About this research

A Quantum Leap: Building a data-driven treasury is an Economist Intelligence Unit report, commissioned by Deutsche Bank. Our analysis explores what it means to be a data-driven treasury, the factors motivating the transition and key considerations when developing a data strategy. The study identifies technologies that treasurers are currently using and those they believe will be most important in enhancing their data intelligence moving forward.

The report is based on a survey of 300 senior corporate treasury executives conducted between May and July 2019. Of these, a third represents companies with an annual revenue of at least US$5bn. Executives were drawn from three regions (North America, AsiaPacific, and Europe, Middle East and Africa) and a broad range of sectors, including aerospace/defence (2.3%); agriculture and agribusiness (4%); automotive (7.6%); chemicals (6.6%); construction and real estate (5.6%); consumer goods (7%); energy and natural resources (7%); entertainment, media and publishing (6.3%); financial services (7.6%); healthcare, pharmaceuticals and biotechnology (7.3%); IT and technology (7%); logistics and distribution (4.7%); manufacturing (8.3%); professional services (1.7%); retailing (5%); telecommunications (7%); and transport, travel and tourism (4.7%).

As part of our research, we conducted a series of in-depth interviews in July and August 2019 with senior treasury executives from around the world. Our thanks are due to the following for their time and insight (listed alphabetically):

• Richard Abigail, group treasurer, Arup
• Rando Bruns, head of group treasury, Merck KGaA
• Charles Cao, treasurer, Ant Financial
• Takachida Kuhudzai, EMEA treasury manager, Kimberly Clark
• Wolfgang Ratheiser, VP finance and treasury, Porsche
• Vishal Verma, executive, cash and treasury services, GE

Executive summary

As digitalisation across businesses advances, vast amounts of data generated in these systems present an opportunity for the treasury function. Harnessing the data can deliver smarter insights and enable faster decision-making. But becoming data-driven doesn’t happen overnight. It is a journey that will take many years, and companies are at different stages of this journey. Along the way, treasurers encounter numerous challenges, from complexity of data integration to a lack of data skills among members of their teams.

So that treasurers can identify how far along they are on this journey, our report looks at three different phases: the past, the present and the future. The first chapter discusses the digitalisation that has taken place in treasury departments and the opportunity treasurers have identified to become more data driven. The second explores priorities when developing a data strategy. The final chapter examines emerging technologies that could enhance treasury’s data intelligence.

Key findings

• Becoming data-driven reinforces the treasurer’s role in driving business efficiency, but also as a profit centre. Treasurers say the primary benefits to becoming more data-driven would be higher operational efficiency (39%) and improved return on investments/assets (36%). Data intelligence can also help treasurers to navigate increasingly complex regulation, such as International Financial Reporting Standards 9 and General Data Protection Regulation.
   
• Treasury functions with a high volume of transactions or those with information spread across subsidiaries will benefit most from a data strategy. The treasury functions most in need of a data strategy are investments (29%), cash flow forecasting (25%), and exposure identification and measurement (24%), respondents believe. Accurate data on payments and receivables (values and due dates) are required to identify cash locked in different parts of the business, which can be directed towards short-term investments.
   
• Four in ten treasurers are very concerned about the quality of the data they are working with. Furthermore, the survey provides evidence that those treasurers who are more involved in compiling data and those who have investigated a data-driven approach in depth are more likely to have grave concerns about quality.
   
• Treasurers seek unstructured data to improve the quality of their analysis. When data are pooled from multiple ERP systems and other sources, it may be standardised for use across different parts of the business. For treasury, such standardisation runs counter to the data-driven approach, as it conceals important nuances in the data.
   
• Technologies that aggregate data and those with advanced processing capabilities will enhance a company’s data intelligence. Respondents indicate that cloud computing will be the most important technology for treasurers over the next five years (44%), followed by big data analytics (42%) and artificial intelligence (37%). Interestingly, robotic process automation—considered popular among finance professionals—was cited by only 9% of respondents: treasurers say it facilitates automation more than data analysis.
   
• The complexity of integrating datasets and the cost of external data are critical roadblocks to becoming a data-driven treasury. As open banking develops, application programming interfaces offer a way to seamlessly link cash information from bank accounts to a company’s cash flow model, enhancing the timeliness and quality of data.
   

For a compelling summary of the key findings of our research, view our animated infographic here.