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Strategies for Total Quality Management in Science Essay


The Article

Companies can use the strategies of Total Quality Management (TQM) to enhance their performance and raise the levels of customer satisfaction. It is an approach with long-term goals, which is focused on the process of operations. According to Kakuro (2004), TQM’s practices require teamwork to improve the performance of each department as a separate entity and as a part of the company. The author finds that one underperforming department can significantly affect the efficiency of the whole organization. Therefore, Kakuro (2004) proposes a way to improve collaboration by creating “strategic stratified task teams” (p. 3694). These groups of employees can have different skills and abilities to solve problems occurring in all departments of a company.

Their collaboration should also extend to other workers, groups, and parts of the supply chain. The researcher notes that Science TQM should become the central principle for companies to increase their productivity and level of satisfaction of all participants, including workers and clients. By using statistical quality control (SQC), firms can encourage collaboration and connect the organization on all its levels. The strategic team that deals with problems and tasks should be diverse in characteristics, including people with various beneficial qualities. The example of Toyota given in the study shows that task teams can successfully use this strategy to boost performance and detect mistakes in a short period.

The Future of ITM

The future of information technology management (ITM) depends on the development and successful implementation of innovative technology. The process of incorporating new software and systems can drastically change that way managers collect and interpret data. The analytic element of ITM depends on the ability of computers to gather information and predict future scenarios based on statistics. Here, the incorporation of big data and cloud computing can play a significant role in the business processes. As big data cannot be stored using traditional technologies and databases, access to it can be granted through cloud computing services (Hashem et al., 2015).

The use of large volumes of valuable information can bring the accuracy of calculations to a new level and help firms make successful predictions and set more realistic goals for the future. Furthermore, its value also should be noted, as large sets of data may reveal more hidden aspects and elements of certain processes that may not be accessible with smaller datasets.

Bid data cannot be accessed in full without cloud computing, a technology that allows companies to avoid paying for expensive local servers and provides them with a fast way to complete tasks fast. Moreover, cloud computing services can work with complex analyses without putting a strain on the business’ internal systems. Thus, this technology can save the company’s money and time. The incorporation of cloud computing into ITM brings many benefits to managers including increased storage capacity, access to data, and outsourcing of tasks. For the delegation of operations, ITM can also utilize artificial intelligence (AI) to perform the analysis of data amounts that are hard for the human mind to comprehend (Sharma & Srivastava, 2017). AI is an essential part of many industries as it solves many challenging problems that require advanced calculations and the analysis of massive datasets.

References

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.

Kakuro, A. (2004). Development of ‘science TQM’, a new principle of quality management: Effectiveness of strategic stratified task team at Toyota. International Journal of Production Research, 42(17), 3691-3706.

Sharma, L., & Srivastava, V. (2017). Performance enhancement of information retrieval via artificial intelligence. International Journal of Scientific Research in Science, Engineering and Technology, 3(1), 187-192.

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IvyPanda. (2020, October 23). Strategies for Total Quality Management in Science. Retrieved from https://ivypanda.com/essays/strategies-for-total-quality-management-in-science/

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1. IvyPanda. "Strategies for Total Quality Management in Science." October 23, 2020. https://ivypanda.com/essays/strategies-for-total-quality-management-in-science/.


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IvyPanda. "Strategies for Total Quality Management in Science." October 23, 2020. https://ivypanda.com/essays/strategies-for-total-quality-management-in-science/.

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IvyPanda. 2020. "Strategies for Total Quality Management in Science." October 23, 2020. https://ivypanda.com/essays/strategies-for-total-quality-management-in-science/.

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IvyPanda. (2020) 'Strategies for Total Quality Management in Science'. 23 October.

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