Companies in industries across the globe are undergoing a profound technological change, and digital business models are being embedded as a result. This not only creates unique business opportunities, it offers new ways to add value, such as restructuring working capital and devising new payment strategies.
In order to do this, an effective digital business model means that data is key, as it delivers smarter insights and enables faster decision making. However, becoming a data-driven business does not happen overnight. Factors such as the complexity of data integration or team members’ lack of data skills are particular pain points.
Yet treasury is no stranger to data. After all, decisions made from bank transactions, or from information on exposures, have been made for years. The main problem surrounds how to capture that data effectively and utilise it more efficiently. But how?
According to a new report by The Economist Intelligence Unit, supported by Deutsche Bank, the advance of cloud computing is the most important technological development facing the industry over the next five years (44%), followed by big data analytics (42%) and artificial intelligence (AI) (37%).
“Treasury Management Systems (TMS) deployed in the cloud offer a host of benefits, including a wider and more dynamic view of financial positions, automatic access to the latest analytical tools and an ability to more easily collaborate with stakeholders, reducing the need for data collection and input by treasury,” says Ole Matthiessen, Global Head of Cash Management, Deutsche Bank.
Reviewing the findings in the report ‘A Quantum Leap: Building a data-driven treasury’, he adds: “It has taken some time for risk-averse treasurers to accept the security and robustness of cloud-based solutions, but we are now witnessing a change in mindset.”
Blue sky thinking?
A TMS in the cloud offers a number of benefits for a data-driven treasury. Automatic updates enable treasurers to access the latest analytical tools, whilst also making it easier to connect with subsidiaries and external business partners. Because treasurers can give stakeholders access to relevant parts of the system to add information directly, it eliminates the need for data collection and input by treasury. With fewer people handling the same data, it is likely to reduce data errors too.
Another benefit of having a TMS in the cloud is that any data analytics software can feed cash data directly from treasury systems into forecasting models. This is especially efficient when it comes to setting up macros on basic spreadsheets. Takachida Kuhudzai, EMEA Treasury Manager, Kimberly Clarke, agrees: “With cloud-based solutions, we are now spending less time trying to consolidate the data and more time analysing it and questioning the assumptions.”
More importantly, it gives treasurers a wider, more dynamic view of the financial position of the business. “You are now able to see the data in new ways,” says Kuhudzai. This ultimately supports better strategic decision-making behind investments and operations.
On the other end of the spectrum, big data analytics and the processing power of AI are especially exciting for the treasury function. According to the report, working capital management tops the list (25%), followed by inventory management (23%) and operational risk (21%). However, there remain some big challenges in becoming more data-driven.
Challenges and benefits
Firstly, integrating external and internal data sets is technically complex, not to mention expensive. There is also the problem of the customisation and scalability of external and internal data. Secondly, there is often a lack of knowledge or people to analyse these data sets, a lack of availability of relevant data sets, and a lack of knowledge of the availability of data sets.
Despite these challenges, treasury is not put off. It understands the many benefits that being data-driven can bring. The report found that the top driver for becoming more data driven was improved operational efficiency (39%), followed by improved returns on investments/assets (36%) and improved management of risk (27%).
Establishing a data strategy is therefore a crucial first step in reaching the end goal. “Simply ‘owning’ data is not enough; digital transformation is required in order to extract, aggregate, and analyse good quality data. The journey towards an efficient data-driven treasury takes time,” says Matthiessen.
It seems that in order to build a fully data-driven treasury, corporates need to identify how far along in the process they are, and what steps need to be taken next to progress. At the same time, treasurers must be prepared to act on real-time information and speed up decision-making, not to mention gaining new skills to sustain a company’s growth.
The role of the corporate treasurer is constantly evolving. As the move to become more data-driven enables faster and smarter decisions, the possibilities for fully data-driven treasuries are endless.