Every organization, regardless of size or industry, begins its journey with data. Some have a firm grasp on performance indicators and are able to future-proof their departments through enhanced analysis. There are others who may realize the value but don’t have the plan or the technology in place to succeed.
One of the industries that utilizes analytics most heavily are insurance organizations. Unlike what was the case 15 years ago, insurers now have access to new data sources and behavioral tendencies from their customers. This information leads to more accurate claim resolution and more favorable results for both parties.
There are many cases where this type of analysis is being done on a day-to-day basis, but the great work largely goes unprinted. We seek to change that. Recently, I sat down with Lawrence Maisel, President of DecisionVu to talk to him about his book, Predictive Business Analytics: Forward-Looking Capabilities to Improve Business Performance.
Q: Can you tell us a bit about your background and DecisionVu?
A: Sure, I am the President and Founder of DecisionVu with prior experiences as a Senior Partner at KPMG Consulting and an executive at PeopleSoft. We specialize in providing corporate performance management, financial management, and IT business management services for our clients. I have worked with many Global 1000 companies including MetLife, TIAA-CREF, Citigroup, GE, Bristol-Myers, Pfizer, and News Corp/Fox Entertainment, among others. DecisionVu is focused on delivering measurable performance improvements to our clients.
Q: You mentioned MetLife at the beginning of that list, tell us a little more about their need for performance improvement.
A: I actually have an entire chapter of my book that is dedicated to the MetLife story. They were going through the same challenges of most insurance companies: low interest rates and the necessity to maintain customer care. They brought in a new executive Martin Lippert as Executive Vice President and Head of Global Technology and Operations (GTO). Upon taking over he realized how important data was to the business; namely how key performance indicators (KPIs) lead to improving operating performance and ensuring that quality processes improve the customer experience.
Q: How did you decide what were the most important KPIs to measure?
A: Marty delegated two leaders to enable the review process: a chief of staff Mona Moazzaz and Jeff Nachowitz who leads a new GTO function Global Business Efficiency and Effectiveness (BEE). Together, they implemented the Management Operations Review (MOR) process. This is a fact-based, data-driven approach to management, which was totally new to MetLife. The team constructed KPIs that were aligned to MetLife’s corporate strategies and detailed operating performance measures. These KPIs were organized based on objectives and formed the foundation for a repeatable in-depth monthly review program.
Q: How did you get started to access all the data you needed across the global organization?
A: Jeff and his team leader, David Sullivan, engaged DecisionVu to help jumpstart the MOR program by building governance practices and defining KPIs in addition to establishing important elements like the reporting tools and management resources. One of those elements was defining a reporting structure as you can see in the graphic below. We needed to allow the operating executives and teams to define their own metrics within the MOR program.
As you can imagine, this review process spanned a number of different teams and people across the organization, which meant a lot of disparate data sources organized by “color-coded books” that needed to be culled together.
Q: How did MetLife decide Qlik was the right analytics platform for this performance management initiative?
A: One of the concerns we had was that there was so much data to pull into meaningful analytical dashboards that we didn’t want to overwhelm the users with added metrics. The idea was to select a handful of metrics as opposed to 100: the ones that really tell a story and show the greatest impact. This is why we selected Qlik: it’s not a reporting tool, it’s analytics on steroids. It is much more rapid when you use Qlik against a very large volume of data, which was why it stood out versus the other analytics tools. Qlik allowed MetLife the ability to quickly see the interrelationships in the data, both numerically and visually.
Q: What are the results of the program thus far?
MetLife has seen a profit increase and the organization is making better fact-based and forward-looking decisions. The management team can now use the analytical dashboards to review the status and quality of programs/projects on a routine basis. Two big areas of focus are in customer retention through its call center capabilities and improving operating productivity by focusing on the KPIs that matter most.
I feel like Jeff said it best from a quote in my book: “Making fact-based decisions in a dynamic environment increases the odds of making the right decisions.”
I want to thank Lawrence for taking the time to chat with us about MetLife. For more stories like this you can read his book which is available on Amazon.