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ACC JOURNAL 2022, Volume 28, Issue 2 DOI: 10.15240/ ul/004/2022-2-001
OVERALL LABOR EFFECTIVENESS AS A TOOL FOR MEASURING PERFORMANCE
IN A GIVEN COMPANY
Zdeněk B abec1; Helena Jáčo á2
Technical Uni e si y o Libe ec, Facul y o Economics,
Depa men o Finance and Accoun ing,
S uden ská 1402/2, 461 17 Libe ec 1, Czech Republic
e-mail: 1zdenek.b a[email p o ec ed]; 2helena.jaco a@ ul.cz
Abs ac
To emain compe i i e, a company needs o inc ease he p oduc i i y o i s p oduc ion
equipmen , which can be moni o ed using he O e all Equipmen E ec i eness indica o . The
a icle aims o desc ibe he modi ica ion o he O e all Equipmen E ec i eness indica o in o
he indica o o O e all Labo E ec i eness in a gi en company. The ad an age o his
indica o is ha i moni o s no only he use o he employee's labo pool bu also he ac ual
cos s spen on he p oduc . In addi ion o ha , he impac o he in oduc ion o his indica o
on he economic pe o mance o a gi en company is analyzed. To do so, ou pe iods be o e
and ou pe iods a e he in oduc ion o he O e all Labo E ec i eness indica o we e
analyzed using ou selec ed inancial a ios. The alue o he O e all Labo E ec i eness
indica o is cu en ly in he ange o excellen alues, i.e. he i m uses p oduc ion ime e y
e icien ly. The esul s o he analyzed inancial a ios show ha he in oduc ion o he
O e all Labo E ec i eness indica o inc eased he pe o mance o he gi en company.
Keywo ds
Compe i i eness; Financial a ios; Losses; P oduc i i y; Pe o mance indica o .
In oduc ion
Cu en ends in inancial managemen aim o analyze he company’s pe o mance using he
sha eholde alue c ea ion indica o . This concep is based on alue managemen heo y. This
is a consis en applica ion o he c i e ion o maximizing he ne p esen alue ha he
company is able o c ea e o i s owne s, i.e., maximizing sha eholde alue.
O e se e al decades, a wide ange o measu es has been de eloped o exp ess a company’s
pe o mance. The changes in usage o a ious measu es e lec he de elopmen o iews on
measu ing company pe o mance om p o i ma gins and e u n on in es ed capi al o
mode n concep s based on alue managemen and sha eholde alue c ea ion. Pe o mance
measu emen sys ems con aining benchma ks a e p oposed o suppo he company’s s a egy.
Many companies in he manu ac u ing indus y bo h ab oad and in he Czech Republic a e
nowadays using he O e all Equipmen E ec i eness indica o (OEE) o measu e and manage
hei pe o mance. This indica o has been modi ied in o se e al so-called de i ed indica o s
based on a ious equi emen s in he e iciency assessmen . One o he de i ed indica o s is
he O e all Labo E ec i eness (OLE). Howe e , he applica ion o he O e all Labo
E ec i eness indica o is no e y common in p ac ice. In addi ion o ha , his indica o is no
o g ea in e es o scien is s; i s usage was men ioned e.g., by B aglia e al. [1] o Deepak e
al. [2]. Fo his eason, he au ho s o his a icle ha e ocused on he issue o calcula ing his
indica o and i s applica ion in he selec ed company. Fu he mo e, he in luence o he OLE
indica o ’s in oduc ion on he company’s pe o mance was also analyzed.
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1 Li e a u e Resea ch
Pa men e [3] s a es ha many companies use w ong measu es ha a e inco ec ly called key
pe o mance indica o s (KPIs). He ecommends ule 10/80/10, i.e., he e a e en key esul s
indica o s, 80 pe o mance indica o s, and en key pe o mance indica o s in he company.
O he au ho s, such as Kaplan and No on [4], also add essed he numbe o indica o s and
ecommended a maximum o 20 key pe o mance indica o s. Remeš and Goswami [5] lis
i e basic business pe o mance measu es ca ego ies ( ypes). Howe e , e y ew companies
moni o hei co ec key pe o mance indica o s. The eason is ha e y ew companies,
esponsible pe sons, consul an s, e c., know wha a key pe o mance indica o is.
One me hod o measu ing pe o mance ha companies widely use is “O e all Equipmen
E ec i eness (OEE)” [6]. O e all equipmen e iciency (OEE) is an indica o o p oduc ion
equipmen e iciency, which compa es he e iciency o indi idual p oduc ion equipmen and
en i e p oduc ion lines. In he 1960s, i was compiled by Seiichi Nakajima om he Nippon
Denso company o he Japanese Ins i u e o Plan Main enance. This is a c ucial indica o
ha helps o de ec he hidden capaci y o p oduc ion machines, i.e., o iden i y losses.
U iliza ion o hidden capaci ies helps inc ease p oduc i i y, educe p oduc p ices, secu e
compe i i e ad an age, and ul ima ely inc ease he company’s ope a ing p o i . The OEE
indica o aims o minimize was age, inc ease ou pu and quali y measu es, and hus imp o e
e iciency [7]. The p ope using o he OEE indica o equi es using app op ia e ools
enabling eal- ime managemen o equipmen [8]. This is consis en wi h he indings o
Yazdi e al. [9], who s udied he ela ionship be ween he OEE indica o and indi idual
aspec s o indus y 4.0. The usage o he OEE indica o s was u he s udied e.g., by Li e al.
[10], Di Luozzo e al. [11], o Aminuddin e al. [12].
2 Resea ch Objec i es
The a icle’s main aim is o measu e he in oduc ion o he indica o o O e all Labo
E ec i eness on he pe o mance in a gi en company. The modi ica ion is called O e all
Labo E ec i eness, and i is designed o analyze capaci y losses caused by human capi al-
ela ed down ime in he o m o absen eeism o shi changes. The main eason o
in oducing his indica o is o moni o he use o he labo o ce (wo ke ), i.e., i s
p oduc i i y. This indica o is ela i ely new; he e a e only a ew esea ch a icles ocused on
his opic. The ad an age o his indica o is ha i moni o s no only he use o he
employee’s labo pool bu also he ac ual cos s spen on he p oduc . Fu he mo e, he a icle
analyzes he in luence o he in oduc ion o he OLE indica o in a gi en company ope a ing
in he au omo i e indus y in he Czech Republic. The e o e, wi h he help o selec ed a ios,
he economic pe o mance o a gi en company in ou pe iods be o e and ou pe iods a e
he in oduc ion o OLE has been analyzed.
3 Me hodology
Based on li e a u e esea ch, he O e all Equipmen E ec i eness indica o was
cha ac e ized. Fu he mo e, he p ima y h ee subcomponen s o he OEE indica o we e
de ined. Subsequen ly, he me hod o i s calcula ion was desc ibed. Addi ionally, h ee online
consul a ions using Google Mee (Ap il, Augus , and No embe 2021) we e conduc ed wi h
he CFO o he analyzed company. The analyzed company is a subsidia y o a mul ina ional
company, and i s main business is he p oduc ion o one single componen o he au omo i e
indus y. The company ca ies ou only he inal assembly o a gi en componen , and a he
same ime, each manu ac u ed componen unde goes a inal inspec ion. The analyzed
company is classi ied as a la ge en e p ise acco ding o all he measu es (ne asse s, u no e ,
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and employees). In hese consul a ions, ques ions we e di ec ed o he ollowing basic
in o ma ion:
• wha easons led he company o modi y he OEE indica o o an OLE indica o ,
• whe e he company has d awn expe ience and in o ma ion o he in oduc ion o he OLE
indica o ,
• how he company has se up he calcula ion o he modi ied OLE indica o and how i has
e i ied he accu acy o i s p edic i e powe ,
• how he indica o was communica ed o he s a ,
• how he ade union and he employees eac ed o he new indica o ,
• how long i ook o in oduce he indica o in he en e p ise,
• wha he en e p ise sees as he bene i s o in oducing he OLE indica o .
Based on he in o ma ion men ioned abo e, he o mula o calcula ing he OLE indica o is
p esen ed, including he cha ac e is ics o i s subcomponen s. The calcula ion o he OLE
indica o alue is based on speci ic alues epo ed by he company, which had o be adjus ed
by a single coe icien no o disclose speci ic in o ma ion.
To assess he impac o he in oduc ion o he OLE indica o on he inancial esul s, da a
ob ained om he Magnus Web da abase was used, namely om he basic inancial
s a emen s, including o he supplemen a y da a. Fou pe iods be o e and ou pe iods a e he
in oduc ion o he OLE we e analyzed. Fo his analysis, he ollowing ou indica o s we e
chosen o compa e he impac o OLE: Ne P o i pe Employee, Ea nings be o e In e es and
Taxes pe employee, Re u n on Asse s, and Re u n on Sales.
4 O e all Equipmen E ec i eness Indica o
The OEE alue is i al in o ma ion o companies ha con inuously wan o imp o e and
s eamline hei p oduc ion p ocesses. This indica o comp ises se e al componen s
(pa ame e s) ha can be e alua ed sepa a ely and hus in luence he o e all e ec i eness.
OEE helps maximize he company’s asse s o he a ailabili y o ime (A ailabili y) in
p oducing ou pu (Pe o mance) wi h he bes p oduc quali y (Quali y) [13].
The o e all e ec i eness o he equipmen is an e ec i e ool o iden i ying bo lenecks. I
can be in eg a ed wi h o he con inuous imp o emen ools and echniques [14]. I is used in
imp o emen p og ams such as down ime managemen (DTM), lean manu ac u ing, Six
Sigma, o Kaizen. Hence, he indica o o o e all equipmen e ec i eness (OEE) is sui able
o educing he iden i ied losses and hus imp o ing bo h pe o mance and quali y in
p oduc ion, leading o an inc ease in he company’s ope a ing p o i .
The OEE indica o cap u es in o ma ion on he a ailabili y, pe o mance o p oduc ion
acili ies, and p oduc ion quali y. The esul ing alues o hese h ee sub-indica o s a e
a ec ed by ce ain losses. Sohal e al. [15] iden i ied he ollowing six main losses ela ed o
a ailabili y, pe o mance, and quali y:
• poo p oduc i i y and los yield due o poo quali y,
• se -up and adjus men o p oduc mix change,
• p oduc ion losses when empo a y mal unc ions occu ,
• di e ences in equipmen design speed and ac ual ope a ing speed,
• de ec s caused by mal unc ioning equipmen , and
• s a up and yield losses a he ea ly s age o p oduc ion.
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Jonsson and Lesshamma [16] classi ied hese losses in o he h ee ollowing g oups:
down ime losses (a ailabili y), speed losses (pe o mance), and quali y losses. Each g oup
consis s o wo subg oups ha cha ac e ize he losses in mo e de ail, see Table 1.
Tab. 1: Losses a ec ing he esul ing alues o indi idual ac o s o OEE
Ca ego y
o losses
Fac o o
OEE
Type (subg oup)
o losses
Examples o losses
Down ime
A ailabili y
B eakdown losses
Equipmen ailu e
Damage o he ins umen
Unscheduled b eaks
Wai ing o wo k o be assigned
E o s in logis ics in he deli e y o inpu
ma e ial
Se -up and
adjus men losses
Hea ing p ocesses
Tool change
Speed loss
Pe o mance
Idle losses
(machine does no
wo k)
Tempo a y diso de
Change in p oduc ion
De ec i e ma e ial deli e ed
Speed educ ion
Di e ence be ween cons uc ion speed
and ope a ing speed
Poo echnical condi ion o he machine
Unskilled labo
Quali y
Quali y
Machine un-up
Hea ing p ocesses
Failu e o comply wi h s anda ds
Quali y de ec s
Failu e o comply wi h echnological
p ocedu es
De ec i e inpu ma e ial (sc ap
p oduc ion)
Machine ailu e
Unclea ask assignmen
Employee e o s
Sou ce: Own elabo a ion based on [17] and [18]
4.1 The Calcula ion o he O e all Equipmen E ec i eness Indica o
The OEE consis s o h ee sub-componen s: machine usage (a ailabili y), machine
pe o mance, and quali y le el o p oduc ion. The calcula ed alues o hese indi idual
componen s a e mul iplied oge he o ob ain he esul ing OEE alue. I s alue is gi en as a
pe cen age o he u iliza ion o he s anda dized capaci y o he equipmen . Simply pu , i
de e mines he pe cen age o p oduc ion ime ha is genuinely p oduc i e. I he OEE
indica o is equal o 100%, i means 100% quali y (good p oduc s only), 100% pe o mance
(as as as possible), and 100% a ailabili y (no down ime). I he alue o he OEE is g ea e
han 85%, i usually ep esen s excellen alues, meaning ha he company wo ks e y
e icien ly. Howe e , he esul ing pe cen age a ies acco ding o he ype o p oduc ion -
while in ba ch o piece p oduc ion, he pe cen age is, in p inciple, smalle , in mass and highly
au oma ed p oduc ion, i is be ween 90 and 100% [8]. The OEE indica o is calcula ed using
o mula 1.
OEE = A ailabili y a e × Pe o mance e iciency × Quali y a e × (100%) (1)
The exac de ini ion o OEE di e s be ween applica ions and au ho s. Table 2 shows he wo
app oaches applied by Nakajima [19], he o iginal au ho o OEE, and De G oo e [20].
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Tab. 2: The calcula ion o he OEE indica o
Indica o
Nakajima [19]
De G oo e [20]
A ailabili y
(A)
Loading ime − down ime
Loading ime
Planned p oduc ion ime − Unplanned down ime
Planned p oduc ion ime
Pe o mance
(P)
Ideal cycle ime × ou pu
Ope a ing ime
Ac ual amoun o p oduc ion
Planned amoun o p oduc ion
Quali y (Q)
Inpu − olume o quali y de ec s
Inpu
Ac ual amoun o p oduc ion − nonaccep ed amoun
Ac ual amoun
OEE
(A)×(P)×(Q)
(A)×(P)×(Q)
Sou ce: Own elabo a ion based on [19] and [20]
Figu e 1 shows he inpu alues ha a e used o calcula e he indi idual componen s o he
OEE indica o . The o al a ailable ime ep esen s a pe iod o 7 days pe week and 24 hou s
pe day. The e a e pe iods when p oduc ion is nei he ealized no scheduled wi hin his ime
ame. This is planned down ime, which includes days o wo k and public holidays alling on
a wo king day.
Sou ce: Own elabo a ion based on [15]
Fig. 1: Illus a ion o he main componen s o OEE
In o de o cap u e c i ical da a and o examine how p oduc ion con ibu es o o e all
company pe o mance, i is i al o measu e and unde s and how o quan i y ailu es in he
p oduc ion p ocess. Managemen expe s commonly e e o OEE measu emen as he bes
me ic o iden i ying losses, ad ancing p og ess, and imp o ing p oduc ion equipmen
p oduc i i y. By measu ing OEE, impo an in o ma ion can be ob ained on how o imp o e
he p oduc ion p ocess sys ema ically. Mos manu ac u ing companies, e en oday, ha e an
OEE sco e o abou 60% and a e mo e likely o encoun e companies wi h OEE alues below
45% han companies wi h OEE alues abo e 85% [21].
Today, many companies in he ield o indus ial au oma ion, no only ab oad bu also in he
Czech Republic, deal wi h he measu emen and e alua ion o OEE, which o e consul ing

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se ices and speci ic so wa e, applica ions, and en i e sys ems o da a collec ion, e alua ion,
and p esen a ion.
4.2 Applica ion o he OEE P inciples o he Wo k o ce in he Analyzed Company
Following he new equi emen s in he e alua ion o e ec i eness, so-called de i ed
indica o s ha e been de eloped, which a e ocused on ei he he equipmen o he en e p ise
le el. One o he mos widely used indica o s is he To al Equipmen E ec i eness
Pe o mance (TEEP). The nex de i ed indica o is P oduc ion Equipmen E iciency (PEE).
O he de i ed indica o s co espond o he speci ic equi emen s o pa icula indus ies
(O e all Asse / P ocedu e E ec i eness – OAE, OPE). Fo exp essing he e iciency o he
whole en e p ise, he O e all Fac o y E ec i eness (OFE) indica o is used [22].
The analyzed company has implemen ed i s modi ica ion o he OEE indica o , namely he
indica o o labo e iciency (OLE). In his modi ica ion, capaci y losses, which in he case o
OEE ep esen down ime, se -up, and adjus men , a e eplaced by human capi al- ela ed
down ime in he o m o absen eeism o shi changes. Simila ly, capaci y losses in he case o
OEE a e eplaced by missing p ocesses, lack o aining, o s a wo king non-s anda d. The
las pa o he OEE indica o ocuses on quali y, which ocuses on quali y e o s, he need o
ewo k, o s a -up e o s. These quali y- educing ac o s a e e ained in he modi ica ion o
he OEE o OLE in he case o quali y e o and need o ewo k. A he same ime, he amp-
up e o ac o is modi ied o he non-compliance wi h p ocesses ac o . To calcula e he
O e all Labo E ec i eness, he analyzed company adjus ed he calcula ion o he indi idual
componen s as shown in o mulas 2, 3, and 4.
A ailabili y = P oduc i e ime +Ex e nal ex a wo k
To al p oduc ion ime (2)
Pe o mance = Numbe o aul less p oduc s x s anda d ime + Ex e nal ex a wo k
P oduc i e ime + Ex e nal ex a wo k (3)
Quali y = 1 − Sc apping cos s
Ma e ial cos s (4)
4.3 P ocess o Implemen a ion o he OLE Indica o in he Analyzed Company
To succeed in a compe i i e ma ke , he company consis en ly applies a cus ome -o ien ed
managemen sys em. Fo his eason, i is cons an ly imp o ing and enhancing i s p oduc ion
p ocesses and in oducing indica o s ha will lead o imp o ed p oduc ion e iciency and
quali y. The key pe o mance indica o in he analyzed company is modi ying he OEE
indica o o he OLE indica o .
When he company decided o moni o he OLE indica o , i i s had o answe he ques ion,
“Why in oduce and moni o his indica o ?” Fi s ly, he company decided o use only one
comp ehensi e indica o ins ead o a a ie y o indica o s o measu e and manage i s
pe o mance. The cus ome s pu p essu e on he company o keep he cos o he equi ed
p oduc s as low as possible. The e o e, i was necessa y o s a moni o ing he use o
indi idual employees’ wo k unds o a oid unnecessa y down ime and achie e he highes
possible labo p oduc i i y. The in oduc ion o a single OLE indica o will lead o he
de e mina ion o all employees’ bonuses. A he same ime, i will inc ease he mo i a ion o
each employee. This will align wi h he goals o he company and i s employees.
The second ques ion was, “Whe e o ge expe ience and in o ma ion o implemen he OLE
indica o ?” Selec ed employees comple ed aining on he use o he OLE indica o , whe e
hey could discuss he issue and p oblems wi h he implemen a ion o he indica o wi h
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companies ha al eady had he indica o in place o we e implemen ing i . Finally, ye
impo an ly, i was necessa y o d aw on he heo e ical in o ma ion p o ided in he li e a u e
o p o essional a icles.
In he nex s ep, i was necessa y o ask, “How o se he calcula ion o he indica o and adap
i o he condi ions o he company?” Se e al yea s ago, he company had da a a ailable o
indi idual p oduc ion lines and indi idual shi s. Based on his da a, he company was able o
de e mine a o mula o calcula ing he OLE indica o and se app op ia e goals.
Subsequen ly, he calcula ion o he gi en indica o had been pe o med o se e al p e ious
yea s, which showed ha in some pa ame e s he calcula ion was no accu a e. The o mula
has been modi ied o p o ide ele an in o ma ion based on hese indings.
The inpu alues o he calcula ion o O e all Labo E ec i eness (OLE) in he analyzed
en e p ise, which a e p esen ed in Table 3, we e adjus ed by a cons an coe icien . Based on
he gi en da a, o mulas 2, 3, and 4 we e used o calcula e indi idual componen s o he OLE
indica o .
Tab. 3: The calcula ion o O e all Labo E ec i eness
Ini ial si ua ion
Shi ime s uc u e
Hou s
Shi leng h
8 hou s
P oduc i e ime
130.0
Lunch b eak
30 minu es
In e nal ex a wo k
0.0
Numbe o wo ke s in he line
20 wo ke s
Ex e nal ex a wo k
6.5
Numbe o handle s in he line
1 wo ke
Wai ing o ma e ial
0.0
S anda d ime
125 minu es pe 100 pieces
Manipula ion
7.5
Machine epai s
6.0
Shi eco ding
P oduc ion changes
6.0
Numbe o p oduc ion changes
3 imes pe shi
T aining
0.0
Time o change p oduc ion
6 minu es
Sampling
10.0
Technical down ime
18 minu es
To al p oduc ion ime
166.0
P oduc ion o samples
30 minu es
Addi ional ma e ial inspec ion
1 wo ke
Numbe o aul less p oduc s
6,000 pieces
Ma e ial cos s
900,000 CZK
Sc apping cos s
3,750 CZK
Sou ce: Own
A alabili y = 130.0+6.5
166.0 ×100 =82.23%.
Pe o mance = [(6,000 ×125):100]:60+ 6.5
130.0+6.5 ×100 =125+6.5
136.5 ×100 = 131.5
136.5 ×100 =96.34%.
Quali y = 1 − 3,750
900.000 ×100 =(1 − 0.00417)×100 = 0.99583 × 100 = 99.583%.
OLE = (0.8637 x 0.9634 x 0.99583) x 100 = 82.86%.
The esul ing alue o he OLE indica o co esponds o a good pe o mance bu i should be
inc eased o o e 85%, which is he ma k o excellen companies.
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4.4 Impac o he In oduc ion o he OLE Indica o on he Economic Resul s
o he Analyzed Company
Since he company does no wish o disclose speci ic OLE da a, da a om he Balance Shee ,
P o i and Loss S a emen , and o he supplemen a y da a ga he ed om he MagnusWeb
da abase we e used o assess he impac o he in oduc ion o OLE in he analyzed company.
The a e age alues o selec ed inancial a ios calcula ed o he moni o ed indica o s be o e
and a e he in oduc ion o he OLE indica o a e p esen ed in Table 4. The yea s 2020 and
2021 we e no included in he analysis pe iod as he economic esul s a e al eady a ec ed by
he impac o he Co id-19 pandemic.
Tab. 4: A e age alues o selec ed indica o s be o e and a e he in oduc ion o he OLE
indica o
Ra io
A e age alues o selec ed a ios be o e in oducing
he OLE indica o
2012 – 2015
2016 – 2019
ROA (in %)
7.20
8.63
ROS (in %)
3.22
3.80
EAT pe one ull- ime employee
(in housands CZK)
154.35
208.88
EBIT pe one ull- ime employee
(in housands CZK)
209.08
228.20
Sou ce: Own elabo a ion based on he da a om MagnusWeb da abase
The ne p o i pe employee in he i s yea a e he OLE indica o was in oduced declined.
In he ollowing yea s, he EAT a io g adually inc eased, and he alues in each yea
signi ican ly exceeded he alues be o e in oducing he OLE indica o . A e in oducing he
OLE indica o he a e age EAT pe employee inc eased by app oxima ely 50,000 CZK. The
same de elopmen was also obse ed in he EBIT pe employee. A e in oducing he OLE
indica o he a e age EBIT pe con e ed employee inc eased by app oxima ely 20,000 CZK.
Nex , he de elopmen o wo p o i abili y a ios (ROA and ROS) was analyzed. The inpu s
used o calcula e he ROA a io we e ne p o i and o al asse s. The in oduc ion o he OLE
indica o led o an inc ease in he Re u n on Asse s a io. A e he in oduc ion o OLE, he
a e age ROA a io inc eased by 1.4%. A simila de elopmen was obse ed o he ROS
indica o . A e in oducing he OLE indica o he a e age ROS a io inc eased by 0.6%.
Based on he esul s, i can be concluded ha he in oduc ion o he OLE indica o led o an
inc ease in he company’s pe o mance. F om he esul s o he moni o ed a ios, i can be
concluded ha he en e p ise uses p oduc ion ime p oduc i ely and, he e o e, minimizes
ime losses. The co ec iden i ica ion o ime losses has p obably led o inc eased p o i s,
which is e lec ed in an inc ease in p o i abili y alues. Da a on p oduc sc ap a es we e no
p o ided, so i is no possible o de e mine whe he he e has been a educ ion in sc ap a es.
5 Discussion
The ad an age o his indica o o he company was ha i s in oduc ion did no en ail
signi ican in e en ions in managemen . The indica o was in oduced in he company wi hin
six mon hs. This b ie pe iod o ime was due o he ac ha he company had he necessa y
da a om se e al yea s back, on which i could e i y he design, unc ionali y, and
in o ma i e powe o he OLE indica o . In e ms o he achie ed alue o he OLE indica o
p esen ed in Table 3, he esul anks he analyzed company among he companies ha wo k
e y e icien ly, i.e. ha hey use p oduc ion ime e ec i ely. The in oduc ion o he OLE
15
indica o also led o an inc ease in he inancial pe o mance indica o s, as shown in Table 4.
The ob ained esul s ela e only o he analyzed company, and o his eason, hese esul s
canno be gene alized.
Gene ally speaking, he OEE and de i ed indica o s co e all he causes o ime loss ha can
be conside ed in a gi en si ua ion. In addi ion o ha , hese indica o s can be exp essed in
mone a y uni s almos immedia ely. The e is no need o wai o he publica ion o inancial
s a emen s o calcula e he loss. In e ms o quali y, he issue o he p oduc ion o de ec i e
p oduc s en e ed he subconscious mind o employees, which led o i s educ ion. Howe e , i
is necessa y o ealize ha he p oduc ion o a de ec i e p oduc may no be caused only in he
p oduc ion p ocess bu may be caused by o he in luences, such as he de ec i e ma e ial
supplied, e c. [1]. When e alua ing he esul ing alues o he OLE indica o , i is always
necessa y o conside he ield o business and he ype o p oduc ion. Fu he mo e, he OLE
indica o moni o s he use o he employee’s labo pool and he ac ual cos s spen on he
p oduc [2]. O he au ho s, such as Bonci e al., sugges in oducing a new LEAN-ROLE
indica o ha can iden i y he employees’ con ibu ion o he cus ome ’s alue [23].
Conclusion
The OLE indica o mus be aken as a concep co e ing e e y hing ha happens in he
p oduc ion p ocess. The eason o he in oduc ion o his indica o was o moni o he use o
he labo o ce (wo ke ), i.e., his p oduc i i y. I is also c ucial o employees o be gi en one
indica o ha hey can moni o hemsel es, which has also led o a modi ica ion o he
emune a ion sys em. This indica o a ec s he bonuses o all employees based on hei wo k
pe o mance. Employees see (unde s and) ha his is a ai dis ibu ion o bonuses and
he e o e accep his indica o . The in oduc ion o he OLE indica o has led o an inc ease in
employee awa eness o he impo ance o p oduc ion.
The au ho s would like o con inue wi h hei esea ch by p epa ing a ques ionnai e su ey,
which would ocus on companies wi h he same ield o business as he analyzed company.
The esul s o he esea ch would p o ide in e es ing in o ma ion, since he OEE, OLE
indica o s o o he modi ica ions o he OEE indica o and hei impac on inancial
pe o mance a e no a e y common opic o esea ch a icles.
Acknowledgmen s
This a icle was c ea ed in acco dance wi h he ins i u ional suppo o he concep ual
de elopmen o he Facul y o Economics o he Technical Uni e si y o Libe ec P ojec :
In e nal g an compe i ion called “Využi í mode ních ukaza elů e ek i nos i p o řízení
podniku nejen době globální k ize”.
Li e a u e
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L.: Re ised o e all labou e ec i eness. In e na ional Jou nal o P oduc i i y and
Pe o mance Managemen . 2021, Vol. 70, Issue 6, pp. 1317–1335. ISSN 1741-0401.
DOI: 10.1108/IJPPM-08-2019-0368
[2] DEEPAK, V.; BHASKAR, S.; BALAJI, M.: Enhancing O e all Labou E ec i eness
o CSD Wa ehouse by Adop ing Lean Tools in Cons uc ion Equipmen Manu ac u ing
P ocess. Indus ial Enginee ing Jou nal. 2021, Vol. 14, Issue 1, pp. 40–48. ISSN 0970-
2555.
[3] PARMENTER, D.: Key Pe o mance Indica o s: De eloping, Implemen ing, and Using
Winning KPIs. 3 d edi ion. Wiley, Hoboken, 2015. ISBN 978-1-118-92510-2.