Cash & Liquidity ManagementCash ManagementCash ForecastingOnce Bitten… The Cautionary Tale of Cash Forecasting

Once Bitten... The Cautionary Tale of Cash Forecasting

In the past 18 months, the impact of the credit crisis on the corporate environment has been well documented. Not least the impact on liquidity and the lack of available credit that has suddenly left every organisation looking long and hard at its working capital arrangements, putting an erroneous burden on the treasury department to ensure that cash management is as accurate and efficient as possible.

While a recent Parliamentary Treasury Committee report concluded that “the origins of the banking crisis were many and varied” and that “some of the banks have been the principal authors of their own demise,” it also goes onto point out that the culture of risk-taking in British banking, as well as the supervisory system designed to protect the public from systemic risk, were the main factors that brought about this mess.

However, while the current economic situation has greatly highlighted these flaws, it’s worth noting that none of these ‘systemic’ issues are, in fact, new. And the problem, whilst largely being laid at the feet of the banking sector, extends to all organisations where cash management is integral to business success. Indeed, the deficiencies that exist for all organisations in their systems and procedures for managing liquidity risk – namely risk tolerance, monitoring and projecting cash flows, managing daily transactions and ensuring a sufficient ‘cushion’ to withstand stresses, as well as understanding the linkages among different aspects of their businesses and market forces – have been acknowledged for about ten years. And ironically, the appetite to rectify these deficiencies has been lacking, largely due to the fact that credit has been so easy to come by and, until recently, inexpensive, making it all too easy to shore up shortfalls with quick cash advances.

In today’s new world, though, the opportunity cost and the margin cost have changed all of this and created a vastly different business case scenario. Whereas before you might have been relaxed about paying that little bit extra, justifying it as ‘wastage’, nowadays it’s not so much about paying more for the credit, it’s about finding the credit in the first place. So, where organisations had no real need to deal with the issues, now they have no choice. And let’s face it; the ‘do nothing’ strategy just won’t wash anymore. As some have already found out to their peril, if you can’t improve your cash management position, you could be pushing the organisation to the brink of extinction or risk losing worthwhile investments or divestitures that could ultimately have an impact on your market position.

However, having accepted this new raison d’être, many CFOs will find that their cash management systems – whether they be software or a series of technology tools already in situ or ‘out there’ in the marketplace – are no longer viable because they work on pre-determined rules and parametric models, approaches that are now proven to be flawed, post-credit crisis.

Parametric models work by estimating model parameters from historical data under the strong assumption that the form of the model is correct. So, providing the data are of sufficient quality and the model is indeed appropriate for the situation, the organisation will be given a meaningful view of its cash management situation. However, should conditions change such that the model is no longer valid, the indicators generated could be potentially misleading or even damaging to the organisation. Therefore, critical decisions could be taken, based on this information, that impacts the organisation negatively, only to be realised later or when it’s too late.

The credit crisis has, by and large, taken businesses into new territory, such that old parametric cash management models are found to be unreliable, rendering the tools in place to support the cash management function of very limited value. So, cash management reports, which are intended to provide such a critical barometer of an organisation’s health, could be providing, at best, a shallow view of the real picture or, at worse, a completely false picture.

The Non-parametric Approach

To get the real picture, organisations require instead reporting systems that work on a ‘non-assumptive’ basis. These work by taking all the business’ information (that relates to risk), the ‘corporate memory’, if you like, and using this information together with real-time information which is then fed into a non-parametric representation of the ‘real world’ to show the likely future outcomes along different decision paths. The key difference with this model is that it uses extremely powerful constructs for handling time so that the possibilities built into the model provide more factual and more rigorous forecasts. So, instead of them working on ‘what might be’ they work more on ‘what is’ and ‘what will be’ in a real world scenario.

Ultimately, if organisations are to make sense of the vast amounts of data required for accurate cash management, they need also to understand the rules that govern this data, the processes by which it can be analysed and sorted and the rules governing the use or handling of this data, to ensure that what you are analysing is of real ‘value’ to the business.

However, the strategic decisioning skills required to create these models and analyse the data are hard to come by. Not surprisingly, there is demand for what were previously thought of as individual ingredients, but which are now recognised as needing to be combined. The resultant mix is very hard to find in the treasury sector. In addition, there’s a great demand for analytics software to gather meaningful information, particularly from a high volume of unstructured data that is constantly changing.

This analytics-based solution draws on information across the institution – as typically banks and other organisations won’t have this in one place – so it’s not just about front end and the right algorithms but structuring data flows to give the right outputs. And it’s all very well simplifying processes across the board, thinking that this will give you a rea,l true picture. This will only work if the picture is not formed from assumptions.

Non-parametric analytics provides us with a scientific methodology that enables sophisticated cash management. Understandably, faced with the rules of the new credit environment, banks and other organisations are daunted by the prospect of upping the ante in this area. Even if they re-use talented mathematicians in their quant departments, they won’t necessarily have the right blend of skills to meet the changed demand. It could also prove to be too costly at a time when spend is being reduced.

Case Study

To understand how critical we believed this situation to be, it’s worth noting out own response to the credit crisis. Sixteen months ago, at the outset of the crisis, CSC recognised that we had a set of capabilities that, with some adjustments, could make a material benefit to the treasury management capability of our business, over and above that currently available in the marketplace. It was clear to us those traditional forecasting approaches, based on trending data, which was changing by the minute in some cases, was not sufficient to generate a true picture of the organisation’s cash management position. We realised too that the credit crisis was sufficiently severe to seriously challenge our own treasury capabilities. While a lot of traditional analytics capabilities existed in parts of our business, this particular non-parametric approach had evolved throughout a number of our deployments over the past 10 years.

Our new cash management capability has an organic aspect, so that it grows and develops in tune with the organisation. Once embedded, it enables the company to build up algorithms that gather more and more data, based on real behaviours and decisions, giving the company the capacity to forecast and analyse accurately, ensuring that liquidity risk is managed as optimally as possible.

Conclusion

Macro economists continue to paint a very dark picture of what challenges we can expect to face over the next two years because of the continued pressure on credit. However, companies that are moving to better manage their liquidity can expect to survive with less dependency on loans and other forms of credit, lessening their exposure to risk (and reducing their costs) at a time when survival is crucial.

Unfortunately, I wouldn’t be surprised to find some treasury departments who are reviewing this capability, currently looking and hoping for a ‘quick and dirty’ solution to this problem. A word of warning to you though – this is precisely the same route that led you to this point in the first place. By choosing something that will only deliver a short fix for a longer-term problem, will result in a nearsighted view of what is really happening within the business. If the organisation cannot manage its cash, it cannot ensure that it remains competitive, adaptable and informed, leaving the doors open for competitors to steal the march on its market share.

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