Business Intelligence and Decision Making PDF

   

Added on  2021-06-17

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BUSINESS INTELLIGENCE AND DECISION MAKING: POSTAL CLERKSTHE FUTURENameDate
Business Intelligence and Decision Making PDF_1
IntroductionAs technology continues to advance at a breathtaking pace, some tasks and jobs hitherto done by human beings are being taken over by machines and computers; an example is in manufacturing where welding and assembly jobs previously done by people have been taken over by robots. Robots and machines can work in harsh conditions and continuously, without the limitations associated with human beings such as getting tired, injured, sick, or the need to take leave (Rendall, 2016). In this context, this paper discusses a job category involved in supply chain management; with a focus on Australia Post, a logistics company. The specific job category to be discussed is thatof a Postal Service ClerkDiscussionIn the modern computing world characterized by computer systems, robots, and artificial intelligence (AI) systems that have human-like intelligence and reasoning, certain jobs that require the use of data and other information sources to shape reasoning and make decisions are in danger of becoming extinct in the near future. The job of a postal service clerk, specifically relating to mail includes sorting and preparing mails for delivery and work mostly in the mail room: they also checkis mails are properly addressed and offer customer services, such as when clients call to track their mail and deliveries. In the past decade, the concept of AI (artificial intelligence) has grown in leaps and bounds, to the level where AI is used to autonomously drive cars, and can take off and land aircraft. AT present, AI based systems like IBM Watson and Google’s Alpha Go have demonstrated that they can beat the best human beings in their fields in tasks that involve critical thinking such as playing chess (Looft, 2018). The reality is that the future looks scary for certain professions such as postal clerks and mail room workers, something unfathomable just a few years back. Already, majorpostal services providers such as the US Postal Service (USPS) are already using AI in the form of chatbots to simulate questions and filed questions from customers (USPS Inspector General, 2018). And because AI is now interfaced with the concept of machine learning (ML) in which computer systems eventually learn certain concepts using algorithms, it is probable certain jobs, including those of postal service clerks will become extinct. Already, robots such as Baxter (Guizzo and Ackerman, 2012) are already in existence and can be customized and ‘taught’ to be more efficient and tireless mail sorting clerks at Postal Service firms. These robots do not require skilled technicians to program them; instead, they use algorithms and some basic inputs to learn their trade,fast ML technology and AI can address more and more complex problems more accurately, with less effort, and in a significantly shorter time. Because AI systems using ML algorithms have an almost unlimited scope to learn, have low overhead costs, and can work for longer, they will become more attractive to logistics companies, such as Postal Services that are increasingly required to fund themselves (Frey and Osborne, 2013, pp. 3-4). Computer controlled by robots, that
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