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Tableau > Case Studies > Bank BRI Indonesia's Journey Towards Decentralized Analytics for Rapid Business Insights
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Bank BRI Indonesia's Journey Towards Decentralized Analytics for Rapid Business Insights

Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Data-as-a-Service
Applicable Industries
  • Cement
  • Finance & Insurance
Applicable Functions
  • Logistics & Transportation
  • Product Research & Development
Use Cases
  • Last Mile Delivery
  • Smart Campus
Services
  • Data Science Services
  • Training
The Challenge
PT Bank Rakyat Indonesia (BRI), one of the largest banks in Indonesia, was facing a significant challenge in its data analytics process. The bank, which is data-driven in its approach, was struggling with a centralized system where data analytics was considered a task for the IT department only. Business teams had to put in a request to IT every time they needed a new report or dashboard, and then wait up to four weeks for a response. The reports and dashboards were prepared using complex queries and coding, which often led to requests for changes and further delays. In some cases, the dashboard was no longer required by the time it was complete. BRI wanted to enable faster delivery of data to business teams and build a foundation for self-service analytics.
About The Customer
PT Bank Rakyat Indonesia, commonly known as BRI, is one of the largest banks in Indonesia. As a state-owned company, BRI is committed to providing banking services that extend beyond the cities and into the rural areas of Indonesia. BRI’s broader vision is to become the most valuable banking group in Southeast Asia and the champion of financial inclusion. The bank is data-driven in its approach to achieving these goals and has built a data culture that encompasses the entire organization.
The Solution
To address this challenge, BRI started by rolling out Tableau within the IT department and using it to create dashboards for the business. The company then began to build data literacy across the organization. Tableau helped BRI implement a self-service strategy, making it possible for non-IT users to independently explore data and extract insights on their own. BRI's data specialists worked closely with business users to develop solutions that best met their needs. The bank also runs a program called 'Pendekar Data' (Data Warriors) to boost data literacy, which includes training for the business and is supported by a network of data champions. As a result of the training, business users are equipped to analyze data on their own using Tableau. Currently, there are more than ten datasets connected to Tableau which are used by 18 divisions for self-service analytics.
Operational Impact
  • The implementation of Tableau and the shift towards a self-service analytics model has significantly improved BRI's agility in data analytics and the development of solutions for business users. Business users are now able to independently explore data and extract insights on their own, without needing to know a query language. This has not only sped up the process of data delivery to business teams but also fostered a data culture within the organization. The bank's 'Pendekar Data' program has also boosted data literacy across the organization, equipping business users with the skills to analyze data on their own. This has led to more informed decision-making and has allowed the bank to better meet the needs of its business users.
Quantitative Benefit
  • Potential savings of US$300k/month in cost to serve data to all business units
  • Eliminated the 36 hours previously required to create new analytics solutions
  • More than ten datasets connected to Tableau for self-service analytics

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