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Case Study
Automating cost allocation to improve accuracy and efficiency
Client type
Alternatives Managers & Private Markets, Asset Management
Client Challenges
An investment manager relied on manual cost allocation processes that were time-consuming and error-prone. Complexity reduced accuracy and control across entities. A more efficient, scalable approach was required.
alpha approach
Alpha implemented a driver-based cost allocation engine within Anaplan to improve the efficiency and consistency of allocation processes. We automated calculations and standardized workflows to create a controlled approach across entities. Scenario modeling capabilities enabled flexible analysis and planning without disrupting core data, while reporting outputs were aligned with financial systems to support accuracy and reconciliation. This delivered a controlled and efficient allocation process, improving reliability, scalability and confidence in financial reporting.
How we delivered lasting value
Turning insight into impact
Reduced manual effort through automated allocation workflows
Automation replaced manual Excel processes. Teams completed allocations faster with reduced operational effort.
Improved allocation accuracy through driver-based methodology
Driver-based calculations reduced errors. Validation controls strengthened confidence in allocation outputs.
Flexible scenario modeling for allocation planning decisions
Scenario modeling enabled fast adjustments. Teams tested allocation strategies without impacting final data.
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