Boosting employee morale - Essay Example

Boosting Employee Morale Boosting employee morale enhances the realization of goals and objectives that guide the operations and activities undertaken in the workplace. Knowledge and skills are critically employed in the process, and the outcome can be assessed or evaluated in terms of skills or methods used against employee performance. The process to boost employee morale can be characterized by either success or failure, a scenario that can actually be tested.Increase in employee morale translates to improved employee performance, and consequently enhances operational success in the workplace relative to the activities that employees engage in.

To test whether the skills or methods used in the process increases employee morale, the first step is to identify the variables involved. These could be qualitative or quantitative in nature (Johnson 304). The impact of increased employee morale can be quantitative, but the skills or methods applied are highly qualitative. To test the impact that skills or methods used create in boosting employee morale, quantifying skills/methods variables is vital. ANOVA tests suit this process (Johnson 357).

Once the qualitative variables are quantified, they can be linked to the outcome of increased employee morale through the necessary testing steps in ANOVA statistical procedures.Achieving the above goal can be subject to a number of issues that influence the inferences made from the test. These are: difficulties in choosing the quantitative variable to use following improved employee morale (for example increased output or revenues), individual differences across employees may not be accounted for, and quantifying some qualitative variables of skills/methods nature may result in a totally different outcome.

On the other hand, the testing design adopted exhibits both strengths and weaknesses. The quantification of qualitative variables makes the testing process quick and easier (Johnson 391). However, the testing procedure may be prone to statistical errors that may result in conclusive inferences that are rather limited.Works CitedJohnson, Richard. Statistics: Principles and Methods. New York: John Wiley & Sons, 2009.