A global insurance organization needed a data-driven analysis to assess the efficiency gains of a potential automation software implementation. BPM-D identified and presented over 339 pain-points and improvement opportunities over three business areas to the organization, creating greater transparency between the business and technology teams. Using business process simulation analysis, BPM-D projected a total annual cost reduction of over 50% following the implementation of automation software, equating to a potential cumulative savings of over $600,000 annually. With the help of BPM-D, the organization was able to proceed with their business transformation initiative with a clear understanding of their business requirements.
The organization is a global insurance firm, offering services such as insurance brokerage, risk management, reinsurance, talent management, investment advisory, and management consulting. With over 500 facilities in 130 countries and 81,000 employees worldwide, it is a leading player in the industry. The project focused on analyzing the processes of their Brazilian business, aiming to identify areas for improvement and optimize performance. Organization Background The organization, a world-leading insurance firm, operates across 130 countries with over 500 facilities and 81,000 employees globally. The project centered on analyzing the processes of their Brazilian business to enhance efficiency and effectiveness, leveraging their expertise in the insurance industry to strengthen their presence in the Brazilian market.
The main driver for the project was to assess the efficiency gains and manual task reduction within their business processes following the implementation of a potential automation software. This required a process simulation analysis. To do this, BPM-D needed information with regards to the task level details of their current processes in order to create the foundation for the identification of automation opportunities and pain-points. Business Challenge For each task level detail, BPM-D identified IT systems used, documents required or produced, and additional participants required. In addition, BPM-D needed to collect attribute information of each task level activity, such as cost, execution time, hand-offs, human resources, and lag time. This information allows for a detailed analysis that generates visibility and projects efficiency gains within their process.
Interviews were held with the Business Process Owners (BPOs) and technical leads to define the businesses As-is processes and automation technology capabilities. With this information, BPM-D analyzed potential improvement areas and potential pain-points within each task of their process based on the business needs and automation capabilities. This allowed for the identification of main drivers within the technology implementation for process improvement and savings, such as improvement in automation, reduction of tasks, a centralized document location, reduction in IT systems and greater visibility of processes. The Solution Knowledge of the automation software capabilities and drivers for process improvement led to the creation of To-be reference models for each business process analyzed. Hundreds of tasks were identified as automation opportunities in the models. Each task within the As-is and To-be were associated with attribute information provided by SME and technology leads. Using process simulation, quantifiable cost and efficiency results were produced predicting the efficiency gains of a future automation software implementation. These results were then produced and presented to the organization in a systematic and understandable approach, allowing for clear and apparent understanding of their current business and potential business decisions.
The successful simulation project achieved the following results:
Figure 1: This image identifies the As-Is to To-Be Analysis. The improvement opportunities identified in this process using a reference key. Activities which were automatable were identified.
Figure 2: This image is an example of the simulation results of the total processing time of each activity. By analyzing these results, we can identify the process bottlenecks and where a process improvement can take place.
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