Cash & Liquidity Management

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Value Chain Liquidity Forecasting - Deeper Insights Faster It is more vital than ever for corporations to identify internal financing capabilities and to have a clear view on their future liquidity development. Both are necessary to survive volatile economic cycles and to ensure sufficient funding to keep operations running.

Value Chain Liquidity Forecasting - Deeper Insights Faster

by Thomas Schräder, Partner, and Thomas Hampel, Senior Manager, PwC - Corporate Treasury Solutions

Attempting to forecast their future liquidity, global corporations are increasingly challenged. Highly volatile markets, macroeconomic ambiguity and political risk in target markets are factors that boost uncertainty. In such an environment, expected revenues are likely to fail to materialise and banks as well as capital markets provide external funding only reluctantly and at high costs. Because of this, it is more vital than ever for corporations to identify internal financing capabilities and to have a clear view on their future liquidity development. Both are necessary to survive volatile economic cycles and to ensure sufficient funding to keep operations running.

One major prerequisite for coping with these requirements is the establishment of a robust, comprehensive and reliable liquidity forecasting and reporting process. The immediate availability of validated information and transparency as to its origins are critical success factors. At the same time, flexibility in assessing, consolidating and presenting the information needs to be granted.

However, the growing complexity of business processes imposes two major challenges:

1. Implementing consistent and comprehensive horizontal data integration covering all relevant systems and business units involved in the process

2. Implementing vertical data integration which combines operations’ transactional data and further decision-relevant information

The traditional forecasting approaches (i.e., direct and indirect cash flow forecasting) applied by corporates are not always capable of fulfilling those requirements.

Indirect cash flow forecasting is based on forecast balance sheets and income statements. As they are usually the result of the yearly budgeting process, the time horizon is often limited to the financial year end. Moreover, the budgeting itself is usually focused on goals such as resource allocation and target setting. Cash flows are often calculated on the basis of historical figures, scaled to a certain extent to adapt to future expectations. Since indirect cash flow forecasts are also often closely aligned to the overall target as defined by the companies’ top management, they may be less useful for the operational management of liquidity. Their potentially political nature and the fact that they are not purely based on forward looking facts may harm the general applicability for decision-making within treasury organisations.

On the other hand there are - within treasury organisations - widely used direct cash flow forecasting methods. They emphasise the direct determination of cash flows and are purely value date focused. Depending on the industry and business model of a company, a large amount of forecasting data for the short- to mid-term horizon may be directly obtained from corporates’ ERP or treasury systems. For instance, receivable or payable transactions already accounted for in the ERP usually provide sufficient information to consider them directly in the cash forecast. As long as there is at least information on the over-all amount and the future maturity date, one can use that directly for forecasting purposes.

However, future-ranging cash data from an ERPs receivable / payable ledger, forward order book or modules related to financial or investing transactions is not usually available long-term. Instead cash flows for the long-term horizon are often estimated simply based on the scaling of historical data or rough approximations of certain individuals. Next to those content deficiencies there are often challenges associated to the underlying forecasting process and a lack of appropriate IT support. Many forecasting processes are supported solely by the use of spreadsheet programmes such as Microsoft Excel. The strong reliance on Excel often makes the whole process very time-consuming, inefficient and error prone. Usually people spend more time managing the complex spreadsheets than actually analysing the data. As a result, internal and external reporting requirements are only insufficiently adhered to. Confidence in the resulting planned liquidity can be low, which makes it less useful for management decisions.

A new approach

To address the issues inherent in traditional forecasting approaches, PwC Corporate Treasury Solutions together with a leading German automotive manufacturer has developed a new approach called Value Chain Liquidity Forecasting. This establishes maximum transparency on the origin of forecasted cash flows and takes planning accuracy to a new level. Considering relevant information from every major department and division of the company, the approach explores all cash generating mechanisms within the value chain. In doing so, all parameters determining both extent and occurrence of cash flows are uncovered. In the end full transparency on future cash flows and their origins is established, which is of significant benefit particularly when considering the ever increasing complexity of business processes and operations.

More specifically, the value chain-driven approach enhances the direct cash flow forecasting method. It can significantly increase data quality, forecasting accuracy and transparency over the full forecasting horizon by automatically integrating data from a large variety of pre-systems, and it is not restricted just to finance or accounting systems like ERPs. Pre-systems which allow for an analytical construction of cash flows are often operational systems; for instance systems which control production processes, storage and logistics, sales and distribution, materials management, investment projects or R&D expenses. Obviously, information from all of these systems have to be processed in order to provide the desired cash flow information. To make this happen, the complete value chain of the given company gets simulated, using specific calculation logic based on the particular data input.

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