Over the decades, technological advancement intensified the quality of business competition and management strategies. In this case, a significant percentage of enterprises focus on the essence of incorporating strategies that elevate productivity and customer service experience. Another factor contributing to the prominent aspect of innovation enshrines the emergence of a well-informed consumer baseline. Therefore, Babatunde, Bolu, Oyawale, and Fayomi (2019) establish that artificial intelligence is the key solution to the contemporary challenges encountered during service delivery. According to the researchers, relevant stakeholders must 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.
The article offers a profound approach regarding the significance of exploiting technological resources to elevate the flow of operations. Babatunde et al. (2019) investigate the best discrete distribution technique with artificial intelligence to enhance the predictability of probable events. In a manufacturing outlet, the management encounters a tough situation based on the lack of sufficient employees during the changing peak hours within the organization. The customer behavior within the region is unpredictable due to the distinct work scheduling.
As a result, many 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. The Nigerian manufacturing plant aims at boosting the delivery system. However, the employees face the challenge of 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 the ability of 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 the calculation of 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 dynamic factors that contribute to the marketability of the services, such as public holidays and ceremonies. Primarily, the technological tool renders advanced expertise among the employees mainly involved in decision-making. The article provides an in-depth analysis of the different forecasting aspects about the frequency of occurrence of certain practices.
The use of discreet distribution statistics in business intelligence systems fosters the main essence of improving the decision-making within the management team. Babatunde et al. (2019) investigate the interdependent relationship between the distinct probable variables while ensuring effective informed supervisory tactics. In my opinion, there are dynamic filed of professionals whose proficiency relies on the contribution of the statistic analytical aspects. The intensification in the global enterprise world demands the incorporation of distinct strategies.
It is crucial to integrate ideologies that enhance the implementation of proactive measures elevating marketability. An excellent example of the utilization of Poisson engulfs its integration with weather forecasting technologies. Robotics play a vital role in the prediction of 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 artificial intelligence within the transportation industry renders proficient positive results. One of the challenges that the airport management team encounters involve the incorporation of practices that enhance the alleviation of plane crashes and accidents. In this case, it is vital to establish mechanisms that empower the workers with adequate information based on the emerging trends in the international market. Business competition is a profound element that negatively impacts an organization’s acquisition of market position. As a result, using the dynamics advances the implementation of proactive initiatives to elevate profitability margin.
Succinctly, 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 in the enterprise to boost productivity and the consumer service experience. The organization 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.
Reference
Babatunde, A., Bolu, C., Oyawale, F., & Fayomi, O. S. I. (2019). Application of business intelligence technique to manufacturing system with the stochastic process (a case study of “product-based” manufacturing company in Nigeria with a make-to-order strategy). Journal of Physics: Conference Series, 1378, 042104. Web.