Big data is continuously being generated from multiple sources and in diverse data formats that are either structured or unstructured. AT&T company is making every attempt to improve its responsiveness to its customer preferences and provision of seamless services. To achieve the mission, the organization applies advanced recommender algorithms to provide personalized TV content according to customer's specifications. Such personalized content is achieved by creating relevant adverts for consumers based on metadata related to their entertainment videos. AT & T has also developed a machine-learning algorithm that predicts when its consumers are experiencing service downtime. Through the algorithm, they can conduct a proactive investigation on issues and correct them before any complaints from the clients arise.
AT &T Strategy
Managing an effective big data analytics implementation requires strategy changes that understand the limitations of initiating such a new program. It is a matter that organization implementation teams will experience changes and transformation, yet it depends on how they are prepared to handle such limitations should they arise (Aneato, 2020). For instance, the teams should first establish a sense of urgency based on implementing the new ideas. The type of leaders leading the implementation is crucial for the significant change. As a matter of urgency, the organization should empower their leaders and give them the power to motivate other workers to produce the new work standards. On the same note, the organization should also ensure that its leaders remain progressive to inspire at different organization levels. The sense of urgency and necessity requires that the organization communicate the specific change to all employees in the organization to be aware of the direction the organization is moving. Prior and proper communication by the AT&T management would help diminish any resistance that may arise and would otherwise interfere with the implementation of the big data strategy implementation.
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Similarly, AT&T should change by building a powerful coalition. Implementing the idea requires a team dedicated solely to implementing big data analytic (Aneato, 2020). A change can begin with a few people dedicated to achieving the organization's goal, developing a powerful coalition that aims to achieve a transformational change. Having a great leadership team would be an effective organizational change at the company, and through the participation and contribution of the senior leaders, such a coalition will be empowered to lead the employees to the change process.
Finally, AT&T should institutionalize the latest approaches to be implemented as its corporate culture (Aneato, 2020). it should develop a conceptual model that describes the content of the ideas to be implemented so that the organization can control the implementation process. Once the idea is adopted to be part of the organization's vision as a corporate change process, employees will develop new behaviours that shall become the organization's new share values and culture.
The implication of using Big Data
Despite its massive achievements for the organization, big data analytics has challenges that may affect its implementation. For instance, there is no intelligence for the big data sources, a lack of scalable real-time analytics capabilities and the need to expand the peer to peer network. Further, there is always no cost-effective data storage subsystem (Darwish, 2018). Finally, the idea requires expensive software and computational infrastructure to support the data analysis during the implementation process.
Conclusion
In conclusion, using big data has led to remarkable growth at AT&T, and the organization still needs to adjust to its operations and make changes that can improve the implementation of ideas related to big data analytics. From the paper analysis, building a powerful coalition, institutionalizing the new approach and developing the urgency are some of the changes noted that the organization should realize the full benefits of big data analytics. However, the use of big data analytics remains an expensive and complex idea that requires skilled labour to enhance sufficient analysis.
References
Aneato, D. (2020). Strategies to Implement Big Data Analytics in Telecommunications Organizations.
Darwish, T. S., & Bakar, K. A. (2018). Fog based intelligent transportation big data analytics in the internet of vehicles environment: motivations, architecture, challenges, and critical issues. IEEE Access , 6 , 15679-15701.
