«Gotta catch ‘em all» – liquidity drivers (an article on liquidity forecasting)

Lack of liquidity damages the reputation of a business, reduces its competitiveness and can ultimately trigger bankruptcy.

 Yet many businesses have little or no focus on liquidity management until a situation of illiquidity arises. Management sole focus is often on controlling for and forecasting of sales and financial results, liquidity forecasting routines are typically less developed and get less attention if any.

Well-designed liquidity forecasts give management running estimates of available cash resources. Good forecasting routines give an early warning of future capital needs, and thus allowing management to handle liquidity needs before they become acute.

Liquidity forecasts also allow capital allocation to go to the business areas where the need at any time is the highest and/or the return on capital is the greatest.

It’s tough to make predictions, especially about the future

The liquidity situation sets the premise for the operations of any business, and for most, cash is a scarce resource that needs sensible rationing. Reliable liquidity projections are achieved through a fundamental understanding of the business and its outlook. Every individual business and the industry it operates in has their own unique traits to consider when making cash flow predictions. For example, liquidity modelling for enterprises whose core business comprises large projects require a different approach to that of a fast moving consumer goods company selling high volumes of low-cost products.

A good forecasting routine focuses solely on the main and significant liquidity drivers. It utilizes all available data to the best possible extent in order to meet management’s informational needs and any external requirements.

Liquidity forecasts are necessarily more ruthless than profit forecasts. At the time of control, there are no provisions or accruals that can be adjusted to reach a target.

New investment opportunities or changes to the funding situation are examples of circumstances that can trigger a sudden need for liquidity forecasts. It is challenging to establish good routines for liquidity forecasting if this is not already established, e.g. to gather relevant and reliable input data.

Cash focus

The cash generating capacity of any business determines its intrinsic value. Liquidity forecasts lay the ground for optimizing your financing and appropriately allocating its available capital. Hence, this directly contributes to increasing shareholder value.

Having a thorough understanding of cash flow drivers and a suitable overview of the liquidity outlook, allows the business to link incentive programs to cash-based KPI-targets rather than on accrual accounting figures. Liquidity oriented incentive programs will better match employees’ objectives with the interests to that of the shareholders.

“Reliable liquidity projections can only be achieved through a fundamental understanding of the business and its outlook”

Who should “own” the prognosis, how frequently and when should it be made?

The forecasting routine needs to be adapted to the size and complexity of the individual business. In smaller businesses, it is often adequate that the finance department alone develops the forecasts. Larger corporations and more complex business models, conversely, it may be necessary to involve other parts of the organization. For example, investment, credit and sales managers. To achieve the most reliable liquidity forecasts the routines should always have an “owner”. This dedicated resource is responsible for consolidating all data and presenting the results.

Internal needs and external requirements play a role in determining the frequency of the forecasts. As for the timing of the forecasts this must harmonize with; invoicing and attestation cycles, salary payments and other relevant accounting procedures, as well as other significant liquidity driving factors, e.g. taxes, fees and loan payments.

Cash positions

The first step for any liquidity forecast is to establish an overview of the current cash position. For smaller enterprises, this normally will not pose an issue. On the other hand, for large corporations with a large number of subsidiaries, several cash management partners and a considerable amount of bank accounts this can be more challenging. Normally it will be possible to have automatic reporting of bank balances through MT 940. This is however not without cost. Prices vary widely from bank to bank and in between countries. How manual the routine needs to be decided based on a cost/benefit analysis.


Liquidity drivers

Relevant liquidity drivers, and consequently relevant cash forecasting parameters, need to be individually set in relation to the specific business model and its company dynamics. Even though this need be adapted to the individual case there are still some dimensions that generally should form part of your considerations.

It is often sensible to align input parameters utilized in the cash flow forecasting with those already used in other forecasting and/or budgeting routines. However, it can be wise to lower the granularity of details for cash forecasting. There are various reasons for this. This will increase input simplicity for large organizations with many forecasters. Another reason is that the possibilities for controlling, and reconciliation against actuals, is normally more limited for cash forecasts due to limitations in retrievable data from the cash management providers.

Time horizons

Liquidity forecasts can span different time horizons; short, medium and long term. Depending on the time horizon there are various forecasting approaches that fit better. Each forecasting methodology with its unique characteristics and, with individual strengths and weaknesses. See Figure 1 for an overview.

«Gotta catch ‘em all» – liquidity drivers (an article on liquidity forecasting)
Figure 1 – Forecasting methods and time horizons

Method of choice should be decided based on informational needs, availability of and data quality. Nor is it so that the choice of horizon and approach is mutually exclusive. On the contrary, it makes sense to apply several approaches and gather data over time. By comparing the different approaches against one another, the forecasters can continuously enrich their future assumptions with subsequently improved precision in future forecasts.

Short term

Normally defined as periods of up until six weeks or so, and estimates are given on a daily or weekly basis. It is normal to project cash outlay by utilizing data from customer and supplier accounting ledgers. The method is for that reason classified as a direct approach. To ensure exhaustive input it may be sensible to enrich such data from the accounting ledgers with data from purchasing and order systems. This input is combined with estimates of other significant cash flows e.g. wages, taxes, fees and financing.

The quality of the forecasts depends, amongst other, on in-house cost approval processes, bookkeeping, invoicing cycles, customer’s payment behaviour and credit terms.

The method is usually very precise for the near term and is reconciled against bank accounts. The method also will give you an indication of future currency developments. Weakness can come from data corruption stemming from; data is collected from the accounting ledgers at a point of time when the books are not fully up to date, irregularities in the approval routines of incoming invoices, infrequent and sporadic billing cycles, irregularities in bookkeeping etc. Applying empirical assumptions can, to a certain extent, accommodate for this. However, the method will always be less exact the further you look ahead into the forecast.

Medium term

Normally defined as up to 12 months, typically based on existing budgets, or if available, on rolling 12-month forecasts. It is an indirect method because it seeks to convert accrual accounting results into cash flows. This requires projections of balance sheet items and capex spending.

For balance sheet items, it is particularly challenging to project future working capital movements. Access to accounting data gathered over several years, under similar and stable conditions, allows the use of regression analysis to predict future developments. Alternatively, one can use other metrics of correlation between balance sheet items and profit and loss statement to achieve similar results.

When accounting procedures have been inconsistent, the business has changed significantly, there is little data available etc., then different methods are more appropriate. It will then be important to identify significant actual historical credit periods for both, suppliers and customers, and get an understanding of expected future payment patterns from the customers.

The indirect method does not distinguish between available cash and “trapped cash” positions, e.g. “pay-as-you-go” withholding tax or guarantee accounts. As a rule, it does neither distinguish between currency flows. Another repeatedly experienced cause of misunderstandings come from differences between accounting cash balance and actual cash available in the bank.

Long term

Forecasts further into the future than 12 months are considered long term. Typically founded on the financial long-term plan. Often this requirement stems from external demands, often from a creditor, to provide an outlook of cash status as far as seven years into the future. Given this longer forecasting horizon, it is natural to use wider intervals for the forecasts, for example quarterly.

Also seen as an indirect method, with similarities in approach, weaknesses and strengths to the medium term. Accuracy will necessarily diminish farther into the projections, but deviations here are more prone to stem from estimation errors in the profit & loss and/or investment forecasts rather than from “missing” out on cash effects.

Cash generating unit (CGU)

Frequently Management desires to evaluate cash forecasts from various sub-groups/Cash Generating Units (CGU). In many instances, internal divisions of the group’s legal entities make up such CGUs, and a single legal entity can be connected to many CGUs. This can complicate the task if the business does not have appropriate routines and IT-systems in place, irrespective of which forecasting approach is utilized.

  • Direct method: Payment data stem, to a large extent, from accounting ledgers (balance figures) which are commonly not separated according to which CGU it originates from.
  • Indirect method: Often accounting P&L results are forecasted on a CGU level, but there will usually not be created a pro forma balance sheet that fits the CGUs.

Even in the instances where a given CGU solely comprises a group of legal entities then there are in many instances no accounting rules demanding for a consolidation of the group’s balance sheet. Lacking such a requirement, we quite often find that this is usually not performed.

Preparing a pro forma CGU balance sheet would entail netting out any intercompany transactions between companies. This challenge can be overcome by both IT-systems and work processes being set up properly. If not, depending of course on the size and complexity of the company, setting it up takes time and can be costly.

Monitoring and control leads to better forecasts

A well-developed cash forecasting routine involves monitoring, analysis and follow-up of the forecasts. Figure 2 sets out how an ideal forecasting routine can be established.

«Gotta catch ‘em all» – liquidity drivers (an article on liquidity forecasting)
Figure 2 – Process flow

When actual cash flows are being reconciled against forecasts it is, as mentioned briefly before, important to be aware that the granularity of data usually differs severely between actuals from cash management systems and the input data. How to carry out a meaningful control routine depends on a specific assessment of what data is available from the cash management provider and how this data can be sensibly “manipulated”. In some instances, you will only get meaningful comparisons on a net in and out flow basis. Other financial reports, ad hoc reports from ledger systems, factoring partners, etc., can however give valuable additions to your deviation analysis.

Once the reconciliation between the most recent forecast and actuals is completed and a new forecast is prepared, it is sensible to compare the corresponding periods’ forecasts against each other. E.g. if you are forecasting on a weekly basis and you have just finished the forecast for week 40 and onwards. You are then able to compare actuals for week 39 with the previous forecast for the same week. In addition, you can compare your estimates made now in week 40 to the previous forecast made in week 39. If larger deviations exist on either:

  • The reconciliation and analysis of actuals versus forecast; or
  • Between the new cash projections versus the previous projections

It gives reason to dig into the numbers, find the underlying reasons for the change and potentially adjust the recently made forecast. Through a constant adjustment of the cash forecasting routine and the basis used for your estimates, will ensure an increased future precision in your forecasts.


Still, it is worth mentioning that given the larger challenges in doing cash forecasts versus other forecasts it is seldom wise to make a rash decision based on only a few data points. The forecasts are measured against cash in the bank and for instance, a one-day difference between the valuation date in the bank and that of the accounting books can in some cases create large deviations.

Our approach

Mimir Consulting has strong expertise in developing and implementing liquidity forecasting routines. Both for large multinational and complex groups, as well as for smaller businesses.

We have broad industry experience and strong competence in the field of forecasting. This way we quickly identify our client’s information needs and can start tailor fitting solutions.

Together with our clients we identify the key significant cash flows drivers, assess key data sources and find the optimal level of detail for modeling.

Based on our examinations, we assist our clients in setting up liquidity forecasting routines, that will utilize all available information to the fullest and with as little manual effort as can be.