Total Number of Subscribers: 1626
Date:08^th July 2010	Compiled by: M Sathya Kumar
Common Mistakes in Cash Forecasting and How to Avoid Them Cash forecasting is essentially the process of collecting information on balances and future cash flows from business units and being able to consolidate them instantly. Why is it so difficult and is there a simple, pragmatic approach to make it easier? I graduated from university as a nuclear physicist (engineering), but almost five years ago some lucky incidents resulted in me working with corporate treasury processes, particularly cash forecasting. Having followed expert articles, treasury survey results and the enormous focus in liquidity and risk management conferences, it is evident that cash forecasting is a constant hit song, almost an evergreen, on the top of corporate treasury development priorities list. Then why haven’t they fixed it already? Cash forecasting is not nuclear physics, and by this I mean that it is not regulated by the natural laws of quantum mechanics, but our everyday actions and choices. Having come into the world of treasury processes from the outside and with little theoretical background, I feel privileged to be able to approach cash forecasting in a simple, pragmatic way. The First Steps Define Whether You Win or Lose Then why is it that cash forecasting initiatives tend to turn into such complex and scary engagements? Is it because solution vendors do not know how to develop easy and efficient solutions for cash forecasting? Or do they not want to? A major systems project is worth a lot more consultancy revenue than a light, shrink-wrapped tool. This can be part of the explanation, but in most cases the corporate treasury should look in the mirror - they forget the golden rule of ‘keep it simple, stupid’. Here are some examples of how that happens: · Cash forecasting is viewed as an inseparable part of the concept of liquidity management. · Cash forecasting is mistaken for a mandatory systems project. · Cash forecasting is seen as a treasury task and the development effort is confined within the limits of the treasury department. Not being able to separate cash forecasting from liquidity management sets the wrong mindset from the outset. Cash forecasting is essentially the process of collecting information on balances and future cash flows from the business units and being able to consolidate them instantly. Liquidity management is more typically a process that takes place between the treasury department and the bank - quite different. Tying the knot too tight also means that forecasting tool development is tied to the other systems or process initiatives in liquidity management. Pushing cash forecasting behind developing the pooling structures, or installing an upgrade to the liquidity management system, will continue to set you back year after year after year. Taking it as a systems project often results in a stubborn determination to implement a perfect match to the current way of working, i.e. creating a highly customised system environment instead of implementing best practice tools. This approach can lead to years of an infernal project treadmill, where the biggest winners are IT and business consultants. In the worst case, not even all that time and money will buy you a functioning solution. Why turn such a simple task into a nightmare? Sadly, in some cases it looks like people may be driven to madness by their egos, which would rather do something big than something small. Another similar mistake is to aim too high - to set the objective to a super-compatible, fully automated and integrated solution. Being a fancy goal, it is not easily justified from the economical perspective. There is no such thing as a fully-integrated solution - such integrations have to be built, and they have to be maintained through the lifecycles of the respective systems. The fourth original sin in cash forecasting initiatives is to limit the scope inside the treasury department. It is forgotten that the quality of the forecast is ultimately a result of the reliability and timeliness of the reports from the business, i.e. the subsidiaries. Therefore, the scope of the initiative shall cover the organisation-wide motivation to improving the forecast information. Avoiding the Pitfalls Just like any project, cash forecasting is easy to screw up. But luckily cash forecasting is by its very nature not a complex process, so getting it right is possible for anyone who follows these rules: · Get on with it already. · Focus on the essentials. · Improve step-by-step. · Step into the shoes of the subsidiary. Stop making excuses for why cash forecasting could not be fixed today. Starting with a systems evaluation is the wrong way: start by understanding what cash forecasting is all about and what is essential in it for you. Cash forecasting is all about collecting reliable information about how your liquidity will change in the near (and mid-term) future. A step-by-step approach may mean that you should start off with a simple Excel reporting template, in order to figure out things like: · What are the sources of the information you need? · Who is a required contributor? · How much complexity do you need or can achieve in the reporting structure? · What is the volatility of your cash flows? · How intense the reporting cycle needs to be in order to achieve reliability? Once your overall understanding of your capabilities and requirements develops and the subsidiaries are used to the idea of forecasting, you will be in a position to implement a more automated, tools-based process. Is it Worth it? At best, cash forecasting can be a return on investment (ROI) star project; little investment will normally provide significant savings with an almost immediate effect. Having continuous visibility into the global cash balances and at least the most significant forecasted events is not too much to ask, is it? Every organisation has their own reasons to prioritise cash forecasting but it will be to hard find one without any: · Cost of cash: how much can you save by putting all your idle cash into use? · Cost of banking: how much could you save in credit and transaction cost by rationalising fund transfers? · Cost of human resources: can you afford to let your employees struggle with reactive work instead of performing optimised and proactive tasks? · Foreign exchange (FX) and risk management: is there room for improvement in the centralisation of your FX position management? · Process audits: how much do you spend on ad hoc reporting and does your corporate governance satisfy the auditors? · Balance sheet: do you think your current idle cash could be invested towards improving the balance sheet? · Waste: if your business units have an abundance of cash and you think that means you do not need to forecast, think again. Do your owners really want you to be sloppy with their money instead of maximising returns? Summary We live and operate in a complicated world. However, sometimes it is worth taking the simplest approach - just because you (still) have a problem does not mean you need a million euros and two thousand consultancy hours to solve it. Forecasting liquidity is a serious objective but the solution may be lighter than you think. A step-by-step approach is an excellent development method and, what’s best, it gives you results from day one. Article by Sanna Outa is chief operating officer (COO) at Exidio where she manages all aspects of the operational business including product and sales operations. Since 2005, she has also been driving Exidio's co-operation with three major global banks, pioneers in providing B2T solutions to their corporate customers. She has worked closely with the banks' major corporate account teams in training them on how to structure the value proposition in B2T, and how to understand the related priorities for corporations. Prior to Exidio, Outa was a member of the executive management team at SmartTrust, a Swedish provider of platform solutions to nearly 200 mobile networks globally. She holds a Master of Science degree in Engineering Physics from the Helsinki University of Technology (1998).
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