Why Did Nationwide need an enterprise-wide data warehouse?
Nationwide is large mutual insurance company with variety of products. They had each business units operating on their own by leveraging multiple different technology platforms. Data was collected and stored in different forms and structures. They suffered with data redundancy and high operational & maintenance costs. With data being spread across multiple stores, it was nearly impossible to generate analytics and take strategic decisions based on the data. In addition to that, with acquisitions they brought a different set of data on to already complicated data model.
In order to streamline the data process and create a centralized data store to act as a system of record, they needed
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With the integrated data being brought together from mergers, from different business units, they were able to do what-If analysis and standardize the policy premium rates which benefited the customer and eliminated the uncertainty on the premiums. With data being integrated and available in the data warehouse, business users were given the capability of viewing the data on the dashboards with interactive visualizations and reduced the need to ad hoc reports. Because the data is readily available on the dashboards with drill-down feature the cycle to create and reports were reduced by half and the there are no manual policy …show more content…
They brought different kinds of customer data, financial data, policy related data, purchase history to behavioral trending. They made the data available for reporting for trending, dashboards and Descriptive analysis. By coupling the customer data with Teradata CRM data, they were able to create segment of customer for special care and launch more targeted campaigns. By using the payment, purchase history they created customer behavioral prediction model to help the company to take personalized care of the customer which lead to increase in customer retention. By analyzing the weather patterns and inform the customer with claim process. Nationwide also integrated the financial data which used to spread across multiple data sources and spreadsheet. With this integrated data by applying the prescriptive analytics, they were able to help the business effective plan, assess the risk. With the new acquisitions and with new data brought into a centralized integrated data warehouse, they are able the conduction conduct what-If prescriptive analysis to standardize the premium rates and helped the customer without having the huge premium rate swings. With the enhanced reporting capability on the integrated data warehouse they used BI tools to create dashboards with drill-downs. They transformed the business with the help of BI from DSS where they were preforming the basic reporting and analysis in silos to EIS and ES where
CarMax faces challenges from several fronts that could threaten to disrupt their growth plans and their position as a disruptor in the used car market. The biggest challenge they face is being able to continuously secure a study supply of high quality used cars, due to the extremely competitive nature of the used car market. CarMax offers cutting edge technology to help the company identify buying trends, pricing trends, and consumer preferences down to the zip code that gave them a large competitive advantage, as “data mining” has matured and competitors have developed their own software tools, eroding the competitive advantage to CarMax.
IBM has a tool “Social Media Analytics” for discovering customer needs and sentiments, to gain better understanding of the market. It also helps understand new market trends and patterns, which is advantageous to the product development team of a firm. The tool also helps in targeting prospective customers by:
Instead of segmented purchasing through regional managers, all purchasing decisions were shifted to Atlanta, Home Depot’s headquarters. He also changed the managerial decision making process to be based on performance data rather than “gut-feelings”. Companywide analytics and improved information systems were implemented to support this new approach. In addition, GE engineering processes such as six sigma was used to create strict KPIs to allow management to track performance of stores. Failure to meet KPIs resulted in termination of managers or employees, creating a climate of fear.
The continuous growth of the business analytics software markets signifies an increase in the adoption of business analytics in business organizations. Business analytics has been crucial in optimizing organizations internally as well as maintaining flexibility to overcome unexpected external pressures as businesses shift from operating on intuition to utilizing the growing data volumes. Business analytics is defined as the processes that enable organizations to apply metrics based decision making to all business functions. Among the companies that have been successful with business analytics is Netflix, the American entertainment company. However, other companies, such as Trader Joe’s, although successful, still use the traditional intuition
Not only did we want to provide a consistent brand image, but he also wanted a single point of contact for customers which include a intergrated website that gives bot h sales personnel and customers access to all products and service offerings. In order to accomplish this it requires, “investing in enterprise-level data.” InnsuraCorp’s decision to use a centralized approach to IT was due to the fact that they had a decentralized IT organization structure. This caused processing inefficiencies and duplicate IT resources which caused barriers to the company’s data integration initiatives. A centralized structure would consolidate all IT resources at corporate headquarters.
They have set a specific goal of updating or completely remodeling 70% of their existing stores that are over 10 years old. They have completed these updates to some of their stores in the recent past and have realized immediate boosts to their performance.
This is a point that rings very true. Store development is important, but there are other key features that need to be considered for continued growth
At the same time to expand their services to be competitor in the payment industry. One of the main reason behind their success having excellent strategy in their external environment. In the external environment they have the extensive network throughout the world and they are still maintaining that standard in their
Multiple data sources like Point Of Sale, Circulation and Billing, SalesLogix, Wholesaler data (Magnet) and few more were feeding the system with each data provider regulating the security guidelines that BI must adhere to thereby, limiting the clients to see the data information pertaining to the contracts. Furthermore, to comply with the order and regulations of data providers, business requirement was to deliver reports accessible exclusively for internal Time Inc users or reports open to all Time Inc and Clients with no data limitations ( no data level security) or reports for Clients executing on data limited to their respective brands( Non-Magnet Security).
Arc Customer360 is a business intelligence tool architected for retail marketers for customer analytics solution which provides a blend view of customer topography. It gives detailed analysis of what when and where they buy, what products they prefer along with the frequency of their purchase and what kind of offer’s will attract them to the same store back next time they purchase.
The key strategy implementation efforts at Amazon all surround the use of “big data”. Big data is the growth and availability of large volumes of structured/unstructured data. The use of big data has allowed decision making based upon data and analysis instead of past experience and intuition. Big data has directed organizational change in allowing Amazon to expand from an online book store to an internet giant. Revolutionary application of big data has allowed Amazon to create superior service quality while motivating employees by providing real time information to solve customer issues. Big data has strengthened Amazon’s competitive capabilities by pioneering the application of big data and charging a monthly fee to smaller businesses
Now days, companies are searching for new ways of gathering data so that they can get useful data in order to make well informed decisions regarding the market they are operating in. Google analytics is considered one of the best tools offers extensive amount of data to business owners for free. However, the success of business is highly depended on how well they can arrange data and customize their collected data corresponded to their business priorities. Google analytics provides beneficial information for companies regardless of their extent of operation.
Currently, businesses want to use the information effectively for competitive advantage to make better decisions that improve and optimize business processes, predict the market dynamics accurately, optimize forecasts to adequately maintain resources to name a few reasons.
Companies have transformed technology from a supporting tool into a strategic weapon.”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions."(Davenport, 2006) Data is compiled to enhance business practices. When samples are taken, they are used to examine research and understand how to solve problems or why situations are as they are. Furthermore, in this article, Thomas Davenport discusses analytics from a business standpoint. He refers to organizations that have been successful in their usage of data and statistical analysis. In addition, he also discusses how data and statistics can be vital in the efforts to improve the operations of businesses.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...