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The Forensic Evidence Department: Quality’s Implantation Research Paper

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Updated: Oct 31st, 2020


The effects of implementing a quality management system on forensic evidence department employees in Abu Dhabi were analyzed with mixed methods by surveying 30 employees. It was found that the majority acknowledged the benefits of the system and claimed that it had positive effects on productiveness. However, the respondents mostly failed to recognize the effects on behaviors. Based on the study, improvement in the implementation process—in terms of training and tailoring a system to a department—were recommended.


The implementation of quality management systems (QMSs) is based on the recognition that the outcomes of work can be significantly improved by modifying the working process in which staff members engage. In this context, the notion of quality refers to the compliance with targets’ expectations and with certain standards and strategic goals. However, to ensure that a QMS successfully achieves the objective of improving operation, it is necessary to analyze how it is applied to a specific workforce, how it improves performance, and how the staff members affected by it perceive it.

The presented study will explore Abu Dhabi’s forensic evidence department, in which a QMS is being implemented, with the purpose of identifying tangible and intangible effects of the implementation on employees’ behaviors and productivity. It is hypothesized that the addressed QMS makes employees more committed to their work and increases productivity. Based on the research purpose above, the first objective will be to identify appropriate measurement tools for testing the hypothesis. Second, it is planned to examine the relationship between quality procedures and business activities. Third, there is the objective to examine the relationship between quality requirements and the employees’ acceptance of change. Finally, it is needed to integrate the findings and draw conclusions from the established relationships to present recommendations.


Research Design

The presented study will employ mixed—both qualitative and quantitative—research methods to identify the forensic evidence department employees’ perceptions of the implementation of a QMS. According to Piening, Baluch, and Ridder (2014), employee perceptions constitute an integral part of evaluating organizational change because they can help researchers gain insight into factors that facilitate the implementation of change, barriers to successful adoption, and mechanisms through which maximum possible benefits of change can be achieved.

The qualitative survey strategy will focus on asking the employees about the effects of the QMS implemented in their department on the quality of their work, and the quantitative strategy will focus on asking the employees to assess the study’s dependent variables based on predesigned scales (Gable & Wolf, 2012). The employees’ perceptions of the efforts invested in their work before and after (or during) the implementation will be taken into consideration, too.


The study’s participants are the employees of the forensic evidence department of Abu Dhabi Police. Two types of approvals need to be obtained: approval from the head of the department for the conduction of the research and informed consents from the participants (Myers, 2013) who received questionnaires upon being included in the sample. Out of all initially contacted employees, 30 individuals both agreed to participate and were found to comply with the inclusion criteria (being affected by the implementation of the QMS and holding a full-time position at the department). According to the requirements of research ethics, the participants were properly explained the purpose of the study and the contributions they were expected to make.


The research technique adopted in the presented study is surveying. The participants will be provided with questionnaires in which they will be asked to assess their current satisfaction with the process of implementing the QMS and with the consequences of implementation. The questionnaire will incorporate a Likert-type scale, the effectiveness of which in the assessment of perceived performance outcomes has been confirmed in similar studies before (Benavides-Velasco, Quintana-García, & Marchante-Lara, 2014); this will constitute the quantitative element of the research design.

However, to comply with the qualitative design, the questionnaire will incorporate open-ended questions, too, in which the employees will be prompted to describe their perceptions of the effects on their own and their colleagues’ productivity and behaviors. The quantitative data will be analyzed using the Microsoft Excel software, which will allow composing a statistical report (Saldaña, 2015). The qualitative data will be analyzed based on common themes revealed in the employees’ responses.


The results of surveying generally confirmed the initial hypothesis about the positive effects of the QMS on productivity and behaviors. The majority of participants assessed these effects on the quality of their own and their colleagues’ performance as good to excellent, and only 3 percent assessed their satisfaction with the implementation of the system as extremely poor (n = 1).

The quantitative data also revealed that a large group of 80 percent of the respondents (n = 24) acknowledged the positive effects on productivity, while only a minority comprised of 10 percent of the sample (n = 3) claimed to have observed positive effects on behaviors; most participants, according to the satisfaction scale assessment results, thought that the QMS did not significantly affect the employees’ organizational behaviors. Sixty percent of the participants (n = 18) disagreed that the new QMS improved their commitment to work and its outcomes in general and to newly adopted quality management processes in particular.

Concerning the qualitative data collected in the presented study, it was revealed that all of the participants except for one referred to the improved efficiency of operation as a major effect of implementing the QMS. In compliance with the relevant academic literature (Chang & Gurbaxani, 2012), the respondents confirmed that there was a connection between efficiency and productivity, and the former increased the latter by optimizing processes and ensuring larger output with smaller input.

Further, the participants explained the results of the quantitative survey regarding behaviors; the majority stated that they saw no ways in which the QMS affected behaviors. It did affect the procedures and interactions, but more than two-thirds of the participating employees failed to acknowledge behavioral change as one of the goals of quality management in general and the QMS implemented in their department in particular.

Also, another major theme that emerged from the responses is the low level of the QMS’s compliance with the existing operation. Although acknowledging benefits, half of the participants thought that there could have been more benefits if the QMS had been initially tailored to their department more thoroughly and with a better understanding of what forensic evidence specialists do in their everyday work.


A major aspect of the findings presented above is the employees’ lack of understanding of the concept of organizational behavior and its connection to work processes and procedures. Organizational behavior should be understood as the way in which people interact within groups; specifically, the concept refers to the interaction among colleagues who are members of the same organization, team, or department (Pinder, 2014; Wagner & Hollenbeck, 2014).

In contrast, the respondents seemed to put a different meaning in the notion and rather associate it with their individual characteristics and behavioral patterns based on personality types and personal differences. Berry, Carpenter, and Barratt (2012) argue that the perception of productivity and performance quality (both self-reported and other-reported) is linked to the understanding of the ways in which organizational behaviors shape interaction and cooperation among staff members. Therefore, it may be beneficial to include organizational behavior information in the training provided to employees as part of the implementation of QMSs.

It is also important that, despite generally approving of the new QMS (according to the quantitative results), most employees referred to the system’s poor compliance with the essence of their working processes. Zelnik, Maletič, Maletič, & Gomišček (2012) suggest that the lack of employee understanding and approval of implemented QMSs is a predictor of failure to achieve the maximum possible benefits of quality management. Therefore, it is important to ensure that the way in which a QMS will improve particular aspects of operation is properly and explicitly explained to the employees who will be affected by the system.

It can be concluded that the initial hypothesis was mainly confirmed. The implementation of a QMS improved the perceived productivity of the forensic evidence department employees. In fact, the second part of the hypothesis (that behaviors are improved, too) can be considered partially confirmed as well, as the level of successful cooperation increased, although the participants failed to attribute it to effect on organizational behaviors.

Improved commitment to work was not confirmed. Based on the results of the presented research, it can be recommended that the implementers of QMSs include additional information on organizational behavior in the training provided to employees. Also, it should be ensured that such systems are tailored to the needs of a given departments based on the profound understanding of working processes in it.


Benavides-Velasco, C. A., Quintana-García, C., & Marchante-Lara, M. (2014). Total quality management, corporate social responsibility and performance in the hotel industry. International Journal of Hospitality Management, 41(1), 77-87.

Berry, C. M., Carpenter, N. C., & Barratt, C. L. (2012). Do other-reports of counterproductive work behavior provide an incremental contribution over self-reports? A meta-analytic comparison. Journal of Applied Psychology, 97(3), 613-636.

Chang, Y. B., & Gurbaxani, V. (2012). An empirical analysis of technical efficiency: The role of IT intensity and competition. Information Systems Research, 24(3), 561-578.

Gable, R. K., & Wolf, M. B. (2012). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings. New York, NY: Springer Science + Business Media.

Myers, M. D. (2013). Qualitative research in business and management. London, England: Sage.

Piening, E. P., Baluch, A. M., & Ridder, H. G. (2014). Mind the intended-implemented gap: Understanding employees’ perceptions of HRM. Human Resource Management, 53(4), 545-567.

Pinder, C. C. (2014). Work motivation in organizational behavior (2nd ed.). New York, NY: Psychology Press.

Saldaña, J. (2015). The coding manual for qualitative researchers (3rd ed.). London, England: Sage.

Wagner, J. A., & Hollenbeck, J. R. (2014). Organizational behavior: Securing competitive advantage (2nd ed.). New York, NY: Routledge.

Zelnik, M., Maletič, M., Maletič, D., & Gomišček, B. (2012). Quality management systems as a link between management and employees. Total Quality Management & Business Excellence, 23(1), 45-62.

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