium.

This data exist in the form of HR profile records and includes organization dependent and personal information of the employees such as sex, name, address, citizenship, marital status, seniority data, salary grade, minority status, employment history, retirement, experience, and education level. Besides, the records collected may be inclusive of special preferences by employees.

In addition, the data captures skill inventory for each worker. In some cases, it contains information surrounding test scores, work experience, preferences, interests, and proficiencies or special skills. Besides, government reporting and compliance data avail information as indicated by laws that facilitate monitoring and observing compliance within regulations. These government initiated regulations aim at reducing costs and improving productivity.

For instance, job analysis system provides data on guideline compliancy, safety measures, and relevancy of skills for every department in an organization. Generally, data contained in the Operational Information System include information on position control, placement, and application, performance management information, and compliance to government standards information. [2]

On the other hand, Tactical HRIS provides support information to managers on decision making process such as design and job analysis, development and training, and compensation plans for employees. Generally, Tactical HRIS data capture information on recruitment, design and job analysis, benefit and compensation, and development and employee training systems.

Information on compensation and benefit records is vital in designing a comprehensive compensation program and fast tracking retirements and replacements. In decision making, properly collected and scientifically analyzed data provide accurate and reliable decision variables necessary in determining resource allocations for training, expansion, and structuralism to keep a competitive edge.

Among the most reliable methods of data storage in HR, management include the electronic data storage and traditional filing. Electronic data storage devises are effective in terms of space and time. Under this medium, data irrespective of its magnitude can be stored in digital and analogue formats. After the desired data is encoded, the non-volatile computer storage system captures all details permanently and allows for editing.

In the contemporary global arena, technology has made it possible to create backup systems that ensure safety of information. On the other hand, traditional system of filing records provides an alternative especially for small scale use. Under this system, data storage is organized alphabetically in cabinets and a reference sticker placed besides each record. This method is easy to monitor and safe especially when records are few.

The United Kingdom has policies and regulations on data collection, storage and accessibility. For instance, the ‘Acas Code of Practice’: Discipline and grievances at work provide guidelines on training courses which equip HR professionals with proper management policies and monitoring records.

In addition, the Regulation of Inventory Powers Act of 2000 cover limits placed for organizations for monitoring records in private and public networks. Reflectively, it empowers employees to benefits from organization’s carelessness with personal information. Also, the Data Protection Act of 1998 contains a code of conduct monitoring employer’s compliance. Specifically, part one of the act cover selection and recruitment rules. Moreover, part two is consistent in defining limits and ways of keeping employment records secured.

Part three and four deal with observations made at work and confidentiality of medical records respectively. A breach of the above policies attracts hefty fines and penalties as defined in the law. Stated in the code, information obtained or stored via the monitoring system should be used within the purpose of collection and must be secured. However, employers may breach this especially where there is proof of crime detection or prevention.

In a company of 200 employees, records analysis concentrates on the Absence Data Bank. This record is generated electronically and it records absence, time of reporting, details of each employee upon clocking in the thumb screen located at the entrance.

On Monday, two employees are absent with permission, however, another employee is also absent without formal explanation. Among the present employees, there are four arrive late for work. In the afternoon shift, six employees are out on official duty. The above data can be presented in the pie chart below.

From the above data, it is apparent that performance rate is slightly above 95%. Besides the Absence Record indicating three employees as absent, the computerized system captures the percentage of those who arrive late at 2%. This data captures general data as recorder in the system.

Therefore, further analysis should give clear statistics and foster creation of monitoring framework for marking the absence list and defining instrumental aggregates of valid comparison. Specifically, the scope of this analysis provides finer details of each employee as generated over a five day period. Therefore, information obtained is vital for determining performance of each employee and managing payroll especially for late arrivals and absentees with no formal notification.

Conclusively, HR Management is dependent on relevant data collection, proper record storage, and practical application in policy formulation and decision science. Reflectively, these actions must be in line with policies instituted by the government. Data on employees can be used in operation and tactical functions in an organization. Generally, data collection and management as a science should embrace systematic approach and in-depth analysis to understand labor management and factors surrounding its functionality.


Brown, C., & Arianne, H. Policy and practice in European human resource management: the Price Waterhouse Canfield survey. Rutledge, Alabama, 1994.

Martin, J. Key Concepts in Human Resource Management. SAGE Publications Ltd, Alabama, 2010.

Taylor, S. People resourcing. CIPD Publishing, New York, 2005.

Martin, J. Key Concepts in Human Resource Management. SAGE Publications Ltd, Alabama, 2010.
Brown, C., & Arianne, H. Policy and practice in European human resource management: the Price Waterhouse Canfield survey. Rutledge, Alabama, 1994.

Categories: Decision Making


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