MBA504 Introduction to Data Analytics for Business Case Study 1 Sample

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MBA504 Introduction to Data Analytics for Business Case Study 1 Sample

Your Task

Analyse the “The future of work after COVID?19” report from a data analytics perspective.

Assessment Description

This assessment requires you to read and interpret a report written by McKinsey Global Institute. The report analyses trends following the impact of Covid-19, such as remote work and the uptake of digitalization and automation in work processes.

McKinsey Global Institute research combines the disciplines of economics and management, employing analytical tools with the insights of business leaders.
This report explores the post Covid work environment in 8 countries from a range of perspectives and metrics.

Assessment Instructions

In this assessment, you need to:

Part A

• Study “The future of work after COVID?19” report from a data analytics perspective and provide an analysis incorporating the key points. A synopsis without analysis is insufficient to satisfy the requirements of the assessment.

a. The key insights, commentary on methods used, critique of the presentation methods and visualisations as well as possible improvements should be described. This should be addressed based on your learnings from the course.

• Specifically:

a. Derive and quote and describe appropriate statistical metrics from the report

b. Suggest alternative graphical or visual representation

c. Comment on the data collection and management.

Part B

• Reflect on the key takeaways from this report, specifically those regarding the importance of developing your data analytics skill.

Solution

Introduction

Covid-19 has brought significant changes in the working scenario of various sectors and across several nations. University assignment help, The research work conducted by Lund et al. (2021) helps to highlight the changes in the working scenario of the countries in the post-pandemic times. The researchers have taken the help of data analytics to establish the working condition and have been successful in presenting the unbiased approach of apprehending the working scenario and the subsequent development in the post-Covid working condition (Ghani et al. 2019). This report helps to analyse the statistical visualization and the methods that have been used to depict the data that establishes the changes in the working arena after the Covid-19.

Part A

Data analytics has been instrumental in providing specific help or guidance to complete the assessment of scenarios regarding economic growth in the post-Covid times (ur Rehmanet al. 2019). It is important to look over the needs and requirements of the post-Covid working condition with this process.

 

Figure 1: Change in the revenue patterns of the e-commerce industry after Covid-19
(Source: Lund et al., 2021)

It will help the various industries to adapt to the post-pandemic times through the implementation of remote working strategies (Galetsi, Katsaliaki, & Kumar, 2020). It is seen that performance data analytics can help in understanding the development of the industry across different countries. The result of the research conducted by Lund et al.2021 suggested that the growth in the e-commerce industry of the UK and Spain is the highest. This method permits aids in understanding that the mentioned that it is observed that the efficient performance data analytics system aids in understanding that the development of the e-commerce industry is quite high. “In China, e-commerce, delivery, and social media jobs grew by more than 5.1 million during the first half of 2020” (Lund et al. 2021). This graphical representation has established the growth of the e-commerce industry across 8 nations in a comprehensive way.

It is seen that this method will help to get a better view of the requirements as well as the opportunities it will benefit the post-Covid working condition as well as the various industries and the employees. This data analytics can assist in how well the employees improve to more closely align with the organizational development of the e-commerce industry. It is also seen that this process often looks into the method in a very keen manner which impacts the development of the e-commerce industry in the time of the post-Covid times (Lund et al. 2020).

 

Figure 2: Change in the employment sector after Covid-19.
(Source: Lund et al., 2021).

The data analytics looks over the method and evaluates through it to understand which employees are eligible to receive the promotion. This visualization method impacts positively as they are motivated to work intensely and provide a better-quality depiction of the available data and this also helps to conclude about the drastic changes that have occurred in the employment sector after Covid-19.It can be seen that the process only advances with the employees' performance and they can work in a positive environment in the case of the health department. It is seen that if the post-Covid working condition are provided with the proper facilities and are discussed and the increase or decrease in the various working sectors can be assessed. Hence in case of the various industries are taking steps in providing entrepreneurs with the facility so that they will be able to enhance their problematic situation and consider working in a positive and better environment.

 

Figure 3: Depiction of job transition in the e-commerce industry after Covid-19.
(Source: Lund et al., 2021)

It is observed that the working force will benefit, as well as the various industries will improve their working strategy as well as profitability. This has resulted in changes in the mindset of the employees which in turn has resulted in the given rise to the transition to the new jobs.

On the other hand, Sheng, Amankwah?Amoah, Khan& Wang, (2021),also observed that there is a requirement to look over the transitions in the new jobs after the post-Covid-19 scenario and this can be done with the aid of data analytics.The results suggest that there is a growing tendency of job transition in the post covid times and this will persist till 2030. It is seen that if the work is not done properly then it becomes quite an issue to hold on and this will be prevalent in all the It is the reputation that builds the various industries and if they are facing challenges in incorporating work with the employees and providing them with the proper needs and requirements it can impact in losing their job which will show the positive impact of the working process or the management of the organization and this will lead to the It will showcase the positive side of the working process of the organization. This show how there is a need to work positively and provide the employees with their needs and requirements which impacts the need and growth of the various industries.

Hariri, Fredericks & Bowers (2019) states that it is a method that maximizes job satisfaction if the problems or the obstacles that the employees or the post-Covid working condition are facing are taken properly and better care of impact in enhancing the workforce situation in a proper and better manner. It can be seen that the members feel they are worthy as their opinions are taken into consideration which helps in generating their workstyle and the way of the teaching process in a better and appropriate manner. It is the performance data analytics that is observed to be increasing their expectations as they will rely on the institute and work on their part to provide the learners with better guidance so that they will be able to excel in their part. It is the expectations that impact increasing the needs and want of the individual. If the problems are solved by the organization, then they want or expect something more which will help in understanding the matter in a proper and better manner.

In this case, the representation could be done in alternative ways that guide performance data analytics management in the right direction and gives a blueprint following which a transparent, accurate, and unbiased performance evaluation can be performed which will help to understand the situation of the e-commerce industry through the proper data analysis.

The visual representation could have been done with the help of the matplotlib which is a Python programming-aided visualization technique. This will aid in the categorization of the dataset in a more appropriate way. However it must be that the graphical representation have been done in an effective way by taking the data and this has been represented without any confusion . The data collection has been done by taking the primary data from the various working sectors of the industries including the e-commerce industry across the 8 countries.

PART B

According to my opinion, data analytics determines the significance of the performance of various industries by highlighting the drastic alterations that were implemented by the various industries in the post-Covid times. The results have helped me to comprehend the improvement of the e-commerce sector in all the 8 nations that were taken during the course of the study without any type of misleading representation.

The data analytics aids in understanding the improvement of the e-commerce section by the implementation of the appropriate statistical methods. The analysis of the actual scenario in the post-Covid times will aid in understanding whether there has been any shift in the employment in the post Covid times. The increase or decrease in the engagement of employees in the various sectors have also been illustrated in details. The results of the report suggest that the sectors which have seen boom in revenue generation would subsequently result in the augmented employment generation in those specific section like the healthcare sector.

The data analytics of this report helps in understanding the potential of the industries in the post-Covid times. The individuals develop positive working arena having observed the performance of other working staff in the various industries which enables them to self-realize to differentiate their ability from others in the organization. For instance, the entrepreneurs who are looking to improve their performance in the various sectors across the nations and measure the information gap regarding the data statistics of the sector. According to my perception the researchers have highlighted the post-Covid scenario with accurate statistical visualization. It might help entrepreneurs to develop a positive attitude to understand the serious needs of the particular scenario and give their best to solve the issues that are linked to the working arena after the times of the pandemic.

Conclusion

The performance data analytics of the post-Covid working condition can be determined by taking the data of the various countries across the nations which reflects the changes in the scenario as described earlier. This particular report addresses the working scenario across the 8 countries and will help to devise the strategies that would help to adapt to the situation after the pandemic. Henceforth the analysis of the statistical depiction helps to identify that the researchers have effectively handled the complex dataset which in turn has helped to furnish a comprehensive idea about the research topic.

References

Galetsi, P., Katsaliaki, K., & Kumar, S. (2020). Big data analytics in health sector: Theoretical framework, techniques and prospects. International Journal of Information Management, 50, 206-216.https://doi.org/10.1016/j.ijinfomgt.2019.05.003

Ghani, N. A., Hamid, S., Hashem, I. A. T., & Ahmed, E. (2019). Social media big data analytics: A survey. Computers in Human Behavior, 101, 417-428.https://doi.org/10.1016/j.chb.2018.08.039

Gupta, R., Tanwar, S., Tyagi, S., & Kumar, N. (2020). Machine learning models for secure data analytics: A taxonomy and threat model. Computer Communications, 153, 406-440.https://doi.org/10.1016/j.comcom.2020.02.008

Hariri, R. H., Fredericks, E. M., & Bowers, K. M. (2019). Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big Data, 6(1), 1-16.https://doi.org/10.1186/s40537-019-0206-3

Lund, S., Madgavkar, A., Manyika, J., Smit, S., Ellingrud, K., & Robinson, O. (2021, February 18). The future of work after COVID-19. McKinsey & Company. Retrieved April 26, 2023, from https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-after-covid-19#/

Sheng, J., Amankwah?Amoah, J., Khan, Z., & Wang, X. (2021). COVID?19 pandemic in the new era of big data analytics: Methodological innovations and future research directions. British Journal of Management, 32(4), 1164-1183.https://doi.org/10.1111/1467-8551.12441

ur Rehman, M. H., Yaqoob, I., Salah, K., Imran, M., Jayaraman, P. P., & Perera, C. (2019). The role of big data analytics in industrial Internet of Things. Future Generation Computer Systems, 99, 247-259.https://doi.org/10.1016/j.future.2019.04.020

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