Success Story – Versicherungskammer

The Customer

Based on premium income, Versicherungskammer Group ranks among Germany's ten largest primary insurers and is the country's largest public-sector insurance group. The Group comprises eleven insurance companies operating under the regional brands Versicherungskammer Bayern, Feuersozietät Berlin Brandenburg, and SAARLAND Versicherungen. It employs approximately 7,900 people. Its product portfolio ranges from property and casualty insurance to life insurance and retirement provision, as well as health, long-term care, and travel insurance. Just as diverse as its product portfolio are the data collected from various source systems within the controlling department, which must be consolidated and prepared for group-wide analysis.
 

Behind the Scenes of Group-Wide Data Analysis

Sales Controller Thomas Lederer and his colleague Steffi Klinger are responsible for group-wide sales and production figures. Together, they ensure that the right data is available to all controlling units at the right time. Given the large number of data sources, evolving structures, and complexity of the insurance business, this is no easy task.

One of the most important tools behind the scenes of data analysis is Qlik Sense. The data analytics solution has been used on-premises for analysis and reporting tasks for many years. As a result, the Sales Controlling team has built up extensive expertise: Around 90 to 95 percent of Qlik development is carried out internally, with external support required only occasionally.

This level of expertise is essential because Versicherungskammer's data landscape is complex. A central starting point is the data warehouse, which replicates information from operational systems. Additional data sources include SAS, Access, SQL Server, and supplied CSV and Excel files. In some cases, data passes through several stages before reaching the controlling department. Maintaining an overview of this data landscape is crucial to identifying changes in original data sources and ensuring they are reflected in downstream analyses.

"We work deep behind the scenes. Our job is to understand the various interfaces and data sources and make the information available in a way that enables other controlling units to use and interpret the results," he explains.

It is not only the data landscape that is complex, but also the structure of the KPIs. In the insurance industry, business requirements and calculation logic are closely interconnected: One KPI may depend on several others, which in turn incorporate additional definitions and variables. "Some KPIs have three levels of dependencies. That can quickly add up to six or seven additional KPIs and multiple variables," explains the Sales Controller.

Greater Efficiency and Standardization Across Applications

As the number of Qlik applications grew, so did the effort required to track and consistently use these nested KPIs across applications. This brought two objectives into focus: greater efficiency and stronger standardization.

Within a single application, Qlik Sense provides effective tools for developing and managing KPIs and dimensions. However, things become more challenging when the same definitions are used across multiple applications and their dependencies need to remain fully traceable. Particularly with multi-level KPIs, the team previously had to open each formula individually and follow the references step by step.

The team therefore sought a way to develop and manage KPIs and dimensions across applications, visualize their relationships, and reuse existing calculation logic with less manual effort. "When developing new solutions, we wanted to make standardization easier, while also being able to identify relationships between KPIs and variables more quickly in existing applications," says Thomas Lederer.

Two Hours Instead of Several Days

A projection for the life insurance business demonstrated the tangible benefits of this improved visibility. In the insurance industry, "production" refers to new business generated by sales activities, expressed as a monetary value in euros. For planning purposes, the Sales Controlling team wanted to forecast how production would develop through the end of the year.

Steffi Klinger had already developed various forecasting methods in Qlik Sense for another project. The calculations involved nested KPIs and numerous variables. Previously, the team would have had to open the application, examine each formula, and trace the dependencies step by step.

With the iVIEW Library, the entire structure could be visualized. Since Versicherungskammer already uses standardized data models, Thomas Lederer was able to transfer the required definitions into his own application. "I didn't have to reinvent the wheel," says Thomas Lederer. "With iVIEW, I could see exactly which KPIs and variables I needed and reuse the existing logic. The task was completed in about two hours. Without this overview, it would probably have taken me several days."

iVIEW Library

The benefits remain largely invisible to business users, and that is precisely the intention. The controlling units receive their figures reliably and on time. Behind the scenes, the Qlik team can work faster and take on additional tasks. "We're becoming more efficient and can handle more tasks that we previously lacked the resources for. Quite simply, iVIEW saves us time," the Sales Controller summarizes.

A Speedboat Alongside the Tanker

Beyond the tangible benefits of the Library, Thomas Lederer also values the collaboration with Informatec. As an employee of a large corporation, he is familiar with the coordination processes associated with complex organizational structures. This makes it all the more refreshing to work with a specialized provider where he can speak directly with people who know the product and respond to requirements without lengthy processes. He also finds the collaboration straightforward and fair when it comes to support requests.

For Thomas Lederer, in-depth technical expertise is equally important. Anyone extracting and reliably mapping complex dependencies from a Qlik environment needs a detailed understanding of the underlying technology. "I was genuinely amazed by what the Informatec team has built. Developing a solution like iVIEW requires an extremely deep understanding of Qlik Sense. You can really see that expertise in the product."

Standardization Starts with the Data Foundation

In addition to saving time, the iVIEW Library helps Versicherungskammer gradually standardize its KPIs. The team has already stored commonly used definitions in the Library that can be applied across different lines of insurance business, such as production figures covering all lines or specific areas like life insurance. New applications can reuse these predefined KPIs instead of recreating them from scratch. In older applications, dependencies and inconsistent structures can be identified more quickly. However, a reliable foundation is essential to ensure that all processes behind the scenes of data analysis work seamlessly together.

For similar projects, the Sales Controller recommends starting with a standardized data foundation, regardless of the BI tool being used. Reliable analyses are only possible when the underlying data is aligned from both a business and technical perspective.

The diversity of insurance lines illustrates why this groundwork is particularly important in the insurance industry. "Life, health, and property and casualty insurance generate their data in different policy administration systems. As a result, the datasets differ in structure, content, and field names," he explains. To ensure that KPIs work across different lines of insurance business, these differences must be consolidated into a common data model. Versicherungskammer has therefore standardized key attributes so that different sales organizations and controlling units can use the same definitions.

He also recommends introducing centralized KPI management as early as possible: "Ideally, the iVIEW Library should be implemented alongside Qlik Sense right from the start. The earlier you standardize, the less cleanup work you'll have to do later."

"We work with highly nested KPIs: Some have three levels of dependencies, six or seven additional KPIs, and multiple variables. With the iVIEW Library, we can see these dependencies immediately and reuse existing calculations directly in new applications. What used to take several days can now be completed in around two hours."

Thomas Lederer, Sales Controller, Versicherungskammer