Big Data gives Britam Insurance a competitive advantage over it competitors in the insurance industry. The ability to analyze the data provides enormous breakthroughs in terms of response to client needs, quality of services, customer satisfaction and cost efficiency. The availability of up-to date, quality-controlled data is changing decision making processes within the organization leading to gains in quality, warranty costs, customer satisfaction and profitability.
The company obtains data from the web and integrates it with the operational data it obtains from its clients to arrive at a conclusion and forecast on the future. The data obtained in a mining process need to be analyzed, transformed and aggregated at different levels of abstraction. Thus, data content is one value added feature utilized by e-commerce sites to convey a relationship with the user. Data content is comprised of textual and graphic representation sourced from HTML/XML pages and scripts. The content data involves the semantic or structural meta-data that are embedded within pages sites, attributes descriptive keywords among others.
The company currently provides analytic services using its custom made tools that suites small start ups and developed enterprises. The BAnalytic is its proprietary software offered to its clients on a standard free version and paid version. Currently due to technological constraints, the BAnalytic software is outsourced from partner developers. Britam’s strategic plan involves the development of custom made software’s for its clients according to their needs. As part of its strategic plans for the next 18 months, the company envisions to broaden its analytical tools through integration of social media metrics. By so doing, it estimates that the business will attract more than 60% growth due to increased subscription from start up as well as non-start up world.
The analytical interface of the CMS systems and the BAnalytic tools is the significant driver that delivers what the user understands and provides interpretable and actionable information. Analytical dashboards should, therefore, guide the user on what he has to do and provide mechanisms such as clickthroughs necessary for further analysis. The design considerations of such tools have incorporated design principles that are aimed at understanding the user interfaces. This includes; user-centric analytic models that allow the user space for setting modeling parameters and improved visuals. The visual parameters associated with size, space and position makes for faster adoption as well as improved summary.
In the figure below, some of the screenshots illustrating the interface that organizational users will utilize is given.
– Chart, b) User interface and c) graphical representation of analytic tool
NEED FOR CLOUD COMPUTING
Data in the clouds pose serious security challenges, and as such, the company will secure its databases through AES encryption techniques. Cloud information protection platforms at the company’s network edge ensure that data is fully protected before it leaves for the clouds. Other mechanisms include sufficient encryption key management and user policies.
Britam Insurance company captures numerous amounts of data from its insurance information systems. This data are transmitted to the clouds and then back to the company for analysis. Britam believes that, in a world where smart technological innovations is the way to go, it is important to leverage the numerous amounts of data generated from its clients and convert them to usable analytics.
Clouds is undoubtedly the best cheap and virtually unlimited storage for large volumes of data. Considering the volumes of data streamed into Britam centralized analysis hub, clouds are the best option for them. Britam generates terabytes of data from its customer relation systems, dealership systems, and product design and development systems among other departments. The clouds are cheap with no installation and maintenance, has no physical presence hence reduced risks, requires no environmental and personnel to power and manage it. As a result, it provides a clear business advantage.
Analysis of large volumes of data in the clouds provides a host of advantages to the company. First, the data patterns provide a mechanism to detect potential issues and concerns in the early process of a particular product. Potential legal and operational problems may be detected early enough before the user and the company is exposed to them. Through well crafted analytics, the concerns are analyzed and solved through adjusted design processes. It becomes economical to the company to rectify the concerns when spotted in the first 1000 clients than when it is spotted after half a million subscriptions have been entered. The customer impacts are also detrimental when business concerns are detected in numerous volumes of products and policy designs already sold. Customer trust is crucial for business and growth of a company, and a change in policy terms and conditions to the disadvantage of the customer has an impact of tainting the company image and hence sales. Thus by analyzing past and current business scenarios and product designs, the insurance company is able to tailor products that are beneficial and needful to the client.
Analytics as a service has made it possible to spend more time on analysis and less time on administration of software and hardware. Service delivery is hastened with less resources and capital. Britam will combine analysis and reporting as a core business practice. With the use of dashboards, the company will derive user interfaces that provide multiple layers of related data. Likewise, data visualization will slice up data into useful schematics. For instance, sales could be analyzed according to demographics, sales channels or geography. This will reveal underlying problems behind underperforming stores. At the same time, untapped markets could be exploited effectively.
In the figure below, the data flow diagram illustrates how raw data is transformed into useful deliverables. Data is sourced from clients and business records of which it is analyzed using analysis tools and used to for managerial and decision purposes.
I strongly recommend sufficient security parameters in safeguarding data in the clouds. Data in the clouds pose serious security challenges, and as such, the company will secure its databases through AES encryption techniques. Cloud information protection platforms at the company’s network edge ensure that data is fully protected before it leaves for the clouds. Other mechanisms include sufficient encryption key management and user policies.
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