Organization (AT&T) could use descriptive analytics to improve their business performance through the provision of the matrices of the analyzed data. Since there is vast data available in the field, the organization cannot depend on this massive data to make business decisions. Therefore, the organizations use the matrices in setting business goals and future models for better performance. Descriptive analytics helps in decision-making processes by connecting the data with the matrices. The analyzed data shows the business trends over time, and as a result, the business managers can identify the next step the business will take. The information obtained from descriptive analytics helps most organizations better understand customer’s behaviors ( Chams & García-Blandón, 2019). And by knowing their customers, they can plan strategies more precisely. For example, banks can use descriptive analytics to understand what happens when loan interests are raised; the customer tends to struggle to repay the loan and the risk associated with failure to repay the loans over time. Thus banks rely on descriptive analytics to understand their exposure to business risks. Therefore, such organizations like banks can develop the best strategy for recovering the loans in the future.
Organization (AT&T) use descriptive analytics to efficiently assess how various processes are working to the full realization of the business goals. These are made possible by providing historical context reflecting on the past to understand the relationship between goods and consumers and assessing business goals ( Appelbaum et al., 2017). Information gathered can provide present models adopted to achieve the business goals by checking business revenue growths and general operations. Lastly, descriptive analytics provide a holistic approach to businesses that checks on the business’s dynamic nature and identifies readjustments to the current trends in the market, which shall help identify the business’s strengths and weaknesses and subject to future modifications for optimal operations.
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Organization (AT&T) could as well depend on descriptive analytics to develop metrics and key performance indicators (KIPs) in data collection and aggregation, data extraction, data analysis, and data presentations (Raffoni et al.,2018). This process involves setting business goals, obtaining relevant data from various sources, and transforming the data and cleaning processes. The information is then displayed to stakeholders as either visual, charts, or graphs to summarize the business’s findings like changes in costs, interest rate, and revenue trends over time.
Organization (AT&T) performances are assessed through descriptive analytics, which provides information about the organization. The performances are based on business trends over time, developed model evaluation, and future benefits. In analytic descriptive business intelligence are used in answering the fundamental questions of when, where, what, and how the data is used (Alam,2017). The analytic process may present in other forms like diagnostics analytics that determine why somethings occur in the organization by relating the cases. Predictive analytics brings the full meaning of correlations, trends, and causations by telling what will happen in the future, and lastly, prescriptive analytics tells the business the recommended actions to be taken by providing the best action to take before making final decisions. To realize the business goals and trends in the environment.
References
Alam, S. (2017). Financial Analysis of Retail Business Organization: A Case of Wal-Mart Stores, Inc. Inc.(April 4, 2017) .
Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems , 25 , 29-44.
Chams, N., & García-Blandón, J. (2019). On the importance of sustainable human resource management for adopting sustainable development goals. Resources, Conservation and Recycling , 141 , 109-122.
Raffoni, A., Visani, F., Bartolini, M., & Silvi, R. (2018). Business performance analytics: exploring the potential for performance management systems. Production Planning & Control , 29 (1), 51-67.
