Data Analytics in HR

DATA ANALYTICS

Data Analytics

Introduction

From the onset, it would be prudent to note that the relevance of deploying data analytics in the realm of human resource management cannot be overstated. This is more so the case given that data analytics could come in handy as a crucial aid to decision making. A data-driven approach to human resource management seeks to ensure that organizations are directed by factual input in their decision making efforts, as opposed to guesswork or mere intuition. In the words of Waters, Streets, McFarlane, and Johnson-Murray (2018), “HR analytics can improve the credibility of the HR function by showing the linkage between people and business outcomes” (9). This write-up concerns itself with some of the scenarios whereby analytics could be deployed from a workforce perspective. More specifically, the specific workforce areas to be highlighted are: employee turnover and employee engagement.

Idea 1: Employee Turnover

Employee turnover (which is also routinely referred to as employee turnover rate) could be defined as the rate at which employees of a firm leave employment over a specified period of time. This is more so the case in relation to those employees that the organization has to replace. It is for this reason that Dessler (2018) defines employee turnover rate as “the loss of talent in the workforce over time” (152). The employee turnover rate is one metric that an organization should not ignore. This is more so the case given that it enables the organization to assess how effective its HR policies and practices are. It should also be noted that when employee turnover rate is high, the company incurs high hiring costs. This is more so the case given that, as has been indicated above, employees that the company loses in his case have to be replaced. Thus, hiring costs associated with a high employee turnover could be inclusive of, but they are not limited to, advertising costs, administrative costs associated with selection, training costs, etc. A high rate of employee turnover also comes with the associated cost of productivity loss. Productivity loss could in this case be taken into consideration from the perspective of actual productivity loss when the employee leaves a position vacant and loss of productivity as a new employee is being oriented into a new role. Yet another overlooked downside of a high employee turnover rate is decreased morale among the remaining employees. This is more so the case given that when their colleagues leave, the remaining employees may have to work overtime. On the basis of the downsides presented above, the relevance of deploying analytics in this context cannot be overstated.

a) Hypothesis/Business Question

Has the turnover rate of the organization been on an upward or downward trend over the last five years?

b) Leading Indicators

i. Overall turnover rate: This would help us make sense of data relating to the number of employees who leave the company during the specific year of interest. To compute the overall turnover rate, the number of those who leave the organization, say in year X, could be divided by the average number of employees (which is essentially the total number of employees that the organization has at the beginning of year X added to the number of employees who remain with the organization at the end of year X, divided by two). The figure obtained is then multiplied by 100. This could then be compared with the industry average.

ii. Voluntary turnover rate and involuntary turnover rate: There could be need to distinguish between those employees who leave the company willingly and those who are forced out, i.e. fired. It could be argued that the company may be interested in the voluntary turnover rate as this is what would be more representative of underlying HR issues, if any. Whereas voluntary turnover rate could be computed by dividing the number of employees who depart on their own volition (within a certain time period) with the total number of employees (on average), involuntary turnover rate could be found by dividing the number of employees who are terminated by the company with the total number of employees (on average). The figure obtained is then multiplied by 100.

iii. Employment length (on average): This could provide the company with important insight on how long employees stay on its employ. If employees stay for a short period of time and then leave, then this could be an indication of deep-seated HR issues that need to be resolved. The length of stay could in this case be compared with the industry average.

c) Business Impact Metrics

On this front, we could seek to establish whether the employee turnover rate over the sad period of time had an impact on productivity. Productivity happens to be one of the business impact metrics highlighted by Pease, Byerly and Fitz-enz (2013). If turnover is found to be correlated with productivity, then the relevant interventions can be deployed. This is more so the case given that as “HR interventions are designed with business outcomes in mind” (Pease, Byerly and Fitz-enz, 2013, p. 32). The main aim in this case would be to establish whether the organization has a high employee turnover rate and how the said turnover impacts productivity.

Productivity could in this vase be measured in terms of:

i. Company profitability (i.e. net income)

ii. Comparison between input (i.e. total labor time) and output (i.e. in terms of the number of manufactured products).

Idea 2: Employee Engagement

In basic terms, employee engagement could be defined as “the extent to which employees feel passionate about their jobs, are committed to the organization, and put discretionary effort into their work” (Dessler, 2018, p. 211). Towards this end, the author is categorical that employee engagement differs from employee satisfaction. This, according to the author, is more so the case given that as opposed to employee satisfaction which is largely concerned with the extent to which employees are content and/or happy, employee engagement takes into consideration how emotionally invested or committed employees are, as well as their involvement and motivation levels (Dessler, 2018). It therefore follows that employee engagement could be deemed one of the key HR concerns.

a) Hypothesis/Business Question

To what extent could the employees of this organization be deemed engaged?

b) Leading Indicators

On this front, the organization’s employee engagement data, would come in handy. Employee engagement data could be derived from the results of an employee engagement survey. To ensure that such a survey is effective, there will be need to not only benchmark it against organizations similar to ours, but also ensure that it is statistically validated. In our case, there are five metrics that the employee engagement survey could focus on:

i. The motivation levels of employees

ii. How well the employees comprehend the overall goals and objectives of the company

iii. The morale and mood of employees

iv. Employee-manager relationship

v. Workload perceptions

c) Business Impact Metrics

Here, there may be need to establish whether the extent to which employee engagement impacts profitability. Revenue is one of the business impact metrics highlighted by Pease, Byerly and Fitz-enz (2013). On this front, the focus would be on determining the impact (if any) the level of employee engagement has on the organization’s bottom-line.

To obtain the relevant financial data, there will be need to focus on the income statement and the balance sheet. This is especially important owing to the fact that it is from the said statements that the relevant data on the profitability of the enterprise will be sourced. More specifically, the focus will be on statements from the three most recent financial years. For better perspective, profitability will be compared with that of close competitors. Crucial metrics on this front will be inclusive of: