As digitalisation advances, a vast amount of data is being generated – and this represents a key opportunity for the treasury function. If treasurers can effectively sift through this ‘data lake’, they stand to unlock smarter insights and enable faster, streamlined decision-making. But placing data at the heart of a treasury department is not something that happens overnight – and the journey is fraught with challenges. So how exactly can treasurers incorporate a ‘best practice’ data strategy?

Traditionally, when treasurers wanted to maintain visibility over their available cash positions, they would often simply check their account balances, which would be correct as of the end of the previous working day. Since the proliferation of real-time payments – and as global companies have increasingly worked across regions with different closing times – this visibility is no longer fit for purpose.

In response, real-time visibility of cash balances, as well as expected outgoings, has become a central feature of an efficient treasury operation. To achieve this goal, treasurers should ensure that all information – across the entire value chain – is automatically collated and analysed, allowing them to seamlessly manage operational KPIs, resolve disruptions and perfect fulfilment.

Unfortunately, getting the necessary data from the various Treasury Management Systems (TMS), Enterprise Resource Planning systems (ERPs), bank portals and data service providers – in both its structured and unstructured form – in the right place and in a usable format is harder than it might seem.

“One of the biggest challenges for treasurers looking to integrate data into their day-to-day work is the lack of collaboration across departments”
Claudia Villasis-Wallraff, Head of Treasury Advisory APAC, Deutsche Bank

One of the biggest challenges for treasurers looking to integrate data into their day-to-day work is the lack of collaboration across departments. Often, the treasury, finance and procurement teams act in isolation from each other – meaning that their forecasts and plans for the year rarely match up. This becomes a problem when treasurers are looking to identify cash balances across the whole business – an issue that was brought into sharp focus by the Covid-19 pandemic.

These corporate silos – and the data silos they create – need to be broken down for the treasury department to respond effectively to today’s demands. It begins with better collaboration and transparency with the other key parts of their business.

Underpinning the effectiveness of the treasury function’s data strategy is the quality of the data available; in the Economist Impact survey A Quantum Leap: Building a Data Driven Treasury which was published in 2019 in cooperation with Deutsche Bank, four in 10 respondents agreed that they are very concerned about the poor quality of financial and business data in their organisations.¹

For example, in some companies, the complexity of the IT set-up – particularly the lack of a single SAP instance – can interfere with the information that the treasurer is trying to map. When data from different internal and external systems is pooled, it is often standardised so that various business departments can analyse it. For treasury, such standardisation runs counter to the data-driven approach, as it conceals important nuances in the data. In this sense, while treasurers recognise that data is the new ‘gold’, they also realise that mining it will take much effort.

Another consideration is that many unstructured data sources, such as the weather, social media and current events, are not necessarily compatible with existing data models. But they may, nonetheless, still be useful. For example, whether it is sunny or not can correlate with seasonal sales – and factoring in external data, such as weather reports, can help to improve cash forecasting. As a result, treasurers are creating repositories of unstructured data, which is becoming essential for a more nuanced analysis.

“TMS providers might have solved and digitalised a number of single treasury processes, but they are no longer the tool of choice for data analytics”
Claudia Villasis-Wallraff, Head of Treasury Advisory APAC, Deutsche Bank

With such a diverse store of data across hundreds of applications, ensuring everyone has access to this information – and can use this to make informed decisions anytime, anywhere – is a challenge. One reason for this is that the technologies used by treasurers are still catching up with the requirements for a data-driven treasury. TMS providers might have solved and digitalised a number of single treasury processes, but they are no longer the tool of choice for data analytics. Instead, treasurers are using other tools, such as Excel and Tableau, to not only bring the data together, but to also run analytics on it.

As corporates look to put data at the heart of their operations, there are several questions they should ask themselves:

• As an organisation, are we working in a transparent, collaborative way to ensure all data is available for the treasury function?
• Are my treasury processes and technologies up to speed with the new real-time world?
• Is my data of sufficient quality to provide effective, reliable insights?
• Am I able to aggregate and visualise unstructured data to improve my analysis?

This article was first published in the ACT International Treasury Peer Review – Best Practice Guide which was developed by the Association of Corporate Treasurers (ACT) in cooperation with Deutsche Bank.

Sources

¹ See A Quantum Leap: Building a data-driven treasury at corporates.db.com