Customer Case

Precision Assortment Planning at Scale through Decision Workflows

Digital solutions for Finance
Swiss Banking Platform Operator

Situation

A leading Swiss provider of digital solutions for the finance and insurance sectors need to equip its finance team with a more robust and structured approach to financial planning. As business operations expand, controlling and accounting teams are increasingly burdened with time-consuming tasks around budgeting and forecasting, leaving little room for analysis or strategic planning.

Key challenges in the existing process

Today the process runs on disconnected, error-prone Excel sheets, but rising volume demands a robust, secure, enterprise-grade platform. Preparation alone takes three times longer than the actual planning process. To minimise delays, only a few individuals are involved, excluding many operational teams and stakeholders, who are only informed of the outcomes. The process also struggles with different levels of granularity: revenue forecasts often diverge from cost and resource plans. Furthermore, forecasting lacks flexibility: it’s based solely on the perspective of cost centre managers, making it difficult to accommodate alternative views, such as project-based planning.

Solution & Benefits

By implementing a decision intelligence platform, the entire budgeting and forecasting process will be automated, and manual, error-prone template rework eliminated. The system will retain the familiar structure of the original process, while allowing end users to customise data entry templates to suit their specific analytical needs. This will create a single, standardised template (adaptable by every user) that will become the organisation’s shared foundation. As a result, operational stakeholders will actively join financial planning: by managing familiar KPIs and measures, they will supply figures that will automatically feed the planning P&L and other reports. Ultimately, adopting this structured workflow will significantly speed up the process, improve data consistency, and lift forecasting from today’s 3–4 cycles a year to seamless monthly updates.