If the whole organisation understands the importance of cash, it becomes easier to harvest more diverse, accurate and timely data. From here, better forecasting can drive stronger working capital performance. It’s what most stakeholders expect, so how can it be delivered?
Cash is King, maybe; it’s hard to tell as the power that this particular monarch carries has not always been appreciated. However, since the global economy tanked and then started on its long road to recovery, the value of understanding cash basics – such as how much, where and in which currencies – has been rising higher up the agenda.
An accurate picture of current and future cash needs is only possible if every function that affects the ebb and flow of cash understands its importance. Indeed, every touchpoint needs to be able to report its cash position to treasury, with equal accuracy and timeliness, if an enterprise-wide viewpoint is to be achieved.
However, rallying the troops has not always been easy. The list of key protagonists required to achieve this in an industrial context, for example, includes departments as diverse as sales, procurement, finance, production and logistics; each will harbour their own private drivers and agendas.
Regardless of how many functions commune with the King, the importance of building a sustainable cash culture cannot be overstated. It is the driver of accurate forecasting, which is used primarily as a tool to help improve accuracy in investment and borrowing decision-making by identifying in advance potential surplus cash or gaps in cash flow.
Producing today’s cash position is relatively easy compared to accurate forecasting weeks or months ahead. The further out treasury goes, the harder it becomes to offer anything beyond an educated guess. Nonetheless, the ability to deliver accurate cash predictions can be the difference between running out of money and not running out of money, says Tim Bartlett, Senior Liquidity Commercialisation Manager, HSBC. Indeed, he comments, no matter how much a company is valued on paper, without accurate cash flow forecasting, running out of day-to-day cash is a potentially fatal risk.
There is no one correct method of creating a forecast; it depends upon factors such as the nature of the business or sector, the type of forecast sought, its purpose and format. This may sound somewhat unscientific, but with so many unknowns with which to contend, not least macro-economic ‘events’, forecasting is very difficult to optimise, notes Bartlett.
Of course, there will be some regular and predictable incomings and outgoings which make forecasting a little easier: predictability is the friend of the forecaster. Nonetheless, delivering detailed forecast data with a high degree of accuracy remains a challenge.
Actuals are used to validate forecasts, giving the opportunity to adjust and improve the margins of error in light of any variances identified (and any targets set through KPIs). These validations may be made daily, weekly, monthly or on a longer timescale, according to appetite and ability to monitor, extract, analyse and respond to the data. The more frequently a forecast is updated with real numbers, the more accurate it will be but there comes a point where the effort outstrips the return.
There are many different forecasting methodologies – the distribution method, regression analysis, and time series trends and seasonal variances, for example – most relying on analysis of historic cash flow data. Because there is no guarantee that patterns identified using historical data will reoccur, these techniques will generate a forecast probability which is commonly weighting, in the form of an accepted margin of error. As the actuals are made available, the degree of ‘wrongness’ can be fine-tuned with each set of actuals.
The use of technology can take some of the hard work out of this process. Off-the-shelf solutions, from third-party providers such as Kyriba, CashAnalytics and FiREapps use analytical algorithms written with the benefit of the wider industry experience of each vendor. These can offer complex mathematical responses to common scenarios which will be tuneable to more closely represent a company’s individual circumstances and strategic approach.
Indeed, such systems can improve forecasting accuracy, for example, by incorporating a computer-based understanding of the behaviours of clients in terms of incoming revenues, and the expectations of suppliers in terms of outgoings.
Of course, many businesses use spreadsheet calculations, adding their own margins of error and iterating each set of results to reach the next waypoint. With output from bank reporting tools having become more sophisticated in recent times there is no suggestion that companies cannot produce sufficiently accurate forecasts using their own tools.
However, the nature of forecasting is such that there is always room to increase accuracy, driving stronger working capital performance.
The cutting edge
One area in which advancement is being made is in the adoption of pre-cognitive technology that borders on the realms of artificial intelligence. This is widely used in fraud detection, enabling the recognition of complex patterns of flow and the predictability of certain activities. This, argues, Bartlett, is the kind of solution from which forecasting can and will benefit.
The encouragement of open banking (largely through regulatory measures such as PSD2 in Europe), where institutions share data flows through API-led connectivity could also bring a more easily aggregated view of flows across a multi-banking environment.
Regardless of technological advances applied to any aspect of treasury or finance, Bartlett comments that “these are only ever tools, and tools by definition are something people use to help get the job done”. Of course, the treasurer must know how to use these tools but Bartlett notes a fine line between using them simply as a means of looking for or proving a preconceived notion, and accepting what these tools deliver as the absolute truth.
Is there appetite for change? Achieving 100% accuracy every time is an unrealistic goal. However, although some businesses do let cash flow drift to the point of becoming technically insolvent, many do not. This suggests that today’s forecasting measures are, by and large, adequate.
But with many treasuries having become P&L centres in their own right in recent years, Bartlett argues that there may be expectations of increased return overall for the company, itself demanding higher expectations of forecasting precision.
“Cash generation is the clearest measure of success for an enterprise and this is why we have decided to place such an emphasis on working capital.”
Todd McElhatton, CFO, SAP North America
We know specialist software can bring about a greater degree of accuracy and this may in turn bring about greater working capital efficiencies. But it is clear that to achieve sustainably positive results, not only is the treasurer’s input vital but also cash has to be given a commanding position by all parts of the business.
Spread the word
There is an essential “anecdotal” component that must be applied to sharpen the cold logic of technology. Treasurers must have a real feel for, and understanding of, their own business, customers and suppliers. The human element is in part based on the treasurer’s own experience and professionalism but this can be enhanced when allied to a strong communicative approach to the role.
This is where the enterprise-wide promotion and support of a corporate cash culture plays out. Indeed, the ability to reach out to other functions – such as sales, procurement and production – and to incorporate their accurate, function-specific data into the forecast in a timely manner, will deliver the greatest level of forecasting accuracy. For treasurers and other stakeholders such as the board, the investors and the analyst community, this is highly beneficial.
The practical power of cash
One company that has spotted the power of putting cash front and centre of every part of the business, is global tech giant, SAP. “Cash generation is the clearest measure of success for an enterprise and this is why we have decided to place such an emphasis on working capital,” says Todd McElhatton, CFO at SAP North America.
Developing a culture of cash across an organisation as vast as SAP has been a challenge, with some fundamental changes required at an operational level. One of the keystones of project success has been the incentivisation of employees to see cash in this new light, shifting KPIs to reflect first-class working capital management principles and practices.
By developing a creative new set of KPIs for SAP’s sales team, for example, it was able to evolve that function into an effective cash collection team. In the spirit of the old adage that ‘it’s not sold until its paid for’, the sales reps now receive their commission payment for a sale once payment has been received from the customer, explains McElhatton. “Through linking cash collection and commission in this way, our sales reps are now engaged with finance to understand who has and hasn’t paid and chasing up any late payments.”
It was readily acknowledged that such a fundamental change to the day-to-day working practices of the sales team had potential to create resentment; without their buy-in, and that of other teams, the project to drive working capital performance would never work.
For SAP, the natural solution was to leverage technology. “At the same time that we have focused on working capital management, we have also focused on building a world-class finance department to support these efforts,” he explains. Core to this has been the adoption of new technology that has created efficiencies and provided enhanced visibility and analytics, allowing the company to better align the goals of the different departments within the business.
In one practical example, this has seen cash collections benefit from machine learning and AI technology. The approach, says McElhatton, has allowed the finance and sales teams to collaborate closely, focusing only on problematical non-payments. Where finance has a real-time and historical overview of customer payments performance, it can better understand the nature of non-payment, working with the sales team who can reach out to customers only where necessary to begin resolving the issues.
Through the clever application of technology and the adoption of considerate change management techniques, SAP has been able to progressively transform its cash culture across the whole organisation. It has delivered on its initial working capital improvement objectives but will remain focused for some time, says McElhatton who adds that real-time information provides many more opportunities for improving working capital performance.
Taking off with automation
Another example of where an analytical approach has yielded results is with India’s low-fare airline, IndiGo. As the Overall Winner of the 2017 Adam Smith Awards Asia Best Cash Flow Forecasting Solution, the company demonstrated how automation of its entire cash forecasting mechanism could offer a huge payback on several levels.
Not least of the benefits has been the realisation that it can bolster its institutional placement funding with its own optimised cash reserves to purchase rather than lease most of its planes as a more cost-effective option.
IndiGo is one of the largest airlines in India with almost 40% market share. With over 20 banking relationships and more than 40 accounts, its treasury team was having to tackle numerous cash management challenges on a daily basis.
Lacking full visibility into many of its accounts, it was troubled by a liquidity management model that it felt was fraught with manual administrative exercises. The lack of visibility also meant it was susceptible to various financial and operational risks.
Shveta Kapur, Associate Director, Treasury, Finance, recalls that its treasury model “lacked much needed scalability”. It was realised that existing processes needed “an immediate re-engineering” to manage treasury operations more effectively. In partnership with its principal bank, IndiGo carried out an end-to-end review of its liquidity management processes. This set it on a path towards a number of core objectives.
To give it accurate cash positioning and risk mitigation, it wanted real-time and actionable visibility on all its cash positions and flows. From here, automated rules-based movements could facilitate “easy cash mobilisation”, providing centralised access and control. As a third goal, treasury wanted to apply automation to its daily investment programme. This, it was felt, would enable IndiGo to put a major portion of its significant (and growing) daily collections immediately to work, enabling it to earn better interest.
The key to success was a multi-bank cash pooling platform. By automating its entire cash forecasting mechanism, Kapur says the solution was able to eliminate all manual intervention in the IndiGo’s liquidity analysis and interbank fund management.
The project also enabled it to reduce manpower and improve productivity, affording it annual savings of around 2,000 man-hours. In creating a single consolidated view, process automation also introduced enhanced analytics and the kind of cash forecasting accuracy and liquidity yield that treasurers often strive for.