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How to improve the performance of individual agents selling policies from a global insurance company?
An global insurance company lost
control over agent performance
and needed insights
to optimize margins

Insurance

How to improve the performance of individual agents selling policies from a global insurance company?
An insurance company with a worldwide network of agents lost control over the performance of the network and needed insight into how each each agent performed.
In just a few weeks, we successfully harmonized performance data from over 1,200 systems across diverse cloud storage platforms into a unified digital twin. Our intuitive visualization tools provided an initial overview, and through in-depth analysis, 32% of agents received actionable insights to enhance their performance.
In a few weeks, performance data from over 1,200 systems across various cloud storage platforms was harmonized into a unified digital twin. Initial impressions using out-of-the-box visualization tools led to further investigation, resulting in clear performance improvement instructions for 32% of agents.
The challenge
  • Each agent's information was stored in different geographical cloud repositories, making the data difficult to access for most agents and insurance companies.
  • Management of relevant data in the cloud was poor.
  • How can we avoid miscalculations due to local currency?
  • How can we visualize performance per insurance per segment and even per customer for each agent?
  • How can we optimize individual performance through more visibility to show which policies to focus on and which stop selling?
Solution
  • Improve data management and examine which data is necessary for the use case.
  • Integrate relevant data into the ontology, to produce a "digital twin" of global agent performance.
  • Examination of data within two weeks via the visualization tool Contour provides a first impression of overall performance.
  • Setting the threshold for all policies with respect to agent selection based on profitability.
  • Heatmap results by policy per agent to indicate which policy is profitable and which is not.
  • Rearrange product portfolio based on the data.
  • Portfolio teams advise current agents how to operate and improve their performance and assess prospect agents to optimize coverage in the field.
  • Instead of querying complex databases, agent personnel organized by function can now interact in a no-code way with a real-world object model, examining agent and overall performance, customers and other key business concepts.

 

  • Each agent's information was stored in different geographical cloud repositories, making the data difficult to access for most agents and insurance companies.
  • Management of relevant data in the cloud was poor.
  • How can we avoid miscalculations due to local currency?
  • How can we visualize performance per insurance per segment and even per customer for each agent?
  • How can we optimize individual performance through more visibility to show which policies to focus on and which stop selling?
Solution
  • Improve data management necessary for the use case.
  • Integrate relevant data, to produce a "digital twin".
  • Examination of data within two weeks via Contour provides a first impression of overall performance.
  • Setting the threshold for all policies based on profitability.
  • Heatmap results by policy per agent.
  • Rearrange product portfolio based on the data.
  • Portfolio teams advise current agents how to operate and improve performance.
The impact
  • Estimated up to $72M in annual savings based on a 12% improvement in performance.
  • Up-to-date administration of data, twelve cloud environments integrated into a "digital twin" build within 14 days.
  • Real-time performance insights of individual agents according to insurance company requirements.
  • First-time insurance company had global control.
The project
  • A combination of Foundry's Cloud and agent-based sync was used to connect with data from the Cloud and locally stored data to generate the digital twin in Foundry's ontology.
  • Visualizing the results is crucial for the adaption of the solution by the individual agent. Visual and analytics tooling like Contour and Object Explorer was used to drive decision-making.

 

  • Estimated up to $72M in annual savings based on a 12% improvement in performance.
  • Up-to-date administration of data, twelve cloud environments integrated into a "digital twin" build within 14 days.
  • Real-time performance insights of individual agents according to insurance company requirements.
  • First-time insurance company had global control.
The project
  • A combination of Foundry's Cloud and agent-based sync was used to connect with data from the Cloud and locally stored data to generate the digital twin in Foundry's ontology.
  • Visualizing the results is crucial for the adaption of the solution by the individual agent. Visual and analytics tooling like Contour and Object Explorer was used to drive decision-making.