Cash Forecasting & Working Capital Made Easy for Treasury

About Unilever

Unilever is a globally operating enterprise and one of the world’s largest consumer goods companies. More than 400 brands are available through Unilever in over 190 countries, and the company generates an annual turnover of around 50 billion Euros. As a result of their extremely complex business environment which spans the whole globe, treasury’s cash forecasting workflows can be very challenging to execute. Crucial data is needed from a range of different sources & systems, from hundreds of entities worldwide, and, accordingly, from more than 200 banks and over two thousand accounts.

Unilever’s Treasury Technology & Cash Forecasting Objectives

Putting an end to Excel sheets, manual processes, and dependencies on local entities were some of the main objectives Unilever had in respect to their global cash forecasting setup. Because their existing cash forecasting process was cumbersome, slow, and involved a lot of manual work, the accurate forecasts were mainly built for countries with high interest rates or heavy penalties in case bank accounts are overdrawn, but not consistently across all entities worldwide. The fact that Unilever (given its superior credit rating) could borrow easily and relatively cheaply (e.g. in the commercial paper market) was another reason not to focus earlier on getting the process and the tool right.

To optimize their cash forecasting on a global scale, Unilever was looking for a solution capable of aggregating and analyzing all the information needed from their different data sources, from banks as well as from ERP-systems, in an automated way. Centralized cash flow forecasting, clear workflows, cost savings, better visibility to cash balances, and continuous improvement of forecast accuracy over time were the primary benefits Unilever wanted to achieve. But, most importantly, Unilever wanted to ensure their new forecasting solution was future-proof and could exist without heavy and ongoing IT projects. They were also looking for a solution that was easy to implement, flexible in terms of scalability, and that provided a broad range of connectivity options.

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