Relationship between Working Capital Management and
Profitability- Case of Pakistan Textile Sector
*Mehrunisa Sajjad and **Khuram Shahzad Bukhari
Working capital management is concerned with short-term investment
and financing decision of an entity which makes it an important area of
financial management. The study presents an in-depth analysis of how
cash management, inventory management and trade credit management
practices affects the WCM in a local spinning, weaving and composite
units' setting and the way they impact the firm's profitability. Desired
information is elicited with the help of a structured questionnaire and indepth discussions with executives and analyzed using linear regression
analysis, analysis of variance (ANOVA) and analytical hierarchical
process (AHP). It is observed that with relatively poor cash management
and inventory management practices, textile companies have remarkably
better trade credit management arrangements. Working capital
management practices along with its components have been found to
have a significant positive relationship with the earning per share (EPS),
earning before interest and tax (EBIT) - the profitability measures and
size of the respective entity. Larger companies have superior cash
management, inventory management and trade credit management as
compared to medium and smaller units. No significant differences have
been reported with respect to the textile unit type, spinning, weaving and
composite, however, trade credit management practices appeared to be
significantly better in case of composite units as compared to spinning
and weaving setups. The research findings are likely to be beneficial for
the corporate decision makers of the textile industry, financial institutions
and policy makers in Pakistan in order to execute the most favorable
strategies to support industrial growth.
JEL Codes : G39
1. Introduction
Short-term operating needs are inevitable by every business in order to trigger their fixed
assets and generate profits from them. Therefore, working capital is a major business
requirement and a significant part of corporate finance. Working Capital Management
(WCM) deals with difficulties which occur during the course of managing current assets and
current liabilities. The aim of working capital management is to strike an optimal balance of
each component. Effective management of cash, inventory, receivables, payables and
credit releases funds for other purposes since the unnecessary investment in working
capital leads to decreasing returns (Filbeck, Kreuger.2004).On the other side, supplying
inadequate funds for working capital may lead to financial tensions and liquidity problems
as the firm is unable to satisfy its short-term liabilities (Lamberson, 1995, Appuhami, 2008;
Viskari et al. 2011). So, a value maximizing risk return trade-off is an all-time obsession of
finance manager dealing with working capital management. Though, many studies have
been conducted in past worldwide, no single indisputable understanding of managing
working capital has been developed. Due to distinctive characteristics and challenges faced
by every industry, the dynamics of WCM are unique for every industry.
________________
*Mehrunisa Sajjad Email: mehrfatima@ymail.com
**Khuram Shahzad Bukhari, Email: khurambukhari@bzu.edu.pk, Institute of Management Sciences
Bahauddin Zakariya University Multan, Pakistan
Textile industry is a major contributor to the exports in Pakistan, but high mark-ups on bank
credit and high inflation has resulted in high cost of production. The sharp rise in cotton
prices in Pakistan has largely affected every unit's buying power as it necessitates greater
working capital investment for replenishing cotton stocks. Price volatility combined with
higher cost of financing, amplified energy costs, the devastation of cotton crop due to
recent flood and complications of reformed general sales tax (RGST), has led to the
creation of severe cash flow tribulations for the textile businesses. These times brought
attention towards effective cash flow management, which is in fact extremely challenging
due to the high cost of doing business in textiles and the present country's scenario. It
deduces that effective working capital management may have a significant impact on the
earnings or profitability of the organization.
In Pakistan, very insignificant research has been done in this area. This paper tends to
explore the current WCM practices of spinning, weaving and composite firms in textile
industry of Pakistan with respect to their sizes, and their impact on firm's profitability. An indepth analysis of management of various working capital components for selected firms is
carried out and further, how each component affects the working capital management in a
local textile setting is investigated. The study not only supplements the existing literature,
but also gives an insight to the finance managers about value maximization of the firm
through efficient working capital management. The research findings are likely to be
beneficial for the corporate decision makers of the particular industry, financial institutions
and policy makers in Pakistan in order to execute the most favorable strategies to support
industrial growth.
2. Literature Review
Many studies have been conducted to develop an understanding of working capital
management. But most of them have examined working capital management from the
perspective of their domestic country like (Smith and Sell, 1980; Gilbert and Reichert, 1992;
Soenen and Sun, 1989, 1995). Not all the researchers have focused on overall working
capital management. Some of them have focused only on one particular component like
cash management particularly cash flow volatility, inventory management or trade credit
management and sometimes particularly receivables (Tse, Buckley & Westerman, 1998;
Gilbert & Reichert, 1992; Soenen & Aggarwal, 1989; Frankle and Collins, 1987; Kamath et
al., 1985; Anvari and Gopal, 1983; Cooley and Pullen, 1979; Grablowsky, 1978).
Early researches in this field started with William Baumol (1952) who proposed that a stock
of cash is like inventory of a commodity and put the first nail by linking the inventory theory
with the monetary theory, which led to further research in the area of cash management
and inventory management models (Tobin 1958; Friedman 1959; Nadiri1969). Meanwhile
the individual research studies in the area of recievables management and inventory
management was also carried out. Mishra (1975) working on the problems of working
capital management identified four areas; inventory, receivables, cash and working finance.
International cash management practices of large US corporations and UK based firms
were investigated by Collins and Frankle (1985) and Sonen (1986). The area was further
explored by Srivasan (1986) by presenting a network optimization approach that would lead
to an efficient cash management system. According to Froot, Scharfstein, and Stein (1993),
effective cash flow management provides sufficient funds to avail attractive investment
opportunities. Minton and Schrand (1999) empirically verified more volatile the cash flows
are, lower the investment of the firm in capital expenditures and R& D, and higher are the
costs of raising external funds. Ross, Westerfield and Jordan (2008) categorized the
motives behind firm cash holdings into transaction, precautionary and speculative motives.
According to Preve and Allende (2010), firms are expected to maintain higher cash
balances, if ; they have high levels of cash-based transactions (i.e., cash inputs and/or
expenses), they are small, they have volatile cash flows, their MTB ratio is high, their R&D
investment is high, and they have a weak relation with banks and financial investors.
Inventory management policy is one of the most important factors in working capital
management as it is one of the major components of current assets (Talekar 2005). The
firm has to measure and maintain optimum inventory level in all the circumstances of
varying demands, production needs and limited resources. With time, several inventory
management techniques were formulated by several research studies in several areas of
management sciences, including operations management, logistics and distribution and
supply chain management. Arroe, Harris (1951) outlined a method for deriving optimal rules
of inventory policy for finished goods. Some firms do not set an explicit Inventory policy, but
instead purchase inputs or goods on an as-needed basis. Other firms, in contrast, prefer to
buy large quantities to take advantage of size discounts and to avoid stock-out problems.
Some firms manage their inventory using more sophisticated optimization mechanisms
based not only on cost-benefit analysis but also on risk-return analysis. Finally, the bestknown approach for managing inventory is economic order quantity approach. (Blackstone
1985, Lanconi 1993, Jones 1993).
Several empirical papers also address trade receivables. Among the first and more cited of
these papers is Petersen and Rajan (1997), who provide a comprehensive examination of
the determinants of trade credit. Using data from the 1987 National Survey of Small
Business Finance, they analyze both trade receivables and trade payables, and test the
theories described previously. Consistent with the information advantage explanation of
trade credit, they find evidence that better and quicker access to information makes firms
more competitive lenders than financial institutions, especially when their clients are credit
constrained. Petersen and Rajan (1997) show that firms can manage these various
functions of trade receivables by (1) establishing a captive finance subsidiary, (2) issuing
account receivables–secured debt, (3) using factoring, (4) employing a credit reporting firm,
(5) retaining a credit collection agency, and (6)purchasing credit insurance, either internally
managing or outsourcing each of these activities.
Mian and Smith (1992) seek to provide evidence on how firms can manage the trade credit
process. They divide the commercial lending process into five functions, namely, credit risk
assessment, credit granting, account receivables financing, credit collection, and credit risk
bearing. In a recent study, Molina and Preve (2009) examine the effect of financial distress
on the investment in trade receivables. Their paper‘s main finding is that firms tend to
increase their investment in trade receivables when they start having profitability problems;
however, as soon as they enter financial distress (and start having cash flow problems),
they show a decrease in client financing. If we assume that firms that are not facing
financial problems have an optimal investment policy, then we can infer that firms in
financial distress have a suboptimal policy of under investing in financing clients. Such
suboptimal investment policy has a cost, which is among the numerous costs of financial
distress.
Credit terms granted seem to depend to some extent on the traditions and customs of the
trade in which the business is operating, and some trade association have fairly strict rules
about trade credit terms, and discounts; but there is little doubt that on occasion, the
extension of trade credit on more favorable terms can be a way of extending sales (Bates,
1971). Ricci (1999) explored the receivable management practices of 200 large US
corporations. The earlier work was carried particularly about, expediting cash flows and
reducing administrative expenses. Beranek and Scherr (1991) carried out a survey to find
the trade credit limit policies in Fortune five hundred firms.
Short-term liability management practices were investigated by Jain and Kumar (1999) in
India and South-east Asia. Short-term loans and advances, and account payable originated
as the key elements of current liabilities. The companies selected under sample offered
discount facilities to their customers in order to have timely payments. For determining
working capital, the length of operating cycle and percentage of budgeted production/sales
has been used.
Short-term asset management practices were examined by Jain and Yadav (2000) in India,
Singapore and Thailand. In all three countries, bank overdraft/ cash credit was found to be
the primary mode of managing cash shortages. The research explored the numerous ways
of surplus cash management. With a major investment in marketable securities, paying off
short-term debt, and saving deposits in banks are the major ways. And most of the firms
under sample, offer cash discounts to their customers in India while discounts policies are
rare in Singapore and Thailand.
Grablowsky (1976) found a strong relationship of employment of formal working policies
and procedures with success variables of a firm. The firms with limited financial resources
are more likely to get benefit from surplus internal funds, so an appropriate management of
cash flow and cash conversion cycle is a vital for their financial health (Walker and Petty,
1978). Superior working capital management policies not only shield organizations from
financial turbulence but can be managed to get a competitive edge over the competitors.
Shorter cash cycles with better management of receivables and payables leads to higher
profits and improved liquidity (Johnson & Soenen, 2003). The individual components of
WCM – cash, receivables, payables, and inventory management influence the WCM
performance in many ways (Schilling, 1996). In addition, the decisions regarding any one
WCM component have a significant impact on the other WCM components (Sartoris,
1983).
Most of the research studies are based on secondary data and no significant primary
research has been carried out to probe the working capital management problems,
particularly in Pakistan. The study by Sana and Shah (2006), conducted in oil and gas
sector of Pakistan found a negative relationship between working capital management and
Profitability. Working capital management proxies were cash conversion cycle; days
account receivable and days in inventory, while ‗Gross profit margin‘ was used as a proxy
for profitability. Rehaman and Nasr (2007) confirmed the strong negative relationship
between working capital management variables and profitability in the case of 94 Pakistani
firms. Profitability was measured by ‗Net operating profit‘ this time, whereas average
collection period and average payment period were the additional proxies for working
capital management. Afza and Nazir (2008) found that operating cycle, leverage, return on
asset (ROA) are the internal factors influencing the working capital requirements
significantly in 204 non-financial Pakistani firms. The impact of aggressive/conservative
working capital investment and the financing policies on the firm was also examined by
Afza and Nazr (2009) and found a negative relationship between profitability measures and
degree of aggressiveness.
Working capital practices of international companies operating in Pakistan were explored
by Noreen, Khan, and Abbas (2009) .The focus of the paper was to discover the tools
employed by multinational organizations for international cash management, international
sales and foreign exchange activities. Zubairi (2010) showed the impact of profitability on
working capital management policy in automobile sector of Pakistan and found firms have
shifted their concerns towards low cost and efficient methods related to international
working capital management decisions. A limited attention has been paid to the cash
management, inventory management and trade credit management practices of Pakistani
companies. Also, the knowledge of present working capital policies of Pakistani companies
to find the problem areas in industry, in order to have a further improvement has been
neglected. The present study is therefore, an attempt to bridge this gap.
3. Methodology
To get an insight of working capital management in textile industry of Pakistan, the study
has employed the multiple case study method in order to gain the holistic view of a process
as well as to observe replication between organizations for conceptualization purposes.
The textile industry of Pakistan consists of mainly three types of units, namely spinning,
weaving and composite. The list of all the public limited spinning, weaving and composite
companies was elicited from Karachi Stock Exchange. Using Cluster sampling, all listed
units were first divided into clusters city wise. Three large clusters namely Lahore,
Faisalabad and Karachi were selected for conducting study (Annexure-1).One large, one
medium and one small company are selected from each type of unit (i.e., spinning, weaving
and composite) in every city, resulting in nine companies in total from every cluster. Due to
fewer weaving units in respective clusters, 21 companies from textile industry came under
this study. The size of the company is determined on the basis of ‗Total Assets‘ in rupees,
as reported on Balance Sheet for year 2009.
Evidence is collected from primary and secondary data sources. A structured questionnaire
having both open-ended and close-ended questions covering the areas of working capital
management components was designed. In order to obtain desired information and to have
in-depth discussions related to the issue, personal visits were paid to the corporate offices
of the companies under study. The respondent firm‘s senior finance managers in the
finance department (i.e., chief financial officer, director finance or the senior manager
finance) carrying a minimum of five years experience in the respective organization were
interviewed.
In the light of significant literature and suggestions of finance executives, three working
capital management components namely, cash management, inventory management and
trade credit management were selected (Exhibit-A). The three working capital components
are measured on the basis of forty factors classified into six dimensions, namely, cash
forecasting and management, cash control, inventory management, trade credit policy,
terms of credit extended and credit policies using Analytical Hierarchical Process (AHP) in
order to know the relative weight each component carries, in the formation of working
capital management of textile companies. Priority vectors are developed after doing pair
wise comparisons.
Earning per share (EPS) has been used as a proxy for profitability and regression analysis
has been carried out to determine the relationship between working capital management
and profitability in textile companies of Pakistan for a span of 5 years (2005-2009).
4. Descriptive Statistics
Results from the study provided a snapshot of how effective current working capital
management practices are, in textile industry of Pakistan. Three components cash
management, inventory management and trade credit management were subdivided into
further dimensions. All the questions are designed on the 5-point likert scale from ‗Never‘ to
‗Always‘.
Cash forecasting and management was measured with the help of seven dimensions
(Exhibit-B). Finance executive were requested to rate the predictability of their cash flows
for their company. According to 70% of the companies, cash flows are often predictable
with an exception to volatile raw material prices. Cash flow predictability has aids the
company in financial planning. The dimension has been rated by managers at minimum 1
and maximum 5, on the scale of 1 to 5. 23.8% of textile companies under investigation
have never forecasted their cash flows and 28.6% rarely forecast, though 60% of the
companies reported the presence of an institutionalized budgetary system, which depicts
that textile industry is paying limited attention to cash flow management. How much cash to
keep as minimum cash balance is determined in most of the companies, while the 57% of
the companies under investigation, do not calculate the optimal level of cash required. All
the companies somehow kept minimum cash balances as minimum cash balances are
rated at minimum 2(i.e., rarely) to maximum 5 (always) by the finance managers (Exhibit
A). The lower number of companies with optimal cash balance determination policy is
contributing negatively towards working capital management of the whole industry. Along
with that, almost all the companies in the industry have a standing arrangement for fund
sourcing, which is a plus for effective management of working capital.
Short-term investment policies of textiles companies are explored by inquiring the
respondents about the presence or absence of surplus cash, nature of short term securities
and investment aims behind them. Among all spinning, weaving and composite units,
eighty five percent of finance managers were of the view that they do have surplus cash
and they often invest it in saving deposits. Only 23.8% out of textile companies under study
go for investment in money market instruments like T-bills, rest go for saving deposits and
bonds or stocks. The investment objective behind surplus cash investment for major
proportionate of industry was capital preservation (52.4%) followed by capital appreciation
(41.3%) and current income (23.8%).The smaller organizations use surplus cash to finance
the capital asserts of the organization. For a few companies who are mostly involved in
exports, they have over draft lines or OD lines so they don‘t keep any surplus cash.
Cash control of the company is evaluated by soliciting information about use of systems
and techniques for expediting cash collections and impeding cash disbursements. The
finance executives were asked if they have any special arrangements for accelerating
collections, 38.10% of the textile companies always do deliberate efforts to get received
cheques faster, while 23.80% of companies often use special accelerated cheques clearing
system for getting their cheques faster and in some cases pay extra charges for this
purpose too. The respondents were inquired about their disbursement policy, 85% of the
executives were of the opinion that they never or rarely do some deliberate efforts to slow
down disbursements. The probable reason behind this behavior is that most of them
perceived the variable as related to performance or image of the company or may be
there‘s not much awareness about the positive impact of slowing down disbursements on
working capital management.
Inventory management of the respective companies is determined using two dimensions
(Exhibit-B). Executives were requested to evaluate their inventory record keeping and rate
them on the scale of 1 to 5 from extremely inaccurate to accurate. About 47.60% of the
textile companies accessed their record keeping as average and only five managers out of
twenty one claimed their inventory record keeping system as extremely accurate. Larger
companies usually had more accurate inventory record keeping systems as compared to
smaller ones for the reason that the later might not have sufficient resources to manage
their inventory. 85.7% of the companies under study have an inventory control system.
Inventory record keeping has got maximum rating of 5 (extremely accurate) and minimum
of 2 (Below average) (Exhibit A).
Traditional system relying on past judgment and experience of managers was found to the
most common system of inventory control (used by 71.4 percent of companies). Fewer
companies reported the use of other models like mixed models, periodic review and
continuous models. For Larger companies, the inventory control system used is usually
technical one, based on either mixed models, EOQ, MRP, periodic review models or
continuous models, while the smaller ones mostly relied on demand and need factors or
seasonal factors. Medium sized units use relatively simpler models.
In order to identify the inventory re-ordering pattern, the finance executives were requested
to select whether they use Fixed re-order stock levels and Fixed time reordering. 64.7% of
the companies reported the use of fixed reorder stock levels and it is observed that for
determining these levels, other than experience and judgment (38.1%), 19.0% are relying
on material requirements planning (MRP) on production which would result in accurate
estimations. 35.3% of the companies accounted for the use of fixed time-reordering pattern
and the timings are determined on the basis of Seasonal crop timings (66.7%) and demand
and need factors (36.1%).
Trade credit policies were measured using three dimensions (Exhibit-B). It has been
observed that 71.5% of the companies in industry on average take credit from the
suppliers. Textile industry appears to have a heavy reliance on trade credit, while only 23%
reported the use of other forms of trade credit like hire purchase and leasing etc. from time
to time. Finance managers were asked to describe their use of bank source in order to
finance their working capital needs on 5-point likert scale from ‗Never‘ to ‗Always‘. 38.1% of
the companies always cover their working capital requirements by taking financing from a
bank while 42.9% often do so.
Terms of credit extended were evaluated with the help of five dimensions (Exhibit-B). The
finance executives were asked if they have determined credit limits for their customers or
any one particular customer. On average only 30% of textile companies under study have a
determined credit limit that they extend to the customers and even fewer have determined
credit limits for only one customer (19.01%). On the other hand, almost all the companies
have a determined credit period as stated by company policy and has been minimally rated
at 2 (rarely). More than 70% of the executives said they never extend or rarely extend any
discounts. For the few with discount policies, the motive behind discount extension was to
get more sales. The policy for the payment of payables is at due date for 52.4% of the
textile companies, while 38.1% pay at sight. When asked about the pricing of credit sales
as compared to cash sales, it was found that 47.1% of the textile companies under study
never price their credit sales higher, while 28.6% often and 14.3% always take into account
the cost of additional billing, record keeping, additional expenses and the time value of
capital tied up etc.
The credit control policies of textile companies were investigated using five dimensions
(Exhibit-B). When finance managers were asked about the credit risk evaluation of the
customers, it was found that 95.2% always evaluate the customer‘s credit risk but the risk
assessment techniques vary from company to company. The sub-dimension has got a
minimum rating at 3 (sometimes) and maximum at 5(always) (Exhibit A). About 60% of the
managers only rely on collecting market information and market reputation of the customer
with which they intend to deal. 23% of the managers were of the view that they never
interpret the financial statements of their customers and 33% rarely do so. Only 14.3% of
the executives always interpret the financial data of the customers before granting credit.
Finance executives of the respective companies were requested to rate the extent of
strictness in their criteria, on a 5-point scale from ‗very lenient‘ to ‗very strict‘. For the
companies under study, the criteria were strict for 38.1% and very strict for 38.1% with a
minimum rating of 3 (moderately strict) to 5 (very strict). The most common procedures for
collecting bills receivable for textile companies are phone calls (57.1%) and letters (90.5%).
In comparison with receivable insurance, greater percentage of textile companies factors
their receivables. Only 19.04% of the companies are insuring their receivables while
47.60% managers were of the opinion that they often factor their receivables with a
minimum rating at 1(Never) and maximum at 5 (Always).
The descriptive statistics for all the dimensions are presented in the Exhibit-A.
WCM
Dimensi Sub-dimensions
N
Min
Max
ons
Cash flow Predictability
21 1
5
Forecasting Cash flows
21 1
5
Cash
Presence of an IBS
21 1
5
Forecast
21 2
5
Cash
ing and Determining min. cash bal.
Managemen Mgt.
Determining Optimal Cash
21 1
5
t
Standing Agt. for funds
21 2
5
Surplus Cash Investment
21 0
5
Cash
Control
Inventory
Managemen
t
Trade
Credit
Policy
3.76
2.95
2.87
3.71
Standard
Deviation
0.889
1.692
1.652
1.007
2.62
4.67
3.62
1.396
0.730
1.910
Agt. to expedite collection
21
2
5
4.00
0.837
Efforts to receive cheques
faster
Slowdisbursements
deliberately
Assessment of Inv Rec
Keeping
Presence of Inv Ctrl System
Taking Credit Policy
21
1
5
3.81
1.250
21
1
4
1.76
0.995
21
2
5
3.57
0.978
21
21
1
2
5
5
4.29
3.86
1.309
0.910
Bank source to finance WC
21
1
5
4.05
0.973
Other forms of trade Cr
21
1
4
1.81
1.209
21
1
5
2.29
1.271
21
1
4
1.62
0.921
21
2
5
4.38
1.203
21
1
3
1.76
0.889
21
1
5
2.62
1.717
Evaluation of customer cr 21
risk
Extent of strictness in criteria 21
3
5
4.90
0.436
3
5
4.10
0.768
Interpretin
the
F.S
customers
Factoring receivables
of 21
1
5
2.57
1.469
21
1
5
3.52
1.365
21
1
5
1.81
1.436
Determined credit limit
Trade Credit Terms
Det. Cr. limit for 1 customer
Managemen of credit
t
extende Determined credit period
d
Discount Extension
Pricing credit sales higher
Credit
Control
policies
Mean
Insuring receivables
EXHIBIT-A Descriptive Statistics for the textile companies under study, Valid N (list wise)-21.
AHP based Hierarchy of Working Capital Components
To find out which component is the major contributor towards the performance of working
capital management, analytical hierarchical process (AHP) model is designed. AHP is a
multi-dimension decision making technique to categorize a number of choices by
considering a given set of dimensions. Priority vectors are developed after doing pair wise
comparisons. We developed the hierarchical representation of the problem by defining
levels of components and sub-components perceived as most important by the finance
managers.
Pair-wise comparisons of each dimension are made. Components are assigned different
degrees of importance, on the scale of 1 to 5 (1 = Never, 5 = Always). For example, if a
manager replies that dimension A is absolute important than dimension B, A is said to have
a relative weight of 5 times that of B. Then, a pair wise comparison matrix is created for
each dimension of service quality. This is done by dividing each element of the matrix by its
column total.
The EIGEN value is calculated to determine the relative weight of each component in
relation to the one immediately above in the hierarchy. The priority vector is established by
calculating the row averages. each component. The design of the AHP hierarchy must
satisfy the goal of developing a model that allow respondent to decide which factor they
regard most important in working capital management in textile companies of Pakistan
(overall as well as separately). The consistency of the created pairs is examined. The
consistency ratio is used to check whether a component can be used for decision-making.
If the CR value of the component is less than 0.1, the criterion is considered for acceptable
consistency, while bigger value means that it should not be used for estimating the priority
vector. Later, the sub-component priorities are combined to disclose the most important
sub component for each component in order to develop an overall priority ranking. In order
to set weights of the dimensions in a hierarchy, we prefer the geometric means, as the
most common approach to set priorities. It must be noted that the weights for component at
each level, within their parent component sum to 1 (called local priorities).
Forecasting cash flow (12.5%)
Cash flow Predictability (9.77%)
Presence of IBS (8.95%)
Det. minimum cash (12.40%)
Cash Forecast &
Mgt. (35.89%)
Det. optimal cash (11.29%)
Standing Agt. for funds(33.71%)
Cash
Management
(36.86%)
Surplus cash Investment (11.31%)
Agt. to expediate collection 34.9%
Working
Capital
Management
(100%)
Cash Control
(64.10)
Getting cheques faster (54.64%)
Slow disbursements (10.37%)
Inventory
Management
(38.62%)
Assessment inv rec keeping (29.02%)
Presence of inv ctrl system (70.97%)
Taking Credit (37.97%)
Trade credit policy
(22.52%)
Bank source to financeWC(48.8%)
Other forms of trade cr (13.13%)
Determined credit limit (5.87%)
Det cr limit for 1 customer(8.47%)
Trade Credit
Management
(24.50%)
Terms of credit
extended (31.05%)
Determined credit period(44.69%)
Discount extension(20.42%)
Pricing cr sales higher(20.53%)
Evaluating custo cr risk(31.25%)
Credit control
policies (46.41%)
Extent of strictness (28.58%)
Interpretin F.S (8.43%)
Insuring receivables (9.43%)
Factoring receivables( 22.27%)
1
Exhibit-B Analytical Hierarchical Process based Hierarchy of Working Capital Management
Components.
1
IBS-Institutionalized Budgetary System, F.S-Financial Statements, Det- Determined, Agt-Arrangement, , Cr-Credit Risk, Rec-record.
At this point, the consistency index is calculated by the following equation CR = CI/RI.
Consistency index is calculated by the following equation CI = LEMDA max-n/n-1, where n
is the number of sub-dimensions of According to AHP outcomes, inventory management
plays the most significant role in superior working capital management performance of
textile firms with a highest contribution of 38.6%, while cash management and trade credit
management follows with 36.8% and 24.5% respectively. Working capital deals only with
the current assets of the firms and inventory is more than fifty percent of current assets in
textile industry. A thorough analysis of sub-elements in inventory management revealed
that presence of the inventory control system is the driver of better working capital
management.
Ranking of Working Capital Management dimensions for Textile Sector
A hierarchical index based on global priority weights was developed after conducting a
thorough data analysis. These priority weights indicate their relative importance towards the
measurement of working capital management. Global scores for these sub-dimensions are
arranged in descending order of their relative score. Based on significant cut off values, we
have classified them in three tiers (Table-1).The weights provided in Table-I illustrate the
relative importance of sub-dimensions provided by finance executives for working capital
management in textile companies.
Table-I Ranking of Working Capital Management dimensions for Textile Sector in Pakistan
#
Dimensions
Global Priority
Weight
Tier-1 1.
Presence of Inventory Control System
0.274152
2.
Assessment of inventory record keeping
0.112128
Tier-2 3.
Deliberate efforts to clear cheques faster
0.072311
4.
Special arrangements to expedite collection
0.046291
5.
Standing arrangement for sourcing funds
0.044614
6.
Evaluating credit risk before granting credit
0.03556
7.
Determined credit period
0.034021
8.
Extent of strictness in criteria
0.032516
9.
Bank source to finance Working Capital
0.026985
10.
Factoring receivables
0.025341
11.
Taking Credit
0.020957
12.
Forecasting cash flow
0.016603
13.
Determining minimal cash balance
0.016413
14.
Pricing credit sales higher than cash
0.015629
15.
Discount extension
0.015547
16.
Determining optimal cash balance
0.014944
17.
Slow disbursements deliberately
0.013735
18.
Predictability of cash flow
0.012934
19.
Investment of surplus cash
0.012934
20.
Presence of an Institutionalized Budgetary System
0.011857
21.
Insuring receivables
0.010738
Tier-3 22.
Interpreting Financial Statements of customers
0.009601
23.
Other forms of trade credit
0.007251
24.
Determined credit limit for one customer
0.006448
25.
Determined credit limit for customers
0.004469
Most important factors for working capital sub-dimensions in Tier-1 belong to level one
inventory management domain. Tier-1 indicates that most significant working capital
management variables are presence of inventory control system and better inventory
record keeping with the highest priority weights of 0.274 and 0.112 respectively. This
clearly indicates that according to finance executives inventory control system and
inventory record keeping are areas of primary concern. Results imply that deliberate efforts
to clear cheques faster and special arrangements to expedite collection are assigned
higher position by the finance executives.
Tier II of working capital management in textile sector consists of cash management and
cash control related dimensions. Tier III includes factors like determined credit limit for all
customers and for a single customer. Presence of these trade credit factors in third tier
reveal that these factors are least significant in managing working capital by finance
managers
Relationship of WCM components with Size of the Company, Years of Manager’s experience,
and Type of Textile Unit
Analysis of Variance confirmed that cash forecasting and management (representing seven
variables) is significantly dissimilar in different size of companies in textiles industry at a
significance level of 0.001. Post Hoc tests showed that large companies are better in cash
forecasting than medium size companies, which are in turn better than small size
companies. So as the size of the company increases, cash management improves. Multiple
comparisons showed that large and small sized companies are highly different in cash
forecasting with significance level of 0.000 and a greater mean of larger companies clearly
depicted that large companies have a better cash management and forecasting as
compared to small size companies. This is due to the fact that the large companies are
found to have an institutionalized budgetary system and appropriate forecasting
techniques, while most small companies don‘t even bother about forecasting their cash
flows. The finding is empirically verified with one-way ANOVA. Forecasting cash flows are
significantly different with respect to size with a significance level of 0.007. Institutionalized
budgetary system also has a significant relationship with the size of the company with a
significance level of 0.001.
Another significant finding was that as the years of experience of managers‘ increases,
cash forecasting decreases and the more they rely on judgment and experience. Post hoc
tests showed that managers with an experience of 5-7 years more forecast their cash flows
as compared to the managers having an experience of greater than 10 years. The reason
behind is with the increasing years they gain some invaluable experience and industry
knowledge. Their increased confidence results in lesser reliance on cash forecasting
techniques and more on their own judgments.
Interestingly, one-way ANOVA show that textile companies irrespective of their size go for
expediting their collections but only some large composite units slow down their
disbursements deliberately. The reason behind is that control of cash is an essential
component for every firm which it cannot survive. So cash control policies are tighter for
every firm equally irrespective of the size of the firm.
No significant differences were observed in cash management with respect to the type of
unit. While with respect to the cities nothing particular was observed. Working capital
management is managed in a similar way with respect to the cities too. A significance level
of 0.05 with analysis of variance indicates that larger textile companies were far better in
inventory management as compared to small size companies. With respect to cities, job
designation and manger‘s years of experience, there was no major differences in spinning,
weaving and composite units (Exhibit C).
With respect to size, terms of credit extended to the customers is highly significant at a
significance level of 0.000. While examining their post hoc tests, it was found, larger
companies are different from the medium sized companies with the significance level of
0.018, and even more different as compared to smaller size companies with a significant
level of 0.000. So, we can conclude, that greater the size of the company, better the terms
of credit extended are. Larger companies have a determined credit period for customers as
well as for one single customer. They always have a determined credit period and they
always price credit sales higher as compared to cash sales. Smaller companies rarely have
determined credit terms other than credit period, which negatively affects working capital
management of the company.
Another interesting finding was that discount extension is more common in larger units as
compared to medium and smaller units. Larger companies are more interested in getting
more sales and expediting collection by extending discounts to their customers. Also, the
larger companies price credit sales higher than cash sales as compared to smaller and
medium sized companies. The reason behind is in small companies in the name of finance
department, there are only two or three finance managers and they don‘t have a very
formal set up. And as the size of the company increases, its sales increases and in turn,
companies develop more sophisticated ways to manage credit. It has been observed that
there is no difference in terms of credit extended with respect to the location or city in which
it is located. While with respect to type of unit, we found spinning units have a more
determined credit limit and a more determined credit period as compared to the composite
units.
Relating the dimension ‗terms of credit extended‘ with managerial years of experience, the
results were significant for ‗determined credit limit for one customer‘ and ‗preference of
credit sales above cash sales‘. Examining the post hoc tests for the companies, it was
observed that managers with lesser years of experience determine credit limits for every
customer and also put an effort to expedite cash collection. It appears that because the
executives with 5-7 years of experience have a university degree. Further research can be
carried out in this area to explore where the level of education has anything to do with
formulation of trade policies in the textile firms or not (Exhibit-C).
With one-way ANOVA, trade credit policy showed significant differences respect to size.
Trade credit policy is different for large size firms as compared to smaller ones (Exhibit-C).
Post Hoc tests indicate that ‗other forms of trade credit‘ are related with company size at a
significance level of 0.024. Larger companies along with taking credit from the suppliers
take other forms of trade credit too for financing. These other forms are leasing in most of
the cases and a form of hire purchase. A significant relationship has been found between
use of banking source and size of the company. Use of banking source is more common in
larger companies too while most of the small textile companies are of the view that tend to
rely more on the personal sources of directors and don‘t prefer a bank source.
‗Credit control and collection policies‘ when correlated with size of the company, showed a
strong relationship at a significance level of 0.038. Post hoc tests have shown that the
major difference is in credit control policies of larger companies from the smaller
companies. Larger companies have more customers and greater sales so they have to
evaluate the credit risk of customers more strictly as compared to smaller ones. Medium
size companies showed no significant differences. Even in small size companies, some
companies have very strict criteria. After evaluating the credit risk by credit score card, 5-C
and evaluation of customer‘s financial statements, they check the market reputation of the
company. While there are a few who use all kind of mechanisms, majority bases its
decisions on previous relationships with the customers or bank references. This is evident
through one-way ANOVA results too.
Evaluation of financial statements of customers also showed a strong relationship with size
of the company at a significance level of 0.015, while the evaluation of credit risk was found
insignificant, as all the organizations of all sizes evaluate the credit risk of their customer.
Also, the extent of strictness of criteria had a strong relationship with size at a significance
level of 0.057. Relating the credit control and collection policies with the type of unit
(spinning, weaving and composite), we found that the criteria are stricter for the composite
units as compared to spinning and weaving units.
The receivables were also insured mainly by the large size companies. Smaller ones had
most doubtful and unsecured account receivables. The results became evident after
empirical testing where, insuring variables had a strong relationship with the size of the
company at a significance level of 0.051 using one-way ANOVA. With respect to size, there
are no significant differences in factoring of receivables of the company. Insuring of
receivables was found to have a relationship with the type of unit. Composite units insure
their receivables more as compared to spinning and weaving units. City or location of the
company has no impact on the credit control and collection policies of the company. The
mangers years of experience are also correlated with credit and control policies. Greater
the experience of managers, lesser they interpret the financial statements of the customers.
And more they rely on unsophisticated ways. The analysis of variance showed a
significance of 0.000.
Dependent Variables
Cash Forecasting & Mgt. (Computed)
Forecasting Cash flow
Deliberate efforts to slow disbursements
Cash Forecasting and Management
Inventory Mgt. (Computed)
Assessment of inventory recordkeeping
Presence of IBS
Terms of Credit (Computed)
Determined credit limit
Determined credit period
Discount Extension to the customers
Pricing credit sales higher
Determined credit limit for 1customer
TCR Policy (computed)
Taking other forms of trade credit
Use of Banking source to finance capital
Using trade credit
Credit control and collection policies (Comp)
Insuring receivables
Extent of strictness in criteria
Evaluating the financial statements
Credit control and collection policies (Comp)
Factoring of receivables
Extent of strictness of criteria
Insuring of receivables
Interpretation of customer‘s F.S
Independent Variables
Size of the company
Size of the company
Size of the company
Years of Experience
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Years of experience
Years of experience
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Size of the company
Type of textile unit
Type of textile unit
Type of textile unit
Years of Manager Exp
Years of Managers exp
Significance
0.001
0.007
0.026
0.057
0.051
0.021
0.001
0.000
0.021
0.025
0.001
0.025
0.094
0.021
0.024
0.015
0.0185
0.038
0.051
0.057
0.015
0.041
0.091
0.076
0.005
0.000
Exhibit-C One-way ANOVA results for Cash management, inventory management and trade credit
management components
Relationship of Working Capital Management components with Profitability
Linear regression analysis is carried out in order to find the impact of working capital
management on earnings of the company. The primary data measuring three working
capital components; cash management, inventory management and trade credit
management, categorized into six dimensions are correlated with profitability measures.
Earning per share is used as a proxy for profitability. EPS is considered dependent
variable, while the working capital components are taken as independent variables.
Cash management is subdivided into two dimensions, cash forecasting and cash control.
Regression analysis shows a significant relationship between cash management and
earning per share with an R square of 0.463. Further penetration of the two variables
representing cash management makes it evident that cash forecasting is having a
significant positive impact on earning per share of any organization, with a significance
level of 0.040 (Table-1).
Inventory management was also found to have a significant relationship with the earning
per share and earning before interest and tax, of the organizations with an R square of 0.35
and a significance of 0.38 respectively. Trade credit management was further subdivided
into three variables; trade credit policy, terms of credit extended and cash collection
policies. Earning per share is significantly with R square of 0.312 and at a significance level
of 0.021.Further the in-depth look at coefficients show that credit terms and collection
policies have a strong relationship with earning per share of the organization at a
significance level of 0.012 and 0.012 respectively. (Table-2)
Independent Variable
Dependent Variable
Significance
EPS
EPS
EPS
0.020
0.050
0.051
Cash Management
Inventory Management
Trade credit Management
Table-1 Relationship of working capital components with Earning per share (EPS).
Independent Variable
Cash Forecasting
Cash Control
TCR policy
Terms of credit
Collection policies
Dependent
Variable
EPS
EPS
EPS
EPS
EPS
Significance Beta
0.040
0.012
0.042
0.002
0.048
0.582
0.577
0.273
0.718
0.318
Standard
error
2.397
1.930
1.377
3.091
2.923
Table-1 Relationship of sub-components with Earning per share (EPS).
5. Conclusion
Working Capital management practices in textile industry of Pakistan are not very efficient.
Textile industry is one of the largest industries and working capital management which
should be one of the primary concerns of finance executives is given limited attention due
to the short-term nature of investment and financing.
Cash flows are predictable for most of the companies. One half of the industry doesn‘t have
any institutionalized budgetary system and cash forecasting is done by a few. Many of
them determine a minimum cash balance but the optimal cash to be kept is considered
important. Almost all the firms have a standing arrangement for funds. Surplus cash is
usually invested in saving accounts and in some organizations stocks and bonds. Capital
preservation and income are the major investment aims in spite of liquidity.
Due to absence of inventory control systems in majority of the firms with no effective reordering techniques, there appears a serious need to review and strengthen the inventory
management policies and based on revised inventory controls an appropriate re-ordering
system should be designed.
Textile companies are remarkably better at trade credit management and most of the
companies have special mechanisms to expedite collections and cheques. Discount
extension is not common though, but they have determined credit limits and credit periods.
A little amount remains uncollectible and not much is spent on collection of receivables. But
on the other hand, credit sales are not priced higher than cash sales. They always evaluate
the credit risk of their customers but the assessment techniques become more informal in
the case of experienced finance executives. It is observed that composite units have better
trade credit management as compared to weaving and spinning units.
Putting it together, larger spinning, weaving and composite units have superior working
capital management practices as compared to the smaller and medium textile units
(spinning, weaving and composite).The dilemma of the industry is the mindset of managers
always relying on past experience and traditional judgment. A very few have adopted the
sophisticated techniques for cash management, inventory management and trade credit
management.
All components have a significant impact on earning per share and EBIT of the respective
organization as illustrated by linear regression analysis with cash management having the
strongest impact and are found to be critical decisive in the success or failure of a textile
firm.
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