On accounting approach to management of working capital

The accounting approach to management of working capital is regarded as fundamentally flawed basis for decision making as basis for decision-making  regarding the optimization of investment in working capital because of the limitations associated with preparation of accounts related to the computation of cost of capital.  Computing working capital makes use of the traditional concepts accrual accounting instead of the cash accounting.  As there is the disregard of time value of money as commonly understood in finance, in accounting approach, the accrual accounting therefore causes the recording of accounts even if there is no actual cash involved. In particular, under the accounting approach, it would be a fundamental error to assume  that liquidity in terms of a more that 1.0 current ratio or  excessive  working capital position of the company is necessarily optimal. In fact excessive working capital may actually be equivalent to inability to invest funds at cost of capital or higher. On the other hand, a company may have a low working capital at a certain point --  as usually the case because accrual accounting causes the preparation of balance sheet periodically -- yet it can meet its obligation before they are due because cash flows allows the same.

What is not optimal with the concept of working capital management would be its failure to relate with the bigger objective of the organization about the wealth maximization .[1] In other words, if working capital would just make sure that working capital is maintained positive only for different periods of time without ensuring the actual cash flows that would maximize shareholders’ value, then the said model may just be limited in scope and may contradict the ultimate financial objectives of the organization.

Instead of the perceived need to make the working capital positive throughout the period, projected cash flows  should instead be prepared and discounted at cost of capital to make able to see to it that the relationships of one variable to other variables in meeting the objective of wealth maximization are also consistent.  This would be normally followed by the application of the necessary Net Present Value  and Internal Rate of Return (IRR) calculations for capital budgeting techniques to ensure  the consistent effects of  the uses  and sources of working capital  in business decision making.    The use of NPV and IRR under the discounted cash flow (DCF methods) generally recommends the best from among projects because the choice will pass the test on cost of capital.[2] Whatever method therefore that would disregard the time value of method by not discounting cash flows at cost of capital would be deemed not making an optimum contribution to the value maximization objective of the organization.[3]  Working capital must be deemed to be one of these faulty methods of attaining the optimum. The idea of comparing working capital management alone with disregard of the bigger picture because of its failure to consider time value of money is akin to comparing therefore discounted cash flow method and non-discounting cash flow methods. For the same reason that accounting rate of return and payback period method are considered part of the non-discounted cash flow methods and therefore not scientific  or less accurate , so with the use of working capital with its variant measures of liquidity like current ratio and quick ratio.[4] In other words, methods that disregard time value of money disregard what is optimum for busines .

On economic order quantity and its assumptions

The economic order quantity model (EOQ) is a standard model that is particularly applied to the management of inventory as far as determining the correct order size in such a way that should minimize annual inventory costs.[5]  It must be noted that the wealth maximization objective can be either viewed as revenue maximization or cost maximization. Since inventory is a cost to business before it becomes revenue, whenever there is sale of goods to customers, providing and maintaining the same to the business constitute costs that must be minimized. Since various costs take different forms and behavior in relation to certain drivers, EOQ finds the equilibrium point or the trade-off point between annual inventory holding costs and annual order costs to arrive at minimum total cost.[6] This would mean that making a choice under the model sees the balance between two costs which happen to behave in opposite direction.  A company may opt to reduce the number of orders in order to reduce the annual ordering cost but it may mean incurring very high annual storage cost because less number of orders would mean ordering in with high volume or quantity. On the other hand, it may choose to have low storage cost by avoiding the need to lease another warehousing or paying additional refrigeration unit to keep ordered goods in good condition. However, to do this, the company would have to keep ordering more frequently which as stated earlier could also cause too high ordering cost or loss what would have been good source of margin.[7]

The real issue in the use of the EOQ is actually trying to anticipate the future with some assumptions on costs and to the latter’s behavior by determining the correct order size. The assumptions therefore include that the annual demand must be known and constant. This could mean that daily usage in terms of units can be estimated with reliability. It must also be assumed order lead time is known and constant.  To have an order lead time known at ten days should mean having each and every delivery will arrive exactly ten days after the order is placed. Further assumptions include instantaneous replenishment constantan price, known and constant holding cost and availability of inventory at all times.[8] Any failure to one or two of these assumptions may render in the inapplicability of the model.

The right amount of quantity to be ordered is a material decision that would attain a minimized total costs from ordering cost and storage cost on an annual basis.[9]  Hence it is called economic order quantity.

This researcher believes that the model is still robust for decision making so long as its applicability is concerned when assumptions are similar.  The model can be considered scientific since it can be proven mathematically.  Just like any other model, the relevance EOQ as a good model should make sure that the necessary assumptions are there. The moment however that one or two of the assumptions are the not the same as theoretically required, the use of EOQ without effecting the needed change in the model would be disastrous to the business. It would be just like taking the medicine based on wrong diagnosis. Thus, the critical part for any would-be user of the model is to correctly ensure that the assumptions are validly similar to the EOQ model.

Works Cited:

Atkinson, Anthony, et al. Management Accounting. New Jersey: Person Custom Publishing, 2005

Bernstein, J. Financial Statement Analysis, Sydney: IRWIN, 1993

Brigham, E. and Houston, J. Fundamentals of Financial Management. Thomson, 2002

Helfert, E.  Techniques for Financial Analysis. Sydney: IRWIN, 2001

Meigs, R, Meigs, W., & Meigs, M. Financial Accounting.  New York: McGraw-Hill, 1995

Wisner, Tan & Leong, Principles of Supply Chain Management,  Cengage Learning, 2008

[1] Brigham, E. and Houston, J. Fundamentals of Financial Management. Thomson, 2002; Helfert, E.  Techniques for Financial Analysis. Sydney: IRWIN, 2001

[2] Atkinson, Anthony, et al. Management Accounting. New Jersey: Person Custom Publishing, 2005

[3] Brigham, E. and Houston, J., 2002, see above

[4] Bernstein, J. Financial Statement Analysis, Sydney: IRWIN, 1993

[5] Wisner, Tan & Leong, Principles of Supply Chain Management,  Cengage Learning, 2008

[6] Wisner, Tan & Leong,  2008, see above

[7] Meigs, R, Meigs, W., & Meigs, M . Financial Accounting.  New York: McGraw-Hill, 1995

[8] Wisner, Tan & Leong,  2008, see above

[9] Wisner, Tan & Leong, Principles of Supply Chain Management,  Cengage Learning, 2008

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