Self-Service Analytics in Finance: Top Tips for Success

Building a Data-Centric Finance Function that Empowers Users

As FP&A processes become increasingly data-driven, finance chiefs are looking for ways to quickly and efficiently provide business leaders with the information they need for better decision-making. The data typically sought by senior executives encompasses historical data and shared plans, objectives, forecasts, and metrics that drive performance and determine the organisation’s next course of action.

Self-Service Analytics, boosted by cognitive technologies, can provide this much-needed data without any intervention from IT. In turn, more readily available insights can enable organisations to better analyse trade-offs between the speed, cost, and quality of various business decisions.

In today’s marketplace, which is fast-moving and increasingly unpredictable, many people across the organisation find themselves in the role of data analyst. Everyone from finance executives to business function leaders relies on data to develop budgets, manage the performance of their departments, and project future funding needs. A robust Self-Service Analytics solution is no longer a nice-to-have but a necessity, however there are several factors affecting its success.

Self-service streamlines analytics in finance, as it increases the availability of information, rather than just data, across an organisation. As a result, it empowers employees to make better decisions, be mindful of organisational goals and objectives, and work to meet those objectives.

Access your free eBook “Self-Service Analytics in Finance: Top Tips for Success” to identify what you should consider when it comes to how modern Self-Service Analytics in finance weaves into the Financial Planning & Analytics (FP&A) process and the top tips for success.

Self-Service Analytics in Finance

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Learn more about the top tips for success:


  • Eliminating spreadsheet proliferation
  • Partnering with IT to improve data availability and accuracy
  • Enhancing Self-Service Analytics with cognitive technologies
  • Extending analytics insights for next-level planning
Self-Service Analytics in Finance


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