The transformation of the management information system: A case review of the supply chain management system at Amazon

Student’s Name

Course Code and Number

Instructor’s Name

Date of Submission

Introduction

Companies in the electronic commerce business strive to achieve strategic capabilities by developing and maintaining a specialized procedure for collecting personal information concerning clients and their buying behavior and patterns (Abdullah, 2021). A firm’s management information system helps the business and its systems to incorporate more effectively and efficiently in order to bring forth the interplay between individuals and information systems. Management information systems (MIS) assists in the process of decision-making at the strategic and operational levels of a business. It is clear from the case of Amazon that information systems were successfully aligned with the company’s long-term business and strategic objectives. In order to refine its E strategy, Amazon has separated its website systems from those of its order systems, resulting in a uniquely different set of systems. The management information system (MIS) has served a critical role in the development of the organization in a worldwide setting. The organization has employed its management information system (MIS) as a dynamic instrument in the simplification of its management tasks, while also making sure that its consumers are provided a diverse range of services through the system in distribution within the supply chain management. The purpose of this paper is investigating the effects of the emerging technologies on the information systems function in Amazon, seek recommendations that may lead Amazon to align the need of emerging technologies for managing information systems in today’s world.

Roles of past Information Systems in Distribution within Supply Chain Management

The organization employed interactive searching option for its consumers in the distribution function within the supply chain management. Clients were able to choose their desired commodities catalogues to get the product. Multitude of products could be found just by using the searching tools (Ayse, 2021). Oracle was the enterprise resource planning system used by Amazon. It has a large database that contains information about its customers’ purchases. The ordering procedure for the client is automated as soon as the order is placed since it will automatically locate the closest distribution centre for the shipment. Using the order tracking feature, this system expedites the order fulfillment procedure and decreases the likelihood of distribution errors. Since 1999, the firm has cut down the amount of customer support contacts by half, owing to fewer errors as a result of this method.

Past Procedures for Managing Information Systems at Amazon

In 1995, the e-commerce giant was using a distinct website system and order fulfillment system to boost security, according to the company. As early as 1995, Amazon had a massive database that was hosted on Digital Alpha Servers. Amazon completely redesigned its overall system in the year 2000. The proposed program cost the organization $200 million to develop. The systems were inclusive of “Epiphany” analysis software, “Manugistics” logistics software, and a new Oracle database management system. Amazon signed a contract with Excelon to provide a business-to-business integration solution to facilitate communication with suppliers. One of the most important systems built by Amazon is the Amazon Web Service (AWS), which is also known as Simple Storage Service (SS). The organization has been able to sustain its large quantity of commodities and millions of clients as a result of this approach. Amazon’s web service has expanded to become an international marketplace for people as well as businesses to sell their items.

Amazon attains an international dominance via the provision of dependable, scalable, and robust web services. The challenges linked with Amazon.com’s web services are quite known. Millions of consumers seek to purchase goods and services at any given moment in time. The methods used to deliver items and place orders must be swift, reliable and safe, in all aspects. At any given time, a CRM (Customer Relationship Management) system collects data and information on a consumer through different ways like searching, wish lists, data mining, and so forth. Whether a consumer buys something or not, they tend to reveal information regarding themselves. The systems were intelligent enough to analyze the information and deliver service on the basis of the findings. Amazon.com developed a technique known as SAS to hunt down and identify fraudsters (Smart Analysis Search). Through the study user behavior patterns, this technology can help to reduce and detect fraud on the organization’s website. Smart Analysis Search enables Amazon.com to better comprehend and cater to its customers by measuring and personalizing their experiences. Using Service Oriented Architecture (SOA), the firm has built an information system (SOA). Amazon’s information system is more comprehensive and scalable because of SOA, which is a completely decentralized and distributed services platform that allows for easy scaling. SOA focuses on a small number of applications instead of a large number of processes.

Present Policies for Managing Information Systems in Distribution within Supply Chain Management

To offer a personalized experience, Amazon follows a number of policies in ensuring that the personal information collected from consumers is safe for purposes of distribution. Among the policies that the organisation uses in ensuring security of information is the use of encryption software and protocols during the transmission of personal information. The organisation also follows the payment card industry data security standard when it comes to handling of credit card information. Amazon also maintains procedural, physical and electronic safeguards in association with the collection, storage and disclosure of its consumers personal information. The security procedures followed by Amazon implies that the organisation may ask the consumers to verify their identity before disclosing any personal information to them. The devices used by the company offer security characteristics that are meant to protect consumers against unauthorised access as well as loss of information.

Present Management of Information Systems at Amazon

The supply chain management system (SCM) is a critical component of Amazon’s value chain in the area of primary operations, especially the distribution function. The system’s main features are that it is automatic, effective, functional, and precise when it comes to controlling the supply chain flow. The system’s primary function is to automate the control of inbound logistics, activities, and outgoing logistics, hence increasing the efficacy and efficiency of selling commodities. Another function of the system is to enable consumers to place correct orders for commodities and receive them on time. Furthermore, Amazon makes use of the algorithms to effectively make purchases with suppliers, thereby refilling stock levels in response to consumer orders placed on the website. SCM, in its most basic form, allows Amazon to connect suppliers and buyers. In accordance with Amazon’s e-business strategy of reaching multitude of its consumers and providing them with a variety of goods. According to this viewpoint, supply chain management (SCM) contributes to Amazon’s e-business tactic by assisting the company to offer high-quality services and timely product deliveries in response to the demands of consumers who are located all over the world, thereby increasing its ability to compete in the e-commerce space.

Support operations are carried out through the Simple Storage Service (S3), which is an information system that the firm has incorporated into its architecture. The system’s primary traits are that it is secure, long-lasting, memory-scalable, user-friendly, as well as compatible with other web-based programs, among other things. S3 is safe since it offers permission restrictions and encrypts information during the transport of data between servers. Data saved in S3 is extremely durable since it is distributed over multiple devices and centres in a redundant way, reducing the likelihood of data loss or corruption. Amazon’s S3 service has an infinitely expandable memory, that enables it to store an unlimited quantity of data without incurring any further costs. In terms of its user-friendliness, S3 is straightforward and simple when using, thanks to the fact that it functions on both smartphones and computers. Its connectivity with web-based technologies such as Amazon Web Services (AWS) improves the functioning of the internet retail store. The key functions of S3 are data storage, data distribution, recovery of data, and cloud computing, among other things. Because of these positions, S3 is better positioned to support the e-commerce strategy of offering different products to millions of clients throughout the globe through online storefronts. To be more precise, S3 stores, transfers, and recovers information about consumers, suppliers, and products in a precise, efficient, and effective manner, hence advancing Amazon’s e-business strategy.

Trends In Computer Hardware and Software in Distribution

Over the recent past, there has been a significant breakthrough in computer hardware and software. An increasing set of new architecture, hardware and characteristics are increasingly becoming the basis of computing systems (Pan et al., 2018). These trends imply that the techniques are considerably transforming the contemporary traditional data management environment as well as analysis systems inclusive of hardware accelerators and high-performing processors, and remote direct memory access capable networks. Considerably, the current environment which is marked with hybrid storage hierarchy and heterogeneous multi core architecture, makes the already sophisticated software design space to be even more complex (Swanson, 2020). The emergence of high-performance processors along with new accelerators has resulted in a change from single CPU architecture to heterogeneous hybrid processing architectures. On the other hand, strategies of data processing as well as optimisation strategies have transformed from standardization to customisation. In terms of software, several trends have also been witnessed in information technology.

Among the most popular trend in information technology is cloud computing. This is a model in which organisations as well as individuals obtain software applications and computing power over a network, essentially the internet instead of buying their own software and hardware. Amazon has already implemented the Amazon web services which is a comprehensive cloud computing platform that entails the amalgamation of packaged software as a service, infrastructure-as-a-service, and platform-as-a-service offerings (Nirun & Nivea, 2012). Another software trend in Information Management System is mobile application. Mobile applications, usually referred to as mobile apps, has attained significant amount of success since its inception. These applications are designed to run on handheld devices such as tablets and smartphones.

Analytics is another trend witnessed in the software arena and it has grown in several folds over the recent past. Analytics helps organizations in discovering the patterns of information with data. The analytics arena is a mixture of operations research, statistics, and computer programming. Analytics have shown growth in social analytics, data analytics, and predictive analytics. Dota analytics is employed in decision making processes since its converts raw data into information that can be meaningful for the organization. Predictive analytics is employed in predicting future events with regards to the historical and current information. Lastly, social analytics is employed by organizations in understanding and accommodate consumer requirements.

Future Policies for Managing Information Systems

In spite of the fact that corporate regulations have been established and training has been provided, employees continue to play a substantial role in generating data leakage or privacy breaches. Besides policy setting, organizations must engage with staff members regularly, undertake archiving/disposal exercises with workers, and incentivise behaviors that support information security.

Future Roles of Information Systems

With the constant development of technology and information systems, information systems will have new and increased roles in the running of organizations such as Amazon which heavily relies on information for strategic decisions.

Autonomous technologies like robots, autonomous vehicles and robots, utilize artificial intelligence to carry out jobs that were previously handled by people. The automation of these devices and machines goes beyond the automation provided by inflexible programming models and they leverage machine learning and artificial intelligence to deliver advanced actions that engage more organically with their environment and with humans (Romero & Vernadat, 2016). As autonomous devices and machines continue to evolve, there will be expectations in a shift from stand-alone smart devices to a cluster of cooperative intelligent machines and devices, where several devices will function collaboratively, either autonomously or with human input. For instance, if a drone investigated a big field and decided that it was ripe for harvest, it may deploy an unmanned harvester. Or in the distribution market which is the sector where Amazon belongs, the most effective option may be to deploy an autonomous car to transfer products to the target region. Robots and unmanned aerial vehicles UAVs on board the autonomous vehicle might then guarantee ultimate arrival of the goods.

Augmented analytics concentrates on a particular of augmented intelligence, employing machine learning (ML) to revolutionize the way analytics content is created, used, and disseminated. As a crucial element of data preparation, will enhance the management of data, contemporary analytics, the management of business process, process mining, and data science platforms (Merali, Papadopoulos, & Nadkarni, 2012). As such, augmented analytics capabilities will quickly gain traction and become widely adopted. An automation of insights from augmented analytics will be integrated into business applications such as those used by the human resources, marketing and finance departments as well as those used by the customer support, purchasing and supplies, and asset management departments to maximize the actions and decisions of all staff members in their respective contexts, rather than just those of analysts and data scientists. Several tasks associated with data preparation, insight creation, and insight depiction can be automated, reducing the requirement for skilled data scientists in a variety of scenarios. In turn, citizen data science, an evolving collection of competencies and techniques that empower users whose primary work is beyond the statistics and analytics field to derive predictive and prescriptive information from data, will be able to flourish in the next years. 

The term “edge” pertains to endpoint devices that are either utilized by people or are entrenched in the environment in which humans live. Edge computing is a computing architecture whereby information processing, as well as content collection as well as delivery, are located closer to the endpoints being served (Almazán, Tovar, & Quintero, 2017). It makes an attempt to maintain traffic and processing local, with the purpose of reducing traffic and latency as much as possible. In the short term, edge computing is being propelled by the Internet of Things and the desire to retain computing close to the point of use instead of on a centralized cloud server. In contrast to this, cloud computing and edge computing will develop as supplementary concepts, with cloud services being handled as a centralized service that executes not just on centralized servers, but also on distributed servers on-premises and in the edge devices themselves, instead of as a replacement for existing infrastructure (Ågerfalk, Conboy, & Myers, 2020). In the next few years, a broader range of edge devices will be equipped with specialist artificial intelligence chips, as well as increased processor speed and power, storage, and other advanced features. This connected IoT environment is extremely heterogeneous, and long asset life cycles, like those of industrial facilities, will present considerable management issues. The longer-term goal is for 5G to become more established, so that the growing edge computing environment can communicate more reliably back to centralized services. In comparison to 4G, 5G offers lower latency, higher bandwidth, and (most crucially for edge applications) a surge in the number of nodes per square kilometre of land area.

Recommendations of future Information Systems of Amazon

Amazon needs to integrate its website operations with social media. Amazon must improve the synergies that arises as a result of merging information originating from marketing, sales, and after-sales services into one system. The firm’s management information system (MIS) must assist in providing contact points to clients at all times (Pastor, 2020). Amazon should link its whole system with social media sites while simultaneously promoting and attracting new consumers through the use of its customer relationship management platform. It is clear from the management information systems (MIS) of eBay and other future e-commerce firms that the vast majority of clients may be found through social media. The integration of a user’s buying experience with their social media profile will culminate in the promotion of the goods and the services given by the company to the end user’s close social networks. The usage of enterprise resource planning techniques in social networking could assist Amazon in sharing consumer feedback and comments, which would increase customer confidence as well as trust in the company.

The firm also needs to implement artificial intelligence and intelligent virtual agents. A further proposal that would be beneficial to Amazon in the long-term is the utilization of artificial intelligence systems as a method for enhancing the connection with consumers. Amazon and its data management would be set for the future if they made use of intelligent virtual agents. Additional modifications are necessary in the manner in which information systems engage with customers, as well as in the way they are designed. Amazon must make change management a standard practice because the E strategy of the company must be adaptable sufficiently to satisfy the evolving needs and wants of consumers. The synchronization of intelligent virtual agents with the overall management information system (MIS) must be conveyed to all parties involved. Amazon should strive to ensure that the tech and infrastructure it employs outperforms the current information systems of its competitors in terms of performance. The employment of avatars and the branding of that avatar solely as an Amazon business representative could usher in a new era in the utilization of information systems. These virtual assistants, who might collect and assess information for the marketing and logistics teams, will contribute in the improvement of the activities of their various department. Amazon’s intelligent virtual agents may clear the path for the company to provide consumers with individualized interactions that are similar to those experienced by humans. Inevitably, intelligent virtual assistants will achieve widespread popularity thanks to their current client base and sales channels in a relatively short period of time. Amazon can utilize intelligent virtual agents as a means of communicating with customers in order to truly comprehend the challenges related with logistics and operations. One could start a round-the-clock chat service, and the responses and interactions received may be archived as data for future reference. Amazon’s operations management, supply chain management, customer relationship management, including human resource management all rely on the employment of AI-powered virtual assistants to be successful. In light of the reduced efficiency with which MIS responds to consumer inquiries, clients have consistently submitted a slew of grievances about the perceived delay in receiving answers. The use of AI-powered virtual assistants might allow the company to depend a little less on customer service centre and might reduce the high amount of expenses associated with human resource.

Conclusion

Aims of this article are to discuss the development of corporate management information systems, and to make recommendations based on a comparison of the roles played by management information systems in the past, present, and future in order to provide recommendations. Because of this, this article uses the management information system as the organizing framework for discussion, and it delves into the transformation history of management information systems from their inception to the present, as well as making recommendations for their further development in the near future. At the moment, the introduction of artificial intelligence, machine learning, and data analytics will necessitate Amazon’s continual improvement and innovation of its information management system in order to fulfill the demands of the new era. Amazon should prioritize the creation and investment in AI-powered information systems going forward, as well as the rigorous study and practical use of innovative technologies, as a result of this recommendation.

References

Abdullah, I. (2021). A Study on Amazon: Information Systems, Business Strategies

and eCRM. Researchgate. Retrieved 22 November 2021, from http://dx.doi.org/10.13140/RG.2.1.1366.8247.

Abrego Almazán, D., Sánchez Tovar, Y., & Medina Quintero, J. M. (2017). Influence

of information systems in organizational performance. Contaduría y administración, 62(2), 303-320. https://doi.org/10.1016/j.cya.2016.07.005Ågerfalk, P. J., Conboy, K., & Myers, M. D. (2020). Information systems in the age of

pandemics: COVID-19 and beyond. https://doi.org/10.1080/0960085X.2020.1771968Ayse, D. (2021). Management Information System: Case Study of Amazon.Com.

Questjournals.org. Retrieved 22 November 2021, from http://www.questjournals.org/jrbm/papers/vol4-issue11/B4111117.pdf.

Merali, Y., Papadopoulos, T., & Nadkarni, T. (2012). Information systems strategy:

Past, present, future? The Journal of Strategic Information Systems, 21(2), 125-153. https://doi.org/10.1016/j.jsis.2012.04.002Nirun, B., & Nivea, B. (2012). Emerging Trends in information

Technology. International Journal of Emerging Technology and Advanced Engineering, 2(12), 101-106. https://doi.org/10.12816/0025771Pan, W., Li, Z., Zhang, Y., & Weng, C. (2018). The new hardware development trend

and the challenges in data management and analysis. Data Science and Engineering, 3(3), 263-276. https://doi.org/10.1007/s41019-018-0072-6Pastor, C. K. (2020). The Role of Management Information System: Review on the

Importance of Data and Implementation in Organizational Process. Available at SSRN 3558441. https://dx.doi.org/10.2139/ssrn.3558441Romero, D., & Vernadat, F. (2016). Enterprise information systems state of the art:

Past, present and future trends. Computers in Industry, 79, 3-13. https://doi.org/10.1016/j.compind.2016.03.001Swanson, E. B. (2020). How information systems came to rule the world: Reflections

on the information systems field. The Information Society, 36(2), 109-123. https://doi.org/10.1080/01972243.2019.1709931