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JAMAR Vol. 9 · No. 2· 2011 Introduction Refining Measures to
Improve Performance
Measurement of the
Accounts Receivable
Collection Function Offering sales on credit is common practice for
most organisations (Pike, Cheng, Cravens, and
Lamminmaki, 2005) and accounts receivable
can be one of the most significant assets on an
organisation’s balance sheet (Jackling, Raar,
Wigg, Williams, and Wines, 2004). As a
percentage of total assets, accounts receivable
has been estimated to constitute 20% for large
organisations and 30% in small / medium sized
organisations (Jackling, Raar, Wigg, Williams,
and Wines, 2004) and up to 80% of business
transactions between corporations are
conducted on credit (Asselbergh, 1999). Given
the size of the accounts receivable balance for
many organisations and the significant degree
of sales that are made on credit, it is important
that this asset is appropriately managed and
that suitable financial analysis tools are used
for internal control purposes. The imperative
of ensuring this asset is efficiently and
effectively managed is heightened during
economically depressed periods. Philip Leitch*
Dawne Lamminmaki**
Accounts receivable management is an
important facet of financial management.
The average collection period and aging
schedule are two widely used gauges of
accounts receivable collection
performance. These performance
measures are deficient, however,
especially when used for internal
evaluation, as a change in the average
collection period or the composition of an
aged schedule does not necessarily relate
to a change in collection efficiency. This
study proposes refinements to these
metrics. In the case of the ageing
schedule, it is proposed that accounts
receivable values should be related to
their original credit sales. To calculate the
average collection period, it is proposed
that the balance of accounts receivable
should be divided into age categories and
these categories should be matched to the
credit sales that generated them. The
manner in which these revised measures
constitute more accurate internal
indicators of accounts receivable
performance is outlined and empirically
examined. A common goal of accounts receivable
management is to ensure debts are collected
within specified credit terms (Pike and Cheng,
2001). Another common goal is the
identification of delinquent accounts to reduce
the total trade credit which is written off as a
bad debt (Peacock, Martin, Burrow, Petty,
Keown and Martin, 2003; Jackling, Raar,
Wigg, Williams, and Wines, 2004, p. 384).
These two goals normally go hand-in-hand, as
early identification of delinquent customers
reduces the size and age of accounts receivable
and also reduces the probability of accounts
defaulting (Peacock, et.al., 2003).
Accounts receivable collection efficiency
measures indicate the performance of the
accounts receivable processes and the success
of collection policies applied (Carpenter and
Miller, 1979). The two commonly used
accounts receivable collection efficiency Keywords
Accounts Receivable Management
Credit Management
Average Collection Period
Ageing Schedule We would like to acknowledge the helpful
comments from Professors Jerry Bowman, Michael
Bradbury, Chris Guilding and Ken Merchant and
the participants at the 2009 Manufacturing
Accounting Research Conference in Muenster,
Germany. This study would not have been possible
without access to empirical data from In Vitro
Technologies New Zealand. *In Vitro Technologies Pty Ltd, Australia
**Griffith University 1 JAMAR Vol. 9 · No. 2· 2011 indicators are the Aging Schedule and Average
Collection Period (ACP).1 Both of these
measures suffer from deficiencies however,
and can be highly misleading when using
internal information to monitor the efficiency
of the accounts receivable collection function.
Use of the measures can result in an inaccurate
reflection of accounts receivable managers’
performance. The objective of this study is to
outline the manner in which these measures are
deficient and to advance refinements that
correct for the noted deficiencies. The paper’s
focus is restricted to the Aging Schedule and
the ACP measure. Description of the Collection
Efficiency Measures
The Traditional Aging Schedule
The Aging Schedule is a popular accounts
receivable tool (Pike and Cheng, 2001) and is
widely referred to in the normative accounting
and finance literature (Peacock, et.at., 2003;
Arnold, 2005). It comprises a classification of
outstanding balances according to the period of
time they have been outstanding (Equation 1).
These age categories can be calibrated
according to months, weeks, or days,
depending on an organisation’s requirements,
and are frequently expressed as a percentage
relative to the total accounts receivable balance
(Lewellen and Johnson, 1972; Lewellen and
Edmister, 1973; Zeune, 1991). If debts are
collected on time, most debts should be
younger, and few should be older. It is
assumed that increased collection efficiency
would reduce the percentage of debt in the
older categories. Motivation for the study comes from problems
identified within the organisation where one of
the authors works. It was observed that
changing credit sales levels were resulting in
distorted Aging Schedule values, and that this
in turn was providing misleading signals with
respect to collection efficiency. As a
consequence, performance of the accounts
receivable function was being appraised
erroneously. Further motivation derives from
the prior literature’s failure to offer a
satisfactory resolution to this accounts
receivable performance measurement
deficiency. Equation 1: Traditional Aging Schedule
P The remainder of the paper is organised as
follows. Next, a description and literature
review pertaining to the traditional accounts
receivable Aging Schedule and ACP is
provided. This is followed by an examination
of deficiencies inherent to the two approaches
and then a description of how corrections can
be made to overcome these deficiencies. In the
subsequent section, empirical data is drawn
upon to explicate the way that the revised
approaches proposed constitute preferred
indicators of accounts receivable collection
efficiency. The paper’s concluding section
outlines implications arising for practice,
describes the study’s contributions and
limitations, and suggests some avenues for
further research that build on the revised
measures advanced herein. t t ∑r or stated in 30 day categories:
r r 1 Current = ∑r 2 30 Days = 3 ∑r ∑ rt ∑r
120+ Days = r
60 Days = ∞ r
90 Days = 4 ∑r Where:
Pt = the proportion of accounts receivable “t”
financial periods in the past.
rt = the total accounts receivable sourced from
credit sales issued t financial periods in
the past. 1 Average Collection Period is known by a variety
of names, and is frequently referred to as Days
Sales Outstanding (DSO), Debtor Days, or Days
Outstanding. (Peacock, Martin, Burrow, Petty, Keown, JR, and
Martin, 2003; Arnold, 2005) 2 t =5 ∑r JAMAR Vol. 9 · No. 2· 2011 It is evident from Equations 1 and 2 that both
the ACP and the Aging Schedule use accounts
receivable balances to provide indicators of
collection efficiency. However, an
organisation’s accounts receivable balance is
the result of both credit sales and collections
and thus the accounts receivable balance
changes when either credit sales or collections
are made. Because both credit sales and
collections affect the accounts receivable
balance, difficulty arises in identifying whether
a change in an accounts receivable balance has
been caused by a change in collection activity,
a change in credit sale activity, or both. The Average Collection Period (ACP)
The ACP (Equation 2) is a measure of the
average time taken to collect accounts
receivables. ACP is a ratio that draws on credit
sales and accounts receivable, and it appears to
be widely taken for granted that ACP only
reflects collection efficiency (Benishay, 1965;
Lewellen and Johnson, 1972; Freitas, 1973;
Lewellen and Edmister, 1973; Stone, 1976;
Zeune, 1991). That is, if credit sales increase, a
proportional increase will arise in the accounts
receivable balance, and the ACP ratio will
remain the same. If collection efficiency was
to increase, then the balance of accounts
receivable relative to credit sales would
decrease, and the lower ratio would reveal
greater efficiency. Deficiencies in Collection Efficiency
Deficiencies of the Traditional Aging
Schedule ACP has been cited as the most commonly
used accounts receivable collection measure
(Pike and Cheng, 2001). A shortcoming is
apparent in the accounting and finance
textbook literature that widely promotes use of
ACP (Hilton, 1994; Peacock, et.al., 2003;
Bazley, Hancock, Berry, and Jarvis, 2004;
Jackling, et.al., 2004; Arnold, 2005; Birt,
Chalmers, Beal, Brooks, Byrne, and Oliver,
2005; Horngren, Harrison and Bamer, 2005;
Lasher, 2005; Doupnik and Perera, 2007), as
this normative literature systematically fails to
highlight the deficiencies that are endemic to
the measure. The Aging Schedule is usually expressed in
percentages, with the total of all categories
equalling 100 percent. This calculation
signifies that all categories must change when
any accounts receivable category is altered. As
Zeune (1991) notes: “[Aging Schedule]
Percentages are interdependent. They must
always sum to 100%.” (p. 15). This
interdependence creates a challenge when
attempting to interpret a change in a particular
category (Benishay, 1965; Lewellen and
Johnson, 1972; Lewellen and Edmister, 1973;
Zeune, 1991). Equation 2: Traditional Average Collection
Period Where:
ACP = Average Collection Period, in days.
= credit sales -- the total credit sales for
the previous 12 months (referred to
hereafter as “Yearly” calculation), or
credit sales for the previous month
multiplied by 12 (known hereafter as
“Monthly” calculation).
= balance of accounts receivable -- the
total balance of outstanding credit
sales. This problem of interdependency in an Ageing
Schedule is most apparent when changes in
credit sales occur. Rising credit sales will
result in a schedule exhibiting increasing
values in the younger categories, and a
misleading suggestion of increased collection
efficiency for the older categories (Lewellen
and Johnson, 1972; Lewellen and Edmister,
1973; Zeune, 1991). Lewellen and Edminster
(1973) argue that it is only in periods of evenly
occurring credit sales that an Aging Schedule
can be seen to represent a tool that accurately
depicts collection efficiency. Zeune (1991) and
Lewellen and Johnson (1972) conclude that the
Aging Schedule produces an incorrect analysis
and false warning patterns can be raised by
normal sales fluctuations. (Hilton, 1994; Peacock, et.al., 2003; Bazley, et.al.,
2004; Jackling, et.al., 2004; Birt, et.al., 2005) One can conclude that the sum of credit sales
achieved in the most recent 30 day period is ACP r
s ⋅ 365 3 JAMAR Vol. 9 · No. 2· 2011 ACP, independent of any change in collection
efficiency. This is due to an indirect
relationship between credit sales and accounts
receivables. When using total credit sales for
the previous 12 months, every month
contributes equally to the ACP measure even
though only the most recent month’s sales are
likely to be represented in the current accounts
receivable balance. All credit sales occurring
in the last 12 months affect the ACP regardless
of the fact that no receivables from the older
sales may remain uncollected. positively correlated to the current category in
a traditional Aging Schedule.
Deficiencies of the Traditional Average
Collection Period
The workings of the ACP signify that when
credit sales are high and an accounts receivable
balance is low, collection efficiency is deduced
to be high. In other words, the ACP implies
that, given unchanging collection efficiency,
the balance of accounts receivable will stay in
proportion to credit sales. This assumption
does not appear to hold true, however, as an
increase in credit sales will not result in a
proportionally equal increase in the entire
accounts receivable balance. Therefore, we can
conclude that the ACP can provide misleading
indications of collection efficiency when credit
sales are not constant (Lewellen and Johnson,
1972; Stone, 1976). The indirect relationship between ACP and
credit sales is not resolved by utilising a
smaller history of credit sales, such as 3
months. This is because few of the older credit
sales within the 3 month period are likely to
remain as accounts receivable, yet they have
the same degree of influence on the ACP as
sales made in the current month. Utilising
only the last month’s credit sales is also
unsuccessful as a large proportion, perhaps
half or more, of accounts receivable are
generated from prior months and therefore bear
no relationship to the current month’s sales.
Without a direct relationship between accounts
receivables balance and the credit sales that
generated them, the ACP fails to constitute a
reliable indication of collection efficiency. There is a direct relationship between ACP and
credit sales. An increase in credit sales will
trigger an increase in the ACP, falsely
implying a decrease in accounts receivable
collection efficiency. Similarly, a decrease in
credit sales will lead to a false suggestion of an
improvement in accounts receivable collection
efficiency (Benishay, 1965; Lewellen and
Johnson, 1972; Cotter, 1973; Freitas, 1973;
Lewellen and Edmister, 1973; Stone, 1976;
Zeune, 1991; Ridley, 1993). During periods of
credit sale volatility, the ACP becomes
similarly volatile, providing a misleading
suggestion of changing levels of collection
efficiency (Lewellen and Johnson, 1972).
Zeune (1991) showed that when credit sales
are uneven over time, the ACP will relate more
strongly to changes in credit sales activity than
changes in accounts receivable collection
efficiency. Due to the potentially misleading
nature of the ACP, Ridley (1993), Zeune
(1991), Stone (1976), Cotter (1973), Freitas
(1973), Lewellen and Edminster (1973) and
Lewellen and Johnson (1972) have all
concluded that there is little reason to use
ACP. Despite the long-standing nature of some
of these commentaries, as already noted, ACP
continues to be promoted in an uncritical
manner in the normative literature. The effect
of changing credit sales levels on ACP is
demonstrated in Appendix A. Correcting the Measures
Due to the shortcomings identified, some
commentators have attempted to advance
alternative collection efficiency measures
(Lewellen and Edmister, 1973; Gallinger and
Ifflander, 1986; Zeune, 1991). Despite the
documented deficiencies of the ACP and the
Aging Schedule, the alternatives offered have
not been widely acknowledged or applied
(Pike and Cheng, 2001) and we continue to see
the ACP and Aging Schedule widely promoted
in accounting texts (Hilton, 1994; Peacock,
et.al., 2003; Bazley, et.al., 2004; Jackling, et.
al., 2004; Arnold, 2005; Birt, et.al., 2005;
Horngren, et.al., 2005; Lasher, 2005; Doupnik
and Perera, 2007). The paucity of attention
directed to these deficiencies in prior research
is a concern, and is particularly surprising as
the shortcomings of the ACP and the Aging
Schedule were first commented on as early as
the mid 1960’s (Benishay, 1965). From Appendix A it is evident that changes in
credit sales result in changes in the value of the The enduring popularity of the ACP and Aging
Schedule is most likely attributable to their
4 JAMAR Vol. 9 · No. 2· 2011 Prior examinations of Aging Schedules include
Stone (1976), Gentry and De La Garza (1985)
and Zeune (1991). Stone (1976) discussed
payment patterns (i.e. cash flows) and "balance
fractions" (% of credit sales outstanding over
time), however did not consolidate these into a
schedule. Gentry and De La Garza (1985)
outlined a complex system concerned with
identifying collection variations relative to
targets. Although representing an accurate
approach, it was based on specific sale
collections, which detracted from its intuitive
appeal due to interpretation and monitoring
difficulties that would likely arise. Zeune
(1991) used worked examples to largely
replicate what had been established in prior
studies. It is believed the approach outlined
herein is superior to what has been
documented in this prior literature. simplicity of calculation and interpretation. It
would therefore appear to be a useful step
forward if the measures could be modified in a
way that frees them from the distorting effects
of credit sales changes whilst maintaining their
ease of computation and interpretation. It is
believed that such a step can be achieved by
directly relating accounts receivable to the
credit sales that generated them. The following
sections expound on this modification.
Correcting the Aging Schedule
As already noted, the traditional Aging
Schedule is frequently expressed as a
percentage schedule, where each age category
displays the percentage of total accounts
receivable contained within that category.
Therefore, a corrected Aging Schedule should
also categorise accounts receivable in this
manner. The Aging Schedule can be corrected
by the inclusion of credit sale information in
the calculation of the percentages (see
Equation 3). Equation 3: Corrected Aging Schedule
r ⎞
⎛⎜ r1 r2
t ⎟
. .
⎜ s1 s2
s ⎟
t ⎠
⎝ P The traditional Aging Schedule (Equation 1)
relates accounts receivables balances to credit
sales over a longer period, while the corrected
Aging Schedule (Equation 3) relates accounts
receivable categories to their original credit
sales. This corrects for the shortcoming noted
in the Aging Schedule, as it removes period
interdependencies from the measure. Or more concisely:
r t P t s t Where:
Pt = Aging Schedule percentage category for
financial period t. Categories are no longer related to each other
as they are no longer required to sum to 100%.
Detailed comparisons between the traditional
and corrected Aging Schedules are provided in
Tables 1 and 2. Note that Table 2 reflects the
fact that the corrected Aging Schedule is not
required to sum to 100% (in this case it sums
to 99.91%). The correction also ensures that
changes in categories can only be attributed to
changes in collection efficiency. Thus, changes
in credit sales should have no effect on
younger balances. The corrected Aging Schedule utilises the total
credit sales within each period. The total
credit sales “s” generated in period “t” are
represented as “st”:
s ( s1 s 2 . . s t ) Accounts receivable are divided into age
categories matching the periods used for the
credit sale. The total accounts receivables “r”
generated by credit sales from period “t” is
represented as “rt”: The approach presented herein extends the
work of Lewellen and Edminster (1973). A
distinguishing facet of the corrected Aging
Schedule advanced concerns its re-structuring
and re-categorisation of the calculations.
Further, appearing below is an exposition of
how the corrected Aging Schedule can be used
as the basis for preparing a corrected ACP. r ( r1 r 2 . . r t ) The accounts receivable categories, “rt”, are
transformed into percentages of their original
sales, “st”, creating a percentage Aging
Schedule, “Pt”. 5 JAMAR Vol. 9 · No. 2· 2011 Table 1: Formulae Applied in Traditional and Corrected Aging Schedules
30 Days
60 Days
90 Days
120+ Days
(0 - 29 Days) (30 – 59 Days) (60 – 89 Days) (90 – 119 Days) (120+ Days) Credit Sales s Accounts
Receivable r 1 1 s s 2 r r 2 4 ∑s 4 ∑r s 3 r 3 ∞ Traditional
Aging Schedule Corrected
Aging Schedule r r r r ∑r ∑r ∑r ∑r r r r r 1 1 s 1 2 3 2 s s 2 ∑ 4 3 4 s 3 Total 4 ∑r
∑r r t t =5 ∑r
∞ ∑ t =5 ∑r
∑s r t s t Table 2: Computational Example of Traditional and Corrected Aging Schedules Credit Sales
Aging Schedule
Aging Schedule Current
(0 - 29 Days) 30 Days
(30 – 59 Days) 60 Days
(60 – 89 Days) 90 Days
(90 – 119 Days) Total $61,677.56 $56,454.85 $53,547.59 $51,757.76 $223,437.75 $45,368.57 $11,397.89 $1,645.87 $573.96 $58,986.31 76.91% 19.32% 2.79% 0.97% 100.00% 73.56% 20.19% 5.06% 1.11% 99.91% ratios of the individual categories are added
together, they provide a corrected version of
the ACP. The aligning of accounts receivable
to the credit sales that generated them creates a
direct relationship, which in turn creates a
more meaningful ratio. Correcting the Average Collection Period
When developing a corrected ACP, the
objective is to develop a measure that correctly
reflects the average time that credit sales
remain in accounts receivable. The primary
flaw of the traditional ACP concerns an
assumption that the accounts receivables
balance maintains a specific ratio to credit
sales, which was noted above to be incorrect.
Instead, changes in credit sales affect the
accounts receivable in a “deferred” manner, as
demonstrated in Figures A1 and A2 of
Appendix A. This correction will ensure that within each
age category, accounts receivables will remain
in proportion to credit sales (assuming constant
collection efficiency), even if credit sales are
changing. The smaller the time category used
for the ratio, the more direct the relationship
and therefore the more accurate the measure of
collection efficiency2. This flaw may be corrected by calculating the
ACP ratio in a different way. Instead of using
the total balance of accounts receivable in ratio
to total credit sales, the balance of accounts
receivable can be divided into age categories
and those categories are then matched to the
credit sales that generated them. When the 2 If the duration of the age categories is taken to be
a year, then the corrected ACP literally equals the
traditional ACP, and thus no benefit will be gained.
Therefore, a minimum category size of
approximately one calendar month is suggested,
while durations of a week or a day are more
desirable. 6 JAMAR Vol. 9 · No. 2· 2011 It should be noted that a ratio of age
categorised accounts receivables to credit sales
has already been created, as this is the
definition of the corrected Aging Schedule.
Consequently, the calculation of a corrected
ACP can be achieved by adding together all of
the categories of the Aging Schedule (see
Equation 4). The value computed represents
the average time accounts receivable are
outstanding in proportion to the duration of the
category selected.3 For example, given a 30
day categorisation of the aging schedule, a sum
of all Aging Schedule categories of 1.5 would
equate to 45 days (1.5 x 30 days). Equation 4: Corrected Average Collection
ACP ∑ Pt⋅L
t Where:
ACP = Average Collection Period in Days
t = Category or financial period, such as
calendar month.
Pt = Aging Schedule percentage category
for financial period t.
L = Length of schedule categories in days
(i.e. length of t). The calculation of the corrected ACP can be
seen to build from the work of Bineshay
(1965). Two key points of departure are
evident. In the Bineshay (1965) work, static
credit sales were assumed and receivables as a
percentage of credit sales were not identified.
The static credit sales assumption carries
significant calculation implications and
detracts from real world applicability. The
approach advanced herein represents not only a
particularly novel way to calculate the ACP
measure, it also lends itself to real world
application. Appendices A and B present four scenarios of
changing credit sales with collection efficiency
held constant. Appendix C introduces the
effect of changing collection efficiency on the
ACP measure. As can be seen in Figure C1 in
Appendix C, if credit sales remain constant,
both the traditional and corrected ACP
represent mechanisms that will accurately
detect changes in collection efficiency. If
credit sales are variable across periods,
however, detecting a change in collection
efficiency becomes problematic with the
traditional ACP, but not with the corrected
ACP (see Appendix C, Figure C2). The traditional ACP calculation uses the
accounts receivable balance divided by the
total credit sales for the year. The corrected
ACP uses age-categorised accounts receivable
balances divided by their source credit sales.
Thus, both methods utilise all outstanding
balances in accounts receivable, provide a ratio
of accounts receivable to credit sales and
provide an aggregate turnover based measure.
These are two variants of the same measure,
and given unchanging sales they will produce
the same value. As noted in Appendix A, a
shortcoming of the traditional ACP arises
when there are changes in credit sales.
Applying the corrected ACP measure to the
four scenarios described in Appendix A reveals
that the measure advanced is free of distortion
(see Appendix B), as it remains unaffected by
any of the changes to credit sales. In addition to the greater accuracy of the
corrected Aging Schedule and ACP, for these
measures to be useful, they need to be easy to
apply. A report of total sales by period and a
report of a non-percentage bas...


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