Cash & Liquidity ManagementCash ManagementWhy data-driven cash forecasting is the future

Why data-driven cash forecasting is the future

Conor Deegan, co-founder and CEO of CashAnalytics, and Francois Masquelier, vice-chairman of EACT and founder of Simply Treasury, explain why data-driven cash flow forecasting is the future and the short term steps companies can take to leverage the data they already have at their disposal.

The pandemic sorely exposed the lack of resilient, speedy cash flow forecasting operations across many organisations. With a host of new challenges, including inflation and tapering evolving rapidly, and an eye on future crises, many firms are turning to data-driven solutions for managing their financial resources.

Surveys carried out during the pandemic highlight the benefits derived by firms that leverage data more fully. In fact, a YouGov poll of 3,500 European firms last November found 80 percent claiming that leveraging data gave them a critical operating advantage. .

Elsewhere, a study of 130 treasurers by JP Morgan last August found the pandemic had “accelerated their journey to data-driven operations” as they looked to manage new risks to business models and supply chains. Meanwhile, a survey of 340 treasurers of multinationals by the European Association of Corporate Treasurers (EACT) earlier this year found cash flow forecasting to be their biggest priority (63 percent), followed by digitalisation of treasury (43 percent) – well ahead of risks such as FX, interest rates and Libor (33 percent).

Data-driven paybacks

Conor Deegan, co-founder and chief executive of CashAnalytics, says that as well as more accurate and timely cash flow forecasting, making data work much harder   delivers a host of other tangible paybacks including greater transparency; faster decision-making; better use of working capital and smarter insights into customer behaviour.

All of these benefits and more are made possible by the superior understanding of the business gained from leveraging data, he says.

“That deeper understanding of operations and how they interact with each other is a fundamental property of data-driven approaches, it’s their most important and valuable overarching benefit. You’ll have transparency over what is driving cash flow across the business for example; see clearly how your customers are behaving in any given environment; review payments to suppliers more quickly; and instantly analyse each business unit with recourse to base level data.”

To gain such valuable insights, however, it is critical for firms, especially newcomers, to have in mind some key features of the information data-driven solutions generate and its subsequent treatment. The most crucial, says Deegan, is the need to focus much more on understanding the resulting forecasts than their accuracy. This may seem odd considering the forensic financial drilling data-driven techniques enable but Deegan explains the apparent contradiction.

“Everybody is obsessed with accuracy but it’s fiendishly difficult to get a cash forecast 100 percent correct. If it is 100 percent correct, then it’s most likely just an accident,” he says. “The key thing a forecast should provide is understanding of the opportunities and risks ahead. The forecast will paint a picture, most likely a directional one, so step back, analyse and focus much more on the key drivers of that movement within the business. The intelligence you gain from that will then inform your actions and strategy.

“If you’re presenting a cash flow forecast as gospel to your CEO and it’s wildly wrong every week, you won’t have any credibility. So, accuracy is important, but it really needs to be framed around the expectation that the forecast will give you a better analysis and understanding of what’s going to happen in the business. Everybody needs to be on-board with that way of approaching it.”

The second most important tangible benefit of leveraging data is efficiency savings.

“Becoming a data-driven organisation doesn’t just lead to greater efficiency at a treasury level, it means the entire business become more efficient with routine, repetitive tasks taken off the table, allowing more time for analysis and strategy,” says Deegan.

“It also means much more interaction between business units, changes the dynamic of their relationships across the organisation so they are more focused on understanding each other’s concerns and the most important things that relate to cash flow, customer behaviour and supplier payment as opposed to folks chasing data, missing deadlines, letting queries go unanswered – all the kind of drags manual processes generate.”

Deegan stresses, however, that while adopting a data-driven approach to managing financial resources is much more efficient than one heavily reliant on human input, that doesn’t mean it is a 100 percent automated system – it will still require human input. What it does mean, though, is that the majority of the work is already done by the data, resulting in some powerful benefits.

“If, as a treasury or finance team, you’re spending two to three days a week forecasting, you’ll take all those hours of work down to minutes. You can deliver a forecast to the CFO, and you might get 10 questions in return. You could spend a week trying to answer those questions manually.  Using a data-driven approach the majority of the answers will be at your fingertips, leaving you to focus more on adding value.

“To put it simply, it’s a question of whether within your organisation you want to be a data administrator or a data analyst. I’d argue it’s the latter position people really want to get to, a place where they’re contributing to the broader conversation – it’s much more rewarding and empowering for them. Making much better use of the data available with the help of technology will deliver that.”

Adding value

By leveraging data fully firms can also look forward to bread and butter treasury operations becoming key targets for adding value, notably through enabling more efficient day-to-day cash management, mid-term cash and liquidity planning, and more effective risk management in areas such as FX and rates.

“It’s in such high value activities that firms can expect to see the most distinct, solid benefits from adopting data-driven approaches,” says Deegan.

François Masquelier, vice-chairman of EACT and founder of Simply Treasury, a treasury and enterprise risk management (ERM) consultant, echoes Deegan in underlining the impact more effective use of data can have on fundamental treasury operations.

“Cash flow forecasting is a classic risk but what we experienced with it during the pandemic was really zero certainty generated by problems such as long delays in deliveries, defaulting of counterparties, and huge levels of FX volatility. Those kinds of issues make it very difficult to predict cash flow forecast but what makes it even more impossible to react sensibly is lack of accurate information being at hand.

“Taking days to collate data, then spending hours crunching figures on Excel spreadsheets, by which time you are already out of date, will not cut it.  At the same time companies must bear in the mind the competition – can you move faster than your peers? Crises can be very unforgiving and the existential threat alone they pose should make companies more determined to leverage all the data they are sitting on.”

Masquelier adds: “As treasurers we know we are sitting on a huge amount of financial data but we forget from time to time that it is not being used effectively. Covid has helped to shine a brighter light on that shortcoming. In a crisis situation – and there will be others in the future – CEOs want information much faster. When we talk of real-time treasury or treasury-on-demand what we are talking about is being able to respond to that faster level of enquiry, produce standard reports as well as new types of information that is useful in dealing with unusual or extreme situations.”

Road to success

So how can firms successfully adopt data-driven approaches to managing their financial resources? For Masquelier, rapid exchange and communication of data across the organisation, ensuring it smoothly traverses units, divisions, departments and affiliates is key.

“Speed is critical so breaching and breaking down barriers to data transfer between these potential silos is essential. Automation of routine tasks is crucial to support that. A day or two delay can make all the difference between, for example, an FX transaction generating a profit or loss.”

He adds: “Siloed data really penalises companies and often reflects inadequate investment in IT systems integration. It is essential to open up silos for successful data-driven operations and that is a company-wide responsibility. Treasuries should not have to work alone on, for instance, generating accurate cash flow forecasts. Like working capital, these are cross-department projects.”

Deegan too highlights the importance of cross departmental collaboration, noting that often treasury teams will need to work closely with IT colleagues when starting out on implementing a data-driven solution for cash flow forecasting. In practice they will initially need to focus on putting in place some essential building blocks, notably finding out where data is within their organisation and the systems responsible for holding it. The task then will be to figure out how that data can be secured and transformed for use by the chosen data-driven solution on an ongoing, sustainable basis.

“The process of implanting a solution is like peeling back the layers of an onion,” says Deegan. “Once you know where the data is, where it is held, what it looks like, and you have identified the person that can get it for you on an ongoing basis, you are on your way. That is all great new knowledge for you to have in your hands and it will only empower you to push on further with your data-driven journey.

“As collaborative and connected businesses are internally, the mere fact they have divisions, units, and so on necessarily implies people are working in some form of silo, doing their own thing on some levels, including ones that can be relevant if not critical to establishing a successful data-driven solution. Suddenly they are being asked to work towards something – the data-driven solution – that will sit outside of all that compartmentalisation and while that might feel a little daunting to some, that dissipates quickly with progress.”

He adds: “Implementing a data-driven solution, especially in large companies, is no trivial matter. However, when it is planned properly it’s a lot more straightforward than people think. It just needs a little determination and commitment, especially in those very early stages. So figure out where the data is, what it looks like, and who can get it for you in a single instance. Then we can start a serious conversation.”

Flexible solutions

Even the best quality data and solution to exploit it all, however, can struggle under the weight of crises such as the pandemic and the 2008 financial crisis. Building flexibility into their design from the outset is therefore critical, says Deegan, as it allows for highly unusual or outright black swan events to be catered for.

“If you’re running a data-driven model that’s one hundred percent trend-driven something like Covid is going to blow it out of the water,” he says.

“If there’s no ability within that model to intervene manually and update and apply new assumptions and latest data sets, or do that easily, that model is not going to provide very much value in the long term.”

The pandemic has undoubtedly led to a surge in interest in data-driven forecasting and new challenges – ranging from growing uncertainty over inflation; potential for US tapering near future; Libor transition; accelerating changes in customer behaviour; through to the ongoing shakeout of supply chains – all of which further highlight the vital role it can play in ensuring corporate resilience.

“Integrating data-driven technology and techniques is often hailed as the utopia for companies – they all want to, need to, get there some day.” adds Deegan. “Entire industries have been built on the back of data. The likes of Amazon, Google, and Facebook are at the forefront of that revolution. Most businesses are nowhere near them in the skill they have with data gathering, management and analysis, or the scale at which it’s carried out.

“However, more and more organisations are moving to make better use of their data and as they do so people will become a lot more comfortable with dealing with data sources, managing and manipulating data, employing it much more usefully. It will become second nature. You can’t arrive in a meeting at Amazon without data backing you up. That is what all organisations are looking at over the long-term. As the saying goes, ‘In God we trust. Everybody else, bring data.’”


Kam Patel is a freelance financial journalist. He contributes regularly at CashAnalytics, a provider of cash flow management software for growth-focused businesses.

CashAnalytics gives CFOs, treasurers and controllers clear visibility over current and future cash and liquidity requirements.

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