Sample Economics Paper on Human Capital Analytics

Human capital analytics is the process of applying the analytic procedures to the Human Resources division of an organization to get better employee performance and as a result, boost the return on investment. Most companies are changing from operational research to human capital analytics applications by just applying simplified logic instead of statistical data. Human capital analytics is a three-dimensional module, namely data quality, analytics capabilities, and strategic ability to act, and all this is embarked upon on three levels, which are individual, structure, and process.

Data quality is one of the dimensions and i, if not up to standard, it becomes an exceedingly vital barrier to the progress of reliable human capital analytics. How data was collected, the rules applied in its collection, how data sets are merged, and also their advantages or disadvantages is rather crucial since all these factors matter in analyzing the quality of data (Kassim &Naggy, 2015,P.110). Data quality comes at a cost, but if correct and consistent, it simplifies the workings of an organization and hence increases investments.

In addition to these analytical capabilities is another dynamic of human capital analytics that deals with the analytics team’s capacity to assess variables, put together conceptual models, accurately analyze them, and give a convincing account (Felin, Foss, Heimeriks & Madsen, 2012, P.1360). Most analytics teams hardly ever conduct researches that cover all aspects of analysis they, however, give oversimplified explanations in their models.

For any analysis to be of assistance to an organization, it has to be buried, including all required features of the investigation, and have accurate results that can explain sophisticated models and facilitate the model’s execution in the organization.

 

 

An organization’s strategic ability to act is the last dimension of human capability analytics. It generally refers to a company’s ability to work on the analytics projects and implement them for the betterment of the company (Ulrich & Dulebohn, 2015, P.192). The changes that will be put in practice will increase the company’s productivity by default because they have been statistically and practically proven.

Each of the three dimensions of human capital analytics has to perform well for the overall effect of being positive. Most of the organizations that have great performances employ Human capital analytics at the foundation level, so they gradually grow into great businesses.

There are three levels to human capital analytics, which are individual, processes, and structure. At the individual level, data quality is the most critical factor; it is ensured by the use of KSAs, which allows companies to configure, categorize, and manage vast quantities of corporate data (Bersin, Houston & Kester, 2014, P.270). Members of analytics teams should be able to incorporate quantitative analysis with qualitative methods for great outcomes.

The next level is organizational processes which with ensuring data quality by creating and sustaining data systems aimed at large data organization. With random data collection errors such as data, duplication will occur, therefore failing the organizational processes.

Lastly, we have structures, which are very important in the development of HCAs. Social structures and organizational culture have to be implemented; this will only work if everyone from the top managers to the workers acknowledges the significance of HCAs in the organization.

Human capital analytics is a gradually developing concept in the business world, but one that is highly promising since organizations that have implemented it have obtained immense profits as a result.

 

References.

Kassim, I., & Nagy, M. (2015). The state of workforce analytics in Europe. Workforce Analytics Summit.

Felin, T., Foss, N. J., Heimeriks, K. H., & Madsen, T. L. (2012). Microfoundations of routines and capabilities: Individuals, processes, and structure. Journal of Management Studies, 49(8), 1351-1374.

Bersin, J., Houston, J., & Kester, B. (2014). Talent Analytics in practice: Go from talking to delivering on big data. Deloitte University Press. Date Accessed, 3(01), 2015.

Ulrich, D., & Dulebohn, J. H. (2015). Are we there yet? What’s next for HR?. Human Resource Management Review, 25(2), 188-204.