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Fac o s A ec ing Raw Ma e ial W i e O : A
Case S udy o he S i Lankan Appa el Indus y
Gayani Madhushan hi Ranasinghe
G adua e, Depa men o Indus ial Managemen , Facul y o Applied
Sciences, Wayamba Uni e si y o S i Lanka, Kuliyapi iya, S i Lanka
Shanika Dilan hi
1
Senio Lec u e , Depa men o Indus ial Managemen , Facul y o
Applied Sciences, Wayamba Uni e si y o S i Lanka, Kuliyapi iya, S i
Lanka
Abs ac
The S i Lankan appa el indus y is conside ed as he mos signi ican and
dynamic con ibu o o he coun y’s economy. Though he indus y c ea es
p o i s in signi ican s ill i has many losses in inancial aspec s such as he cos
o aw ma e ial. The e o e his esea ch was ca ied ou as a case s udy in he S i
Lankan appa el indus y o iden i y ac o s a ec ing aw ma e ial w i e o . The
main aw ma e ial conside ed in he s udy was ab ic being he single la ges cos
ac o in he appa el indus y. This esea ch andomly selec ed 85 schedules as
he sample. Bo h p ima y and seconda y da a we e used and collec ed h ough
au ho obse a ions, in e iews and seconda y da a sou ces. The da a we e
quan i a i ely analyzed wi h eg ession analysis. The esul s showed ha bo h
excess o de ed aw ma e ial quan i y and yield pe ya dage sa ing we e he
signi ican ac o s ha a ec ed on aw ma e ial w i e o in he S i Lankan
appa el indus y. Fu he desc ip i e analysis e ealed ha pa e n changes and
ma ke imp o emen mainly con ibu ed o his yield pe ya dage sa ing. The
eg ession analysis u he iden i ied a signi ican ela ionship among he aw
ma e ial w i e o quan i y, excess o de ed aw ma e ial quan i y and yield pe
ya dage sa ing. Also his s udy sugges ed o c ea e a Lean manu ac u ing cul u e
o minimize aw ma e ial w i e o in he appa el indus y.
Keywo ds: Excess O de ing, Excess Recei ing, Raw Ma e ial, S i Lankan
Appa el Indus y, W i e O , Yield pe Ya dage Sa ing (YY Sa ing).
Ci e his a icle: Ranasinghe, G. M., & Dilan hi, S. (2015). Fac o s A ec ing Raw Ma e ial
W i e O : A Case S udy o he S i Lankan Appa el Indus y. In e na ional Jou nal o
Managemen , Accoun ing and Economics, 2(7), 727-736.
1
Co esponding au ho ’s email: sha[email p o ec ed]c.lk
In e na ional Jou nal o Managemen , Accoun ing and Economics
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ISSN 2383-2126 (Online)
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728
In oduc ion
The S i Lankan appa el expo indus y is conside ed as he mos signi ican and
dynamic con ibu o o he coun y’s economy. I has g own o be he coun y’s one o
he leading con ibu o s o he expo e enue (Dhee asinghe, 2003 ci ed in Ranawee a,
2014). S i Lanka is well known in he appa el indus y o p oducing designe label
clo hing o epu ed cus ome s in he USA and Eu ope. The e enue om appa el expo s
has es ablished a sus ained inc ease o e he las wo decades.
As he S i Lanka’s la ges expo indus y, he appa el indus y has conside able
po en ial o de elop h ough minimizing unnecessa y cos s such as ab ic w i e o which
is ocused h oughou his esea ch. Fab ic w i e o de ines he quan i y o ab ic le in
he s o es a e he pa icula o de has been deli e ed o shipped. Also i is a dead s ock
o aw ma e ial, which cos s o he o ganiza ion.
Figu e 1 – Raw Ma e ial wise Con ibu ion o he Value o W i e O
P o i is he p ima y conce n o any manu ac u ing o ganiza ion in he appa el
indus y. Thus he appa el manu ac u e s a e paying mo e a en ion on educing he cos s
in hei inancial s a emen s. Cos o ab ic o a ga men is signi ican compa ed o o he
aw ma e ials such as sewing ims, packing ims, e c. The aw ma e ial w i e o also
con ibu es o his cos . Figu e 1 p o ides e idence o ha showing 69.7% con ibu ion
o he o al aw ma e ial w i e o in he selec ed appa el manu ac u ing company.
Figu e 2 illus a es he alue o w i e o ab ic in he selec ed appa el manu ac u ing
company in yea 2014.
Fab ic
Packing T ims
Sewing T ims
Ca ego y
16.3%
14.0%
69.7%
Raw Ma e ial wise W i e O
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729
Figu e 2 - Fab ic W i e O Value
Due o he apid changes in he cus ome equi emen s and ashion de elopmen s in
he appa el indus y, his dead s ock o ab ic is a was e as he same ab ic is no used o
ano he s yle and has become a p oblem o he appa el indus y. The e o e his esea ch
was ca ied ou o iden i y ac o s a ec ing aw ma e ial w i e o as a case s udy o he
S i Lankan appa el indus y.
The main objec i e o his esea ch is o iden i y he ac o s a ec ing aw ma e ial
w i e o in he S i Lankan appa el indus y. Once he signi ican ac o s a e iden i ied,
seconda y objec i es o be add essed a e,
To iden i y possible oppo uni ies o minimize he aw ma e ial w i e o
quan i y
To make ecommenda ions in o de o minimize he aw ma e ial w i e o
Li e a u e Re iew
The S i Lankan appa el indus y uses many aw ma e ials. Among hem, Fab ic is he
single la ges ac o in he cos o a ga men and he p ices o ab ic a e con inuously
inc easing (Hands e al., 1997). The ecen s udies ha e explained he u iliza ion o ab ic
in he appa el indus y. Acco ding o Thomas (2012), he bes ab ic u iliza ion is o use
e e y inch o wha is being bough , con e ing i in o ga men s and hen ul ima ely in o
ea nings. Fu he he has shown ha only 82% is being used e ec i ely om he o al
ab ic b ough o an o de . The e o e ul ima ely 18% is being los in one way o he o he .
Tha s udy u he showed he majo con ibu o s o his loss as dead s ock, cu o ship,
ma ke s and wid h con ibu ing 41%, 15%, 42% and 2% espec i ely. Compa ing hese
con ibu ions, dead s ock is a signi ican loss con ibu o . Bu Thomas (2012) has no
p o ided su icien li e a u e add essing he aw ma e ial w i e o .
Li e a u e has de ined he dead s ock o he w i e o quan i y in di e en e ms.
Thomas (2012) has de ined he dead s ock as he ab ic ha is le in he s o es a e he
pa icula o de has been deli e ed o shipped. These addi ional allowances also accoun s
AugJulJunMay
30000
25000
20000
15000
10000
5000
0
Mon h
Fab ic W i e O Value ($)
Fab ic W i e O Value
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730
o u iliza ion o ab ic. The e o e he di e ence be ween he bough quan i y and
achie ed consump ion should be inco po a ed o de ine he w i e o quan i y. This ac o
is conside ed in his esea ch as excess o de ed quan i y o aw ma e ial.
This esea ch also ocuses on excess eceip o ab ic due o supplie ole ances o
sa e y ma gins. Al hough su icien li e a u e could no be ound, his ac o is conside ed
o he s udy based on he obse a ions, wo k low, e c. o iden i y whe he i in luences
on aw ma e ial w i e o quan i y.
The empi ical s udies ha e ound ha he dead s ock o aw ma e ial w i e o is c ea ed
due o se e al easons (Thomas, 2012). One eason is addi ion o allowances in
calcula ing he ab ic consump ion. Cu ing was age, sh inkage and de ec s and o e
shipping p ac iced by he supplie s a e some o hose allowances conside ed. Ano he
eason iden i ied by Thomas (2012) is ha supplied ab ic has a conside able a ia ion in
i s wid h ha ul ima ely leads o his di e ence in ab ic consump ion. In many cases
buye s a e esponsible o changing he pa e n o s yle speci ica ions which con ibu es
o hese a iances. These addi ional allowances accoun o he cos o ab ic while aw
ma e ial w i e o has become a p oblem in he S i Lankan appa el indus y a p esen .
The cos o ab ic is a e y impo an ac o o add ess he ab ic w i e o p oblem.
Powell (1977) es ima ed ha he ab ic cos s alone o be 35% o 40% o he selling p ice
o a ga men (ci ed in Hands e al., 1997). The e o e acco ding o Hands e al. (1997), a
educ ion o 2.5% in ab ic could sa e a company 1% in cos . Fu he , B oadhead (2003)
also s a ed ha no o he single e inemen in p oduc ion can p o ide subs an ial sa ings
as easily as ab ic con ol.
Acco ding o C o on (2000, ci ed in Gam e al., 2009) he appa el indus y is a majo
con ibu o o he en i onmen al p oblems a isen in ex ile manu ac u ing o he appa el
p oduc ion and land ills. The e o e he ab ic w i e o indi ec ly becomes esponsible o
en i onmen al pollu ion s a ing om i s p oduc ion o he disposal. This again
emphasizes he impo ance o his esea ch in an en i onmen al pe spec i e.
Though e iewed li e a u e p o ided su icien e idence o minimizing was ages in
he appa el indus y, a e y ew has add essed he issue o ab ic was es due o w i e o .
Among hem, any esea ch done in he S i Lankan con ex could no be ound wi hin he
accessible li e a u e. The e o e his esea ch is an e o o ul ill ha empi ical gap.
Me hodology
The a iables and ele an indica o s we e iden i ied h ough li e a u e and au ho
obse a ions. The esea ch was de eloped by obse ing p oduc ion o se e al ga men s
in he selec ed appa el manu ac u ing company. Based on he e iewed li e a u e and ield
obse a ions, he esea ch model as shown in Figu e 3 was de eloped.
Ma e ial w i e o quan i y was he dependen a iable and excess o de ed quan i y,
excess ecei ed quan i y and YY sa ing we e he independen a iables.
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The h ee independen a iables we e de ined as ollows;
Excess o de ed quan i y = o de ed ab ic quan i y - ab ic o de equi emen
Excess ecei ed quan i y = ecei ed ab ic quan i y - o de ed ab ic quan i y
YY sa ing = O de ed YY – Ac ual YY
Figu e 3 - Resea ch Model
These a iables a e hen quan i a i ely measu ed and analyzed o es he ollowing
hypo heses.
Excess o de ed quan i y impac s on aw ma e ial w i e o quan i y
Excess ecei ed quan i y impac s on aw ma e ial w i e o quan i y
YY sa ing impac s on aw ma e ial w i e o quan i y
This s udy used andom sampling echnique, and 85 schedules we e selec ed o he
sample. Bo h p ima y and seconda y da a we e hen collec ed acco ding o he iden i ied
a iables, using au ho obse a ions, seconda y da a sou ces and in e iews.
The s a is ical analysis echniques such as co ela ion analysis, mul iple linea
eg ession, e c. we e used o iden i y he signi ican ac o s a ec ing aw ma e ial w i e
o . Hypo heses we e de eloped and es ed o he no mali y o da a, co ela ion be ween
he a iables, signi icance o he model and he coe icien s. A quan i a i e ela ionship
was de eloped o model he ela ionship be ween he aw ma e ial w i e o quan i y and
he signi ican ac o s. Conclusions and ecommenda ions we e hen made o minimize
he aw ma e ial w i e o p oblem based on he esul s.
Da a Analysis
Dis ibu ion o W i e O Ca ego y
Figu e 4 illus a es he dis ibu ion o he wo ca ego ies o w i e o in he selec ed
sample ha a e namely, No mal w i e o and Rese e w i e o . In no mal w i e o , his
W i e
O
Quan i y
Excess O de ed
Quan i y
Excess Recei ed
Quan i y
YY
Sa ing
Pa e n Changes
Ma ke Imp o emen
Wid h Inc ease
Change in Ga men
O de Quan i y
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w i e o ab ic quan i y is emo ed om he s o es pe manen ly and documen ed as w i e
o in he inancial s a emen s. In ese e w i e o , al hough he w i e o quan i y is
documen ed as w i e o in he inancial s a emen s, he quan i y will be emaining in he
s o es empo a ily o ew mon hs. This happens when he pa icula ab ic is p edic ed
o be used o p oduc ion o an upcoming s yle.
Figu e 4 - Dis ibu ion o W i e O Ca ego y
The esul s showed ha he majo i y was no mal w i e o and emo ed om he s o es
as a was e, since he ab ic will no be use ul o ano he ga men p oduc ion due o he
high ola ili y o ashion changes and cus ome equi emen . This emphasizes he need
o a ac ing managemen ’s a en ion o educe w i e o , as i is a was e wi h a alue.
Fu he , ese e w i e o should also be minimized, since keeping a dead s ock in a s o e
would gene a e unnecessa y cos s such as, in en o y cos , disposal cos , e c.
Reasons o Raw Ma e ial W i e O
No mal W i e O
Rese e W i e O
Ca ego y
11.8%
88.2%
W i e O Ca ego y
Excess O de ing
Excess Recei ing
YY Sa ing
Ca ego y
80.9%
13.2%
5.9%
Reasons o W i e O
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Figu e 5 - Reasons o Raw Ma e ial W i e O
Figu e 5 illus a es he con ibu ion o each iden i ied eason o aw ma e ial w i e
o . I showed he majo con ibu o o w i e o as YY sa ing and con ibu ed 80.9% o
w i e o . Excess o de ing and excess eceip o aw ma e ial con ibu ed 5.9% and 13.2%
espec i ely. The e o e mo e a en ion should be ocused on con olling YY sa ing o
minimize w i e o .
Reasons o YY Sa ings
Figu e 6 - Reasons o YY Sa ings
Acco ding o Figu e 6 pa e n changes con ibu ed 39.5% o YY sa ing. This was
mainly because cus ome speci ica ions and equi emen s changed ime o ime du ing
he s yle app o al p ocess. Due o long lead ime and esponsibili y o deli e on ime,
company could no wai un il he inal pa e n app o al was done in o de o pu chase aw
ma e ial.
Ano he eason was ha s yles we e de eloped a on end p oducing wo o ou
samples o check he easibili y. Mos o he di icul ies we e iden i ied once he s yle
was selec ed o be execu ed o a bulk p oduc ion. The e o e du ing i s ial, he
p oduc ion depa men should eques pa e n changes o smoo h he bulk p oduc ion.
Mos ly, ab ic was p o ided in a g ea e wid h han o de ed. This ob iously educed
he ab ic consump ion and led o YY sa ing. Ma ke was also imp o ed and ed awn o
he ecei ed wid h.
Ma ke imp o emen and wid h inc eases also con ibu ed o YY sa ing 27.9% and
17.2% espec i ely. The es ima ion o ab ic equi emen o comple e a ga men o de
was done based on he ab ic wid h. The ma ke was also d awn o a pa icula ab ic
Pa e n Change
Wid h Inc ease
Ma ke Imp o emen
Changes in O de Quan i y
Ca ego y
15.3%
27.9%
17.2%
39.5%
Reasons o YY Sa ing
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wid h and ab ic was o de ed on ha wid h. Bu some imes, supplie s ailed o supply
ab ic in exac wid h o de ed.
Figu e 6 showed he con ibu ion o he changes in ga men o de quan i y o be 15.3%
o YY sa ings. Changes in ga men o de quan i y could be occu ed wi h he eques s o
cus ome . Cus ome may change he o de ed ga men quan i y o may change he o de ed
size a ios. This would also lead o YY sa ing since a change in o de quan i y means he
change in ab ic consump ion pe ga men .
Mul iple Reg ession Analysis
Mul iple Linea Reg ession Analysis was used o de elop a ela ionship be ween he
dependen a iable and independen a iables. The ollowing assump ions we e made in
analysis.
The e o s associa ed wi h any wo obse ed alues a e independen o each
o he .
The e o componen is no mally dis ibu ed.
The e o componen has a cons an a iance.
The unc ional ela ionship be ween he p edic o a iables and he esponse
a iable can be es ablished linea ly.
Fu he a co ela ion analysis was ca ied ou and e ealed ha he e is no co ela ion
be ween he independen a iables. Summa y o he eg ession analysis is shown in Table
1.
Table 1 - Summa y o Reg ession Analysis
Table 1 concluded ha he i ed model is signi ican a 95% le el o signi icance.
Acco ding o he P alues, cons an , excess o de ed quan i y and YY sa ing ha e a
signi ican impac on w i e o quan i y whe eas excess ecei ed quan i y does no ha e.
The model was good enough o explain he da a ha ing R2 alue o 74.1%.
Thus he eg ession equa ion a 95% con idence le el could be concluded as,
W i e O Quan i y = 108.291 + 0.868 Excess O de ed Quan i y + 70.839 YY Sa ing
Model Summa y
R2 Value
0.741
P Value
0.000
Model
Coe icien
P alue
Cons an
108.291
0.000
Excess O de ed Quan i y (Yds)
0.868
0.000
Excess Recei ed Quan i y (Yds)
0.007
0.469
YY Sa ing (Yds)
70.839
0.016
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735
When o he ac o s held cons an , a one uni inc ease in Excess o de ed quan i y will
inc ease w i e o quan i y by 0.868 ya ds. Simila ly, a one uni inc ease in YY sa ing
will inc ease w i e o quan i y by 70.839 ya ds.
Findings & Conclusions
Acco ding o he indings o his esea ch, main easons o aw ma e ial w i e o a e
excess o de ing, excess ecei ing and YY sa ing. The majo eason was YY sa ing when
compa ed wi h con ibu ed alues.
Fu he he iden i ied main easons o YY sa ing a e pa e n changes, wid h inc ease,
ma ke imp o emen s and changes in o de quan i y.
Acco ding o he analysis, he mos signi ican ac o s a ec ing aw ma e ial w i e o
we e excess o de ing and YY sa ing. A model was de eloped o explain he ela ionship
be ween aw ma e ial w i e o and hese wo independen a iables.
Roo Causes o W i e O
Figu e 7 - Roo Causes o W i e O
Th ough add essing he iden i ied oo causes, aw ma e ial w i e o p oblem can be
minimized.
The main solu ion sugges ed h ough his esea ch is adop ing lean manu ac u ing
including echniques such as supplie in eg a ion, main aining e ec i e communica ion
and unde s anding be ween p oduc de elopmen and p oduc ion eams, occupying be e
ained pe sonnel o ope a ions, implemen ing s anda d ope a ing p ocedu es, a oid
adding allowances a e e y poin , ecycling and euse o ab ic, e c. which a e ocused on
add essing he iden i ied oo causes.
Raw
Ma e ial
W i e O
Excess O de ing
YY Sa ing
Pa e n
changes
Changes in ga men
o de quan i y
Ma ke
Imp o emen
Wid h Inc ease
A oid isk o
insu iciency
Mis akes in calcula ion
o equi emen
Sa e y s ock
Allowances
