Overall Labor Effectiveness as a Tool for Measuring Performance in a Given Company

7 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. 8 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 , 9 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. 10 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]. 11 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 12 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 13 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. 14 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 [1] BRAGLIA, M.; CASTELLANO, D.; FROSOLINI, M.; GALLO, M.; MARRAZZINI, 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.