Communication and Decision-Making in the Manufacturing Industry

Paper Info
Page count 9
Word count 2495
Read time 10 min
Topic Business
Type Report
Language 🇺🇸 US

Background

Communication and decision-making play a proficient role in the management of the manufacturing industry. The sufficient flow of information enhances the optimal delivery of services and the production process. It is the responsibility of the managerial team to establish key approaches that enhance the significant sharing of details concerning particular practices. However, hindrance of the correspondence among workers and the executive team risks prominent challenge towards rendering highly competent customer satisfaction. Researchers establish that the production of inhalers is a mainframe that demands the optimal participation of dynamic stakeholders (Jeswani & Azapagic, 2019). Organizational culture is a composition of ultimate share of information and sustainable decision making by the administration for better productivity. The connectivity amid the counterparts in an organization reflects the effectiveness of apt supervisory and policymaking frameworks within the governance system.

Decision-Making among Employees and Management

In a company, different staff attains certain responsibilities such as the administration and the duty to ensure proficient operations monitoring. On the one hand, it is important for the governance system to showcase professionalism and consistency in delivering their services based on experience, acquired knowledge and skills. On the other hand, using a decision support system ensures an observation of the ethical code of practice while empowering the employees to improve their performance records. Therefore, using an organizational support system renders the statistical and inferential comparison of records based on periodical outlines (Lakshmanaprabu et al., 2019). As a result, the personnel address the emergent and crucial issues under the spectral view of the negative impact. The competitive advantage lies in fostering a high-quality service experience between the clients. Therefore, it is important that administration optimizes the integration of personal reflection and the contributory baseline from the analysis within the software.

The development of different support systems fosters dynamic impact within an organization, hence the diversification’s importance. An excellent example is the distinctive role of the CNDSS and ESS within a single enterprise. In this case, the personnel utilize the information derived for specific purposes across the hierarchical rankings of duties and responsibilities (Lakshmanaprabu et al., 2019). Therefore, technology resource renders a profound impact on the delivery of services based on the segmentation and coordination amid the employees. Poor interaction and analysis enhance the risk of misinterpretation, causing significant mishaps within the operational mainframe.

One of the major factors that affect business competence is the role of management in the decision-making process. On the one hand, it is the administration’s mandate to ensure that workers successfully attain the objectives while enhancing optimal satisfaction levels among the consumers. On the other hand, the executive contributes to the growth of an enterprise based on the necessity of interpreting the financial data gathered from the daily cash flow records. Researchers establish different tools that influence the interpretation and presentation of information pose dynamic attributes (Oboh & Ajibolade, 2017). The distinction in examining statistics is a phenomenon that profoundly empowers the leadership with strategic details for developing proficient approaches for the organization regionally and internationally.

Data extraction is a crucial element for management during decision-making to determine the essential factors affecting the performance and the key elements attributing to the competitive advantages. On the one hand, descriptive analysis deals with explaining the abstract details collected from a research exercise (D’Souza et al., 2017). Therefore, the approach seeks to derive information regarding the sampled population under assessment. On the other hand, inferential statistics concerns the establishment of critical insights regarding an entire population and its relation to a phenomenon being gauged. Primarily, the perspectives focus on the representative components to consider the interplay across dynamic values and interpretive framework for administrative duty in implementing organizational policies.

Both analytical approaches contribute to the information derived for different purposes based on the relevance and the necessity for specific points. However, it is important to note that there is a higher certainty with descriptive statistics, while inferential analysis poses a percentage of uncertainty due to the measure of relationship across a larger representation. In this case, the latte focuses on enlarging the sample size to the actual population to reduce the marginal difference and enhance the confidence level during the assessment (D’Souza et al., 2017). It is vital to measure the distinction between the two variables under the spectrum of the scope of segments. The primary duty of the management involves making critical decisions that affect the operations. Therefore, it is essential to integrate both perspectives in the derivation of details during research to determine the objective alignment of interactions.

General Electric Company

General Electric is an international company producing an array of machinery and provides various services. Excellent examples of the company’s products encompass industrial diamonds, jet engines, electrical equipment, and lighting goods. Besides, the firm offers different services such as installation, engineering, and repair of appliances. Despite the wide range of activities GE is engaged in, the corporation faces stiff competition, both inbound and outbound. The enterprise has affiliates in distinct fields, such as telecommunications and banking. Examples of these institutions include the NBC network and Capital Services. The company handles export and import within the United States and foreign countries (Wise, 2020). Consequently, General Electric has acquired a significant global market in the financial, manufacturing, broadcasting industries, and its competent affiliate companies continue contributing to its growth and market expansion.

The management decision approach is a phenomenon that significantly affected General Electric’s financial statements’ credibility by the Securities and Exchange Commission. Over the decades, the corporation optimized the administration’s decisions based on historical experiences. The elevated assumptions in determining profits and losses fostered the incurrence of unbalanced records. An excellent example entails General Electric’s insurance accounting policy of the premium returns. According to the institution’s monetary policy, the insurance premiums are reported as revenue already earned and rough estimates of the incurred expenses on a short-term basis. In this case, the company’s financial statements project the profitability based on the approximations of earnings from premiums. The program regarding the short-term insurance quality contradicts records of sales and purchases after the actual transactions. The policy’s contrast poses a significant challenge in the financial statements due to the accuracy in balancing the incurred profit and loss (Berthelot et al., 2019). Securities and Exchange Commission handles cases such as the lack of impartiality and precision by imposing fines and the condition of hiring external auditors.

General Electric faces the core challenge in managerial decision-making, hence incorporating both statistical perspectives in deriving details. On the one hand, the integral approach gears the provision of adequate information regarding productivity and operations in General Electric under the spectrum of descriptive analysis (D’Souza et al., 2017). On the other hand, the inferential aspect fosters assessing the relationship between products, assistance and customer’s service experience.

Primarily, inferential and descriptive statistics play a vital role in managerial decision-making due to the dynamic derivation of information from the data collected. On the one hand, different companies utilize distinct approaches to extract crucial details that translate to competitive advantage initiatives (D’Souza et al., 2017). On the other hand, poor implementation of perspectives risks the ineffective administration of a company to elevate its market acquisition techniques. It is important to empower the leadership with in-depth knowledge regarding an organization’s operations, such as General Electric, for efficient supervisory responsibilities for growth at regional and international levels.

Over the decades, technological advancement intensified the quality of business competition and management plans. In this case, a significant percentage of enterprises focus on the essence of incorporating strategies that elevate productivity and customer service experience. Another factor that attributes to the prominent aspect of innovation enshrines the emergence of a well-informed consumer baseline. Therefore, Babatunde et al. (2019) establish that artificial intelligence is the key solution to the contemporary challenges encountered during service delivery. According to the researchers, it is crucial for relevant stakeholders to incorporate approaches that integrate the computerized tool with discrete distribution statistical formulas to enhance the performance across the organization. There is a profound interdependent relationship between purchasing behavior and the cultural structure of a company.

It is crucial to integrate operations with technological resources for effective communication and decision-making outlier in the manufacturing industry. Babatunde et al. (2019) investigate the best discrete distribution technique with artificial intelligence to enhance the predictability of probable events. In a production outlet, the management encounters a tough situation based on the lack of sufficient staff during the changing peak hours within the organization. The customer behavior within the region is unpredictable. As a result, a significant percentage of the workers encounter the challenge of observing a standard service delivery system. The client’s encounter with the laborers in an institution highly influences the perception and the alignment of loyalties. Therefore, the determination of the functional structure through the computerized framework empowers the counterparts with the necessary knowledge and skills for the influx.

Management strategy is one of the significant components influencing competitive advantage development. An excellent example is a Nigerian manufacturing plant that aims at boosting the delivery system. However, the employees face the challenge in predicting the periods of customer influx hence the resolution to explore the diverse discreet distributional formulas. Babatunde et al. (2019) utilize the different types of probabilities: Poisson, Normal, Weibull, gamma, and log-normal. The researchers focused on the efficiency of a technique and its compatibility with the business artificial intelligence system. In this case, the component that emerged the best and highly congruent encompassed the Normal approach in the probability test. The framework empowered the executive team with effective decision-making due to the consistent provision of details regarding forecasting customers’ overflow.

The normal distribution involves the symmetrical prediction of an occurrence against the mean. According to Babatunde et al. (2019), the statistical analysis fosters the comprehension of a prediction based on its nearness to the mean than the figure further from the element. An excellent example is calculating the mean peak hours ranging between five o’clock in the evening and six o’clock after sunset. In this case, the approach establishes that the likelihood of the influx of customers is within one hour before and after the time scheduled. However, the business intelligence system fosters the significant assessment of the dynamic factors that contribute to the marketability of services, such as public holidays and ceremonies. Primarily, the technological tool renders advanced expertise among employees mainly involved in the decision-making process. The article provides an in-depth analysis of the different aspects of mathematically forecasting the frequency of occurrence of certain practices.

The use of discreet distribution statistics in business intelligence systems nurtures the main essence of improving the decision-making within the management team. Babatunde et al. (2019) investigates the interdependent relationship between the distinct probable variables while ensuring effective informed supervisory tactics. There is a dynamic field of professionals whose proficiency relies on the contribution of the statistic analytical aspects. The intensification in the global enterprise demands the incorporation of distinct strategies. It is crucial to integrate ideologies that improve proactive measures that elevate marketability. An excellent example of the utilization of Poisson engulfs its integration with weather forecasting technologies. Robotics play a vital role in predicting climatic conditions based on the established pattern. However, the exploitation of the distribution concept enhances the effectiveness and objective overview of the insights.

In a different spectrum, integrating the dynamic discreet distribution approaches with the artificial intelligence within the transportation industry renders proficient positive results. One of the challenges that the airport management team encounters involve incorporating practices that enhance the alleviation of plane crashes and accidents (Babatunde et al., 2019). In this case, it is vital to establish mechanisms that empower the workers with adequate information based on the emerging trends in the global market. Business competition is a profound element that negatively impacts an organization’s acquisition of market position. As a result, using the dynamics advances proactive initiatives to elevate profitability margin.

Ideally, competition in the global business market fosters the implementation of approaches that empower administration with adequate information for decision-making. The Nigerian manufacturing company integrates the normal distribution technique with artificial intelligence to boost productivity and the consumer service experience (Babatunde et al., 2019). The company attains a competitive advantage through the operation organization based on the proactive ideologies provided by the system. Discreet statistics feature as the emblem in the economics department due to the determination and measure of probability frequency.

Solving Communication and Decision-Making Problems Dynamically

Different manufacturing industries encounter distinct challenges within the scope of communication and decision-making. An excellent example is the production of inhalers for patients. It is important to share information among employees, management, and clients concerning the core issues associated with using the gadget. One of the main setbacks is the lack of attaching an inhaler to a spacer, rendering difficulty during the utilization. Sick people suffering from insufficient oxygen face a key health threat during poor exploitation of the component to attain oxygen. Therefore, researchers agree that key stakeholders’ responsibility is to ensure optimal dispensation of insights concerning the perils of poor teamwork coordination and policymaking procedures (Jeswani & Azapagic, 2019). One of the solutions in the sector is the integration of technological resources with operational activities. Automating the processes enhances alleviation and minimizes marginal error during the fabrication of inhalers.

In a different spectrum, another solution is the implementation of effective policies that enhance coherence towards coordination amid employees. The production of inhalers demands significant attention and professionalism from different parties. In this case, it is crucial to restructure the organizational culture to promote an efficient service delivery system. With the paradigm shift in the market determinants with customers as kings and queens, it is vital to indicate the core mainframe of exchanging information between workers to assert quality during the production process (Jeswani & Azapagic, 2019). Sufficient communication ensures a profound trickle-down effect in fostering positive outcomes for consumers and the company due to adherence to production standards.

In conclusion, communication and decision-making profoundly impact competence among manufacturing companies. The production of inhalers demands the optimal acquisition of insights that enhance profitability to the firms and client satisfaction. As a result, it is important to establish measures that contribute to an effective production process. General Electric is one of the organizations that incurred significant losses due to insufficient sharing of details during the operational guideline. Therefore, it is the responsibility of all stakeholders to adhere to policies rendering attainment of insights improving the development of competitive advantages. The key solutions to the challenges encompass teamwork and the integration of technological resources advancing the automation process of the endeavours. The incorporation of distinct perspectives advance quality quotient in rendering services and products among clients. Computerization in the sector is a vital boost since it assists monitoring and execution of highly-graded components for consumption among the consumers. Policymaking is a crucial factor in the management of resources within an organization. As a result, it is the responsibility of workers and administration to focus on optimizing profitability and customer service satisfaction while observing standard manufacturing practices

References

Babatunde, A., Bolu, C., Oyawale, F., & Fayomi, O. (2019). Application of business intelligence technique to manufacturing system with stochastic process (A case study of “product-based” manufacturing company in Nigeria with make-to-order strategy). Journal of Physics: Conference Series, 1378, 042104. Web.

Berthelot, M. J., Lasensky, N., & Somers, P. (2019). The board’s role in monitoring strategy: Lessons learned from General Electric. Web.

D’Souza, M. J., Brandenburg, E. A., Wentzien, D. E., Bautista, R. C., Nwogbaga, A. P., Miller, R. G., & Olsen, P. E. (2017). Descriptive and inferential statistics in undergraduate data science research projects. Advances in statistical methodologies and their application to real problems, 10, 65721.

Jeswani, H. K., & Azapagic, A. (2019). Life cycle environmental impacts of inhalers. Journal of Cleaner Production, 237, 117733. Web.

Lakshmanaprabu, S. K., Mohanty, S. N., Krishnamoorthy, S., Uthayakumar, J., & Shankar, K. (2019). Online clinical decision support system using optimal deep neural networks. Applied Soft Computing, 81, 105487. Web.

Oboh, C. S., & Ajibolade, S. O. (2017). Strategic management accounting and decision making: A survey of the Nigerian Banks. Future Business Journal, 3(2), 119-137. Web.

Wise, G. (2020). Willis R. Whitney, General Electric and the Origins of US Industrial Research. Plunkett Lake Press.

Cite this paper

Reference

NerdyBro. (2023, February 20). Communication and Decision-Making in the Manufacturing Industry. Retrieved from https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/

Reference

NerdyBro. (2023, February 20). Communication and Decision-Making in the Manufacturing Industry. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/

Work Cited

"Communication and Decision-Making in the Manufacturing Industry." NerdyBro, 20 Feb. 2023, nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.

References

NerdyBro. (2023) 'Communication and Decision-Making in the Manufacturing Industry'. 20 February.

References

NerdyBro. 2023. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.

1. NerdyBro. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.


Bibliography


NerdyBro. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.

References

NerdyBro. 2023. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.

1. NerdyBro. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.


Bibliography


NerdyBro. "Communication and Decision-Making in the Manufacturing Industry." February 20, 2023. https://nerdybro.com/communication-and-decision-making-in-the-manufacturing-industry/.