How to Improve Cash Flow Forecasts From Subsidiaries
In a recent gtnews cash management survey, #gtnFeature(195)#, more than 50% of respondents identified cash flow forecasting as the process in most need of improvement.
Most organisations attempt to forecast their cash flow, but often face a multitude of issues when doing so. The gtnews survey identified the following top issues in relation to this:
The use of flexible cash flow forecasting tools in combination with appropriate policies and processes can allow cash managers to address these issues. The use of flexible cash flow forecasting tools makes it possible to address most of these issues and receive more accurate information from subsidiaries, enhance inter-departmental communication and improve the financial performance of the group.
Excel spreadsheets are still the main method for collecting cash flow forecasts. They often involve manual processes such as the emailing of spreadsheets and the use of macros to consolidate a multitude of spreadsheets to create a group-wide cash flow forecast. Even though Excel initially seems to be a very flexible tool, in reality it offers little room for customisation and adoption to the various business unit characteristics.
In a further demonstration of its limitations, Excel does not allow for an audit trail and therefore makes it more difficult to ensure good corporate governance. This presents a serious problem when considering the Sarbanes-Oxley Act (SOX). Moreover, if the forecasts are used as the basis for FX hedging, it creates more problems when showing the necessary documentation to the underlying exposure.
Turning our attention away from Excel, cash flow forecasting is not the only problem the cash manager faces. As the survey revealed, most of the biggest issues were in relation to organisational matters, as opposed to technical ones.
In order to produce an accurate cash flow forecast, the cash manager has to rely on local subsidiary or business unit employees, who can be both physically and structurally remote from central operations. This may result in challenges in terms of convincing these employees to provide data for cash flow forecasts, especially if they don’t see an obvious benefit from it. In such circumstances, the cash manager often simply doesn’t have the authority to demand the data.
As a result, they need to rely on other means for improving cash flow forecasting, such as technical tools and motivation.
A wide range of software offerings are available to assist cash managers with the compilation and consolidation of data, and adding the actual cash flows when they materialise. These tools typically use a centralised database with the possibility to enter or upload data remotely.
Such technology should enable firms to refine the forecast, while also detailing how a forecast has evolved over time. Additionally, they should be capable of comparing different versions of the same forecast.
Cash managers must also be able to use the technology to reconcile actual cash flows with the forecasts. This can then be used to control the delivered data in order to learn from previous analysis so that future forecasts can be improved.
Generating reports should be quick, easy and efficient on both a business unit and an aggregated level. Producing comparison reports between different forecasts from different times as well as between a forecast and actual cash flows should also be a straightforward process.
Tools for use by the subsidiaries must also be easy to roll out. Ideally there should be no need for these to be installed on local PCs. Instead, they will either be web-based, or will use automatically downloadable Java applets or something similar.
Finally, the chosen technology must be able to support workflow, which will help to ensure that all subsidiaries have submitted their forecasts in time. Local workflow needs to take place at the subsidiary level, so that the forecasts are not just entered but also approved by a second and potentially more senior person. After this authorisation, they can then be submitted to the head office to attain the highest level of forecast quality.
It is vital that the software used can accept input in a variety of ways, either manually or electronically, such as the ability to upload Excel files or flat files. Even though a simple upload from another source is preferable, manual work cannot be completely avoided, especially in the process of reconciling the actual cash flows back to the forecasted cash flows.
Naturally, software should be easy and intuitive to use but, more importantly, it must be flexible enough to adjust to the individual business unit’s characteristics. This will help to avoid a situation whereby the cash manager is forced to try and implement a ‘one size fits all’ approach.
It can be tempting to adopt a cash flow forecasting model centrally that fits the requirements of cash manager. However, this will increase training requirements if the local subsidiaries are to understand and use this model. If the cash manager instead tries to adapt to each subsidiary’s business and its characteristics, it can have several positive effects. Principally, users will better understand the model and be more motivated to provide the correct data. In addition, taking this approach should decrease the error rate as well as improve the quality of the forecast and reconciliation to actual cash flows.
A cash forecasting tool that can accommodate several local models will also provide advantages if and when acquisitions are made. The acquired firm may already have its own cash flow forecasting processes in place, so by being able to load the existing format used by the acquiring company, the time taken for it to participate in company-wide cash flow forecasting can be reduced.
The adaptation to the local subsidiaries may mean more work for the cash manager in the initial stages, but this extra effort should pay off by improving the quality of data delivered.
The aggregation of data should take place within the cash flow forecasting tool. It is much easier to do it there than to ask local subsidiaries to convert their data to fit the cash flow forecasting template. By using the tool itself, the cash manager is in control of the data aggregation and its conversion into the desired format.
Not only should this improve the quality of the data received, but it will also reduce the burden on the subsidiaries by making it easier for them to deliver the data.
As the gtnews survey revealed, some of the most difficult issues are the “lack of effort/priority within the business unit,” and “deficiency of inter-departmental communication.” This highlights how crucial it is to stress the importance of forecasting. Most significantly, it shows that subsidiaries need to be sufficiently motivated to provide accurate information, valuable feedback and return services.
One way of facilitating inter-departmental communication is to offer cash flow forecasting reports for the subsidiary. This way, the results and value of the exercise can be easily identified. Using a centralised cash flow forecasting module will also make it possible for the subsidiaries to optimise their local cash position should they have the autonomy to manage cash locally. The feedback provided should also include variance reports and a score for how close the forecasted cash flows were to the actual cash flows.
Furthermore, by showing how FX exposures in cash flow forecasts have been hedged and presenting the effectiveness of the hedge, the central treasury can provide further information back to the subsidiary and the risk reduction service delivered by the treasury will be more transparent.
One of the best ways to motivate local business units to provide better cash flow forecasts is to ensure that their financial results are dependent on the quality of the forecasts. Firms need to find a way to tie the accuracy of the cash flow forecast back to the business unit results. Incorrect forecasts can lead to higher borrowing costs and lower yield on investments, in addition to flawed hedging decisions. If the business units were to pay extra for the money borrowed from the central treasury due to a poor forecast, they would probably be more motivated to provide a better forecast. This would then highlight the importance of accurate, meaningful forecasting is so important.
The Danish Nobel Prize-winning physicist Niels Bohr once said: “Prediction is very difficult, especially about the future.” This is also true when it comes to cash flow forecasting.
A cash flow forecast will never be 100% correct. Naturally, a certain margin of error has to be accepted. Cash managers must also remember that the primary purpose of a business is to generate revenue through the delivery of products or services, and cash management is a supporting, as opposed to core, function. However this does not mean that cash managers should not try to improve cash flow forecasts. Using the most appropriate tools so that the central treasury can adjust to the characteristics of subsidiaries is vital for a successful operation. And by then giving something back in terms of services and feedback, cash managers can improve the quality of the data delivered and the quality of cash flow forecasts.