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Advanced Analytics in the Transportation Industry

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yash sharma

Advanced Analytics Industry Overview by Type (, Statistical Analysis, quantitative & qualitative Data analysis, Customer analytics, visual analytics, Risk analytics, Business analytics, Management as a Service (MaaS), Transportation and Logistics, Customer analytics, Big data analytics, Others). This list highlights the growing importance of advanced analytics services for businesses of all types. While customer analytics is rapidly catching up in terms of usage and application across multiple industries, there are many others that remain relatively untapped markets. However, as companies continue to embrace advanced analytics solutions to streamline their business processes, these services are no longer a luxury, but a necessity. By enabling decision makers to obtain fast, easy access to aggregated and in-depth data, analytics serve as an effective management tool.

By type, there are two main categories: enterprise and consumer. In enterprise analytics solutions, data is collected from a wide variety of sources to be used to make business decisions. Common examples include sales and customer data from retail stores, sales figures from restaurants, utility usage from businesses like gas stations, and even public transportation mileage. Examples of consumer data would include credit card use patterns, disposable income, spending habits on major purchases, and the location of buyers.

The objective of the consumer segment is usually more direct. These data analytics services to collect, sort, analyze, and provide reports on all types of consumer information. Some examples include: gas mileage, shopping trends, marital status, health and medication data, and credit scores. While all this data is useful for making informed decisions, sometimes it becomes impractical to collect, sort, and analyze it without some specialized knowledge or expertise. There are third-party companies that provide business intelligence and data analytics solutions in the consumer segment.

Another application of advanced analytics is in the context of strategic marketing planning. Businesses in the mortgage and foreclosure marketplace need tools to determine foreclosure cost, delinquency rates, and potential buyers. This information is crucial in helping them determine which properties to focus on and which to exclude. In this context, business intelligence and data analytics can provide the necessary guidance to decide which properties to rent versus sell, and which marketing strategies to pursue. In fact, the government has been investing in this area with the grant money provided through the REMIC Mortgage Assistance Program (RAMP).

Global competitive intelligence and analytics are also important in understanding the digital transformation happening across the business and in analyzing potential competitors and their future trends. Analysis of market behavior provides a vital leg up for businesses trying to predict market behavior and react accordingly. This is a particularly important consideration in the context of the restructuring of retail markets. Retailers need to be able to determine what consumers are buying and how they are behaving to maximize their bottom line.

Data analytics can help companies in detecting the emerging trends in global market supply chains. It can help companies reduce costs and efficiencies in the procurement, production, logistics, distribution, and marketing of goods and services. Big data in retail industry The use of data in this context has transcended into the realm of financing and lending as well. Lending institutions such as banks are increasingly using advanced analytics solutions to evaluate risk profiles, the strength and weakness of corporate credit portfolios, and the risk-to-reward ratio of extending credit.

This research article concludes by briefly examining three additional trends that have emerged from examining the relationships between consumers and five publicly-traded companies in the iGoogle/aaS industry. First, it should be noted that increased profitability is one of the main drivers of consumers turning to third-party insight to assist in making purchasing decisions. Consumer preferences for shopping have changed dramatically over the last decade, and third-party insights have become an important part of many consumers' decision making process. Next, it should be noted that predictive analytics has provided consumers with greater access and flexibility in making purchasing decisions. Consumers have access to more detailed and accurate information regarding products and services via third-party channels than ever before. Finally, another emerging trend is that consumers are becoming more "intimidated" of shopping online because of fraudulent activities carried out by companies posing as wholesalers or merchants.

The research was conducted by Booz and AT Kearney and was released in May of 2014. For more information on the advanced analytics industry, visit the Business Intelligence blog. If you would like to receive free weekly articles on cutting-edge business technologies, subscribe to the Technology Industry Insider. You can also follow the career news of Booz and Kearney at Twitter and Facebook. All information is available on the entire BIN website.

 

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