To obtain a forecast of the cash flow, you must complete the following tasks:
This month, we take a closer look at typical procedures and methods that can be used to help achieve this goal. Data collection Collecting reliable, sufficient and relevant data is paramount for an efficient forecasting process.
This is the foundation upon which major financial decisions will be made further down the line. Consequently, starting with incomplete or incorrect information will have a negative impact on the ultimate effectiveness of the forecast in supporting those decisions.
The data collection process is not performed in isolation. It requires co-operation and support from across the company. The level of information detail to collect will depend on the nature of the business, the type of forecast, its purpose and format.
For longer time horizons, there is usually less detail available or needed, for example: Future acquisition plans by senior management. Long-term quarterly net cash positions.
Medium-term monthly or short-term weekly net cash positions. Treasury cash management decision-making. Daily cash flow detail by bank account and currency. From a treasury perspective, the last forecast is the most crucial as it is used to promote more accurate investment and Qantas cash flow forecasting decisions critical to supporting the day-to-day liquidity of the company.
In this article therefore, we focus on the methods and procedures used primarily for short-term forecasting, although the process for developing long-term forecasts will be similar. Actual bank data At the start of each day, previous day forecasts are reconciled with actual end of previous day cash positions downloaded from either a single or multiple banking systems.
This reconciliation process is vital for protecting the integrity of future forecasts.
Banking systems should be programmed to expect a set number of bank statements per day and therefore, when one does not report for any reason, it should automatically flag the situation as a warning of incomplete data.
Unexpected cash movements, such as early and late receivables or payments, can be identified during the reconciliation process and the forecast positions adjusted to allow for these changes. Expected cash flow data The expected cash flows from all operating, investing and financing activities are extracted from a variety of data sources.
In an organisation with a high degree of single platform technology, much of this data may be available from Treasury Management Systems TMSs and Enterprise Resource Planning ERP systems feeding directly into a cash flow forecasting model.
Alternatively, separate systems may interface with a cash flow forecasting model or the data may need to be taken from PC spreadsheets. The diagram below illustrates example data sources and information flows: Lack of systems integration is a barrier to accurate cash flow forecasting, as we discussed last month.
Ideally, as much data as possible should feed directly into a cash flow forecasting system which may be within the TMS.
Appropriate forecasting methods can be systematically applied to the data and intraday reconciliations between forecast and actual data can be performed automatically.
This gives the latest and most accurate information to treasury with the minimum of effort. Forecasting methodologies Forecasting methods use historic cash flow data in order to estimate future cash flows. The simplest form schedules all the receipts and disbursements expected within a period, with appropriate forecast adjustments being made to each of the cash flow items.
This approach also creates continuity and consistency problems when the individual concerned is absent from work. However, statistical methods can be documented and training given to a number of people so that knowledge of the forecasting process and the techniques used is available at all times.
The following forecasting techniques are commonly used: Distribution method The distribution method involves estimating the cash flows for each item during a period and applying an appropriate portion of that cash flow to each day during that period.
This may be calculated using averages eg the average percentage of invoices paid within a certain number of days after despatch or by using regression analysis as outlined below. A more complex distribution method is the calculation of normal distribution probability curves, using mean and standard deviation values derived from historic data, appropriate mathematical formulae and normal distribution statistic tables.
Regression analysis Regression analysis expresses the relationship between two variables one being dependent on the other or multiple variables, for example, the relationship between cash inflows from sales with marketing expenditure.
If there is a regressive relationship, it is possible to consider scenerios such as the impact on sales if marketing expenditure is increased by a certain amount. Alternatively, two mean points can be found by splitting the dependent variable data into two groups, finding the mean value of each group and passing the regression line through the two mean points a method known as semi-averages.
This produces a result less likely to be affected by any extreme values occurring in the data.The cash flow forecast is created in exactly the same way as in the weekly cash flow projection template. Actual income statement and balance sheet account balances need to be entered and a unique management report can then be used to compare the forecasted and actual account balances on a weekly, quarterly and year-to-date basis.
A cash flow forecast should also provide comparisons to historic results. This gives the forecast a context in which projections can be evaluated.
It can also highlight seasonal fluctuations, such as spikes in donations, grants, or salaries. Cash flow management is crucial in providing day-to-day support for construction activities during building projects. This article surveys several cash flow forecasting models as well as several cost flow forecasting models, and shows how they can be variously used and combined to produce a more accurate overall picture of cash and cost flow forecasting.
Key concepts and applications include: time value of money, risk-return tradeoff, cost of capital, interest rates, retirement savings, mortgage financing, auto leasing, capital budgeting, asset valuation, discounted cash flow (DCF) analysis, net present value, internal rate of return, hurdle rate, payback period.
A cashflow forecast is used to predict peaks and troughs in your cash balance, enabling you to consider at what point you may need a loan or sales drive or conversely, periods when there should be an excess.
Banks may ask for this as part of a loan application. Use the this solver in your projects. A cash flow forecast is a plan of when cash will move in and out of your business.
You need to have a cash flow forecast as well as a P&L budget, because your payment terms might mean that your company is profitable, but your bank balance is in the red!