Productivity and Cost Competitiveness †Free Samples to Students

Question: Discuss about the Productivity and Cost Competitiveness. Answer: Introduction Delta is a renowned American airlines company which is headquartered at Atlanta Georgia. The organization operates almost over 5400 flights in a daily basis and they serve a domestic as well as international network that involves over 310 destinations across 54 nations (David Mc, 2013). The main purpose of this report is to highlight that the organization is using real time data generated in the aircraft for the benefits of the customers and to satisfy them to the fullest, aiming monopolizing the business. It is a matter of fact that, United States airline company Delta tries to squeeze out the most benefits from the real-time data gathered by the aircraft for the betterment of customer safety and satisfaction (Oum Yu, 2012). Thus, the organization is using a tool to provide the pilots with necessary information and the level of their flying and landing skills. The organization intends to give the customers more satisfaction and more security for their betterment and the general betterment of the organization (Moreno-Hines Kirkman, 2013). The organization is also taking up some alternate programs using the real time data for the benefits of the customers. Delta airlines are targeting to achieve the most customer satisfaction level than any other airlines company, as they want to monopolize the market. The organization is currently trying to use the real time data to satisfy their customers to the next level (Oum Yu, 2012). The organization can use these data for collect and analyze approach, so that they can analyze more than 150 variables in the customer profile and they can provide highly personalized offers. A regular 6 hours flight produces data of above 240 terabytes sensor data and Delta having more than enough aircrafts they get a lot of data, which can be used for betterment of the customers (Steven, Dong Dresner, 2012). The information from the data allows the organization to detect the issues that can arise in future and the organization would benefit from that for providing a smooth flight to all of its c ustomers. The organization sometimes uses data to analyze the customers purchase activity and thus they can offer them tailor made offers (Moreno-Hines Kirkman, 2013). The big data also allows the organization to detect some specific customer behaviors and they can determine the preferences of those customers so that they can provide the best service they can expect (Yee Liau Pei Tan, 2014). The big data also allows the organization to make strategic decisions to gasp the market by successfully attracting the customers for choosing their organization for travelling (Lee Worthington, 2014). Conclusion Thus to conclude, it can be said that, the organization Delta Airlines of United States of America is trying to reduce the harmful factors and enhancing the satisfaction level of the customers to become the most successful airlines company in America. They are also eying to set a milestone for the other airlines organizations to follow. It can also be said that, Delta is trying too hard for technological advancement to provide the customers with the comfort level that is beyond their expectation along with for the betterment of the safety issues. References Moreno-Hines, F., Kirkman, D. (2013, June). Assessing the NextGen Avionics Business Case from the Airline Perspective. InTenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013). Oum, T. H., Yu, C. (2012).Winning airlines: Productivity and cost competitiveness of the worlds major airlines. Springer Science Business Media. Steven, A. B., Dong, Y., Dresner, M. (2012). Linkages between customer service, customer satisfaction and performance in the airline industry: Investigation of non-linearities and moderating effects.Transportation Research Part E: Logistics and Transportation Review,48(4), 743-754. Yee Liau, B., Pei Tan, P. (2014). Gaining customer knowledge in low cost airlines through text mining.Industrial Management Data Systems,114(9), 1344-1359.