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Global FinTech Player Accelerated Anaplan Performance with Space Optimization

Global FinTech Player Accelerated Anaplan Performance with Space Optimization

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Business impact
  • Reduction in overall model size by 56%
  • Improved real-time collaboration efficiency within the platform by 83%
  • 37% decrease in the average planning process time
Project Timeline
  • Optimized the Anaplan space in within 6 weeks, it was comprised of 2-week discovery followed by 4 weeks of optimization and training for best practices.
Problem statement

The client's business model encompassed seven key dimensions, each requiring careful consideration and financial planning across multiple departments. These factors presented a dynamic challenge as traversing through the sparse data points was needed. The approach was non-productive in their process, and the client could not effectively identify the right combinations to plan. During periods of high concurrency, the client also faced challenges in platform performance, making it nearly impossible to work seamlessly and simultaneously in the model.

Key challenges
  • The high model size was almost 120 GB, reaching the workspace threshold of 130 GB.
  • Delayed and inefficient planning due to data sparsity in the model resulted in lower productivity and a faulty data input process.
  • Inability to add new cost and profit centers due to the model size and space limitations.
  • Need to advanced space optimization as the existing model was limiting scalability and regular enhancement and updates.
Solution framework
  • Identified specific line items taking a substantial share of the total calculation time and combining them without affecting data reliability and securing larger space.
  • Enabled better model structure, real-time collaboration, and efficiency by closely working with the business to determine the appropriate combinations of dimensions using logical reasoning.
  • Conducting comprehensive analysis to assess and minimize the number of extensive and voluminous actions per process, ultimately enhancing runtime optimization.
  • Verifying the model as per the best practice guidelines and implementing compress the model size further and enhance model performance.

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