Methodology Report: ERP architecture and implementation

Study Design

This research analyzes the application of an ERP architecture and implementation strategy at Dunkin Donuts. The research aims to answer the question whether Dunkin Donuts requires an ERP system upgrade. In addition, the efficiency and effectiveness of the system in relation to the operations of the company are analyzed using data from other companies and institutions. Ideally, the research is an analysis of the business operations at Dinkins Donuts and the necessary requirements that would make the company better. In achieving this, the research employs both qualitative and quantitative data from the literature review. An analysis of these data is effective in identifying the most efficient programs and systems to be upgraded in the company

Moreover, the application of Microsoft Dynamics programs is tested for the different roles in the business operations at Dunkin Donuts. The application of the different systems in the execution of such functions as supply chain management, business intelligence and financial management (Mourao & Weiner, 2006) is tested. Data collected in this study will be sourced from past literature on the application of the Microsoft Dynamics system applications. In addition, data from interviews and questionnaires will be incorporated in assessing the perceptions of end users regarding the system upgrade.

Population and Sample

The study employs a population cutting across the different gender because Dunkin Donuts is a company that encourages gender diversity. However, the population is limited to employees of the company to ensure that only people that have a direct relationship with the company are interviewed. In selecting the sample, the research employs a systematic sampling method where the relevant departments in the company are identified. Overall, five departments will be sampled to represent the five different functions that the system application supports within the company. After identification of the five departments, a random sampling technique will be employed to select participants to be interviewed using a questionnaire. Data will then be collected from all the selected participants in the company.

Variables and Measures

In assessing the data collected, the research employs the use of a single question for each of the variables of age, gender, and years of employment in both the current and other organizations. The use of single questions is also important in answering the question of whether they were satisfied with the current system in the company. Moreover, the research uses the variable of preference of new system by asking the question of whether the employees preferred another system.  In addition, the link between past employment and the choice of the ERP system among employees was tested using information sourced from the participants’ past employment.

The responsibilities assigned to the employees will also be tested to ascertain if it correlated with the choice of ERP system in the employees. The general assumption is that employee’s past experience with the Dynamics system applications influences the perception of the employees regarding their application (Luszczak, 2015). Moreover, the research aims to test whether the choice of the system is dependent on such variables as age and gender. The department in which the employees are stationed and their dependence on automated systems further influences the choice of the ERP system among employees. Ultimately, all the variables and measures will be used in the analysis to ascertain the different correlations and to test the hypotheses.

Data Collection Methods

The small scale of the research means that the data collection process is simple and can be performed within a few days. In addition, the diversity in numbers within the group ensures that data collection can be done faster through specialization and division of the different tasks. In the research, the group intends to distribute 30 questionnaires to the identified participants within the organization. Ideally, the questionnaires will be manually distributed in hard copies in a single day. In addition, the questionnaires will not be left with the participants but will be filled in real time as the researcher waits to collect them. The benefit of having the questionnaires filled as the research watches is that it minimizes errors in the process of filling in the questions. After distribution of the questionnaires, all the questionnaires were returned fully filled with no errors in the responses. The high return rate is because of the fact that the researcher waited for the questionnaires to be filled before collecting them. Moreover, the presence of the researchers is an advantage since questions that required elaboration were handled perfectly well and in real time.

Data Analysis Method

After the data is collected, the researchers intend to analyze using a number of instruments. The first step is the determination of the reliabilities for the measures to be used in the sample. Later, the research will use frequency distributions to analyze the demographic variables in which form they will be presented. After the analysis of the demographic variables, the other dependent and independent variables will then be tested using a Pearson correlation matrix (Zwick, 2006). The analysis of the different variables will be used in testing the two hypotheses that the research has identified. The correlation between the different variables will be tested using the Pearson correlation matrix. The analysis of the data also incorporates data from past researches as is documented in the literature review. In this aspect, the research banks on the qualitative and quantitative data in making conclusions regarding the application of Dynamics systems in the company.

 

References

Luszczak, A. (2015). Using Microsoft Dynamics AX 2012: Updated for Version R3.

Mourão, L. X. B., & Weiner, D. (2006). Dynamics AX: A guide to Microsoft Axapta. Berkeley, CA: APress.

Zwick, R. (2006). Some properties of the Pearson correlation matrix of Guttman-scalable items. Princeton, NJ: Educational Testing Service.

 

 
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