Problem Based Learning

1

Introduction

The objective of this study plan is to evaluate the viability of our solution in relation to previously conducted test cases for companies operating in industries analogous to those of our own. In this section, we will concentrate on the manner in which these use cases measure the performance characteristics of various technical and behavioral qualities connected with an investment in technology made on behalf of a business. The viewpoints and data sources of stakeholders will be incorporated into our measuring system. This measurement framework will be utilized by us in order to assess and analyze the overall performance of our product. After the solution has been implemented, we will conduct post-implementation evaluations to determine how the solution affected the organization. The management of change will play a significant role in our overall research agenda. The plan will adhere to a certain format in providing the findings of the data analysis.

Measurement framework

In order to present an all-encompassing picture of performance, the measuring framework must to take into account the many stakeholder viewpoints as well as the various data sources. Perspectives from stakeholders may come from a variety of sources, such as the user community, project managers, or senior leadership. Customer feedback, system logs, and performance statistics are three examples of potential data sources (Thabane, 2009).

The purpose of the measurement framework is to supply stakeholders with viewpoints and data sources that may be utilized to evaluate the effectiveness of an investment in technology. The framework consists of four dimensions: behavioral characteristics, organizational aspects, user factors, and technological qualities (McShane, 2018). To evaluate how well the technology investment is working out, there is a separate set of performance indicators linked with each of the dimensions of the evaluation.

Indicators such as system uptime, reaction time, and throughput are examples of technical qualities. Indicators that make up behavioral qualities include things like user happiness, adoption rates, and the costs of training. Indicators like as return on investment (ROI) and total cost of ownership are included in the category of organizational variables (TCO). The metrics that make up user factors include things like user happiness, adoption rates, and training expenses (McShane, 2018).

The measuring framework draws its information from a variety of data sources, including organizational data, user data, performance data, and financial data. The return on investment (ROI) and total cost of ownership (TCO) of the technological investment may both be calculated using financial data (Jalal, 2017). The uptime, reaction time, and throughput of the system may all be evaluated based on the performance statistics. Data from users may be analyzed to determine factors such as user happiness, adoption rates, and the costs of training (Thabane, 2009). Data from the organization may be analyzed to provide insight into aspects of the organization such as its culture, structure, and procedures.

Effect of measurement on the general performance evaluation

There will be a variety of ways in which each measurement will influence the overall performance evaluation. For instance, if you are evaluating the performance of a brand-new software application, the data that you collect will demonstrate how effectively the application functions as well as the degree to which users are pleased with it. Using this information, you will be able to evaluate whether or not the application successfully satisfies the requirements of the organization and whether or not purchasing it was a wise financial decision (McShane, 2018).

There are a few different metrics that may be used to evaluate how successful an investment in technology has been. The most typical approach is to examine the manner in which the technology is being utilized. Tracking the number of users, the amount of time spent utilizing the technology, and the quantity of work that has been finished are all ways to accomplish this goal. Monitoring the amount of slip-ups and mishaps is yet another approach to performance evaluation that may be used. Tracking the number of calls received by customer support, the amount of system crashes, and the number of software upgrades are all good ways to accomplish this goal (Jalal, 2017).

Post-implementation evaluations

After the technology has been released to the user community and is now being utilized by those individuals, post-implementation assessments have to be carried out. The performance of the technology will be evaluated throughout this stage of the process in order to determine whether or not there are any areas in which it may be improved. In order to determine how well a newly introduced piece of technology is operating, post-implementation evaluations, also known as PIEs, need to be carried out after the technology has been put into use. PIEs are essential to the success of a business since they give feedback on whether or not the newly implemented technology is living up to the organization's expectations (Jalal, 2017). PIEs can assist businesses in recognizing areas in which the newly implemented technology can be enhanced if they are carried out.

Change Management

Assessing the possible effects of a change is the first thing that has to be done when dealing with change management. This involves determining who will be impacted by the change, what that change will imply for them, and how they are most likely to react to it. After gaining an understanding of the possible effects that the change may have, a strategy may be devised to assist in the management of the transition. This may entail drafting new policies and procedures, offering assistance throughout the transition time, and providing training for individuals who may be impacted by the change (Aslam, 2010).

Format to Present Data Analysis Report

Tables, graphs, and charts are just some of the usual ways that the findings of data analysis can be presented after being formatted. Tables are frequently utilized for the display of raw data, whilst graphs and charts are frequently utilized for the depiction of trends and patterns within the data (Thabane, 2009). Because the format for presenting the findings of data analysis will differ based on the particular data that is being analyzed and the audience that the report is intended for, the format for reporting the results of data analysis will change. A report on data analysis should, in general, include an explanation that is both clear and succinct of the data being analyzed, the techniques that were used to analyze the data, and the outcomes of the study. In addition to this, it is essential to make certain that the report is clear and does not contain any complicated terminology.

Test Solution

There are several ways to evaluate a technological investment's performance. Benchmarking is one strategy. This entails contrasting the performance of the technology investment with that of other businesses operating in a related or same industry. Using a before-and-after strategy is another technique to evaluate performance. This entails evaluating the technological investment's performance both before and after it has been made. Data gathered from users, clients, or other stakeholders might be used for this (Aslam, 2010). Using a control group strategy is another option to evaluate performance. This entails evaluating the technology investment's performance for a group of users who have it and contrasting it with the performance of a group of users who do not have it (Thabane, 2009).

The team will need to put the answer to the test after creating the study strategy. The group will need to create test cases to do this. Test cases are particular situations created to evaluate the effectiveness of the technological investment (Thabane, 2009). The test cases should be created to assess how well the technology investment performed in relation to the precise goals listed in the evaluation framework. The team must create a test plan that details the precise actions that must be followed in order to carry out the test cases. The team must also create a data collecting strategy that specifies the precise information that must be gathered in order to evaluate the effectiveness of the technological investment.

Conclusion

In summary, using a measuring framework is a crucial component of any performance assessment. The framework offers a method for taking into consideration the many data sources and the numerous stakeholder opinions. The efficacy of a technological investment may be assessed using this information. The success of a firm also depends on post-implementation assessments. When dealing with change management, the first step that has to be taken is evaluating the potential implications of a change. In order to do this, it is necessary to identify the people who will be affected by the change, what it will mean for them, and how they will likely respond to it (Aslam, 2010).

References

Aslam S, Emmanuel P. (2010). Formulating a researchable question: A critical step for facilitating good clinical research. Indian J Sex Transm Dis. 31: 47–50

Jalal K. (2017). Software Infrastructure to Reduce the Cost and Time of Building Enterprise Software Applications: Practices and Case Studies. Retrieved from: https://www.researchgate.net/publication/322267534_Software_Infrastructure_to_Reduce_the_Cost_and_Time_of_Building_Enterprise_Software_Applications_Practices_and_Case_Studies

McShane, S., & Von Glinow, M. (2018). Organizational Behavior (McGraw-Hill. 8th ed.,) Boston, MA

Thabane L, Thomas T, Ye C, Paul J. (2009). Posing the research question: not so simple. 56:71-79