Logistics maturity model for service company – theoretical background

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Procedia Manufacturing 17 (2018) 791–802 Procedia Manufacturing 00 (2017) 000–000 www.elsevier.com/locate/procedia

28th International Conference on Flexible Automation and Intelligent Manufacturing 28th International ConferenceJune on Flexible Automation and OH, Intelligent (FAIM2018), 11-14, 2018, Columbus, USA Manufacturing (FAIM2018), June 11-14, 2018, Columbus, OH, USA

ManufacturingLogistics Engineeringmaturity Society International Conference 2017, MESIC 2017, 28-30 June model for service company 2017, Vigo (Pontevedra), Spain Logistics maturity model for service company

– theoretical background – theoretical background *a Costing models for capacity optimization inKosacka-Olejnik Industry 4.0:aa Trade-off Karolina Werner-Lewandowska , Monika *a Karolina Werner-Lewandowska , Monika Kosacka-Olejnik between capacity andManagement, operational Poznan University of used Technology, Faculty of Engineering Strzelecka 11,efficiency Poznan 60-965, Poland a a

Poznan University of Technology, Faculty of Engineering Management, Strzelecka 11, Poznan 60-965, Poland

A. Santana , P. Afonso , A. Zanin , R. Wernke Abstract Abstract a University of Minho, 4800-058 Guimarães, Portugal Objective: The paper presents theoretical background logisticsChapecó, maturitySC,model b Unochapecó,of 89809-000 Brazil for service enterprise. Methodology: There Objective: The paper presents theoretical background of logistics maturity modelcompany for service enterprise. Methodology: There were determined: phases of the industry logistics, business activity areas of service according to SCOR model, logistics were phases of the industry business activity areas of service company according to SCOR tools determined: used by service companies, whichlogistics, were adopted from manufacturing companies, logistics maturity levelsmodel, for thelogistics service tools serviceConclusions: companies, According which weretoadopted from manufacturing companies, logistics maturity thethe service sectorused wereby defined. conducted theoretical research and own observations, it waslevels stated,forthat level sector were defined. conducted theoretical research andof: own observations, it was stated, thatinventory the level of logistics maturity Conclusions: in the serviceAccording company to depends on tools used in the areas planning, procurement, storage, Abstract of logistics maturity in theand service company on of tools used in the areas of: service planning, procurement, storage, inventory management, distribution reverse logistics.depends The level logistics maturity in the sector may be referred to particular management, distribution and reverse logistics. The level of logistics maturity theroots service sector mayliebeinreferred to particular phases of industrialoflogistics evolution. Research limitations/implications: The of the model interpretation made Under thetheconcept "Industry 4.0", production processes will be in pushed to be increasingly interconnected, phases of the industrial evolution. Research limitations/implications: The1950s roots of the model liecapacity in interpretation made by authors of based the paper the field of: logistics development and SCM since the observations regarding the logistics information on in alogistics real time basis and, necessarily, much more efficient. Inand this context, optimization by authors of the paper in the field of: logistics development and SCM since the 1950s and observations regarding the logistics tools used in the services sector. Practical impact: The logistics maturity model for service company will be used for scientific goes beyond the traditional aim of capacity maximization, contributing also for organization’s profitability and value. tools used in theout services sector. Practical impact: Theinlogistics forofservice company be service used forsector. scientific research carried on Polish service service industry, order to maturity examine model the level logistics maturitywill in the Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of research carried out on maturity Polish service order to examine level of logistics maturity in the service sector. Originality: Logistics modelservice basedindustry, on threeindimensions of thethe assessment including: SCOR model, phases of the maximization. The study of capacity optimization and costing models is an important research topic that deserves Originality: Logistics maturity tools, modelhas based on three dimensions including: SCORresearch. model, Moreover, phases of the industry logistics and logistics become original approachofinthe theassessment field of logistics maturity contributions both practical theoretical Thisfield paper presentsmaturity and discusses a mathematical industry logistics logistics tools, has become originalperspectives. approach the of logistics research. Moreover, the added-value of from theand model isthe dedication forand service industry, which is ininresearch niche. model for capacity management based on different costing models (ABC and TDABC). A generic model has been added-value of the model is dedication for service industry, which is in research niche. developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization’s © 2018 The Authors. Published by Elsevier B.V. © 2018 The Authors. Published by Elsevier B.V. value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity © 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) This is an open access article under CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) optimization might hide operational inefficiency. Peer-review under responsibility of the scientific committee of the 28th Flexible Automation and Intelligent Manufacturing Peer-review under responsibility of the scientific committee of the 28th Flexible Automation and Intelligent Manufacturing Peer-review under responsibility ofElsevier the scientific © 2017 The Authors. Published by B.V. committee of the 28th Flexible Automation and Intelligent Manufacturing (FAIM2018) Conference. (FAIM2018) Conference. (FAIM2018)under Conference. Peer-review responsibility of the scientific committee of the Manufacturing Engineering Society International Conference Keywords: logistics maturity model, SCOR, service company 2017. a

a,*

b

b

Keywords: logistics maturity model, SCOR, service company Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency

Corresponding author: Tel.: +48 61-665-34-14; fax: +48 61-665-33-75; E-mail address: [email protected]  1.* Introduction

* Corresponding author: Tel.: +48 61-665-34-14; fax: +48 61-665-33-75; E-mail address: [email protected]  2351-9789 © 2018 Thecapacity Authors. Published by Elsevier information B.V. The cost of idle is a fundamental for companies and their management of extreme importance This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 2351-9789 © 2018 Thearticle Authors. Published by Elsevier B.V. in modern production systems. In general, it is defined as unused capacity or production potential and can be measured Peer-review under responsibility of the scientific committee of the 28th Flexible Automation and Intelligent Manufacturing (FAIM2018) This is an open access article under CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) in several ways: tons of production, available hours of manufacturing, management of (FAIM2018) the idle capacity Conference. under responsibility of the scientific committee of the 28th Flexible Automationetc. Peer-review and The Intelligent Manufacturing * Paulo Afonso. Tel.: +351 253 510 761; fax: +351 253 604 741 Conference. E-mail address: [email protected]

2351-9789 Published by Elsevier B.V. B.V. 2351-9789©©2017 2018The TheAuthors. Authors. Published by Elsevier Peer-review underaccess responsibility the scientific committee oflicense the Manufacturing Engineering Society International Conference 2017. This is an open article of under the CC BY-NC-ND (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 28th Flexible Automation and Intelligent Manufacturing (FAIM2018) Conference. 10.1016/j.promfg.2018.10.130

Karolina Werner-Lewandowska et al. / Procedia Manufacturing 17 (2018) 791–802 Author name / Procedia Manufacturing 00 (2018) 000–000

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1. Introduction Authors stated, that logistics has become a critical success factor. The growing importance of logistics in enterprises resulted in the emergence of term: logistics maturity. Authors noticed, that the concept of process maturity of organization is still dominant. In the result, there are only research on process maturity assessment considering logistics as an aspect, not focused on logistics maturity model. The first logistics maturity model was established by USA Research Institute in 2006, which determined a Logistics Maturity Pyramid for research on maturity of American Government Agencies, described in [1].Recently, research in the field of logistics maturity and the development of a logistics maturity model has been carried out by Italian researchers C. Battista, A. Fumi, M. M. Schiraldi [2, 3]. They have conducted research on logistics maturity model application in fashion industry. In Poland there is lack of research on logistics maturity. Moreover, the originality of the presented research is related to object of the logistics maturation – namely service companies. Research conducted on Nominal GDP sector composition in 2017 confirms the significance of service sector [Table 1]: Table 1. Nominal GDP sector composition in 2017 [4,5]. No

Country

Nominal GDP M$

Agriculture %

Industry %

Services %

Agriculture M$

Industry M$

Services M$

1

USA

19362

0.90%

18.90%

80.20%

174.26

3659.44

15528.40

2

China

11938

8.20%

39.50%

52.20%

978.88

4715.35

6231.43

3

Japan

4884.5

1.00%

29.70%

69.30%

48.85

1450.70

3384.96

4

Germany

3651.9

0.60%

30.10%

69.30%

21.91

1099.22

2530.77

5

France

2574.8

1.60%

19.40%

78.90%

41.20

499.51

2031.52

6

UK

2565.1

0.60%

19.00%

80.40%

15.39

487.37

2062.34

7

India

2439

16.80%

28.90%

46.60%

409.75

704.87

1136.57

8

Brazil

2080.9

6.20%

21.00%

72.80%

129.02

436.99

1514.90

9

Italy

1921.1

2.10%

24.00%

73.90%

40.34

461.06

1419.69

10

Canada

1640.4

….

…

1.70% …

28.10% …

70.20% …

27.89 …

460.95 …

1151.56 …

Poland

510

2.40%

40.20%

64.30%

45627

205.02

327.93

24

Authors stated, that value added resulting from service industry activity makes up majority of whole value added created by Economy. According to data in Table 1, services account for almost 70% of Nominal GDP of top 10 Economies. Situation in Poland, corresponds to worldwide trend. Considering that, it was assumed that service sector is vital and it should be analyzed. However, there are research on maturity of industry or agriculture maturation, there is lack of papers on logistics maturity in service sector. Authors reported, that there is lack of logistics maturation assessment in services, however logistics is included in services activities, what justifies presented research problem. To sum up, authors have identified a research gap in the field of logistic maturity assessment of enterprises from service sector. The objective of the research was to present the theoretical basis in the scope of the logistics maturity model for service enterprise. The study was based on the hypothesis: HB: In the service enterprise logistics processes are carried out, what implies the possibility of developing a logistics maturity model for service enterprise, in the theoretical aspect. The established hypothesis – HB, has been verified through achieving the research objective: RO: Development the theoretical logistics maturity model for service companies. The research goal (RO) was achieved by answering the following research questions (RQ1-RQ3):



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 RQ1: what is the logistics maturity?  RQ2: how to define logistics maturity levels for service company  RQ3: what does characterize particular levels of logistics maturity for service enterprise? In the research, there were made assumptions according to the service industry, as following:  A1: Service enterprise is defined as an organization, business or individual, which offers service to others in exchange for payment.  A2: Service is a transaction, in which immaterial goods are transferred from the seller to the buyer. Service can be described in terms of their key characteristics, sometimes called the Five I's of Services (hereafter: 5 I's), like: Intangible, Inventory, Inseparability, Inconsistence (variability), Involvement [6]. Notwithstanding of the scope or type of services, the fact remains that all mentioned features of services are ascribed to them. Moreover it was stated, that if the service is provided, regardless of its type, it is accompanied by parallel logistic processes. In the result logistics processes should be managed, so that both, service providing process and the accompanying logistics processes would create added-value in time and space. However, due to the service’s features (5 I's), it is impossible to apply the same solutions to logistics processes’ implementation, which occur in a production company. It is mainly affected by service’s immateriality and the inability to store it, and thus the creation of stocks. The remainder of the article is organized as follows: Section 2 presents the background on the subject addressed and related works to logistics maturity models. Section 3 describes three pillars of developed logistics maturity model for service enterprise including: stages of industry logistics, logistics tools used by service companies and areas of logistics activities in service industry adopted from SCOR model. The theoretical model of logistics maturity for service enterprise is presented in the Section 4. Finally, Section 5 summarizes the study with limitations and giving an outlook for further research. 2. Research background 2.1. Logistics maturity models Maturity models (hereafter: MM) have been perceived as most common used tools of new generation, designed for permanently changing demands on goods and services, which encompass more than just quality requirements, but also consider issues including: Environment, people, occupational health, etc. [7, p. 165]. Maturity models are defined as a series of sequential levels, which together form a logical path from an initial state to a final state of maturity [8]. The key is to define stages of maturation paths, what requires to characterize each level and to define logical relationship between them. In the result authors stated, that each maturity level requires description, considering that as the maturity level is higher, the expectations on definition, structuring and standardization are greater. Furthermore, a MM provides recommendations in order to ensure continuous improvement and the achievement of full maturity regarding established axes of interest according to specified achievements criteria [9]. Previous studies proved, that there was made a lot of efforts on MMs (e.g. in [10]), mainly with the use of Capability Maturity Model Integration (CMMI) framework [11, p. 1317]. However CMMI is well-known model, even it was not basic one, because it has roots in the software industry with the Capability Maturity Model (CMM) [12]. Success of CMMI has inspired the development of many MMs in other domains. In the result there were noted different maturity/capability models for the following research areas: software development, quality management, product development, SCM, supplier relationships, R&D, innovation, etc. [13]. Considering growing research interest in that topic, authors assumed that MMs becomes relevant research area. Moreover it was stated, that one of the most important issue is that, prepared models fit purpose. However MMs are different, what was an object of work [10], there may be specified list of common elements of MMs [13]:

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 Limitation in maturity levels’ number (usually from three till six),  Level characteristic described by certain requirements, which should be achieved on that level,  Increasing order of maturity levels adequate for increasing perfection. Although increasing number of MMs, there was identified only one project, which have considered Logistics Maturity Model (hereafter: LMM), according to the paper objective. The mentioned model was prepared by Battista et al. and it was dedicated to fashion industry [2]. However, model developed by Battista et al. was an inspiration for authors of the paper, the LMMSE is quite different, what was mainly affected by adopted approach with three dimensions of assessment and service’s sector dedication. According to Battista et al., LMM aims to support the enterprises to understand the more critical areas of process in terms of immaturity improvement and the right actions to be undertaken for increasing the performances [2, p. 4 ]. In the paper, it was adopted from Battista et al., that focus of the LMM is on logistic processes, which are useful to plan, manage and check the flow of raw materials, of finished goods and their informative flows from the place of origin to consumption destination. Authors of the paper have taken a similar view regarding the way of LMM’s treating as Battista et al., stating that, LMM works as a specific maturity model: likewise to the Capability Maturity Model, however the LMM is focused on the specific dominion of logistics [2, 3]. The research findings by Battista et al. [2, 3] have influenced conducted research on logistics maturity model for service enterprise. However, the presented approach is not process – oriented as LMM determined by Battista et al, because in authors opinion it would not be applicable for service industry. Moreover previous study on LMM [2, 3] did not consider reverse logistics, what was included in the presented model, in order to fulfil the research gap. 3. Logistics Maturity Model for Service Enterprise – theoretical background Logistics Maturity Model for Service Enterprise (LMMSE) is based on 3 pillars: phases of logistics evolution and SCM, SCOR model and logistics tools. In the next subsections: 3.1-3.3, there were presented assumptions made on all aspects, resulting from literature review and authors’ experience and their observations. 3.1. Phases of logistics evolution and SCM There were made a lot of efforts on research on the development/evolution of industrial logistics. In the result of literature review on that topic, authors of the paper claimed that, there is lack of common attitude to periodization and nomenclature of particular evolution stages, especially in its initial phases [14]. What is more, there may be also perceived differences in the stages identification, what is result of researchers’ geo-location (e.g. difference between American, European and Asian approach to the problem). In the paper there were adopted research findings of logistics evolution phases and SCM of Ronald H, Bailou [14]. In order to establish the LMMSE, there were defined stages of Logistics evolution presented in the Table 2. In accordance to data presented in Table1, there were considered two additional logistics evolution stages (P5, P6) in respect of traditional approach to Logistics development. The first one is P5 phase related with Internet and its accessibility, which was considered as a result of looking for a way to operational costs of logistics processes implementation reduction. It has been reflected in e-commerce popularity. What is more, use of the Internet has also influenced the globalization, which is also characteristic feature of phase P5.

5

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Table 2. Phases of evaluation of logistic [14]. Phase

P1

P2

P3

P4

P5

P6

Period of time

to 1960s

to 1980s

1990s

2000s

21 century

Unknown future

Feature

Fragmentation

Consolidation

Functional Integration

Value adding

Network Globalization

Automation

Typical

Demand Forecasting Requirements Planning Sourcing/Purchasing Warehousing Inventory Manufacturing Inventory Material Handling Packaging Distribution Planning Customer Service Transport Order Processing

Materials Management Manufacturing Inventory Warehousing Inventory Packaging Physical distribution

Logistics management 3PL BRP

SCM 4PL Eco logistics Sustainability

Lean SCM SCN GSC e-commerce

4.0 Industry IoT

activities

st

The last phase – P6, was claimed as unknown future in the practical context, however it is not distant, which is apparent from the development of automation and robotics, that is Industry 4.0 age and the Internet of Things. Although many production companies have already achieved this phase, it has still became a far-reaching approach to widespread use, particularly due to the high automation and robotics cost. However, in the field of IoT, a lot of solutions have been already widely used, primarily in trade and marketing. Noteworthy is also the development in the so-called SCM phase. What is more, in authors’ opinion in the 2000s there was the development, or rather the prevalence of the use in the field of Logistics, the pro-ecological approach and thinking in the category of the sustainable development, however it hasn’t been discussed by researchers so far. In the result, Eco Logistics and sustainability were added as typical activities undertaken within the framework of industrial logistics in the 2000s period (phase P4). 3.2. Logistics areas of service company activities The originality of the proposed model lies in leaving well-known maturity models related to the process approach. Although the process orientation was not introduced into LMMSE, process maturity models were not disputed in the paper. The objective of the research was to determine the model in a broader context, which would extend for process approach and allow to assess Logistics maturity in service companies. Therefore, the particular logistics processes are not assessed in LMMSE. On the other hand, the area of logistics activity was examined. In order to determine the logistics areas of the service enterprises, there were used findings of research on LMM [13, 14]. Battista et al. applied a LMM on the basis of SCOR, that they identified four Logistics areas, which become a basis for processes’ classification. In the presented paper, the classification of Logistics areas was adopted from SCOR model, by analogy. The authors adopted this approach in their research. Logistics Areas in LMMSE in reference to LMM areas were presented in the Table 3.

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Table 3. Logistics Areas in LMMSE [3]. SCOR

LMM by Battista

LMMSE

Description

Plan

Plan

Plan (P)

Processes about demand planning

Source

Source

Source (S)

Processes about procurement planning, identification and selection of the suppliers and operative management of procurement orders

Make

Storage

Inventory/Storage(I/S)

Processes about stock management, in/out warehouse flow control, storage areas management and goods transportation management

Delivery

Distribution

Distribution (D)

Processes about shipment planning and transport management

Return

N.A.

Return (R)

Process about reverse flow planning, collecting, recovering and redistributing

With reference to Table 3, it should have been noted that, in the presented model, the Return area, which refers to reverse logistics activities, was introduced, however it was not included into approach developed by originators of incorporation of SCOR model into LMM. 3.3. Logistics tools in service companies In the LMMSE, it was assumed that, the level of logistics maturity achieved by the service company depends on its logistic evolution phase. However, in order to prove, in which phase the company is located, the measurement is necessary. Therefore, it was assumed, that the performance measurement system is based on use of logistic tools, widely known and used in manufacturing enterprises (best practices). In the result, there was used a list of 90 most popular logistic tools proposed by G. Richards, S. Grinsted [15]. Tools were selected, choosing those which were considered as acceptable for services sector. Moreover, authors have added their own proposition of tools. In the result a list of 81 logistic tools was created, which were recognized as appropriate for logistics process realization in a service enterprise. Logistics tools for LMMSE were divided into 11 groups, as shown in Table 4: Table 4. Logistic tools for LMMSE. Group of logistics tools for LMMSE

Number of tools

01 Warehouse management (WM)

15

02 Transport management tools (TM)

6

03 Inventory management tools (IM)

18

04 Supply chain management tools (SCM)

11

05 General management tools (M)

7

06 Performance management tools (PM)

6

07 Financial management tools and ratios (FM)

2

08 Problem-solving tools (PS)

4

09 IT tools (IT)

12

10 Eco-tools (ECO)

N.A.

Total

81



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For the group no 10, Eco-tools group, no tools were defined at this stage of research. This aspect is a subject of other research which have been carried out in parallel research. It has been planned to include that aspect into prepared LMMSE after previous research end. Considering list of Logistics tools, authors were aware that it was not closed and could be developed or modified, based on future research carried out by authors of paper or by other researchers. The list of tools is included in Annex A1. 4. Logistics Maturity Model for Service Enterprise – conception On the basis of the adopted assumptions on the 3 pillars of LMMSE, there was developed the model concept in accordance to the following research steps:  Step 1: Determination of logistics maturity levels based on the phases of industrial logistics evolution,  Step 2: Assignment of the Logistics tolls for LMMSE to SCOR model areas,  Step 3: Assignment of the Logistics tolls for LMMSE to Logistics evolution phase according to the rule: tool ascribed to the phase, where it was applied,  Step 4: LMMSE determinantom. The presented concept is shown in the Table 5: Table 5. Logistics Maturity Model for Service Enterprise.

Logistic Maturity Model for Service Enterprise Area 

  

Level 1

Level 2

Level 3

Level 4

Level 5

Level 6

Fragmentation

Consolidation

Functional Integration

Value adding

Network

Automation

P

SCM01

SCM05, M02, PM01

SCM06, SCM07, M04, M05, M06, PM02, PM04

SCM10, M07, PM05, PM06

WH15, SCM11

IT07, IT08, IT09, IT10, IT11, IT12

S

SCM02, SCM03

SCM04, M03, PM01

SCM09, M04, M05, M06, PM02, PM04

PM05, PM06

IT03, IT06

IT07, IT08, IT09, IT10, IT11, IT12

I/S

WH01, WH02, WH03, WH04

WH05, IM06, IM07, IM08, IM09, IM10, IM11, IM12, M01, M03, PM01

WH06, WH07, WH08, WH09, WH10, WH11, WH12, IM13, IM14, IM15, IM16, IM17, IM18, M04, M05, M06, PM02, PM04

WH14, WH15, PM05, PM06ITO1, IT02

IT06

IT07, IT08, IT09, IT10, IT11, IT12

D

TM01

TM02, TM03, TM04, M01, M03, PM01

SCM08, M05, M06, PM02, PM03, PM04

IT04, IT06

IT07, IT08, IT09, IT10, IT11, IT12

R

No tools

M01, MO3, PM01

M04, M05, M06, PM02, PM04

TM06, M04, PM05, PM06, IT05 TM05, M04, PM05, PM06

SCM11

IT07, IT08, IT09, IT10, IT11, IT12

In the recommended model, there were defined four assumptions (AS1-AS4), which result from each other (Fig. 1).

AS1

A service company may achive one of six logistics maturity levels

AS2 BUT

AS3

AS4

The LMMSE In each Logistics indicates directions BECAUSE logistics area may THAT'S WAY maturity level and areas of be achieved should be assessed company's different level of indyvidually for development in logistics maturity each area order to achieve

Fig. 1. Assumption of LMMSE.

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Considering presented assumptions on LMMSE (Figure 1), there was made a visual presentation of the prepared LMMSE, what was presented in the Figure 2. According to the research theoretical background described in the Section 3, the model was a result of matching three elements: logistics evolution phases (indirect), logistics tools and areas from SCOR model. IT07, IT07, IT07, IT07, IT07,

6

IT08, IT08, IT08, IT08, IT08,

IT09, IT09, IT09, IT09, IT09,

IT10, IT10, IT10, IT10, IT10,

IT11, IT11, IT11, IT11, IT11,

IT12 IT12 IT12 IT12 IT12

WH15, SCM11 IT03, IT06 IT06 IT04, IT06 SCM11

5 SCM10, M07, PM05, PM06 PM05, PM06

4

LEVEL

WH14, WH15, PM05, PM06ITO1, IT02 TM06, M04, PM05, PM06, IT05 TM05, M04, PM05, PM06 SCM06, SCM07, M04, M05, M06, PM02, PM04

3

SCM09, M04, M05, M06, PM02, PM04

LMMSE

WH06, WH07, WH08, WH09, WH10, WH11, WH12, IM13, IM14, IM15, IM16, IM17, IM18, M04, M05, M06, PM02, PM04 SCM08, M05, M06, PM02, PM03, PM04 M04, M05, M06, PM02, PM04 SCM05, M02, PM01 SCM04, M03, PM01 WH05, IM06, IM07, IM08, IM09, IM10, IM11, IM12, M01, M03, PM01

2

TM02, TM03, TM04, M01, M03, PM01 M01, MO3, PM01

1

SCM01 SCM02, SCM03 WH01, WH02, WH03, WH04 TM01 No tools

LMMSE tools

Logistics Areas in LMMSE

Plan

Source

Inventory/Storage

Distribution

Return

Fig. 2. Logistic Maturity Model for Service Enterprise.

In order to evaluate the company with the use of LMMSE, there should have been made a diagnosis of the use of logistic tools. Identification of introduced tools was planned to be performed with the use of simple verification sheet on the basis of questions about tools’ utilization in the company, where there would be only YES/NO answers. Therefore, the result of logistics maturity level will depend on logistics tools applied in the company. 5. Conclusion In the paper, there was presented an original concept of LMMSE, which became a result of conducted research on the literature on the subject of logistics maturity model for service sector. In the authors' opinion, the proposed model has got two limitations: unclosed list of logistic tools and the lack of the possibility of an overall LM evaluation of a service company. Regardless indicated limitations, they not affect the achievement of the research goal presented in the Section 1. The objective was achieved, because research problems were solved. The LMMSE will be used for research on the level of logistics maturity in the Polish service sector. Based on the model, a questionnaire survey will be prepared, regarding the use of logistic tools from the presented list (Appendix A). The survey will be carried out in the second quarter of 2018, on a sample of 2000 enterprises. It will allow to assess LMMSE level in areas defined by the SCOR model. As a direction of future work resulting from this paper, it was proposed to expand the model with logistic strategies implemented by service



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companies. That approach is a consequence of assumed research hypothesis, that there is a correlation between the logistic strategy applied by the company and the logistics maturity level, with respect to the analyzed logistics area. Acknowledgements This paper refers to the research financed by the National Since Center, Poland, project: Research on logistics maturity in service enterprises, grant no. 2016/21/D/HS4/02116 Appendix A. A.1 Toolkit for LMMSE No

Logistic tool

Group

Tool’s ID

1 Pareto analysis /rule, ABC analysis or the vital few analysis

WH01

2 Selecting warehouse storage equipment

WH02

3 Selecting warehouse material handling equipment (MHE)

WH03

4 Warehouse location

WH04

5 Warehouse space calculation

WH05

6 Warehouse location numbering

WH06

7 Warehouse audit 8 5S or 5C, also known as Gemba Kanri 9 Resource planning (including MRPII)

01 Warehouse management (WH)

WH07 WH08 WH09

10 Task interleaving

WH10

11 Using warehouse management system (WMS)

WH11

12 Warehouse maturity scan, by Jeroen van den Berg

WH12

13 Warehouse risk assessment

WH13

14 How to ‘green’ your warehouse and save energy

WH14

15 Outsourcing warehouse 3PL or 4PL

WH15

16 Calculating road freight transport charges and rates

TM01

17 Transport management system (TMS) selection process 18 Transport problems – matching customer demand with supplier capacity 19 Transport audit checklists 20 Calculating emissions in freight transport

02 Transport management tools (TM)

TM02 TM03 TM04 TM05

21 Vendor assurance of transport logistics service providers

TM06

22 ABC Pareto analysis for inventory management

IM01

23 Cycle counting or perpetual inventory counting

IM02

24 Replenishment order quantities

IM03

25 Stock counting

IM04

26 Ballou’s inventory-throughput curve 27 Maister’s rule or the square root rule 28 Measuring demand variation 29 Periodic review inventory management system 30 Reorder point inventory management system

03 Inventory management tools (IM)

IM05 IM06 IM07 IM08 IM09

31 Economic Order Quantity (EOQ), by Geoff Relph

IM10

32 Managing spare parts inventory

IM11

33 Material Requirements Planning (MRP)

IM12

34 Inventory management audit

IM13

800 10

Karolina Werner-Lewandowska et al. / Procedia Manufacturing 17 (2018) 791–802 Author name / Procedia Manufacturing 00 (2018) 000–000

No

Logistic tool

Group

35 Consignment stock

Tool’s ID IM14

36 Combining Pareto with EOQ to enhance group analysis

IM15

37 Safety stock calculation

IM16

38 Vendor-managed inventory (and co-managed inventory)

IM17

39 Identification and disposal of surplus stock

IM18

40 Demand forecasting

SCM01

41 Supplier relationships

SCM02

42 Calculating ordering cost

SCM03

43 How to calculate stockholding cost 44 Sales and Operations Planning (S&OP) 45 Supply chain risk assessment 46 Time-based process mapping

04 Supply chain management tools (SCM)

SCM04 SCM05 SCM06 SCM07

47 Omni-channel distribution

SCM08

48 Strategic procurement

SCM09

49 Supply chain management audit

SCM10

50 Collaborative, Planning, Forecasting and Replenishment (CPFR)

SCM11

51 Flow charts

M01

52 Gantt charts

M02

53 SWOT analysis 54 DMAIC: a process improvement tool 55 Mind maps

05 General management tools (M)

56 The PDCA tool

M03 M04 M05 M06

57 Enterprise Resource Planning – ERP

M07

58 SMART

PM01

59 Performance measurement and quality improvement 60 Performance measures for freight transport 61 Warehouse KPIs 62 Balanced Scorecard 63 Benchmarking 64 Activity-based costing (ABC) and time-driven activity-based costing (TDABC) 65 Supply chain financial ratios and metrics 66 Cause and effect analysis, or fishbone or Ishikawa 67 The 5Whys 68 Brainstorming

06 Performance management tools (PM) 07 Financial management tools and ratios (FM) 08 Problem solving tools (PS)

PM02 PM03 PM04 PM05 PM06 FM01 FM02 PS01 PS02 PS03

69 The -8D approach

PS04

70 EDI

IT01

71 RFID

IT02

72 Purchasing by internet 73 Supplying by internet 74 Truck&Tracing 75 WiFi

IT03 09 IT tools (IT)

IT04 IT05 IT06

76 Bluetooth 77 NFC

IT07

78 Z-WAVE

IT09

IT08



Karolina Werner-Lewandowska et al. / Procedia Manufacturing 17 (2018) 791–802 Author name / Procedia Manufacturing 00 (2018) 000–000 No

Logistic tool

Group

79 Smartphone 80 Cloud 81 Apps Any one

801 11 Tool’s ID IT10 IT11

10 Eco-tools (ECO)

IT12 ECO

12

802

Author name / Procedia Manufacturing 00 (2018) 000–000

Karolina Werner-Lewandowska et al. / Procedia Manufacturing 17 (2018) 791–802

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