Optimization

1. What are analytics? What are the advantages of using analytics for corporate decision making? Use arguments and examples provided in article # 1 to support your answer. (3 points)

Analytics is a method of organized analysis of data with the help of statistical tools. Analytics helps companies to support their distinctive capabilities and improve their business planning. For example, Harrah’s distinctive capabilities of customer loyalty and service was enhanced with analytics-driven strategy. The smart use of business intelligence tools and predictive analytics have helped many businesses to outperform their competitors. For example, Netflix has profited hugely by using analytics. Its algorithm-driven movie recommendation is a huge success.

The advantage of analytics is that it makes better and faster corporate decisions based on data-analysis. A business can profit from becoming more analytical. Analytics can help a business in understanding its customers better, performing its operations optimally, and thus making better corporate decisions. Organizations take several approach to gain a competitive advantage with data. Some organizations gather valuable data about their customers and prospects that competitors can’t match. Capital One is an example of such an organization. Capital One used its analytical skills to beat the market as it gathered and analyzed its data about its customers in a unique fashion. Capital One made smarter decisions by analyzing the consumer credit information and thus made better decisions about potentially risky credit customers.

 Accurate information is essential for analytical competition and managers can take proper action based on the relevant data.  With the help of business intelligence (BI) tools organizations can become analytical powerhouses. With the help of BI, Analyst have direct access to accurate data.  As there is easy access to proper data and reports, managers can focus on improving business processes and making important decisions rather than worrying about compiling data. Moreover with BI and analytics, high-volume, mission-critical decision-making processes are highly automated and integrated. Amazon, Capital One, Netflix and many other organizations have automated decisions like which products are recommended to customers or prediction of customer’s spending power etc. Analytics has made decision making faster. For example, an algorithm can process lengthy payment histories of accounts, extensive demographic data, tough calculations about insurance policy premiums etc. etc. An insurance company can use these analytical tools in the actuarial department and make the decision-making processes swift. All this analytical tools saves a lot of time for managers who can now focus on making decisions on data truly reflective of their business performance.