The challenge

Unilever’s global scale, breadth and historic growth made cash flow forecasting extremely challenging. Unilever had deployed a diverse range of cash flow forecasting processes across the enterprise: some countries effectively produced no forecasts; others – most notably countries with high interest rates and onerous penalties for overdrafts such as Brazil, Indonesia and the Philippines – produced relatively detailed forecasts that required labour-intensive manual inputs (using Excel) at a local level. As a result, Unilever had limited timely visibility over its forecast cash and the company was often surprised by late adjustments to cash positions. While Unilever’s credit rating meant it could borrow easily and relatively cheaply, it recognised that the period of historically low interest rates was certain to come to an end in most countries and therefore it would be advantageous to improve its cash flow forecasting in advance.

The solution

Unilever’s global treasury centre in Switzerland issued a request for proposal (RFP) with the objective of improving its global cash flow forecasting. It wanted to centralise forecasting (and reduce its dependence on local entities) by leveraging its universal data lake, which combines all the data from its SAP instances globally. It intended to integrate additional data sources from its TMS and its bank platforms and analyse the aggregated data. Unilever sought to introduce clear workflows and automate forecasting processes to as great an extent as possible to reduce costs and improve timely visibility over cash balances forecast. It wanted a solution that was straightforward to implement, easily scalable and which offered a broad range of connectivity options for layering in additional data sources through inorganic growth and associated system inheritance. It also wanted a future-proof solution with minimal ongoing IT requirements and the capacity to continuously improve forecasting horizon, frequency and accuracy.

Unilever selected Cashforce (subsequently acquired by TIS in 2022) for its solution. By leveraging its universal data lake, it was able to adopt an accelerated implementation timetable. Integration with Unilever’s TMS was also relatively straightforward given the company’s experience of technology integration projects and strong support from its partners coming equipped with proven system adapters. Moreover, Unilever was already in receipt of significant volumes of data from its banks, including Citi, for reconciliation and other purposes. Although there were some initial challenges relating to the quality of source data from Unilever’s SAP instances that needed to be addressed, close collaboration between the company, TIS (which appointed a dedicated project manager) and Citi through the multi-year Citi/TIS relationship meant the solution was operational in less than five months. Minimal IT resourcing was required during the installation, with Unilever business resources best placed to advise on sources and drivers of the forecast.

Best practice and innovation

Working with TIS, which is a small and nimble fintech, Unilever gained access to innovative technology that could integrate seamlessly with its data lake. While Cashforce (especially prior to its TIS acquisition) was a relatively small and young company, the close collaboration between the fintech and Citi provided Unilever with the comfort, scale and experience necessary to push ahead with the project and laid the foundations for a rapid and straightforward implementation.

Rather than sitting on Unilever’s or Citi’s systems, the TIS solution is software-as-a-service (SaaS), enabling it to be updated frequently and to plug in new data sources as the needs arise through, for example, growth. New capabilities and functionality can be added every few weeks. TIS has been specifically enhanced in response to Unilever’s feedback several times since implementation and the use of APIs also helped to accelerate implementation.

Key benefits

• Cost savings.

• Headcount savings.

• Process efficiencies.

• Return on investment (ROI).

• Increased automation.

• Risk mitigated.

• Improved visibility.

• Errors reduced.

• Manual intervention reduced.

• Increased system connectivity.

• Future-proof solution.

• Exceptional implementation (budget/time).

• Improved key performance indicator (KPI) metrics.

“The global scale of our activities combined with the pace of delivery (full implementation took less than five months) means this ambitious cash flow forecasting solution sets a benchmark for other global corporates.”

Gerard Tuinenburg, Treasury – Director Systems, Innovations and Transactional Banking