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Self-Service Business Intelligence, Why it is Essential?

Hemant Todi, SVP, Rabobank

Hemant Todi, SVP, Rabobank

Disruption is not new in banking; after all, today’s banks look very different from even ten years ago. But the scale of separation and the pace of change are unprecedented. Digitalization is rapidly changing customer demands and experiences; those who can differentiate themselves through tailored services and products that add meaningful value to customers would be the ultimate winner. To drive quick outcomes and improve performance, banks have to embrace data-driven culture across the entire span of the organization – not just pockets of expertise in a single function.

Serving California communities grounded in agriculture since 2002, Rabobank, N.A. offers a wide range of financial products and services for individuals, businesses, and agricultural clients. As a bank, we captured a treasure trove of customer data ranging from demographics, transactional, behavioural, web site and social media data. We used only a fraction of our data to generate insights. Sprawling legacy systems, siloed databases, data complexity and sporadic skill sets were common obstacles. Organizations relied on a technology team to drive specific outcomes they’re looking to achieve through data optimization. All this was hindering business to harness the power of data to solve for unmet and under-served needs of a customer.

Over the last four years, we have evolved our approach to enable rapid delivery of advanced self-service business intelligence (BI) and data visualization capabilities. By moving to a user-centred model and establishing stronger working partnerships with our business groups, we now have a robust centre of excellence model delivering self-service data platforms, mobilization of information workers (power users and casual users) and business education and enablement across enterprise. See Image on the next page. Our self-service BI platforms have empowered business groups to analyze information rapidly, make faster, better-informed decisions, and respond quickly to business opportunities. We still have long ways to mature it consistently across all facets of the business. To us, it’s an ongoing journey.

Many factors went into making this journey successful. We took a five-pronged approach.

Management Buy-in: Defined the data strategy roadmap for both short and long term, presented and got buy-in from management on the action plan and investments needed to stand up the self-service BI initiative.

Partnerships: Established a partnership framework for working closely with our business groups to ensure optimal prioritization and management in aligning data delivery to business value.

Agile Methodology: Adopted agile scrum methodology for fast, iterative, and incremental data and BI projects, treating data as a product for self-service consumption.

Business Education and Enablement: Actively focused on information workers to adopt the data platform. I trained them on tools, data interpretation and data communications.

Data Governance: Adopted an overall policy through governance to determine data inventory, data ownership, data quality, information security, and data lineage, so that information workers have a good understanding of the data across the organization and its meaning and confidently apply it for greater business insight and results.

Our next steps include the addition of data platforms for increasing the use of big data as part of our modernizing data access. Also, we are working on ways to more quickly deliver productive, consistent, and secure user experiences on the cloud.

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