Founded in 1868, the Metropolitan Life Insurance Company (MetLife) (www.metlife.com) is among the largest global providers of insurance, annuities, and employee benefit programs, with 90 million customers located in more than 60 countries. As a result of acquisitions, new products, and various software deployments over the years, MetLife had grown into a $68 billion company with 70 software systems that could not communicate with one another. To make matters worse, each system had its own data- base. These problems made it difficult for MetLife to communicate with its policyholders. For example, customer service representatives could not always tell if a client with an automobile insurance policy also had a disability plan with the company.

MetLife had to rely heavily on humans to integrate its separate systems and databases. Customer service representatives and claims researchers had to access multiple applications and utilize as many as 40 screens just to gather all of the data and documents required to answer customer questions. That process decreased both worker productivity and customer satisfaction. Because MetLife offers multiple lines of insurance as well as annuities and other lines of business, it was critical that the company develop a unified, consolidated view of its customers.

To accomplish this task, in 2013, MetLife turned to MongoDB, a document-oriented NoSQL database, to integrate all relevant customer data on a single screen. MetLife called the project, which was inspired by the Facebook Wall, the MetLife Wall. With the deployment of the Wall, MetLife representatives no longer view policyholders merely as ID numbers scattered among different insurance products. The MetLife Wall integrates different sources of customer data to let representatives review customers’ histories, their conversations with the company, any claims filed and paid, and their various policies—all on a simple timeline. Representatives can access these data with one click, and they can settle issues more efficiently and quickly assess how a customer feels about the company. The MetLife Wall has significantly increased customer satisfaction. Since the company implemented a limited launch in April 2013, more than 1,000 customer service representatives and claims researchers in the United States and Europe have been using MetLife’s Wall successfully.

In addition to the MetLife Wall, MetLife is using MongoDB for two other applications. The first is a recruiting site to store resumes, which makes the resumes easier to analyse than would be the case if they were stored in Word files or PDFs. Next, MetLife deployed a customer-facing mobile app that allows its customers to upload documents, videos, photos, and other content that they can designate to be shared only with selected individuals at some future date. For example, access to a life insurance policy can be made avail- able to the beneficiaries after the policyholder has passed away. Celente, a research and consulting firm, awarded MetLife its 2014 Model Insurer of the Year. The award recognized MetLife’s effective use of technology in the form of the company’s MetLife Wall.

Sources: Compiled from “MetLife Honoured as Celente 2014 Model Insurer of the Year,” MetLife Global Technology & Operations, April 14, 2014; “5 Lessons Learned from the MetLife Wall,” inetpost.mobi, May 1, 2014; J. AL server, “Technology Is the Best Policy,” Fortune, November 18, 2013; J. AL sever, “At MetLife, Technology Is the Best Policy,” CNN Money, October 31, 2013; “Build in Record Time, the MetLife Wall Knocks Down Barriers to Great Customer Service,” MetLife Global Technology & Operations, October 23, 2013; K. Nicole, “MetLife’s Big Data Revolution,” Forbes, October 11, 2013; D. Henschel, “When NoSQL Makes Sense,” InformationWeek, Octo- beer 7, 2013; D. Harris, “The Promise of Better Data Has MetLife Investing $300 M in New Tech,” Gigamon, May 7, 2013; www.metlife.com, accessed February 27, 2015.
Questions ( answer in 300 Words minimum)
1. Describe the problems that MetLife was experiencing with customer data before it implemented the MetLife Wall.
2. Describe how these problems originated.

 

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