CHAPTER-4
ar
PRESENTATION AND ANALYSIS
OF DATA
el
 Introduction of Sample Cement Industries
 Evaluation of Inventory Management Performance
 Inventory Turnover Ratio
Es
t
 Days of Inventory Holding (DIH)
 Size of Inventory
 Linking Inventory Management to Profitability
 Statistical Analysis
 Regression Analysis
 Analysis of Primary Data
129
130
ar
el
Es
t
CHAPTER-4
PRESENTATION AND ANALYSIS
OF DATA
Inventory is one of the key determinants of the productivity of cement
industry. The productivity of the cement industry is judged by its capacity
ar
utilization and economical use of major inputs such as limestone, coal,
gypsum, stores and spares, and power consumption per tonne of cement
production. Inventory management plays an important role in the cement
industry both in production of new assets and operational maintenance of
el
existing assets. Therefore, the continuous availability of inventory is a prime
requirement for the uninterrupted working and better capacity utilization.
Against this backdrop, a modest attempt has been made to analyze the size
Es
t
and relationship of inventory with various items in the balance sheet of the
selected cement manufacturing companies in Nepal, during the Nine years
period commencing from 2001-02 to 2009-10. So this chapter deals with the
presentation and analysis of data following the research methodology. In the
course of analysis, data gathered from various sources have been inserted in
the tabular form according to their homogeneous nature and they are
analyzed using financial and statistical tools. Finally the result obtained from
the analysis has been interpreted on the basis of some conventional
standards.
4.1 Introduction of Sample Cement Industries
4.1.1. Udayapur Cement Industry Limited
It is the largest cement industry in Nepal which was established in 31 Jestha,
2044 B.S. (14 June 1987 AD) at Jaljale, Triyuga Municipality ward No. 11 of
Udayapur district although, it started it’s commercial production from Poush
131
2049 B.S. (November 1992 AD). It was incorporated under the Company Act
2021 (now Company Act 2053) with the share investment of Nepal
government and Overseas Economic Co-operation Fund (OECF)’s assistance to
meet the foreign currency requirement. OECF has contributed Japanese Yen
18770 million and Nepal government has contributed Rs. 450 million to its
total paid up equity capital. The main objective of establishing this industry is
to make substantial contribution to the process of development of Nepal by
ar
producing highest quality of cement through the maximum mobilization of
raw materials and manpower available in the country. The specific objectives
of the industry are as follows.
1. To produce the basic import substantial and export quality cement based
el
on available resources in the country.
2. To manage for an extensive market
3. To enable the country become self reliant by supplying to the national
Es
t
requirements.
4. To enhance industrial and economic development.
5. To provide employment opportunities.
The capital structure of the industry is as follows:
Table No. 4.1
Capital Structure of Udayapur Cement Industry
Sources
Amount (Rs. in ‘000’)
Equity share
4437512
Preference share
3204300
Government debt
2556200
The industry has production capacity of 840 metric tonne of clinker per day
and subsequently 277200 metric tonne of cement per annum. Despite its
132
rated annual production capacity the industry, due to various reasons, is not
being able to yield its full-fledged production from the very beginning of its
establishment. The average capacity utilization during the 15 years period is
about 45 percent means it produces about 125,000 metric tonne per year and
the industry alone meet about 15 percent of the total demand of the nation.
(The estimated annual requirement of cement in the country is 2.5 million to
per year.)1 Until 2009 (2065-66 BS) this industry has made the cash payment
ar
of 1500 million rupees to Nepal Government as capital and interest.
To operate in its full capacity, the industry requires the following quantity of
raw material and fuels.
Table No. 4.2
el
Annual Quantities of Raw Materials and Fuel of Udayapur Cement Industry
Particular
Utilities
Units
Remark
1
Limestone
330000
Metric ton
Per year
2
Clay
57000-82500
Metric ton
Per year
3
Sand
21000
Metric ton
Per year
4
Iron ore
4000
Metric ton
Per year
5
Gypsum
10500
Metric ton
Per year
6
Coal
50000
Metric ton
Per year
7
Jute bags
5540000
Piece
Per year
8
Furnace oil
12000
Kilo liter
For contingent use
9
Electricity
10000
Kilo watt
Per year (Approx.)
10
Diesel
900
Kiloliter
Per year (Approx.)
Es
t
S.N.
Source: Udayapur Cement Industry Ltd.- At A glance.
Among the above mention raw materials the major raw material for cement
production i.e. limestone is acquired from Sindali limestone quarry district.
Similarly Clay and Sand are available in the local area. But the industry has to
133
import coal, gypsum, iron ore and furnace oil from other countries,
particularly from India.
The industry produces high quality “Gainda” trade mark cement that has
received certificate of quality standard (NS mark) from Nepal government.
Quick setting, highly durable and triturated characters are other features of
the cement produced by this industry.
ar
4.1.2. Hetauda Cement Industry Limited
The Hetauda cement industry ltd. is situated at Lamsure of Hetauda
municipality, Makawanpur district of Narayani zone about 80 Kilometers from
the capital city of Kathmandu. It was established in 2033 B.S. (1976 A.D) under
el
the company act 2021 (now company act 2053). The industry covers about
149 bighas (249.9 acres) of area. Basically, an import substitution industry
totally dependent on locally available raw materials-lime stone- the HCIL was
Es
t
established to make the country self reliant on such an important construction
material as cement and there by facilitate the acceleration of the tempo of
the all around development of the country. The industry has generated direct
employment opportunities for about 1100 persons and indirectly benefiting
about 6000 persons.2
It has an installed capacity of producing 800 metric tonne of cement or 16000
jute bags of cement a day i.e. 260000 metric tonne or 5.2 million jute bags of
cement per year. In this way the industry is helping to meet substantial
percentage of the present cement requirement of the country. In HCIL
marketing of Cement all over the country was done through three
Government's agency namely National Trading Ltd., Sajha Bhandar and Tara
Gaon Bikash Samiti and 62 private dealers. At present about 270 dealers are
engaged in sales & distribution of cement.
134
By way of sales tax from the very year of the start of the commercial
production of cement and by way of excise duty after three years of the
production the HCIL is contributing substantially to the national exchequer.
The average capacity utilization of this cement industry is about 45% during
the last 20 years period.
It was financed with the share investment of Nepal government and the loan
assistance of the Asian Development Bank (ADB). The industry also used credit
ar
from national and international commercial banks. Of the total cost of 1389
million rupees, ADB has provided a credit of 732 million rupees while Nepal
government has invested 206 million rupees in shares. Of the rest 243 million
rupees have been received as short term loan from Nepal bank limited and
el
208 million rupees from other international commercial banks.
Table No. 4.3
Annual Quantity of Raw Materials and Fuels
Es
t
of Hetauda Cement Industry Ltd.
Materials
Quantities (metric tons)
Limestone
396000
Clay
20000
Coal
50000
Gypsum
12000
Iron ores
4000
Jute bags
5.2 million pieces
The major raw material limestone is acquired from the Bhaise where a deposit
of about 10 million tons of limestone is estimated. Similarly about 10 million
tonne of high grade limestone is also estimated at Okhre danda some 8 km
from Bhaise.
135
4.2 Evaluation of Inventory Management Performance
Inventory management is a part of overall management process of an
organization. It is the formal management of the organization in term of
minimizing investment on inventories and maximizing the organization’s
overall earnings. Profit is the major element of each and every business
endeavor for its existence, survival and to fulfill the organizational
expectations. To achieve the profit objective one of the major task of the
ar
organization is to manage inventories efficiently. An efficient inventory
management system is dependent upon the development of appropriate
planning and control techniques and proper implementation of those
techniques. Inventory control primarily concerns with the administration of
el
the established policies and procedures. Thus, in inventory control involves
maintenance of inventory records for the physical and accounting control of
the inventories. Inventory management function involves the development
Es
t
and administration of policies, systems and procedures which will minimize
total cost relative to inventory decisions and related functions such as
customer service requirements, production scheduling, purchasing, traffic
etc.3
4.2.1
Structure of Inventories in the Selected Cement Industries
of Nepal
The composition of inventory is mostly affected by the nature and type of
business. In the trading concern the major portion of total inventory would
consist finished goods and they would have little investment in the raw
materials, work-in- process and spare parts but a manufacturing organization
has to invest in each component of inventory for the smooth and
uninterrupted production and sale. A manufacturing firm generally holds four
types of inventories viz., raw materials work-in-process, finished goods and
spare parts.4 The share of each component in the total inventory varies from
136
industry to industry. Generally in public enterprises like cement industry there
is high investment in store and spare parts in comparison of raw materials.
The structure of inventory in the two- cement industries of Nepal divided into
four categories.
(i)
Raw material- It includes Limestone, Coal, Fuel, Iron ore, Gypsum and
bags.
(ii)
Semi finished goods- It includes clinker and raw meal.
goods.
ar
(iii) Finished goods- cement produced by the industry denotes finished
(iv) Spare parts and store- Generally, store and spare parts denotes loose
tools and spare parts of machine but in the cement industry spare part
el
include general store in mine and plant, mechanical and electrical store
in mine and plant, explosive, Japanese lubricant and fuel store in plant
and mine.
Es
t
4.2.2 Structure of Inventory
The size of investment in inventories in the two- public cement industries are
different due to their production capacity and inventory management policies.
In public enterprise like cement industry, there is high investment in stores
and spare in comparison of other type of inventories. In the cement industries
raw materials includes coal, gypsum, iron ore and lime stone and in-process
goods consists crossed limestone, raw mill and Clinker. Therefore, in the
context of cement industry raw material and work-in-process are basically
same because in the production of cement inputs should pass through
different stages of production. The composition of various type of inventory in
the public cement industries of Nepal is presented below.
137
Table No. 4.4
Composition of Inventory Investment in UCIL (Rs. in millions)
Fiscal
Year
Types of Inventory
Raw materials Work-in Process
%
Amount
%
Amount
%
Spare Parts &
Stores
Amount
Total
%
26.98
7.1
35.8
9.42
26.22
6.9
292
76.84 380
2002-03
33.86
8.54
42.52
10.72
24.3
6.13
295.75
74.6
396.5
2003-04
58.29
12.61 58.68
12.7
55.8
12.07
290.2
62.78 462.2
2004-05
93.32
18.92 50.88
10.31
43.4
8.8
305.8
62
493.2
2005-06
56.3
11.78 53.8
11.25
41.2
8.62
326.59
68.38 477.89
Es
t
el
2001-02
ar
Amount
Finished Goods
2006-07
77.74
14.66 61.2
11.54
52
9.8
339.7
64.04 530.4
2007-08
89.66
14.03 79.1
12.38
85.24
13.34
389.51
60.97 638.84
2008-09
150.3
19.94 86.72
11.50
115.6
15.33
412.75
54.75 753.77
2009-10
155.8
19.07 97.4
11.93
112.6
13.78
450.79
55.20 816.59
Mean ( X ) 82.47
62.9
61.81
344.78
S.D(σ)
43.31
18.83
31.63
49.35
C.V.
0.53
0.30
0.51
0.14

138
139
ar
el
Es
t
From the above table No. 4.4 and chart No. 1 it is clear that in the UCIL the
size of three types of inventories (raw material, WIP & finished goods) were in
raising trend throughout the period of study except in year 2005-06. The
materials consumption in the industry is erratic. This indicates that there is no
sound purchasing policy in the organization the figure of raw material
inventory was Rs. 26.98 million in 2001-02, which increase every year and
became Rs. 155.8 million in year 2009-10 except in year 2005-06 where the
ar
value of raw materials was Rs. 56.30.
The average size of raw material was Rs. 82.47 Million, standard deviation was
43.31 and C.V. was 53%. The rate of increase in the size of raw material
according to trend line equation was Rs. 27 million which is very high. The
el
percentage of raw material inventory to total inventory was also in raising
trend except in year 2005-06. The stochastic trend of material figures during
the study period indicate that the industry was not using modern
Es
t
procurement techniques like properly maintained stock level, practice of
safety stock and economic order quantity.
Similarly, the size of Work-In Process (WIP) inventory and percentage of WIP
to total inventory were in increasing trend throughout the study period. It was
Rs. 35.8 million in year 2001-02 and at the end of study period (2009-10)
became Rs. 97.4 million. The average value of work-in- process inventory was
Rs. 62.9 million, the percentage of variability was 18.33% and co-efficient of
variation was 30%.
Cement represents finished goods in this industry, as there is high demand of
Nepali cement product in the Nepalese cement market therefore, the
proportion of finished goods inventory in the total inventory is comparatively
small but the trend of finished goods inventory during study period was
increasing. The figure of finished goods inventory was Rs. 26.22 million in
2001-02 and became Rs. 112.6 million in 2009-10. The percentage of finished
140
goods inventory to total inventory was also in increasing trend which was
6.9% in 2001-02 and 15.33 in 2008-09.
The stores and spares generally represent spares parts of machine in
average manufacturing industries but in the cement industry it includes
general store in mine and plant, mechanical and electrical store in mine
and plant, explosive, Japanese lubricant and fuel store in plant and mine
is very high.
ar
therefore, the value of stores and spares inventory in the cement industry
Almost all spare parts brought from third country so their composition and
stocking policies are different from that of raw materials and consumable
el
finished goods. Share of stores and spares parts to total inventory was very
high in the beginning of the study period i.e. Rs. 292 million out of Rs. 380
million or 76.84%. It was in decreasing trend thus, at the end of study period it
became Rs. 450.79 million out of Rs. 816.59 million or nearly 55%. The
Es
t
average size of spare parts and stores was 344.78 and C.V. was 14%. The rate
of decrease in the size of spare and stores was Rs. 8.6 million per year
according to regression line equation.
141
Table No. 4.5
Size and Composition of Inventory Investment in HCIL ( Rs. in millions)
Fiscal Year
Types of Inventory
Raw materials
Work-in
Finished Goods
Spare Parts &
Process
%
Amount
Stores
%
Amount
%
2001-02
42.66
18.03 29.54
2002-03
52.59
20.89 24.56
2003-04
76.57
30.10 27.28
10.72 12.59
4.95
2004-05
64.52
26.92 15.59
6.5
%
12.48 31.42
13.28 132.94
56.19 236.56
9.75
11.2
146.34
58.13 251.72
138.07
54.28 254.33
11.22 132.65
55.34 239.66
12.62 9.07
3.94
134.95
58.69 229.93
el
28.2
Es
t
26.89
2005-06
56.8
24.7
2006-07
87.53
33.33 31.18
11.87 10.41
3.96
133.45
50.82 262.56
2007-08
100
35.27 30.78
10.85 10.7
3.77
141.96
50.08 283.45
2008-09
111.93 32.36 61.97
17.92 23.09
6.67
148.81
43.03 345.79
2009-10
136.27 36.01 73.15
19.33 18.23
4.81
150.7
39.83 378.35

29.04
Amount
ar
Amount
Total
80.92
35.89
18.94
139.92
S.D(σ)
29.0
17.69
8.17
6.76
C.V.
0.36
0.49
0.43
0.048
Mean ( X )
142
143
ar
el
Es
t
The size of various types of inventories in the HCIL during the study period
was not found in the homogeneous trend. The size of raw material was
showing peak and troughs. It was Rs. 42.66 million in 2001-02 which kept
increasing, for the following two year then decreased for the next two years,
finally increasing back again for the last four years i.e. it was in increasing
trend. The figure of raw material inventory was Rs. 52.59 million in 2002-03,
Rs. 76.57 million in year 2003-04 then showing decreasing trend for the year
ar
2004-05 and 2005-06 with value of Rs. 64.52 million and Rs. 56.8 million and
then finally for the last three years it was in increasing trend so it became Rs.
150.3 million in year 2008-09 but at the end of study period it decreases to Rs.
136 million.
el
The average size of raw material was Rs. 80.92 million, standard deviation was
29 and the fluctuation of 29% in the raw material was seen during the study
period, which shown by the C.V. of the industry. The rate of increase in the
Es
t
size of raw material according to trend line equation was Rs. 12 million per
year which seems reasonable in comparison of total inventory holding. The
percentage of raw material inventory to total inventory was also in rising
trend except in year 2004-05 and 2005-06.
Similarly, the size of work-in process inventory and percentage of WIP to total
inventory were in increasing trend throughout the study period except in year
2004-05. It was Rs. 29.24 million in year 2001-02 and at the end of study
period (2009-10) became Rs. 73.15 million. The average value of work-inprocess inventory was Rs. 35.85 million, the percentage of variability was
17.69 and co-efficient of variation was 49%. The trend of finished goods
inventory in the HCIL was stochastic i. e. in year 2001-02 Rs. 31.42 million then
in 2002-03 and 2003-04 decrease to Rs. 28.2 million and Rs. 12.59
respectively. After then in the year 2004-05 it again increase to Rs. 26.89
million. Then again in 2005-06 it decrease to Rs. 9.07 million and for the rest
144
two years it was in the minor increasing trend but in the year 2008-09 it
increased dramatically and became Rs. 23.09 million. In the final year the
amount of finished goods inventory decreased to Rs. 18.23 million. The
percentage of finished goods inventory to total inventory was also in
stochastic trend indicating mostly decreasing patterns.
Percentage of stores and spare parts to total inventory in HCIL was
comparatively high in the beginning of the study period i. e. Rs. 132.94
ar
million out of Rs. 236.56 million or 56.10%. It was in decreasing trend thus,
at the end of study period it became Rs. 150.7 million out of Rs. 378.35
million or about 40%. The average size of spare parts and stores was Rs.
139 million, standard deviation was 6.76 and CV was 4.8%. The rate of
el
decrease in the size of spares and stores was Rs. 8.6 million per year
according to regression line equation.
The composition of various components of inventory is determined
Es
t
according to the nature and type of organization therefore it varies
industry to industry. Hence, balance has to be maintained to control the
total investment in inventories but accumulation of high percentage of
spare parts in the total inventories is a common problem in the cement
industries. Stores and spare parts in Nepalese cement industry are
imported from and outside of India which takes long time to procure and
their cost is also very high. Due to these reasons the percentage of stores
and spares is relatively high in comparison of other type of inventory.
Inadequacy of stores and spares might interrupt production process and
excessive holding involve heavy financial and administrative burdens on the
firm which ultimately decreases profit.
145
4.3 Inventory Turnover Ratio
After the analysis of distribution of the inventories amongst the different
components the next important aspect of inventory management is to seek
answer about the utilization of the inventories investment. The general
measure of assessing the utilization of the inventory investment is to compute
inventory turnover because the review of the behavior of turnover ratios over
ar
a period of time can indicate the utilization of the inventory.5
The inventory turnover ratio measures a company’s efficiency in managing its
investment in inventory. The ratio shows the number of times the inventory is
turned over during the year. It indicates how quickly inventory is sold. Higher
el
the ratio, the more efficiently an enterprise has managed inventory, other
things remaining the same.6 In other words inventory turnover ratio measures
the rate of speed with which inventories move through and out of the
enterprise. Inventory turnover establishes a relationship between the sales
Es
t
during a given period and the average amount of inventory outstanding during
the same period and also establishes a relationship between average
inventories to sales. Inventory turnover indicates the speed with which assets
are being converted into sales. Turnover of inventory directly affect the
profitability of the firm.
The higher is the turnover, the greater is the profitability of the firm and vice
versa. A higher turnover also indicates that the firm has conducted more
business with less amount of inventory. Inventory turnover acts as an
indicator of the liquidity of inventory.7 Ordinarily, the higher the inventory
turnover, the smaller the amount of working capital tied-up in the inventory
and more current stock of merchandise, leading larger the amount of profit.
Conversely a very high level of inventory turnover may be the result of very
low level of inventory which may cause frequent stock out problem, even
146
though high inventory turnover ratio is always desirable in normal condition.8
There are two approaches of analyzing inventory turnover.
4.3.1 Cost of Goods Sold to Inventory Ratio
The inventory to sales ratio measures the percentage of inventories the
company currently has on hand to support the current amount of sales. The
ratio is computed by dividing the period's cost of goods sold by the average
ar
inventory balance. The denominator, average inventory, is determined by
adding beginning and ending inventory and dividing by two. Preferably, the
average inventory value should be calculated by summing the monthly figures
during the year and divide by twelve. If monthly data are not available one can
el
add the beginning and ending figures and divide by two.
Both methods adjust for growth but not for seasonal effects.9 In this study due
to the lack of monthly data of the inventory annual inventories data is taken
Es
t
for the computation of inventory turnover. A single figure of inventory
turnover is meaningless. It becomes meaningful only when it is compared with
the enterprise’s past inventory turnover therefore, to find out the inventory
management performance of the public cement industries of Nepal inventory
turnover for the nine consecutive years are presented below.
147
Table No. 4.6
Inventory Turnover Ratio on the Basis of Cost of Goods Sold (Rs. in millions)
Year
HCIL
UCIL
Inventory
Turnover
CGS
Inventory
Turnover
2001-02
372.5
236.56
1.57
350.4
380
0.922
2002-03
388.54
251.71
1.544
365.58
396.52
0.921
2003-04
507.61
254.52
2004-05
471.54
239.65
2005-06
502.04
230
2006-07
483.83
262.58
1.843
2007-08
714.7
283.42
2008-09
658.52
345.79
ar
CGS
395.77
462.15
0.856
1.968
405.17
493.22
0.822
2.183
509.68
477.6
1.067
422.74
530.4
0.797
2.522
432.57
638.85
0.677
1.91
398.06
753.8
0.528
406.21
816.59
0.497
Es
t
el
1.995
2009-10
Mean
Deviation
CV
710.63
378.35
1.88
1.93
0.79
0.2801
0.30
0.15
0.57
148
149
ar
el
Es
t
From the table above it is observed that the inventory turnover ratios of both
cement industries were very low. The inventory turnover ratios of HCIL during
the study period were better than that of UCIL but turnover ratios of both
industries were not satisfactory and were far from the benchmark of
inventory turnover ratio. The inventory turnover ratio of HCIL varied from
1.544 times per year to 2.522 times per year. In year 2001-02 the ratio was
1.57 times per year, meaning that the amount of money invested in
ar
inventories were turn into cash after 232.48 days. The inventory turnover
ratios of UCIL throughout the study period were very low, indicating-except in
year 2005-06 no turnover of inventory even one time in a year. In this industry
the highest turnover ratio during the study period was 1.067 in year 2005-06
el
and lowest 0.49 in year 2009-10. The mean value of inventory turnover ratio
was 1.93 times and .79 times in the HCIL and UCIL respectively. The standard
deviation of HCIL’s inventory turnover was 0.28 and UCIL’s inventory turnover
Es
t
was 0.30 and C.V. were 15% and 57% respectively.
The inventory turnover ratio of both industries is very low which indicate
inventories are kept in stock for a long period of time; as a result
unnecessarily funds are ties up in them. The direct effect of low inventory
turnover will be on profit, therefore the net profit of the industry throughout
the study period were very poor. The main reason of being inventory turnover
ratio very low lay on high proportion of stores and spares parts inventory in
the total inventory in the both industry. Large amount of funds was blocked in
the stores and spares part that simultaneously affected in the raw material, as
a result inventory turn over ratio became low.
4.3.2 Sales to Inventory Ratio
A problem arises in calculating and analyzing inventory turn over ratio. Sales
are stated at market prices, so if inventories are carried at cost, as they
generally are, the calculated turnover overstates the true turnover ratio.
150
Therefore, it would be more appropriate to use cost of goods sold in place of
sales in the formula’s numerator. However, established compilers of financial
ratio statistics such as Dun and Bradstreet use the ratio of sales to inventory
carried at cost. To develop a figure that can be compared with those
published by Dun and Bradstreet and similar organization, it is necessary to
measure inventory turnover with sales in the numerator.10
While computing inventory turnover ratios, it is always advisable to use
ar
figures of the cost of goods sold instead of sales but the cost of goods sold
data may not be available to an out side analyst from the published annual
account. In such situation inventory turnover ratio is calculated by dividing
sales by the inventory. The inventory turnover ratio calculated on the basis of
el
the goods sold is more logical because both the numerator-the cost of goods
sold and denominator-inventory are valued at cost while in the sales based
inventory turnover sales are valued at market price and inventory is valued at
Es
t
cost so they not comparable.11 The use of the cost of goods sold figures in
computing inventory turnover ratio avoids any variation arising due to change
in sales price therefore, it is preferred than sales. In fact when average stock is
used at cost value, sales should also be used at cost value. The inventory
turnover results obtained through sales figures is theoretically less valid but it
can still be used for comparison and trend development purpose, especially if
used consistently and when sharp changes in profit margins are not
presented.12
151
Table No. 4.7
Inventory Turnover Ratio on the Basis of Sales (Rs. in millions)
Year
HCIL
UCIL
Inventory
Turnover Sales
Inventory
Turnover
2001-02
398.6
236.56
1.685
463.9
380
1.221
2002-03
416.05
251.71
1.653
473.39
396.52
1.194
2003-04
655.4
254.52
2004-05
658.72
239.65
2005-06
655.96
230
2006-07
706.3
262.58
2.69
2007-08
989.69
283.42
2008-09
770.73
2009-10
840.5
ar
Sales
546.47
462.15
1.183
2.749
532.85
493.22
1.080
2.852
709.8
477.6
1.486
505.72
530.4
0.954
3.492
552.8
638.85
0.865
345.79
2.229
675.47
753.8
0.896
378.35
2.225
694.71
816.59
0.851
Es
t
el
2.575
Mean
2.461
1.081
Deviation
0.551
0.199
CV
0.224
0.184
152
153
ar
el
Es
t
From the above table it is apparent that the inventories turnover ratios of
both industries on the basis of sales were some how satisfactory in
comparison of CGS based turn over ratios.
The turn over ratio in HCIL had a fluctuating trend. In this industry the
inventory turnover ratio varied from 1.653 times per year to 3.492 times per
year. In year 2002-03 the inventory turnover was 1.653 times per year which
implies inventory of finished goods turning to sales was 1.653 times a year or
ar
the HCIL was holding average inventory of 217.78 days. In year 2007-08 the
inventory turnover was 3.492 times a year which indicates that the inventory
of finished goods turning to sales nearly 3.5 times a year means it was holding
inventory of nearly 102 days. The average inventory turnover ratio in HCIL
el
during the study period was 2.461 per year and its standard deviation and coefficient of variation were 0.551 and 0.199 respectively.
Similarly, the inventory turnover ratio of the UCIL was not so fluctuating but it
Es
t
was very low in comparison of HCIL. In this industry, in year 2009-10 the ratio
was .85 times per year and in year 2005-06 it was 1.486 times per year
indicating the lowest and highest inventory turnover ratio of the UCIL
throughout the study period. It means the industry was holding finished goods
inventory for more than one year period in year2007-08. In other words fund
once invested in inventory had been converted into cash after 422 days. In
year 2005-06 the inventory turnover ratio was highest i.e., finished goods
inventory of UCIL in year 2005-06 was converted into cash nearly. The average
inventory turnover ratio of UCIL was 1.081 which was very low in comparison
of HCIL. Standard deviation and coefficient of variation of this industry’s
inventory turnover were 0.199 and 0.184 respectively. The average inventory
turnover of UCIL was very much less than average inventory turnover of HCIL
in term of sales, however the coefficient of variation of inventory turnover
were similar in both industries.
154
4.4 Days of Inventory Holding (DIH)
Inventory holding in relation to sales is determined by calculating days of
inventory holding. It is also known as average inventory period or inventory
holding period. It indicates time duration of inventory holding and represents
the average time taken from the purchase of raw material to the ultimate
sales of finished product.13 When the number of days in a year is divided by
inventory turnover we obtain days of inventory holdings. It is also called
ar
inventory conversion period.14 The inventory conversion period is essentially
the time period during which a company must invest cash while it converts
materials into a sale. Smaller the DIH higher the efficiency in managing
inventory and vice versa. A high number of days of inventory holding indicate
el
that there is a lack of demand for the product being sold and a low days
inventory holding days may indicate that the company is not keeping enough
stock on hand to meet demands. The detail of inventory holding days of the
Es
t
public cement industries of Nepal is presented below.
155
Table No. 4.8
Days of Inventory Holding
HCIL
UCIL
2001-02
231.79
395.84
2002-03
236.46
395.88
2003-04
183.01
426.2
2004-05
185.51
444.31
2005-06
167.21
342.02
el
2006-07
ar
Year
198.08
457.97
144.74
539.06
191.66
691.16
2009-10
194.34
733.82
Mean
192.55
491.74
Standard dev.
27.021
128.69
C.V.
0.141
0.262
2007-08
Es
t
2008-09
156
157
ar
el
Es
t
From the table No 4.8 and figure 5 it is clear that the average inventory
holding days of UCIL were nearly 471 days which indicates no turnover of
inventory even one time in a year but in the HCIL average inventory holding
days were nearly 192 days which was better than that of UCIL. The inventory
conversion period of UCIL was less than one year period in the year 2005-06
i.e. once in 342.02 days but in rest of eight years it was more than one year
period. The higher the days of inventory holding, the smaller the liquidity of
ar
the firm and hence, overall profitability will also be smaller. In UCIL, due to
higher days of inventory holding its annual profits throughout the study
period were also poor. In this industry the smallest inventory conversion
period was 342.04 days in year 2005-06 and longest inventory conversion
el
period was 733.82 days in year 2009-10. The standard deviation of the
inventory conversion period of the UCIL was 128.69 and CV was 0.262 which
indicates high fluctuation in the conversion period of inventory.
Es
t
In comparison to UCIL the inventory conversion period of HCIL was good but it
was not up to the benchmark of days of inventory holding in the
manufacturing organization. In an average turnover of inventory once in each
month is considered as a benchmark of inventory turnover in the
manufacturing firm.15 In HCIL the shortest days of inventory holding was
144.74 in year 2007-08 and longest was 236.46 in year 2002-03 but in UCIL
shortest days of inventory holding was nearly double of the longest inventory
holding days of HCIL, which indicates inefficiency of UCIL in managing its
assets.
Test of Hypothesis
To test the null hypothesis Ho: there is no significant different in the mean
value of these two industries.
158
Table No 4.9
Student t- test of the Mean Value and Standard Deviation of the DIH in UCIL
and HCIL (2001-2 to 2009-10)
Measures
HCIL
UCIL
t value
df
Result
–X
186.668
470.9429
2.013
10
Not significant
σ
26.1477
105.74
at 5%
ar
From the above table the calculated value of 't' i.e. 2.013 is less than table
value of 't' i.e. 2.179 at 5% level of significant, so null hypothesis is accepted.
Hence the calculated result implies that there was no significant difference in
the mean value of days of inventory holding in UCIL and HCIL.
el
4.5 Size of Inventory
The proportion of inventory to the various forms of assets is called size of
inventory. In general it is observed to find out the percentage of assets that
Es
t
are not used to generate long term regular cash inflows. Other things being
same, the higher the size of inventory in the total assets the smaller the profit
of the firm and vice versa.
4.5.1 Percentage of Inventory to Total Assets
One ratio used to assess operational management and inventory turnover is
inventory to total assets ratio. In general, a low inventory to total assets ratio
is indicative of good performance and profitability. The percentage of
inventory to total assets is known as Inventory to assets ratio. It shows the
percentage of the assets tied up in the form of inventory.
Generally, the lower percentage value of this ratio is considered better for the
company. The higher the percentage of inventory to the total assets, the
lower the profitability of the firm as the opportunity cost of fund invested in
the inventory will be loosened.16
159
Companies with high inventory turnover generally will have a low percentage
of inventories to total assets. By looking at the inventory to total assets ratio
over time, one can determine inventory levels for the company. If the ratio is
rising, inventory levels are increasing, which may be a sign of low demand and
over supply of the inventoried asset.
Financial analysts consider such situation as a negative sign. Conversely, if
inventory levels are decreasing, it may be a sign of increased demand which
ar
points to a higher level of profitability.
The ratio of inventory to total assets computed for the selected non finance
Nepalese enterprises according to ministry of finance in 2001 was about 22%.
el
To invest on an average, about 22% of total assets in the form of inventories
by Nepalese enterprises indicates that larger amount of money has been
invested in the form of inventory which is not good sign of assets allocation.
The percentage of inventory to total assets in public cement industry of Nepal
Es
t
is as under.
160
Table No. 4.10
Percentage of Inventory to Total Assets (Rs in millions)
Year
HCIL
Total
UCIL
Inventory Percentage
Assets
of
Total
Inventory Percentage
Assets
of
13.74
inventory
2001-02
1720.82 236.56
2002-03
1735.73 251.71
2003-04
1762.05 254.52
2004-05
1792.43 239.65
ar
inventory
4687.23 380
2005-06
1831.6
2006-07
1823.41 262.58
4571.18 396.52
8.6
14.44
4451.6
462.15
10.38
13.92
4209.6
493.22
11.17
12.55
3986.4
477.6
11.98
14.4
3952.62 530.4
13.41
el
14.5
Es
t
230
8.10
2007-08
1907.67 283.42
14.85
3781.05 638.85
16.89
2008-09
2028.17 345.79
17.04
3655.23 753.8
20.62
2009-10
2118.96 378.35
17.86
3579.23 816.59
22.81
Mean
14.80
13.77
Standard
1.39
4.02
0.094
0.29
Dev
C. V.
161
162
ar
el
Es
t
The ratios of inventory to total assets in both industries during the study
period were between 8.6 to 20.62 percent. In the HCIL the ratio was best in
the year 2005-06 and worst in 2008-09 because the lower percentage value of
this ratio is an indicative of better inventory performance. The average value
of this ratio in the HCIL was 14.80 percent and standard deviation of the ratios
during the study period was 1.39 percent.
The above calculations show that HCIL has low variability in its inventory to
ar
total assets ratio as a result its C.V. was also lowest (.094) indicating high
consistency in maintaining the inventory in relation to total assets. In
comparison to HCIL the inventory to total assets ratios of the UCIL were not so
consistence. In the year 2001-02 it was 8.10% at the end of the study period
el
(2009-10) it became nearly 23% meaning that in the UCIL there was high
variation in this ratio during the study period. The average value of this ratio in
UCIL was 13.77% and standard deviation was 4.02% which indicates greater
Es
t
variability of the ratio in comparison to HCIL. The consistency of the ratio in
this industry was also poor which was clearly indicated by the value of C.V.
4.5.2 Percentage of Inventory to Current Assets
Current assts, sometimes called liquid assets, are those resources of the firm
which are either held in the form of cash or are expected to be converted in
cash within the operating cycle of the firm. The operating cycle is the time
taken to convert the raw materials into finished goods, selling finished goods
and convert receivable into cash. Current assets include cash, marketable
securities, receivable and inventories.17
The quality of current assets has been viewed in term of liquidity of current
assets therefore, the high ratio of cash to current assets indicates qualitative
current assets and high ratio of inventory to current assets indicates less
qualitative current assets. The higher ratio of inventory to current assets
163
would indicate a large volume of inventory holding. There is an opportunity
cost of holding inventory that grows inventory cost and hence reduces profit
of the firm. Therefore, higher percentage of inventory to current assets can be
taken as a sign of poor inventory management.18 The ratio of inventory to
current assets of the public cement industries of Nepal has been presented in
the following table in the form of percentage.
Table No. 4.11
Year
HCIL
2001-02 367.46
2002-03 393.69
Inventory Percentage Current
Assets
Inventory Percentage
236.56
380
48.24
64.38
787.68
251.71
63.93
704.59
396.52
56.27
254.52
56.3
636.07
462.15
72.64
Es
t
2003-04 452.11
UCIL
el
Current
Assets
ar
Percentage of Inventory to Current Assets (Rs. In millions)
2004-05 471
239.65
50.87
784.69
493.22
62.88
2005-06 527.45
230
43.61
852.55
477.6
56.02
2006-07 537.54
262.58
48.83
896.03
530.4
59.15
2007-08 625.61
283.42
45.3
1026.1
638.85
62.18
2008-09 639.08
345.79
54.11
1122.1
753.8
67.18
2009-10 685.17
378.35
55.22
1173.9
816.59
69.56
Mean
53.61
62.57
Std.
6.62
5.49
0.12
0.087
Dev.
C. V.
164
ar
el
Es
t
From the table no. 4.11 and figure 8 & 9 above it is clear that the ratios of
inventory to current assets of HCIL were comparatively lower than that of
UCIL except in year 2002-03. The percentage of inventory to current assets of
165
HCIL was highest (nearly 70%) in year 2002-03 and lowest in year 2005-06
with 43.61%. The average percentage of inventory to current assets of HCIL
was 53.61 which denote that the industry was holding about 50% of its
current assets in the form of inventory. The variability of this percentage
measured in term of standard deviation was 6.62 and coefficient of variation
was .12 that indicates minor fluctuations.
As there is no universal standard for this ratio since each industry has its own
ar
pattern of inventory requirement therefore, the ratio of inventory to current
assets is determined by their own need.19 In HCIL the ratios of inventory to
current assets from 2001-02 to 2009-10 were found in haphazard trend i.e.
sometime increasing and sometime decreasing. It means the industry was
el
open regarding the percentage of inventory to current assets which is not
good from the view point of profit earning organization.
Similarly the percentages of inventory to current in the UCIL were also in
Es
t
stochastic trend. In year 2001-02 it was 48.24% then increase to 72.64% in
year 2003-04 then for the next two years it decrease. From 2006-07 it
continuously increased and became 69.56% in year 2009-10. The average
percentage of inventory to current assets of the UCIL was 62.52% which was
neatly 12% greater than the average inventory turnover of the HCIL. The year
wise ratio of inventory to current assets in HCIL indicates that the share of
inventories in the current assets- some how- has decreased but in UCIL it has
increased. It shows that current assets of the HCIL and UCIL were less
qualitative over the time as inventory is the least liquid form of current assets.
A comparison of ratios of inventories to current assets for the individual
industries, it may be noticed that the ratio has increase for both industries
over a period of time. The above analysis indicates that the Nepalese cement
industries were not given due importance to inventory management as the
share of inventories in the current assets has been largest during the study
166
period, therefore they are recommended to give considerable importance to
the inventory management.
4.6 Linking Inventory Management to Profitability
Profit is the ultimate goal of the company and it will have no future if it fails
to make sufficient profits; therefore, every company should earn profit to
survive and grow over a long period of time. In general, profitability is the
ar
net result of a number of policies and decisions. The efficiency of a
company at generating earnings is called profitability. In other words the
efficiency of a company in term of profit is called profitability. The
profitability of a company is measured in term of profitability ratio which
el
shows combined effects of liquidity, assets management and debt
management on operating results. 20
Inventory management has a significant influence on profitability. Profit is the
Es
t
difference between revenues and expenses over a period of time. The
expenses in the context of manufacturing company denote costs of
production. The cost of production consists various components including raw
material, labour, overhead, etc. and out of total cost of production the
percentage of raw material and spare parts would be about 60%. If these two
major components of the cost of production are managed efficiently the firm
would be able to reduce inventory holding cost significantly, as a result it can
increase overall profitability.21
4.6.1 Inventory to Profit Ratio
Just as a business net profit margin can affect the way it manages its
inventory, inventory management also can have a direct impact on sales and
as a result, change profit margins. This is a result of a business ability to
maintain inventory of its production and to meet customer demand.
167
Other things being same, the higher the volume of inventory holding the
smaller will be the percentage of gross profit margin on inventory investment.
Large quantity of inventories indicates low sales, and low sales generate low
profit. The percentage of operating profit on inventory investment of the
public cement industries of Nepal is presented below.
Table No. 4.12
Inventory to Profit Ratio of HCIL
Year
Inventory
ar
(Rs. in millions)
Change in
Profit
Change in
Inv/Profit
Profit
Ratio
-
Negative
Inventory
236.56
-
(7.84)
2002-03
251.71
15.15
(13.82)
(5.98)
Negative
2003-04
254.52
2.81
96.6
109.82
37.95
Es
t
el
2001-02
2004-05
239.65
(14.87)
139.97
43.37
58.4
2005-06
230
(9.65)
105.66
(34.31)
45.94
2006-07
262.58
32.58
154.3
48.64
58.76
2007-08
283.42
20.84
180.97
26.67
63.9
2008-09
345.79
62.37
(4.8)
(185.77)
Negative
2009-10
378.35
32.56
5.6
10.14
37.31
168
ar
el
The above table 4.12 and figure 10 exhibit the percentage of operating profit
Es
t
to inventory of HCIL during the study period. It indicates that the percentage
of profit was registered negative in the year 2001-02, 2002-02 and 2008-09
and found maximum 63.9% in 2007-08 showing a fluctuating trend. In the year
2001-02, 2002-03 and 2008-09 the industry suffered loss thus it has negative
value of the inventory to profit ratios in these years. Also, this table clearly
exhibits the positive correlation between inventory and profitability in this
industry because in the year 2003-04 it had inventory of Rs. 254.52 million and
operating profit of Rs. 96.6 millions whereas, in the next year 2004-05 the
value of inventory decreased to Rs. 239.65 millions but the amount of profit
increased to Rs. 139.97 millions.
Similarly, in year 2005-06 the value of inventory decreased by Rs. 9.65 millions
but profit was not increased rather it decreased nearly by Rs. 35 millions. The
most striking feature of the table No. 4.11 is that the inventory holding and
profitability of this industry seems quite contradictory with the well
169
established principles of inventory management and profitability of the firm.
Due to high percentage of stores and spare part inventory, which are mostly
remaining idle in the stock, the profitability of this industry has not followed
the trend of inventory holding.
Table No. 4.13
Inventory to Profit Ratio of UCIL (Rs. In millions)
Inventory
Change in
Profit
Inventory
-
Change in
INV/Profit
ar
Year
Profit
Ratio
105.4
-
27.73
83.96
(21.44)
21.17
2001-02
380
2002-03
396.52
2003-04
462.15
65.63
114.37
30.41
24.74
2004-05
493.22
31.07
87.14
(27.23)
17.67
2005-06
477.6
(15.62)
150.04
62.9
31.46
2006-07
530.4
52.8
36.34
(113.7)
6.85
2007-08
638.85
108.45
63.12
26.78
9.88
2008-09
753.8
114.95
228.72
165.6
30.34
2009-10
816.59
62.79
93.23
135.49
30.15
Es
t
el
16.52
170
171
ar
el
Es
t
From the above table 4.13 and figure 11 it is evident that in UCIL there was
less fluctuating trend in the value of percentage of inventory to profit during
the period of study in comparison to HCIL. It was maximum 31.46 in 2005-06
and minimum 6.85 in year 2006-07. This table clearly exhibits that in most of
the years (three out of eight) there was positive correlation between
inventory holding and amount of profit and for the rest five years it was
negative. In the year 2001-02 profit was Rs. 105.4 million and inventory was
ar
Rs. 380 million. In the year 2002-03 there was inventory of Rs. 396.52 millions
and operating profit Rs. 83.96 millions whereas, in the next year 2003-04 the
value of inventory increased to Rs. 462.15 and the amount of profit also
increased to Rs. 114.37 that shows positive correlation between these two
el
variables but in the next three years the correlation is negative. Then for the
next two years their correlation again exists positive but in the final year there
exists negative correlation between these two variables. As comparing, these
two industries the inventory management practice of UCIL seems better than
Es
t
that of HCIL in terms of profitability.
4.6.2 Gross Margin Return on Inventory (GMROI)
Like most manufacturers, cement industries are no doubt concerned with
inventory management. They invest a lot of time and money for incorporating
MRP, JIT, ABC, and other techniques into their inventory management
systems or, they concentrate on managing gross margins. An important area
for linking inventory management to the profitability of the firm that’s often
misunderstood is the relationship between turnover, margins, and
profitability. Effective asset management is one of the primary means of
improving overall profitability of the manufacturing companies. But assets
can’t be managed effectively as a whole thus; they must be managed
individually. Because inventory is among a manufacturer’s largest assets
therefore, effective management of inventory is critical to profitability. Three
172
benchmarks of inventory management effectiveness are of particular
importance to manufacturers. The overall measures of inventory productivity
are:
(1)
Gross margin percentage
(2)
Inventory turnover and
(3)
Gross margin return on inventory.
ar
A calculation which determines the gross margin is earned by the company by
its products or services and whether or not a company can efficiently turn
inventory into cash at acceptable margins is called Gross Margin Return On
el
Inventory (GMROI).22
An important tool in analyzing inventory, sales and profitability is GMROI also
known as GMROII which stands for gross margin return on inventory
investment. The GMROI calculations assist manufacturer in evaluating
Es
t
whether a sufficient gross margin is being earned by the products sold,
compared to the investment in inventory required to generate those gross
margin. Gross margin return on inventory is considered the best single
measure of inventory management effectiveness because it includes gross
margin component as well as an inventory movement component. GMROI
analysis provides three important benefits.
(i) It shows how inventory buying and pricing procedures be combined with
inventory management procedures to affect profitability.
(ii) It shows how products with a relatively low gross margin and high
turnover can be just as profitable as those with higher margins and lower
turnovers.
(iii) It demonstrates that as gross margins decrease, inventory turnover must
increase otherwise profitability will suffer.
173
Gross Margin Return on Inventory (GMROI) is a "turn and earn" metric that
measures inventory performance based on both margin and inventory
turnover. In essence, GMROI answers the question, "For every rupee carried
in inventory, how much is earned in gross profit?" In the calculation of GMRIO
two terms are incorporated in the formula i.e. earns term and turn term. The
earn term, gross profit/sales, is simply the gross profit margin percentage on
sales. The turn term, sales/average Inventory at cost same as inventory
ar
turnover, which is the cost of goods sold, divided by average Inventory at cost.
Therefore, the GMROI formula can be simplified to address the impact of
these two terms in a single formula
GPM% × ITO
1-GM%
el
GMROI =
or
GMROI =
Gross Margin
Inventory
Es
t
GMROI has been used much less frequently in manufacturing organizations,
most likely because of the difficulty of associating raw material inventory with
specific end item products. However, with much more extensive databases
and data collection along with a shift to the greater use of contract
manufacturing, it can be possible to calculate and track GMROI in
manufacturing organizations as well.
174
Table No. 4.14
Gross Margin Return on Inventory (GMROI) of HCIL (Rs. In millions)
Particular
2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10
398.6
416.05
655.4
658.72
655.96
706.3
898.69
770.63
840.5
Less CGS
372.5
388.54
507.61
471.54
502.04
483.83
714.7
658.52
710.63
Gross M.
26.1
27.51
147.78
187.54
153.93
222.24
275.55
112.20
129.87
Inventory
236.56
251.71
254.52
239.65
230
262.58
283.42
345.79
378.35
Gross M.%
6.55
6.61
22.55
28.47
23.46
31.46
27.84
14.56
15.45
Inventory
1.575
1.544
1.995
1.968
2.183
1.843
2.522
1.91
1.878
97.30
32.54
34.32
GMROI(%)
11.03
el
turnover
ar
Sales
10.93
78.33
66.91
Standard Deviation=30.03
Es
t
Average GMROI=52.67%
58.08
175
84.59
C.V.=.57
The measures of the gross margin return on inventory of the HCIL presented
above in table No. 4.14 and figure 12 shows that the industry was earning on
an average of 52.67% on inventory investment during the study period. It
means that for every rupee invested in inventory, the industry was getting
back on an average Rs. 1.5267 to pay expenses and make a profit.
The gross margin return on inventory was very low (10.93%) in year 2002-03
and it was very high (97.30%) in year 2007-08. The coefficient of variation of
ar
this percentage was very high i.e. 52.67% which indicates inconsistency of
gross margin return on inventory in this industry. The advantage of this
measure is that one may assess the impact of inventory turnover upon the
GMROI. For example, in the table above the percentage of gross profit margin
el
was greater (31.46) in the year 2006-07 and was smaller (27.84) in year 200708. However, when we look in the GMROI row of the table the figure is quite
opposite because in the year 2007-08 the industry has turned its inventory
Es
t
more than that of the year 2006-07.
Gross margin return on inventory is considered the best single measure of
inventory management effectiveness as, it shows how a relatively low gross
margin can be enhanced into high profitability by using high turnover. The
gross margin return on inventory includes Inventory related expenses as well
profit. As the inventory related costs on the Nepalese cement industries are
remarkably high so, on an average 61% gross margin earned on inventory
cannot be considered satisfactory. Therefore, this industry is suggested to
increase the times of inventory turnover so as to increase net earning on
inventory investment.
176
Table No. 4.15
Gross Margin Return on Inventory (GMROI) of UCIL (Rs. In millions)
Particular 2001-02 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10
463.9
473.39
546.47
532.85
709.8
505.72
552.8
675.47
694.71
Less CGS
350.4
365.58
395.77
405.17
509.68
422.74
432.57
398.06
406.21
Gross M.
113.4
107.81
50.7
127.68
200.12
82.98
120.23
277.41
288.5
Inventory
380
396.52
462.15
493.22
477.6
530.4
638.85
753.8
816.59
Gross M.% 24.4
22.77
27.58
23.96
28.19
16.41
21.75
41.69
41.53
.921
0.922
0.856
0.822
1.067
0.797
0.677
0.528
.497
18.82
37.75
35.33
Inventory
GMROI(%) 29.84
el
turnover
ar
Sales
27.18
25.90
41.88
Standard Deviation=8.29%
Es
t
Average GMROI=29.77%
35.6
177
15.64
C.V.=0.278
From the table No. 4.15 and figure 13 it is observed that the inventory
turnover ratios of UCIL was less than one during a year except in year 2005-06
meaning that inventory conversion period of this industry was more than one
year. Due to this reason the gross margin return on inventory of the industry
were comparatively smaller than that of HCIL. The gross margin return on
inventory was lowest (15.64%) in year 2006-07 and it was highest (41.88%) in
year 2005-06. It means on the whole the percentage of GMROI marked a
ar
fluctuating trend. The average value of this percentage was 29.77% and
coefficient of variation was 0.279 indicating nearly 27% fluctuation in the
gross margin return on inventory investment during the study period. While
comparing the GMROI of these two industries obviously HCIL seems better in
el
term of annual and average GMROI during the study period but in term of
variability of the GMROI UCIL exhibits better performance.
Es
t
4.7 Statistical Analysis
Statistical analysis refers to a Collection, examination, summarization,
manipulation, and interpretation of quantitative data to discover its
underlying causes, patterns, relationships, and trends. It provides ways to
objectively report on how unusual an event is based on historical data.
4.7.1 Correlation Analysis
The correlation is one of the most common and most useful statistics. A
correlation is a single number that describes the degree of relationship
between two variables. The correlation analysis is generally used to describe
the degree to which one variable is related to another. It helps to determine
whether a positive or a negative relationship exists. The positive correlation
indicates that increase in value of one variable leads to increase in value of
other variable, and the negative correlation indicates that increase in value of
one variable leads to decrease in value of the other variable. The correlation
178
coefficient lies between +1 and -1. The +1 coefficient indicates that the
variables are perfectly positively correlated and -1 coefficient indicates that
the variables are perfectly negatively correlated. And if the correlation
coefficient is 0, it means that the variables are not related to each other. The
number indicates the degree of correlation between the variables.
4.7.2 Correlation between Sales and Inventory
ar
Theoretically, the correlation between inventory and sales must be negative.
As per objective of the study the correlation between sales and inventory of
the public cement industries in Nepal is calculated and interpreted in the
following.
el
Table No. 4.16
Es
t
Correlation Coefficient between Sales and Inventory in the Public Cement
Industries of Nepal
(Rs. In millions)
Year
HCIL
UCIL
Sales (X)
Inventory (Y)
Sales (X)
Inventory (Y)
2001-02
398.6
236.56
463.9
380
2002-03
416.05
251.71
473.39
396.52
2003-04
655.4
254.52
546.47
462.15
2004-05
658.72
239.65
532.85
493.22
2005-06
655.92
230
709.8
477.6
2006-07
706.3
262.58
505.72
530.4
2007-08
898.69
283.42
552.8
638.85
2008-09
770.63
345.79
675.47
753.8
2009-10
840.5
378.35
694.71
816.59
Mean
676.93
275.84
572.78
549.9
S. D.
161.34
36.61
83.71
115.34
C. v.
0.238
0.137
0.146
0.209
Correlation(rxy)
0.43
Probable Error
0.29
0.59
0.23
179
Table No. 4.16 shows the relationship between actual sales and inventory of
the public cement industries of Nepal during the nine year period. From the
above table it is evident that in HCIL the actual sales which increase over the
period but the increment in the inventory has not followed the same trend.
Sales were increase for four years and decrease in fifth year then increase in
sixth and seventh year. In the eighth year it has decreased and in the final year
increased again. On the other hand inventory increased for three years and
ar
decreased for another two years and for the rest period it was in the
increasing trend. However, the change in these two variables was not well
defined; there was intermittent rise and fall during the nine years.
Mean, standard deviation and coefficient of variation were calculated to
el
analyze the nature of the variability of sales and inventory in both industries.
The average value of the sales and inventory in HCIL ware 676.93 and 275.84
respectively. The deviation of annual sales and inventory from average value
Es
t
calculated as standard deviation in this industry were 161.34 and 36.61
respectively. The variability of these two variables calculated in term of
coefficient of variations were 23.8% and 13.7% respectively. This signifies that
inventory was more consistent as compared to sales.
In UCIL sales were increased for the first three years and decreased in the
fourth year. In the fifth year sales were again increased and in the next year it
decreased then after it continuously increased up to the final year but
inventory followed an increasing trend for all nine years during the study
period. This table also depicted that the increase in sales resulted into
increase in inventory in UCIL and the intermittent trend of sales increase in
HCIL has not directly affected in the inventory value. In UCIL average sale was
572.78 with standard deviation of 83.71 signifying the either deviation of
annual sales from average sales. Similarly average inventory was 549.9 with
standard deviation of 115.34 relatively less deviated as compared to sales.
Relating to the uniformity and stability sales were found relatively stable in
180
comparison of inventory which is shown by lower value of coefficient of
variation for sales 14.6% compared to that of inventory 20.9%.
On the other hand, correlation coefficients were calculated for the both
industries to analyze the relationship between sales and inventory. The value
of coefficient of correlation always lies between +1 and -1. A value -1 indicates
a perfect negative relationship between the variables and a value of +1
indicates a perfect positive relationship. A value of zero indicates that there is
ar
no relation between the variables. The positive value of correlation coefficient
between these two variables justify movement of both variables in the same
direction i.e. increase in sales cause to increase in inventory and vice versa.
el
Coefficient of correlation of sales and inventory in UCIL was 0.59 which
signifies high positive relationship. High positive correlation implies that a
certain percent increase in one variable cause to increase for about same
percentage increase in the other variable and vice versa. In other words 59%
Es
t
variation on inventory was due to sales. Theoretically, the correlation
coefficient between inventory and sales must be negative but in our
calculation for the UCIL it was positive which indicates less effectiveness of the
inventory management in this industry.
Probable error was also measured to ascertain the reliability of the value of
correlation coefficient and conclude whether simple correlation coefficient is
significant or not. Principally, the value of correlation coefficient must be 6
times smaller than the value of probable error. Here, r<6PE i.e. 0.62<
.22x6=1.32) shows that the coefficient correlation is significant meaning that
the relationship of these two variables is highly interdependent.
In the HCIL the coefficient correlation between inventory and sales was 0.43
and probable error was 0.3 which implies that the coefficient correlation is
significant because 6 times value of probable error would be 1.8 which is
greater than simple correlation coefficient.
181
4.7.3 Correlation between Profit and Inventory
Without an effective and efficient management of inventory no organization
can achieve their goals. Inventory management helps to maximize the profit
of the firm. Higher the volume of inventory smaller the amount of profit so
there is always negative relationship between the inventory holding and the
profitability of the firm. To examine this established principle the correlation
between inventory and profit of the public cement industries in Nepal is
ar
calculated and interpreted in the following.
Table No.4.17
Correlation Coefficient between Inventory and profit in the Public Cement
Year
el
Industries of Nepal
HCIL
Profit(X)
Inventory (Y)
UCIL
Profit(X)
Inventory (Y)
(7.84)
236.56
105.4
380
2002-03
(13.82)
251.71
83.96
396.52
2003-04
96.6
254.52
114.37
462.15
2004-05
139.97
239.65
87.14
493.22
2005-06
105.66
230
150.04
477.6
2006-07
154.3
262.58
36.34
530.4
2007-08
180.97
283.42
63.12
638.85
2008-09
(4.8)
345.79
228.72
753.8
2009-10
5.6
378.35
93.23
816.59
Mean
72.96
275.84
103.92
549.9
S. D.
66.97
36.61
59.27
115.34
C. V.
0.92
0.137
0.57
0.209
Es
t
2001-02
(Rs. In millions)
Correlation(rxy)
(0.34)
0.45
182
From the above table it is evident that in HCIL the annual profit which
increases over the period but the increment in the inventory has not followed
the same trend. In the year 2001-02 and 2002-03 the operating profits of HCIL
were negative it started to increase except negative in year 2008-09. On the
other hand inventory showed increasing trend throughout the study period.
However, the change in these two variables was not well defined i.e. there
was intermittent rise and fall during the nine years.
ar
Mean, standard deviation and coefficient of variation calculated to analyze
the nature of the variability of sales and inventory in both industries showed
the average value of the profit and inventory in HCIL were 72.96 and 275.84
respectively. The deviation of annual profit and inventory from average value
el
calculated as standard deviation in this industry were 66.97 and 36.61
respectively. The variability of these two variables calculated in term of
coefficient of variations were 34% and 13.7% respectively. This signifies that
Es
t
inventory was more consistent as compared to profit.
In UCIL in year 2003-04 profit was increased then in year 2005-05 it was
decreased. In the fifth year the amount of profit again increased then for the
next two years it has decreased and in year 2008-09 the amount of profit
increased to Rs. 228.72 millions but in the final year it decreased to Rs. 93.23
million. On the other hand inventory followed an increasing trend for all nine
years during the study period. This table also depicted that the increase in
inventory resulted into increase in profit in UCIL and the intermittent trend of
profit increase in HCIL has not directly affected in the inventory value.
In UCIL average profit during the nine year period was 103.92 with standard
deviation of 59.27 signifying the either deviation of annual profit from average
profit. Similarly average inventory was 549.9 with standard deviation of
115.34 relatively less deviated as compared to profit. Relating to the
variability and inconsistency; profits were found relatively unstable in
183
comparison of inventory which is shown by higher value of coefficient of
variation for profit 57% compared to that of inventory 20.9%.
On the other hand, correlation coefficients were calculated for the both
industries to analyze the relationship between profits and inventory. The
coefficient of correlation of profit and inventory in UCIL was 0.45 which
signifies high positive relationship. High positive correlation implies that a
certain percent increase in one variable cause to increase for about same
ar
percentage increase in the other variable and vice versa. The co-efficient of
correlation between Profit and inventory in UCIL indicated high degree of
positive association that is not supported statistically. But there are other
factors like capacity utilization, reputation of product and mobilization of
el
other financial resources affecting the profitability of the industry.
In the HCIL the coefficient correlation between inventory and profit was (0.34)
or Negative. Negative value of correlation coefficient implies that an increase
Es
t
in one variable cause to decrease in the other variable. Theoretically, an
increase in inventory cause profit to decrease therefore, the inventory
management practice in HCIL in term of correlation between inventory and
profit is found statistically significant or in consonance with established
principle.
4.8 Regression Analysis
Regression analysis in the general sense denotes the estimation or prediction
of the unknown value of one variable from the known value of other variable.
It is especially used in business and economics to study the relationship
between two or more variables that are related casually. In other words
regression analysis is used to determine the statistical relationship between
two or more variables and to make prediction of one variable on the basis of
the others.
184
4.8.1 Regression on Inventory and Sales
To analyze the relationship between sales and inventory of the cement
industries, here inventory is assumed as a dependent variables and denoted
by ‘Y’ and sale as independent variables denoted by ‘X’. The regression
equation of Y on X, which is used to describe the variation in the value of Y for
a given change in the value of X, is
ar
Y = a + bx
Where,
Y = inventory
a = Intercept or mean value of Y.
X = Sales.
el
b = Slop of trend line.
Table No. 4.18
Es
t
Calculation of Regression of Inventory on Sales of UCIL and HCIL
Year
UCIL
(Rs. In millions)
HCIL
Sales(X)
Inventory(Y)
Sales(X)
Inventory(Y)
2001-02
463.9
380
398.6
236.56
2002-03
473.39
396.52
416.05
251.71
2003-04
546.47
462.15
655.4
254.52
2004-05
532.85
493.22
658.72
239.65
2005-06
709.8
477.6
655.92
230
2006-07
505.72
530.4
706.3
262.58
2007-08
552.8
638.85
898.69
283.42
2008-09
675.47
753.8
770.63
345.79
2009-10
694.71
816.59
840.5
378.35
185
According to these data the regression equation of inventory (Y) on sales (X)
of HCIL as calculated and shown in appendices is as under.
Y = 149.12 + 0.1899x
The above regression result shows that there was positive relationship
between sales and inventory of the HCIL. The constant value 149.12 indicate
that the value of sales would be Rs. 149.12 million irrespective of changes in
inventory while coefficient value 0.1899 indicate the changes in Rs. 1 of
ar
inventory cause to change Rs. 0.1899 of sales of the industry. In other words
the slop coefficient of 0.1899 produced by regression equation in HCIL implies
that the marginal propensity to change in sales was nearly 19% due to change
el
in inventory.
Similarly, the regression equation calculated on the basis of sales and
inventory data of UCIL as calculated and shown in appendices is as under.
Es
t
Y = -87.89 + 1.1135x
In the UCIL the slop coefficient was 1.1135 meaning that, if the value of
inventory increase by a rupee on an average the value of sales would increase
by Rs. 1.1135. The intercept value of ‘a’ -87.89 implies that the average value
of sales would be negative by Rs. 87.89 million if inventories were zero. The
linear regression equation of inventory and sales in UCIL indicates that if the
industry invests Re. 1 in inventory sales would be Rs. 1.1135.
4.8.2 Regression on Inventory and Profit
To analyze the relationship between inventory and profit of the cement
industries, here inventory is assumed as dependent variables and denoted by
‘Y’ and profit as independent variables denoted by ‘X’. The regression
equation of Y on X, which is used to describe the variation in the value of Y for
a given change in the value of X, isY = a + bx
186
Table No. 4.19
Calculation of Regression of Inventory on Profit of UCIL and HCIL
(Rs. In millions)
Year
UCIL
Inventory(Y)
HCIL
Profit(X)
Inventory(Y)
Profit(X)
380
105.4
236.56
(7.84)
2002-03
396.52
83.96
251.71
(13.82)
2003-04
462.15
114.37
254.52
96.6
2004-05
493.22
87.14
239.65
139.97
2005-06
477.6
150.04
230
105.66
2006-07
530.4
36.34
262.58
154.3
2007-08
638.85
63.12
283.42
180.97
2008-09
753.8
228.72
345.79
(4.8)
2009-10
816.59
93.23
378.35
5.6
Es
t
el
ar
2001-02
According to these data the linear regression equation on profit and inventory
in HCIL as calculated and shown in appendices is as under.
Y = 293.34 + (–0.2318) x
The above equation shows negative relationship between inventory and profit
in HCIL. The negative slop coefficient indicates that one rupee increase in the
inventory investment cause to decrease profit by Rs. 0.2318.
In case of UCIL the linear regression equation of inventory and profit is as
under.
Y = 464.42 + 0.7995 x
The equation shown above indicates positive relationship between inventory
and profit in UCIL. The slop of the trend line in this industry was 0.7995
meaning that if the value of inventory increase by rupees hundred profit
would increase by rupees 79.95.
187
Test of Hypothesis
There is no impact of inventory management on the profitability of the
cement industries of Nepal.
Table No. 4.20
Correlation, regression and their student t-value of HCIL and UCIL
(2001-02 to 2009-10)
Correlation
HCIL
(0.34)
UCIL
d. f
t- value
8
2.4
0.45
Result
Significant at
ar
Measures
5% level
Y = 293.34 +
Y = 464.42 +
(–0.2318)x
0.7995x
el
Regression
From the table No. 4.20 the calculated value of ‘t’ is more than table value of
‘t’. So the null hypothesis is rejected means there is significant impact of
Es
t
inventory management in the profitability of the cement industries of Nepal.
The rejection of null hypothesis means acceptance of alternate hypothesis.
Therefore, according to alternate hypothesis there is significant impact of
inventory management on overall profitability in the Cement Industry of
Nepal.
4.8.3 Multiple Regression Analysis
The multiple regression equation of X1 on X2 and X3 is
X1 = a + b1x2 + b2x3
Here,
Profit (X1) = Dependent variable
Sales (X2) and Inventory(X3) = Independent variables.
188
Table No. 4.21
Calculation of Multiple Regression on Inventory, Sales and Profit of
UCIL and HCIL (2009-10)
(Rs. in millions)
Year
UCIL
HCIL
Inventory
Profit
Sales
Inventory
Profit
Sales
(X3)
(X1)
(X2)
(X3)
(X1)
(X2)
463.9
236.56
(7.84)
398.6
473.39
251.71
(13.82)
416.05
380
105.4
2002-03
396.52
83.96
2003-04
462.15
114.37
546.47
254.52
96.6
655.4
2004-05
493.22
87.14
532.85
239.65
139.97
658.72
2005-06
477.6
150.04
709.8
230
105.66
655.92
2006-07
530.4
36.34
505.72
262.58
154.3
706.3
2007-08
638.85
63.12
552.8
283.42
180.97
898.69
2008-09
753.8
228.72
675.47
345.79
(4.8)
770.63
2009-10
816.59
93.23
694.71
378.35
5.6
816.59
Es
t
el
ar
2001-02
On basis of variables the multiple regression equation of profit on inventory
and sales of UCIL as calculated and shown in appendices is as under.
X1 = 77.1869 + (0.0872) X2 + 0.1402X3
The above multiple regression equation shows that there is both negative and
positive relationship among the profit, sales and inventory. The intercept
value of 77.1869 means that profit in UCIL would be Rs. 77.1869 million even
if sales and inventory were zero. Similarly the coefficient of X2 0.0872 and X3
0.1402 indicate that when sales increase by Re. 1 profit would increase by Rs.
0.1402 and inventory would decrease by Rs. 0.0872.
189
The multiple regression equation of HCIL for inventory on sales and inventory
as calculated in appendices is as under.
X1 = –335.43 + (–0.1129) X2 + 1.7494X3
This multiple regression equation clearly indicates that profit of the HCIL
would be negative by Rs. 335.43 if sales and inventory were zero. This
equation also indicates that there is negative and positive relationship
between sales, inventory and profit in the HCIL. The regression coefficient
O.1129 and sales by Rs. 1.7494.
ar
implies that to increase profit by rupee one inventory need to decrease by Rs.
4.9 Analysis of Primary Data
el
An empirical investigation has been conducted in order to identify the
problems faced by the cement industries in Nepal. For this purpose a total 25
set of questionnaires with 45 questions in each set were developed and
Es
t
distributed in the 5 cement industries (5 in each industry) to collect
information in the various aspect of inventory management. To explore
inventory management problem faced by the cement industries of Nepal 2
public and 3 private cement industries were selected and in each industry five
concerned departmental head (procurement, production, finance, account
and administration) were consulted to fill the questionnaires.
In the questionnaires of different aspect of inventory management like
inventory policies, motive for inventory holding, determining the size of
inventory, practices of maintaining safety stocks, fixation of reorder point,
lead time analysis, inventory control system and application of computers in
controlling inventory were raised and required to answer.
The questionnaires were asked either for yes/no answer or for choosing one
out of the given alternatives. Some questions were also asked to give their
opinions. The response of questionnaires was not so good. The responses
190
received from various respondents have been arranged and analyzed in order
to facilitate the descriptive analysis of the study. Opinions/views given by the
respondents are expressed in percentage to show result obtained from
primary data.
Table No. 4.22
Analysis of Primary Information Collected Through Questionnaires
S.N.
Issues Raised
No. of
Yes
No
Setting inventory policies
20
8
12
2
Motives of inventory holding
16
7
9
3
Determination of EOQ
23
4
19
4
Practice of keeping safety stocks
21
9
12
5
Fixation of reorder point
19
13
6
6
Lead time analysis
22
18
4
7
Inventory control system
21
11
10
21
9
15
Es
t
el
1
ar
Respondents
8
Application of computer in
controlling inventory
From the above table it became clear that the tools and techniques of
managing inventory have not properly been applied in Nepalese cement
industries for controlling their physical and financial dimension. Due to the
lack of proper inventory policies and practices they are blocking large amount
of capital in inventory and hence, facing the problem of inadequate
profitability.
Inventory policies
Inventory policies concern with the establishment of guidelines relating to
inventory. Most of the Nepalese cement industries were found without
inventory policies because among 20 respondents in this issue 12 respondents
(60%) accepted that their industry does not set inventory policies.
191
Motives of inventory holding
Maintaining inventories involve tying up of companies fund and incurrence of
storage and handling cost. Every firm knows this reality of the inventory
holding even though they hold inventories. There are three general motives
for holding inventory i.e. transaction, precautionary and speculative. In the
context of cement industries in Nepal the majority of the respondents 9 out of
16 or 56% replied that their industry hold inventory with a view to meet day
ar
to day operation of the industry and few answered in fevour of precautionary
motive. It means the basic motives for holding inventory in most of Nepalese
cement industries were transaction and precautionary.
el
Determination of EOQ
Economic order quantity (EOQ) is that size of the order which gives maximum
economy in purchasing any material and ultimately contributes towards
Es
t
maintaining the materials at the optimum level and at the minimum cost. Out
of 23 respondents only 4 replied that inventories are purchased and hold on
the basis of costs effectiveness. 19 respondents out of 23 or nearly 82%
answered that their industry never calculated Economic Order Quantity which
indicates the weakest part of inventory management in the Nepalese cement
industries.
Fixation of reorder point
As its name suggests, re-order point determines the amount of inventory at
which the stores or purchase department should order new stocks of raw
materials to replenish supplies to the optimum quantity. In the issue of reorder point majority of the respondents mentioned that reorder point is
determined in their industry and orders are placed accordingly. Among 19
respondents 13 or nearly 68% answered that raw materials and fuels are
192
purchased as per schedule date fixed by the procure department at the very
beginning of the month.
Lead time analysis
The term lead-time refers to the time normally taken in reciving the delivery
after placing orders with the suppliers. It covers the time span form the point
when the decision to place the orders for the procurement of inventory is
ar
made to the actual receipt of the inventory by the firm. In the Nepalese
cement industries as per respondents answer lead time is normally estimated
on the basis of past experiences and new order is placed by cosidering the
margin of lead time. Out of 22 respondents in this issue 18 (81%) replied that
el
lead time is always adjusted in placing the new order, it means there is
practice of lead time analysis in the cement industries of Nepal.
Inventory control system
Es
t
An inventory control system is a system of maintaining record by the
procurement department which reflects the physical movement of stocks and
their current balance. In other words it is a process for managing and locating
inventory objects or materials. Inventory objects could include any kind of
physical asset, merchandise, consumables and fixed assets, circulating tools or
capital equipment. The most important objective of inventory control is to
determine and maintain an optimum level of investment in the inventory.
In the context of cement industries in Nepal the practice of inventory control
was found some how satisfactory because out of 21 respondents in this issue
11 respondents or nearly 52% accepted the fact that inventories in their
industry are controlled by the store section through records in computer and
ledger. Although nearly 50% respondents replied that their organization does
not apply any system for controlling the physical and financial dimension of
the inventory.
193
Application of computer in controlling inventory
The use of computer in inventory management increases their productivity
and maintains competitiveness. In the modern business environment, even
many smaller businesses have come to rely on computerized inventory
management systems. For the manufacturing firms operating with high
volume of turnover of raw materials and/or finished products, computerized
inventory control systems have emerged as a key component of business
ar
strategies. In Nepal the practice of using computer for record keeping is a new
concept. In Nepalese cement industries the application of computer for
recording and controlling inventory was found very poor because 15
respondents out of 21 answered that in their industry computers are use only
el
for accounting and administration department. The need for exercising
control of the inventory by means of computer is of prime importance
Es
t
particularly in a capital-scare country like Nepal.
194
Reference
Target and Performance of Public Enterprises, Government of Nepal, Ministry
of Finance, 2009.
2.
Hetauda Cement Industry Ltd. (HCIL)- At A Glance. Published by Hetauda
Cement Industry Ltd.
3.
C. Paul Jannis, Carl H. Poedtke and Donald R Ziegler, Managing and Accounting
for Inventories, A Ronald Press Publication, John Wiley and Sons.USA 1980, p.
64.
4.
Vijaya Saradhi P. Sisthla, “Working Capital Management in Public Enterprise”
International Centre for Public Enterprise in Developing Countries. Yugoslavia.
(ICPE monograph No. 51, 1982, p. 51).
5.
M. Chapman Findlay III and Edward E Williams, An Integrated Analysis for
Managerial Finance, (New Jersey Prentice Hall Inc., 1970), P. 70.
6.
I. M. Pandey, Financial Management. Vikash Publishing House Pvt. Ltd., P. 125.
7.
James C. Van Horne and John M. Wachowicz, Jr., Fundamental of Financial
Management, Prentice Hall of India Pvt. Ltd, New Delhi, 1997.
8.
R Derbin Allen and Bierman Harold Jr., Managerial Accounting An
Introduction, W. B. Saunders Company Philadelphia, 1975, P. 155.
Es
t
el
ar
1.
9.
Eugene F. Brigham, Louis C. Gapenski, Michael C. Ehrhardt, Financial
Management-Theory and Practice (9th edition), Harcourt Asia Pvt. Ltd.,
Harcourt Collage Publishers, P. 75.
10.
Ibid.
11.
I. M. Pandey, Financial Management. op. cit., P. 124.
12.
Leopold A. Bernstein, Financial Statement Analysis: Theory, Application and
Interpretation. (Illinois: Richard D. Irwin, Inc.,1978) P. 442; and John D. Martin,
J. William Petty, Arthur J Keown and David F. Scott, Jr. Basic Financial
Management. (New Jersey Prentice Hall Inc., 1979) P. 149.
13.
Lawrence J. Gitman, Principle of Managerial Finance, New York: Harper and
Row Publishers, 1989, P. 156.
14.
MY Khan PK Jain., Financial Management –Text and Problem -2nd Edition. Tata
McGra-Hill Publishing Company Limited, New Delhi.
15.
James W. Prichard & Robert H. Eagle, “Modern Inventory Management” John
Wiley and Sons, Inc, New York, 1965, P. 20.
195
V. K. Bhalla. Financial Management and Policy. Anmol Publication Pvt. Ltd.,
New Delhi, P. 380.
17.
I. M. Pandey Financial Management, Vikas Publishing House Pvt. Ltd., 8th
Edition, P. 32.
18.
Buffa, E. S. and Taubert W. H. Production Inventory System-Planning and
Control Homewood Illinois, Irwin 1972, p. 616.
19.
Production and Inventory Control, Systems and Decisions. James H. Greene,
Richard D. Irwin Inc. Homewood Illinois 1974 Irwin- Dorsey International
London England, P. 213.
20.
I. M. Pandey, Financial Management, op. cit., P. 130.
21.
R. S. Chadda, Inventory Management in India. Allied Publishers’, New Pvt. Ltd.,
New Delhi, P. 12.
22.
http://www.investorwords.com/11626/Gross_Margin_Return_On_Investment_G
MROI.html#ixzz1YjtVMh45.
Es
t
el
ar
16.
196