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A Quick Response Manufacturing
Maturity Model & GAP analysis
Multiple-case study on the QRM concept implementations & importance and
developing a customized improvement guide
J.D. TEN HOONTE
2
A Quick Response Manufacturing
Maturity Model & GAP analysis
Multiple-case study on the QRM concept implementations & importance and
developing a customized improvement guide
Master Thesis, Technology Management University of Groningen, Faculty of Economics and Business
July 10, 2012
J.D. TEN HOONTE Studentnumber: S1944940
Vlasstraat 24a 9712 KV Groningen
Tel.: +31 (0)652161759
E-mail: [email protected]
1st
supervisor/ university Dr. J. Riezebos
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nd supervisor / university Prof. dr. ir. J. Slomp
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Preface I wrote this thesis to complete the master Technology Management at the faculty of Economics & Business
at the University of Groningen. In 2009 I obtained a BSc degree in Mechanical Engineering. After achieving
the bachelor degree, I decided to expand my knowledge with management and operational skills. So, in
2009 I started with the (pre-) Master Technology Management. The Master of Technology Management
gave me the opportunity to expand my competencies in the area of business and economics, without losing
the connection with my previous technological background. The interesting courses, group projects and the
final research project of the master were great learning experiences and a true addition to my future career.
Therefore, I would like to thank several people for their collaboration and support.
First I would like to thank Domingus Usmany. He is a colleague student who informed me in November 2011
about the interesting QRM research, which later became my thesis topic.
Also I would like to thank all the employees at the QRM center and their network partners for their
feedback, suggestions and for spreading the questionnaire around the world. It was a pleasure and honor to
work with the QRM center. Within the QRM center my appreciation especially goes out to Aldert van der
Stoel, employee at the Lectureship lean & QRM centrum Arnhem, which was my contact person within the
practical area of the QRM concept. I really appreciated, that despite his busy schedule and his many long
journeys, he always found time to help and support me during my thesis.
My gratitude goes to Dr. Ir. Jannes Slomp, adjunct professor at the University of Groningen and upcoming
board member at the QRM center, for being my second supervisor.
I would like to thank all participating organizations that took the effort to fill in our questionnaire, without
them it was not possible to make a multiple-case analysis. Especially I want to thank the companies Bosch
Scharnieren en Metaal and Larsen Premium Precision Parts for their extensive tour through their factory
and contribution during the pilot study.
Furthermore I want to thank my colleague students Jeroen, Jana, Jens, Thiemo, Domingus, Matthijs, and
Auke with whom I worked during the (pre-) Master of Technology Management. It was always a pleasure to
work with them and together we achieved great results.
At last but not least, my gratitude goes out to my first supervisor Dr. Jan Riezebos, board member of the
QRM center, professor and director of the Master of Technology Management at the University of
Groningen. Dr. Riezebos was a great supervisor, because with his valuable feedback and suggestions he
guided me in the right directions.
Groningen, July 2012,
Joost ten Hoonte
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Summary Today and tomorrow’s customers demand (high variety, high quality, low price, and timely delivery) are
putting manufacturing organizations under pressure. To survive in these competitive markets, organizations
are forced to improve their product and volume flexibility and improve their dependability, decrease their
costs, and last but not least shorten their delivery times. To become more flexible a new strategy, named
Quick Response Manufacturing (QRM), was introduced two decades ago. QRM is a strategy that creates a
quicker response, by focusing on lead time reduction throughout the entire organization and is aimed for
organizations that deliver custom-made products in small quantities. What is lacking is a tool that aids
organizations to assess their level of response quickness and identifies leverage points for future
improvements.
Within this thesis we proposed a QRM Maturity Model. Maturity models have already been developed and
proven their applicability in a range of fields. We designed a QRM (hybrid) Maturity Model, which consists
of a ''maturity grid'' in combination with a ''Likert-like questionnaire''. The QRM Maturity Model enables
organizations to assess themselves and identify their degree of support for increasing response practices
and recognize opportunities for further improvements. The QRM Maturity Model has been used by already
eleven companies. Their assessment results became also available for scientific purposes. For academia it
generated both insights in what organizations have currently implemented to increase their quickness of
response and what has their priority in setting the next step towards a more quickly responding
organization. Also, more understanding is generated among the relations between the QRM principles and a
company's location in the QRM Maturity Model.
We can conclude by stating that the QRM Maturity Model has formed a major win-win-win contribution
between academia, companies and education.
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Table of Contents Preface .................................................................................................................................................................3
Summary .............................................................................................................................................................4
List of Figures .......................................................................................................................................................6
List of Tables ........................................................................................................................................................6
List of Abbreviations ............................................................................................................................................8
1. Introduction .................................................................................................................................................9
2. Assessment of existing maturity models .................................................................................................. 12
2.1. Types of maturity models ................................................................................................................. 15
2.1.1. Maturity grids ........................................................................................................................... 15
2.1.2. Hybrids maturity models .......................................................................................................... 17
2.1.3. Capability Maturity Model (CMM) ........................................................................................... 17
2.2. Number of maturity levels ............................................................................................................... 19
3. Proposed maturity model for Quick Response Manufacturing ............................................................... 20
3.1. Theoretical constructs ...................................................................................................................... 20
3.1.1. Vision ........................................................................................................................................ 21
3.1.2. Organization structure ............................................................................................................. 22
3.1.3. Manufacturing dynamics .......................................................................................................... 23
3.1.4. Internal scope ........................................................................................................................... 23
3.1.5. External scope .......................................................................................................................... 24
3.1.6. Product development / engineering ........................................................................................ 24
3.2. Number of maturity levels ............................................................................................................... 25
3.3. QRM Maturity Model ....................................................................................................................... 26
4. Questionnaire ........................................................................................................................................... 28
4.1. Designing a questionnaire ................................................................................................................ 28
4.1.1. Reliability and validity .............................................................................................................. 31
4.2. Final Questionnaire .......................................................................................................................... 31
4.2.1. Part one - Assessing maturity level .......................................................................................... 32
4.2.2. Part two - Organizational profile .............................................................................................. 45
4.2.3. Questionnaire's execution method .......................................................................................... 47
5. Results & analysis ..................................................................................................................................... 49
5.1. Case studies ...................................................................................................................................... 49
5.2. Cross-case analysis ........................................................................................................................... 59
6. Discussion ................................................................................................................................................. 65
7. Conclusion ................................................................................................................................................ 69
Bibliography ...................................................................................................................................................... 70
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List of Figures Figure 2.1 Quality Management Maturity Grid (QMMG) (Crosby, 1979) 16 Figure 2.2 Partnership Sourcing Hybrid Maturity grid (Macbeth & Ferguson, 1994) 18 Figure 2.3 Capability Maturity Model Software (CMM) (Paulk & Curtis, 1993) 18 Figure 3.1 QRM Maturity Model 27 Figure 4.1 Sample urgency matrix (manufacturing dynamics elements) 30 Figure 4.2 Most commonly used key performance indicators 32 Figure 4.3 Relationship between environmental uncertainty and organizational structure 34 Figure 4.4 Manufacturing dynamics 37 Figure 4.5 Capacity utilization vs. Throughput time 39 Figure 4.6 Internal scope 41 Figure 4.7 External scope (Supply Chain) 42 Figure 4.8 Organizational profile 46 Figure 4.9 Impression of the on-line questionnaire 48 Figure 5.1 Vision; Sales vs. Engineer within Nicolet Plastics, Inc (22-06-2012) 59 Figure 5.2 (exponential) Relation maturity level & degree of horizontal integration 60 Figure 5.3 (linear) Relation maturity level & recognition of variability 61 Figure 5.4 (power) Relation maturity level & setup time reduction effort 61 Figure 5.5 (polynomial) Relation maturity level & customer(s) compliance service rate 62 Figure 5.6 (polynomial) Relation maturity level & Concurrent engineering 62
List of Tables Table 2.1 Overview and description of assessed maturity models 14 Table 2.2 Overview of different types of maturity models and their number of levels 19 Table 4.1 Implementation and importance Five-point Likert scale 30 Table 4.2 Indicators vision 34 Table 4.3 Indicators organizational structure 36 Table 4.4 Indicators manufacturing dynamics 40 Table 4.5 Indicators internal scope 41 Table 4.6 Indicators external scope 43 Table 4.7 Indicators product development / engineering 45 Table 4.8 Technical questions 47 Table 4.9 Global network partners 48 Table 5.1 Summary of the main characteristics of the seven cases 50 Table 5.2 Type of stocks (sum 100%) (Variass Electronics) 51 Table 5.3 Type of production process (sum 100%) (Variass Electronics) 51 Table 5.4 Scores per theoretical construct (Variass Electronics) 51 Table 5.5 Type of production process (sum 100%) (Bosch Scharnieren en Metaal) 52 Table 5.6 Scores per theoretical construct (Bosch Scharnieren en Metaal) 52 Table 5.7 Type of stocks (sum 100%) (Kaak Bakeware) 53 Table 5.8 Type of production process (sum 100%) (Kaak Bakeware) 53 Table 5.9 Scores per theoretical construct (Kaak Bakeware) 53 Table 5.10 Type of stocks (sum 100%) (AS Trøndelag Industrielektronikk) 54 Table 5.11 Type of production process (sum 100%) (AS Trøndelag Industrielektronikk) 54 Table 5.12 Scores per theoretical construct (AS Trøndelag Industrielektronikk) 54
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Table 5.13 Type of production process (sum 100%) (Brakel Aluminium) 55 Table 5.14 Scores per theoretical construct (Brakel Aluminium) 55 Table 5.15 Type of production process (sum 100%) (Larsen Premium Precision Parts) 56 Table 5.16 Scores per theoretical construct (Larsen Premium Precision Parts) 56 Table 5.17 Type of stocks (sum 100%) (Euro-Bis Poedercoating) 57 Table 5.18 Type of production process (sum 100%) (Euro-Bis Poedercoating) 57 Table 5.19 Scores per theoretical construct (Euro-Bis Poedercoating) 57 Table 5.20 Summary of the achieved maturity level per organization 58 Table 5.21 Relation overall maturity level with each element of the organizational structure 60 Table 5.22 Relation overall maturity level with each principle of the manufacturing dynamics 61 Table 5.23 Relation maturity level & Internal scope (R&D and Design) 61 Table 5.24 Relation overall maturity level with each principle of the external scope 62 Table 5.25 Relation overall maturity level with each principle of product development / engineering 62 Table 5.26 Relation maturity level vs. types of production processes 63 Table 5.27 Average gap sizes from the seven cases 64
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List of Abbreviations Concept Description
ATO Assemble To Order CEO Chief Executive Officer CMM Capability Maturity Model CMMS Capability Maturity Model for Software development CONWIP CONstant Work In Process ERP Enterprise Resource Planning ETO Engineer To Order EU European Union G-POLCA Generic Paired-cell Overlapping Loops of Cards with Authorization JIT Just In Time KANBAN A visual process management system that tells what to produce, when to
produce it, and how much to produce KPI Key Performance Indicator LB-POLCA Load-Based Paired-cell Overlapping Loops of Cards with Authorization LESAT The Lean Enterprise Self-Assessment Tool LT Lead Time. The amount of time that elapses between when a process starts
and when it is completed. Included queuing time. MCT Manufacturing Critical-path Time measure for throughput time.
Manufacturing Critical-path Time is the typical amount of calendar time from when a customer creates an order, through the critical-path, until the first piece of that order is delivered to the customer (Ericksen et al, 2007)
MTO Make To Order MTS Make To Stock N/A Not Applicable NPI New Product Introduction PACE Product And Cycle-time Excellence POLCA Paired-cell Overlapping Loops of Cards with Authorization
PROPOS PROduction and POLCA Observation System
Q-ROC Quick - Response Office Cell QFD Quality Function Deployment QMMG Quality Management Maturity Grid QRM Quick Response Manufacturing R&D Research & Development SME Small Medium Enterprise SPC Statistical Process Control TBC Time Based Competition TPM Total Productive Maintenance TQM Total Quality Management US United States WIP Work In Process. The amount of inventory in the process.
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1. Introduction Thompson (1967) compared organizations with a machine metaphor, striving to maximize efficiency by
having the control over all of the variables and relations. However, nowadays this is not always realistic.
Growing global competition, fast changing markets and introductions of advanced manufacturing
technologies create a complex and uncertain environment (Bayus, 1994; Doll & Vonderembse, 1991). To
survive, organizations face a paradigm shift from industrial systems which are driven by efficiency to post-
industrial systems which are driven by quick response to customer demands (Doll & Vonderembse, 1991).
To be able to respond quickly enough to today and tomorrow’s customers demand - high variety, high
quality, low price, and timely delivery - organizations need to improve their product and volume flexibility
and improve their dependability, decrease their costs, and last but not least shorten their delivery time
(Gunasekaran, et al., 2001). Therefore, a switch is needed from focused to flexible factories (Blackburn,
1991).
To become a more flexible factory, Suri (1998) introduced a new philosophy named Quick Response
Manufacturing (QRM), which is based on ''Time-Based Competition'' (TBC). TBC was introduced in the late
1980’s and aims to increase speed at new product development and manufacturing until logistic and
distribution, in order to gain competitive advantage (Stalk, 1988). QRM is not just an enhanced version of
TBC, it includes also numerous of new dimensions (Tubino & Suri, 2000). QRM aims to reduce the lead times
within the entire organization, especially the times when the product is waiting to be touched (Suri, 2010).
Referring to QRM, there is a variety of literature available. The introduction of QRM went along with the
release of Suri’s (1998) first book, which describes the principles and techniques of QRM. Later, Suri (2010)
developed a ''how to implement QRM'' step-wise procedure for managers. Furthermore, numerous case
studies can be found about implementations of QRM concepts (Suri, 2003, 2009, 2010). Especially much
attention is paid to designing (Riezebos, 2010) and implementing POLCA (Paired-cell Overlapping Loops of
Cards with Authorization), a system to control the material and/or product parts between manufacturing
cells. Fernandes and Carmo-Silvia (2006) compared the performance of Generic-POLCA with the original
POLCA and MRP system and Germs and Riezebos (2010) compared the performance of POLCA with a
modified CONWIP system. Vandaele et al (2008) proposed a load-based version of the POLCA system, which
determines the POLCA parameters according to an advanced resources planning.
While many large companies seem to have embraced manufacturing best practices, such as lean
production, empirical evidence suggest this is not the case for small- and medium-sized enterprises (SMEs)
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(Powell, et al., 2012). One of the reasons is that SMEs, which are often characterized by make-to-order
(MTO) or engineer-to-order (ETO), are more confronted with a higher degree of uncertainty than the large
companies (Bell, 2006). The QRM concept aid SMEs to handle the uncertainty in a better way. Instead of
eliminating (product) variability, QRM adapts to the (product) variability and thereby increases the
competitive strengths of the SMEs. SMEs working according to the QRM concept, become more flexible and
capable to produce high varieties of customer specific products with high quality and low costs. In the
European economy, SMEs play an important role (Wilde, 2011). SMEs represent 99% of the companies
within Europe and these account for 67% of employment in the EU. SMEs are defined by the number of
persons (<250) and by turnover (≤ € 50 million) (EUROPEAN-COMMISSION, sd). The United States (US) make
a different distinction between small and large firms. Small firms (<500 employees) play an important role in
the US economy. In 2008 small firms represented 99% of the companies which accounted for 50% of
employment in the private sector of the US (US small business administration, 2011). According to the just
mentioned facts, QRM might be especially relevant for small and medium enterprises.
Most of the available literature focuses on the techniques and implementation of the QRM and POLCA
concepts. What is lacking in the literature is a tool that both helps organizations to assess their current
quickness of response and identifies leverage points for future improvements. A maturity model is such a
tool that measures and indicates a particular current state by using several (pre-) defined maturity levels.
Maturity models have been developed in a range of fields including quality management (Crosby, 1979),
ERP systems (Powell, et al., 2012; Holland & Light, 2001), and software development (Curtis & Paulk, 1993).
Crosby (1979) is the first who developed a maturity model, namely Quality Management Maturity Grid
(QMMG). The QMMG is based on five maturity levels, reaching from uncertainty ''we don’t know why we
have problems with quality'' till certainty ''we know why we do not have problems with quality''. Firms have
to evolve through five levels of maturity to achieve the quality management excellence (Crosby, 1979).
Currently a maturity model which describes an evolutionary path, from slow uncertain responding to a
mature optimized quick responding organization, is lacking. Such a model will be useful for organizations,
because of multiple reasons. Firstly it creates the opportunity to assess the organization’s capability for
quick response and secondly it can serve as guide in deciding what to do next among the many
opportunities for future improvement (Curtis & Paulk, 1993). The model creates also an opportunity to
benchmark the results of the maturity levels between organization, industries, or countries.
Therefore, the aim is to develop an appropriate maturity model that is able to assess the support for
increasing response practices by SMEs. It should generated both insights in what SMEs have currently
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implemented to increase their quickness of response and what has the priority for SMEs in setting the next
step towards a more quickly responding organization. From a practical standpoint, the proposed maturity
model should be simple and useful for companies to assess themselves on their degree of response
quickness. The results of the assessment should provide understanding of the evolution of becoming a more
quick responding company by providing guidance on how to move towards a more mature quick responding
organization.
The structure of this paper is as follows. Part two will analyze and assess the existing maturity models. In
part three a proposed maturity model for quick response manufacturing will be designed. Part four covers
the questionnaire, necessary to gather data from companies. The data from the companies will be analyzed,
scored and linked to the proposed maturity model in part five. Part six covers the discussion of the results
and includes also the project limitations and proposals for further research. Lastly, the conclusion is in part
seven.
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2. Assessment of existing maturity models A large variety of maturity models have been developed in a range of fields. Though, we restrict the number
of maturity models by focusing only on the founders of the first maturity models and by concentrating on
models that are related to the QRM concept. Our restriction has led to the assessment of maturity models
in the following directions: Quality management (Crosby, 1979, 1996), Software development (Curtis &
Paulk, 1993), Enterprise Resource Planning (ERP) systems (Powell, et al., 2012; Holland & Light, 2001),
''Leanness'' (Nightingale & Mize, 2002), Product development (McGrath, 1996) and Supply chain
relationship (Macbeth & Ferguson, 1994). An overview of these maturity models can be found in Table 2.1.
The roots of maturity models lay in the field of quality management. Crosby (1979) introduced the first
maturity model, the Quality Management Maturity Grid (QMMG). The grid is divided into five maturity
levels (horizontal) and six management categories (vertical). By reading the descriptions at each block of the
grid, organizations can identify the exact status of their present quality program and it shows them what
steps can be taken to evolve and improve their quality program. Crosby improved the model in 1996, by
changing some phases of the model. Based on the original QMMG of Crosby (1979), Curtis & Paulk (1993)
developed the often used Capability Maturity Model for Software (CMMS). The software CMMS is divided
into five levels of maturity starting at; initial, repeatable, defined, managed, and optimizing. These five
maturity levels define an ordinal scale for measuring the maturity of an organization’s software
development capability. Each level provides a generic description and process goals that, when satisfied,
make a significant addition to the sophistication and capability of an organization’s software development
process (Curtis & Paulk, 1993).
There are several maturity models that have interfaces with the QRM concept. QRM has various similarities
with the lean philosophy. The concepts of QRM and lean both focus on eliminating dysfunctional variability,
therefore we studied the Lean Enterprise Self-Assessment Tool (LESAT) (Nightingale & Mize, 2002). LESAT is
developed to create a roadmap for transitioning an enterprise from a mass-production mentality to a lean
enterprise mentality and to assess a companies’ progress in achieving a state of ''leanness''. Macbeth &
Ferguson (1994) designed a model that pays attention to the importance of partnership sourcing. When
customers and suppliers work closely together as partners it can lead to interesting benefits (e.g. reducing
lead times, shorter time-to-market and increasing flexibility). McGrath (1996) introduced the Product And
Cycle-time Excellence (PACE). PACE is developed to set continuous improvements in the product
development cycle time, costs, and quality in a company’s culture. Powel et al (2012) and Holland & Light
(2001) both focused on ERP. The Capability Maturity Model of Powell et al (2012) evaluate the level of
support offered by contemporary ERP systems for pull production at SMEs. The maturity model from
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Holland & Light (2001) supports companies to understand the implementation process and development of
the ERP system use. Both ERP related maturity models are interesting, because ERP systems have often
been classified as sources of waste within lean production literature, but still many lean practices depend
upon high quality data for the processes of problem solving, continuous improvement and effective
production control (Powell, et al., 2012).
The studied maturity models demonstrated several things. First of all they are able to increase quality,
decrease (product development) times, develop ''leaner'' enterprise (mentality), increase efficiency and
flexibility. Secondly, they all have the ability to measure a particular current state and stipulate a road for
further improvements. The maturity models have also proven their applicability to a range of (different)
organizations and are not restricted to one particular company. Lastly Veldman & Klingenberg (2009) and
Powell et al (2012) demonstrated respectively the applicability of maturity models in ''make-to-order
organizations'' and ''SMEs''.
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Maturity model
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Description
Quality Management Maturity Grid (QMMG) (Crosby, 1979)
A model which measures the exact status of companies’ present quality program and shows them what positive steps can be taken to evolve and improve that quality program.
Modified Quality Management Maturity Grid (QMMG) (Crosby, 1996)
Improved version of 1979, but with the same intention as the model of 1979.
Software Capability Maturity Model (CMMS) (Curtis & Paulk, 1993)
A model which provides software organizations with guidance on how to gain control of their process for developing and maintaining software and how to evolve their environment towards a culture of software engineering excellence.
The Lean Enterprise Self-Assessment Tool (LESAT) (Nightingale & Mize, 2002)
A tool to assess a firms’ progress in achieving a state of “leanness” and to guide them as they pursue the lean principle of continuous improvement.
Product And Cycle-time Excellence (PACE) (McGrath, 1996)
A model which identifies the stages in the evolution towards product and cycle-time excellence in the new product development process. The model helps a company understand this evolution by showing where it is and where it wants to go.
Capability Maturity Model of ERP support for pull production (Powell, et al., 2012)
A model which assess the extent to which the usage of a company’s current ERP system supports pull production practices, and to suggest modifications to the ERP system in order to better serve the company’s pull system.
Stage Maturity Model for ERP system use (Holland & Light, 2001)
A model that helps firms understand the implementation process and content of the development of the ERP system maturity and provide guidance on how to move towards best practice.
Relationship Maturity Grid (Macbeth & Ferguson, 1994)
A model that organizations can use to identify their current position and provides insights for future improvements according to internal and external relations.
Table 2.1 Overview and description of assessed maturity models
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Unfortunately most of the assessed maturity models focus only on one particular business function, such as
quality management, management control systems or product development. This is illustrated in Table 2.1.
For example, the PACE maturity model attempts to reduce cycle time, but only in the product development
part of the organization. What is missing is a maturity model that enables SMEs to assess, on multiple
business functions, the current quickness of response of their entire supply chain and identify leverage
points for future improvements. In the field of lean, such an enterprise maturity model (LESAT) proves to be
useful as a reference tool to assist in self-assessment and as a guide for identifying leverage points for
organizational change (Nightingale & Mize, 2002). However, lean does not have an answer on how SMEs
have to handle low production volumes and high product varieties. Therefore, a new maturity model that
exploits the (product) variety as strategic value will be a true addition for both SMEs and academic
purposes. The new maturity model will assist organizations to understand the evolution of time
compression activities and it provides guidance on how to move towards a more mature quick responding
organization. Secondly, from an academic perspective the maturity model will indicate what companies in
the field have achieved till so far and what the company’s priorities will be in setting the next step towards a
quicker responding organization.
Assessing the maturity models of Table 2.1 on several characteristics, raised some discussions. We will start
to discuss the different types of maturity models and end the discussion with the number of maturity levels.
2.1. Types of maturity models
Maturity models can be divided into three basic groups, namely: Maturity grids, Hybrids & Likert-like
questionnaires and Capability Maturity Models (CMM) (Fraser, et al., 2002). The last column of Table 2.2
shows the type of maturity model of each assessed maturity model.
2.1.1. Maturity grids
The QMMG and the PACE models, from Table 2.1, can be both classified as maturity grids. Maturity grids
contain descriptions for each activity at each maturity level. For example the QMMG from Crosby (1979),
see Figure 2.1, is divided into five stages of maturity (columns) and six management categories (rows). By
reading the descriptions at each block of the matrix organizations, the exact status of their present quality
program can be identified and it shows them what steps can be taken to evolve and improve their quality
program (Crosby, 1979). According to Fraser et al (2002) it is complicated to develop a maturity grid that is
totally rigorous, because for each activity at each maturity level, a detailed textual description is necessary.
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Measurement Categories
Stage 1: Uncertainty
Stage 2: Awakening
Stage 3: Enlightment
Stage 4: Wisdome
Stage 5: Certainty
Management understanding and attitude
No comprehension of quality as a management tool. Tend to blame qualiy department for ''quality problems''.
Recognising that quality management may be of value but not willing to provide money or time to make it all happen.
While going through quality improvement programme learn more about quality management; becoming supportive and helpful.
Participating. Understanding absolutes of quality management. Recognize their personal role in continuing emphasis.
Consider quality management an essential part of company system.
Quality organisation status
Quality is hidden in manufacturing or engineering departments. Inspection probably not part of organization. Emphasis on appraisal and sorting.
A stronger quality leader is appointed but main emphasis is still on appraisal and moving the product. Still part of manufacturing or other.
Quality department reports to top management, all appraisal is incorporated and manager has role in management of company.
Quality manager is an officer of company; effective status reporting and preventive action. Involved with consumer affairs and special assignments.
Quality manager on board of directors. Prevention is main concern. Quality is a thought leader.
Problem handling
Problems are fought as they occur; no resolution; inadequate definition; lots of yelling and accusations.
Teams are set up to attack major problems. Long-range solutuions are not solicited.
Corrective action communication established. Problems are faced openly and resolved in an orderly way.
Problems are identified early in their development. All functions are open to suggestion and improvement.
Except in the most unusual cases, problems are prevented.
Cost of quality as % of sales
Reported: unknown Actual: 20%
Reported: 3% Actual: 18%
Reported: 8% Actual: 12%
Reported: 6.5% Actual: 8%
Reported: 2.5% Actual: 2.5%
Quality improvement actions
No organized activities. No understanding of such activities.
Trying obvious ''motivational'' short-range efforts.
Implementation of the 14-step program with thorough understanding and establishment of each step.
Continuing the 14-step program and starting Make Certain.
Quality improvement is a normal and continued activity.
Summary of company quality posture
''We don't know why we have prblems with quality''
''Is it absolutely necessary to always have problems with quality?''
''Through management commitment and quality improvement we are identifying and resolving our problems''
''Defect prevention is a routine part of our operation.''
''We know why we do not have problems with quality.''
Figure 2.1 Quality Management Maturity Grid (QMMG) (Crosby, 1979)
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2.1.2. Hybrids maturity models
Likert-like questionnaires or a combination of Likert-like questionnaires with maturity definitions (known as
hybrids) have similarities with maturity grids (Fraser, et al., 2002). However, hybrid maturity models only
describe one or two extreme levels of maturity, instead of describing each maturity level and activities in
detail, like in a maturity grid. Companies score, on a Likert scale, their organizational performance with
respect to a described highest and/or lowest maturity level.
Holland and Light (2001) designed such a hybrid maturity model. Their definitions of maturity are based on
five theoretical constructs (strategic use of IT, organizational sophistication, penetration of the ERP system,
vision, and drivers & lessons). The quantity of their pre-set constructs is arbitrary and are defined based
upon a literature review (Holland & Light, 2001). Organizations need to fill in a questionnaire to determine
the stages of maturity for each theoretical construct. The questionnaire is based on best practice
statements and organizations will score their degree of approximation to these best practices.
The hybrid model from Macbeth & Ferguson (1994), see Figure 2.2, is a combination of a maturity grid and
Likert-like questionnaire (Macbeth & Ferguson, 1994). The hybrid model consists of nine brief described
issues (quality, delivery, cost, innovation, customer strategy, supplier capability, information flow, nature of
relationship, and business outcomes) which are scored on an ordinal scales. The scales go from pure
Adversarial at rating of one, through a Transitional phase where some changes have happened, to
Partnership with a rating of seven. The average of the scores on the nine issues determines the firm's level
of maturity (Adversarial, Transitional or Partnership).
Hybrid Maturity Models are mostly considered as a simple form of maturity model (Fraser, et al., 2002),
what might be an advantage when the maturity model will be applied for self-assessment purposes.
2.1.3. Capability Maturity Model (CMM)
The models of Curtis & Paul (1993), Powell et al (2012) and Nightingale & Mize (2002) can be considered as
capability maturity models (CMMs). A CMM differs from a maturity model, because to evolve to a next
maturity level, a set of cumulative key process areas (KPAs) needs to be achieved. Each level of maturity
has to be described by the aid of KPAs (Fraser, et al., 2002). For example, to evolve to a more mature level
in the software CMM, see Figure 2.3, a firm needs to perform a number of pre-set KPAs that are assigned to
each maturity level. The KPAs are again divided into five sections called common features (commitment to
perform, ability to perform, activities performed, measurement & analysis and verifying implementation)
which specify the KPAs. This makes CMM relative more complex than the hybrid models (Fraser, et al.,
2002).
18
Adversarial Transitional Partnership
Quality Variable, high inspection/rejects
Some SPC, Taguchi, QFD begun
<100 parts per million, improving trend
Delivery Not measured but complained about
Some ship to stock 90% on time target
100% on time, lead time reducing
Cost Hidden, tough price negotiations
1-way open book, beginning Cost of Quality
Reducing in real terms. Joint action improvements
Innovation - Used as negotiation tactic - 'Forces' supply switch
Welcomed but not coordinated
Major differentiating factor among peers
Customer Strategy - 'Win' in the market - Power play negotiations
- Customer recognizes responsibilities - Open to question
Co-destiny fully understood and operating, shared vision
Supplier Capability Limited, focused, protected
Moving towards increased service range
Contributes multiple skills, solves customer problems
Information Flow Need to know, filtered Limited, unbalanced 2-way, multiple paths, interchanges of personnel
Nature of Relationship What relationships? Tentative, experimental are the serious?
Demanding but supportive, belief in one another
Business Outcomes Uncertain Early performance pay-offs
Increased market share, reduced costs greater competitiveness
Figure 2.2 Partnership Hybrid Maturity Grid (Macbeth & Ferguson, 1994)
Level Focus Process Areas
5 - Optimizing Continuous process improvement Organizational Innovation & Development Causal Analysis and Resolution
4 - Quantitatively Managed Quantitative management Organizational Process Performance Quantitative Project Management
3 - Defined Process Standardization
Requirements Development Technical Solution Product Integration Verification Organizational Process Focus Organizational Process Definition Organizational Training Integrated Project Management Risk Management Decision Analysis and Resolution
2 - Managed Basic project management
Requirements Management Project Planning Project Monitoring & Control Supplier Agreement Management Measurement and Analysis Process & Product Quality Assurance Configuration Management
1 - Initial Competent people and heroics Figure 2.3 Capability Maturity Model Software (CMM) (Paulk & Curtis, 1993)
19
2.2. Number of maturity levels
Each maturity level characterizes an evolutionary plateau on the path toward a more mature best practice
organization. The number of levels is to some extent arbitrary (Fraser, et al., 2002). Table 2.2 indicates the
assessed maturity models and their associated maturity levels. The number of maturity levels varies
between three to five levels. Most common is the amount of five maturity levels per maturity model. There
are no written rules; it’s all about finding the right balance of levels. When increasing the number of levels,
it will become more difficult to characterize each level and it will make the maturity model more complex.
Furthermore, when the number of levels are to low the danger exist that a maturity model is oversimplified
and doesn’t represents the complex reality (Maier, et al., 2009).
Maturity Model Level 1 Level 2 Level 3 Level 4 Level 5 Type
Quality Management Maturity Grid (QMMG) (Crosby, 1979)
Uncertainty
Awakening
Enlightenment
Wisdom
Certainty
Grid
Quality Management Maturity Grid (QMMG) (Crosby, 1996)
Uncertainty
Regression
Awakening
Enlightenment
Certainty
Grid
Software Capability Maturity Model (Curtis & Paulk, 1993)
Initial Repeatable Defined Managed Optimizing CMM
The Lean Enterprise Self-Assessment Tool (LESAT) (Nightingale & Mize, 2002)
Some awareness of this practice
General awareness
A systematic approach / methodology improvement across the enterprise
On-going refinement and continuous improvement across the enterprise
Exceptional, well-defined, innovative approach is fully deployed across the extended enterprise
CMM
Product and cycle time excellence (PACE) (McGrath, 1996)
Informal
Functionally focused project managed
Cross functional project management
Enterprise wide integration of product development
- Grid
Capability Maturity Model of ERP support for pull production (Powell, et al., 2012)
Initial Planned Validated Controlled Optimizing CMM
Stage Maturity Model for ERP system use (Holland & Light, 2001)
management of existing legacy systems
post-implementation exploitation of the ERP system
strategic (innovative) exploitation of the ERP system
- - Hybrid
Relationship Maturity Grid (Macbeth & Ferguson, 1994)
adversarial transitional partnership - - Hybrid
Table 2.2 Overview of different types of maturity models and their number of levels
20
3. Proposed maturity model for Quick Response Manufacturing For our purpose to develop a feasible and simple tool to aid SMEs with self-assessing and improving their
response quickness, it is better to neither use a CMM nor a pure grid type of model. The proposed maturity
model has to cover the entire supply chain, which, if we choose for a CMM type of model, will require an
abundance of detailed KPAs. This will make it too complex for self-assessment purposes and has the risk of
misleading outcomes due to: limited interest, confusion or incorrect applications (Maier, et al., 2009). A
pure grid type of model will become too cumbersome for more or less the same reason, since it requires for
each activity at each maturity level, a detailed textual description. Therefore we decided to design a hybrid
maturity model which consists of a Likert-like questionnaire in combination with maturity definitions. The
advantage of this type of model is that we had to describe just one or two extreme levels of maturity,
instead of describing each maturity level and activities in detail. This gave the right balance between a
simple and usable model and a complex reality. For the development of the QRM (hybrid) Maturity Model,
we focused on a mix of maturity model approaches that have been assessed in the previous chapter (see
Table 2.1).
3.1. Theoretical constructs
The QRM concept is very broad and has plenty of elements. To be able to include all the elements in the
QRM (hybrid) Maturity Model, we used a quite similar approach as Holland & Light (2001) and subdivided
the elements into theoretical constructs, or also called ''focused areas''. We have subdivided the elements
into the following six theoretical constructs:
1. Vision
2. Organizational structure
3. Manufacturing dynamics
4. Internal scope (Diffusion within company)
5. External scope (Diffusion throughout the supply chain)
6. Product development / engineering
21
Theoretical constructs one till three are about the same as the first three core pillars of the QRM concept
and theoretical constructs four till six are based on the last core pillar of the QRM concept (Suri, 1998):
Power of time
Organizational structure
System dynamics
Company-wide approach
Company-wide approach is the fourth and last pillar of QRM concept. The QRM concept is not only intended
for the shop floor, it is a company-wide or even a supply chain wide approach (Suri, 1998).
We wanted to examine the ''company-wide approach'' pillar in more detail. Therefore, we made a
distinction between internal scope (construct four), external scope (construct five) and product
development / engineering (construct six). The internal and external scopes are constructed in order to
make a distinction between QRM activities that are implemented within or outside the organizational
boundaries. It is important for SMEs, that usually can be characterized by make-to-order, to deliver a
customer specific product on time (Smith & Reinertsen, 1991). Therefore we decided to pay extra attention
to internal and external collaboration efforts within the product development and engineering
departments.
What will follow now are descriptions of each theoretical constructs. Each theoretical construct is shortly
introduced and described by a comparison of two extreme levels of maturity. First, a situation at the lowest
maturity level will be described, followed up by a description of the highest maturity level.
3.1.1. Vision
The first construct identifies till which extent an organization is aware of the power of time. To respond
quicker to market dynamics and varying demands, it is becoming more and more important to have short
lead times (Fernandes & Carmo-Silva, 2006). The same applies for QRM as for the lean concept; to become
a success it is necessary that the entire enterprise shares the same vision (Nightingale & Mize, 2002).
Therefore, we developed a construct focusing on the company’s vision. We investigated the company’s way
of thinking (cost- or time thinkers) and examined how the vision is shared throughout the organization.
At the lowest level of the construct, organizations are unaware about the power of time. The organization
still works by the traditional approach and has the most commonly used key performance indicators, cost
and efficiency, as their primary performance criteria.
22
Instead at the highest level, organizations are aware of the power of time and the impact on their
operational performance. Employees throughout the organization share the same vision and have delivery-
time (speed and reliability) as their most important key performance criterion. Organizations are aware of
their performance position and are continuously trying to reduce lead times throughout the entire
organization.
3.1.2. Organization structure
The second construct identifies till which extent the organizational structure supports the organization to
reduce lead times and at the same time deliver a high product variety (flexibility). This construct is a
modified version from the ''organizational sophistication'' construct of Holland & Light (2001), which tries to
find out how the organizational structure - second pillar of QRM philosophy (Suri, 1998) evolves as a result
of the (new) vision.
At the lowest level of the construct, organizations experience problems with low volume and high product
variety, due to their inorganic (mechanic) structure. The inorganic structure can be characterized by (Nahm,
et al., 2003; Jones, 2009):
Decisions that are made high in the organization (centralized decision-making)
Many rules and regulations that discourage creative, autonomous work and learning (highly
formalized)
Many hierarchical layers
Slow and difficult communications between the people
Employees that are only able to perform one task (functional specialized)
Instead, at the highest level of the construct organizations can response quickly to the diverse customer
demands (high product variety). Employees can change and adapt quickly to shifting conditions, due to its
structural flexibility (Jones, 2009). The flexibility is created through their organic structure, which Nahm
(2003) and Jones (2009) characterize by:
Decisions that can be dealt with quickly low in the organization (decentralized decision-making)
Less rules and regulations. Or rules and regulations that encourage creative, autonomous work and
learning (low formalized)
Fast and easy communications between the people
Less hierarchical layers
Employees that are able to perform multiple tasks (joint specialized)
Cross-functional training
23
3.1.3. Manufacturing dynamics
The third construct identifies till which extent interaction between machines, people and products supports
the organization to reduce lead times, decrease costs and to increase quality. This construct covers the third
pillar of QRM ''system dynamics'' (Suri, 1998). The maturity levels of the construct can be characterized by a
number of features (Tu, et al., 2001; Shah & Ward, 2007).
The lowest level of the construct can be best described by the following characteristics. Firstly, employee
involvement is low and specialized workers are located in functional divisions, where the workers perform
each their own tasks. Secondly, error and rework is common, due to infrequent maintenance activities, low
quality control and lack of information sharing. This in combination with long set-up times provokes the use
of large batches sizes. Thirdly, organization’s production is driven by a forecast and pre-estimated
processing times, without feedback from a particular system. The production is ''pushed'' into a system that
has no explicit limit on the amount of work in process that can be in the system. They try to eliminate or
buffer variability by time or inventory. Efficiency and productivity are the main priorities and therefore
capacity utilizations are set on maximum.
Instead the high maturity level can be characterized as follows. Firstly, employees are highly involved in
problem solving and developing time compressing practices. The workers are Joint specialized and work in
teams and are able to work on multiple manufacturing cells. Secondly, much effort is paid into setup-time
reduction, preventive maintenance and quality improvement activities, which results in high quality and less
rework (first-time-right). Thirdly, work in process is limited, due to a ''pull'' or combination of ''push/pull''
production system that uses visual/virtual cards or bins in combination with a smart way of authorization. A
particular production starts only when there is both authorization, enough capacity and raw material at the
required workstations. Further, strategic variability is recognized and exploited. Lastly, buffers are mainly in
the form of idle capacity and inventory buffers are small till zero. Compared to the lower maturity level they
have smaller batch sizes, shorter lead times, lower inventory and higher quality products.
3.1.4. Internal scope
The fourth construct identifies till which extent actions to reduce lead times are penetrated throughout the
organization.
At the lowest maturity level, organizations are still in the phase to discover urgency of taking time
compression actions. Lead time reducing activities and other activities to improve the quickness of response
are lacking in the organization.
24
At the highest level, organizations are increasing their quickness of response throughout the entire
organization. From the shop-floor till the sales and purchase, the entire department works to reduce their
lead times and increase their flexibility.
3.1.5. External scope
The fifth construct identifies till which extent actions to reduce lead times are penetrated outside the
organization boundaries. A firm can have short internal lead times, but those can be easily outweighed by
its suppliers or distributors. All organizations rely on suppliers. Especially organizations with a large product
variety depend on suppliers, because for those organizations vertical integration is not really an option
(Nicholas, 2008). Therefore, it is also important to improve the lead times throughout the organizations
supply chain.
At the lowest level, organizations do not see the urgency to reduce lead times outside their organizational
boundaries. Organizations are not aware of the supplier’s delivery times, they only complain about the long
waiting times (Macbeth & Ferguson, 1994). Economy of scale forms the main priority by determining the
order size. Large infrequent shipping with long waiting times is common to receive quantum discount. The
relationships with both suppliers and customers are weak and mutual information flow is limited.
Instead, at the highest level of the construct, much attention and effort are put in reducing lead times
beyond the organizational boundaries. Every tier of the supply chain is involved, with the aim to reduce lead
times on either the supply of raw materials as well on the distribution of products to the customers.
Interchanges of personnel (e.g. organizing QRM trainings), information and feedback occur frequently
(Stalk, 1988). Suppliers have short delivery times and deliver on time and mostly in frequent small
quantities. Customers are aware of the short delivery times and are encouraged to place frequent low
volume orders.
3.1.6. Product development / engineering
The last construct identifies till which extent organizations realize to reduce the (new) product development
/ engineering time (time to market).
At the lowest maturity level of the construct, we find organizations with long time cycles from concepts or
customized orders till customer. Multiple persons are necessary to perform each their own process steps.
Employees depend on each other, which results in long waiting times, high defect rates and high costs
(Nicholas, 2008). For example, product designers toss their design over the wall to the manufacturing
department, which sometimes cannot make the product conform the design, because manufacturing
capabilities are considered too late in the design process. This lack of communications occurs also between
25
other functions within the firm. The communication and information sharing with the supplier and
customers is also lacking. Time measurement within the product development / engineering does not occur
or is badly managed, and therefore they are uncertain about the impact of time on the (new) product
introduction (McGrath, 1996).
Instead, at the highest level of the construct organizations measure all the process steps within the product
development / engineering and the organization is aware of the power of time. Actions to reduce lead times
are penetrated and applied throughout the entire organization and supply chain. Process steps are
combined or even eliminated, which makes it possible to process multiple steps with less people in relation
to previous levels. Due to integrating both suppliers, customer requirements and production process steps
(concurrent engineering), lead times and costs will be lower and quality will be higher in comparison with
the lower levels (Nicholas, 2008). Organizations within the highest maturity level have short time cycles and
they continuously try to decline the time to market (McGrath, 1996). The quickness of response creates
satisfied customers and increases the organization's flexibility to make late product changes without
excessive disruption or costs.
During self-assessment organizations will score, on a Likert scale, each theoretical construct’s performance
with respect to the just described highest or lowest maturity level. The organization's total maturity level is
the average score on all the five theoretical constructs. More information about the functioning of the self-
assessment and the scoring process can be found in chapter four.
3.2. Number of maturity levels
As discussed in section 2.2 the number of maturity levels varies between three to five levels. Most common
is the amount of five maturity levels. For the purpose of making a simple usable, but also reality
representing tool that can be used for self-assessment, we developed a maturity model existing of five
maturity levels. This gave us the right balance between simple usage and the complex reality. Our maturity
model consists of the following maturity levels:
1. Uncertainty / unaware
2. Awakening / general awareness
3. Defined / validated
4. Managed
5. Optimizing
26
These levels of maturity are based on both Crosby’s QMMG (1979, 1996) and Curtis & Paulk’s CMMS (1993).
The maturity levels cover the stages a firm has to go through before becoming an excellent quick
responding mature organization.
Each maturity model can be described by a goal. There is no level zero, thus each organization starts at level
one. Organizations in level one are uncertain and have no goals with regard to become a more quick
responding organization. In the second level, organizations and their employees start to recognize the
importance and benefits of compressing lead times and increasing their quickness of response. At the third
level, organizations start to shape their structure and system dynamics to be suitable for major lead time
reductions and flexibility growth. Within the fourth level, organizations become more experienced and
clever shaping their structure and system dynamics and they start to highly integrate both internal as
external. At the last level, organizations continuously optimize the QRM elements till the maximum degree,
with the aim to continuously improve the quickness of response by reducing the lead times throughout the
entire supply chain.
3.3. QRM Maturity Model
The design decisions made in the previous two paragraphs of this chapter have resulted in the QRM (hybrid)
Maturity Model, which consist of a Likert-like questionnaire in combination with maturity definitions
represented in a simple maturity grid, see Figure 3.1. The columns represent the five stages of maturity a
firm has to go through before becoming an excellent quick responding mature organization. The first six
rows represent the six theoretical constructs (or known as focused areas). The last row describes the goal of
each maturity level. The model illustrates and briefly describes in a clear way the maturity levels per
focused area. The organization's total maturity level is the average score on the six theoretical constructs.
The Likert-like questionnaire will be discussed in the next section.
27
Maturity Constructs
Level 1 Uncertainty/
Unaware
Level 2 Awakening/
General awareness
Level 3 Defined/ validated
Level 4 Managed
Level 5 Optimizing
Vision
Unaware of
power of time
Aware
… Shared
awareness and start improving
Aware, time measuring and continuously
improving
Organization structure
Fixed
Less fixed … Semi flexible Flexible
Manufacturing dynamics
Cumbersome &
slow
…
…
…
Agile & fast
Internal scope
-Nowhere -No effort to reduce lead
times
Small scale
… Large scale
-Entire company -100% effort to
reduce lead times
External scope
No strategic
relationship(s)
…
…
…
Strategic relationship(s)
Product development / engineering
Slow & rigid Slow … Average Rapid & flexible
Goals
No goals defined Employees start to notice the urgency with regard to lead time reduction
Organizational start to (redesign) structure to become suitable to lead times reductions and become flexible
Organizational structure and system dynamics are clever to further reduce lead times and become flexible
Continuous process improvement of response quickness
Figure 3.1 QRM Maturity Model.
28
4. Questionnaire To identify the location of an organization’s theoretical construct within the QRM Maturity Model, take for
example the first construct ''vision'', we cannot directly ask a person about his or her organization’s vision,
that is simply too complicated and abstract. Therefore we need a more simple method that enables
companies to score themselves on the six theoretical constructs in an indirect way. Hence, a (semi) closed-
questionnaire was developed which was able to collect per company the necessary data from each
theoretical constructs. Most of the included questions or statements were answered on a Five-point Likert
scale. Afterwards a scoring process was applied to the questionnaire’s output to automatically indicate the
maturity level of each theoretical construct. The average of the scores on the six theoretical constructs led
to the company’s overall QRM maturity level.
4.1. Designing a questionnaire
For the construction of the questionnaire we followed the design steps of Emans (2002):
o Set goal of the questionnaire
o Convert the complicated theoretical constructs (conceptual variables) into stand-in
variables (indicators), which are able to gather the information and represent the
theoretical constructs
o Order the questions
o Design formats for answers and notes
o Test the first draft of the questionnaire
o Finalize questionnaire
The goal was to gather objective information from different persons from several organizations around the
world, in order to identify their current QRM maturity level and priorities. To do so, we needed information
about organizations current QRM implementations and their degree of importance. Therefore we
developed a questionnaire. In exchange, we promised to send organizations their results afterwards in a
customized report. The design and the formulas to construct a customized report have been developed. For
a sample customized report see Appendix 1. In this customized report companies can find their current
QRM maturity level per construct and they are able to compare (benchmark) their reached levels with other
countries or industries. The customized report also serves as a guide for companies in deciding what to do
next among the many opportunities for future improvements. Nevertheless, we did not sent any
29
customized report. We have postponed it, because with regard to its benchmark purposes the data was still
too limited.
The questionnaire consisted of two parts. The first part was developed to assess the organization’s QRM
maturity level and was based on the six theoretical constructs: Vision, Organizational structure,
Manufacturing dynamics, Internal scope, External scope, and Product development / engineering. The
questions were ordered randomly, to prevent respondents to discover the direction of the questions. The
first part of the questionnaire took twenty minutes to fill in and required at least two or more persons per
organization with a different function. The CEO, purchaser, sales/marketing, finance and operations
manager were the persons that we preferred to fill in the questionnaire. By collecting data from at least two
or more persons within those functions, generated a more objective and interesting data output. It created
the opportunity to identify for example if the Sales/Marketing shares the same vision as the Operations
function. This is interesting because, in general Operations has the aim to produce goods and services with a
maximum efficiency. Meanwhile, Sales/Marketing wants Operations/Engineers to produce more variety,
higher quality and quicker response, which is leading to less efficiency (Barnes & Holloway, 2008). Conflict
between functions are fatal, hence a shared vision throughout the entire organization is crucial for a
successful QRM implementation (Suri, 2010).
To gather the sufficient information about the theoretical constructs in part one of the questionnaire, it was
not possible to use the defined theoretical constructs (conceptual variables) as straightforward survey
questions. Like already mentioned in this chapter's introduction, we could not directly ask a person about
his or her organization’s vision, that was simply too complicated and abstract. Therefore conceptual
variables were converted into multiple stand-in variables (indicators). These indicators were able to gather
different kinds of information which could be asked directly and at the same time represented the original
concept variable. Converting the conceptual variables into indicators led to a list of indicators per concept
variable. The indicators were largely based on several published questionnaires (Ward, et al., 1998; Nahm,
et al., 2003; Cua, et al., 2001; Shah & Ward, 2007; Tu, et al., 2001; Koufteros, et al., 1998, 2005; Ketoviki &
Schroeder, 2004; Li, et al., 2005). From these questionnaires we selected, dropped, modified and added
questions with the purpose to make them applicable for our questionnaire. Also (QRM) experts from Spain
(Sergi Mussons, professor at Universitat Politecnica de Catalunya), Belgium (Nico Vandaele, professor at
Katholieke Universitiet van Leuven), and the Netherlands (Jan Riezebos, professor at University of
Groningen; Aldert van der Stoel and Jana Pejcinovska, employees at European QRM center) added or
modified questions in our questionnaire, which they found necessary to determine a company’s QRM
30
Figure 4.1 Sample urgency matrix (manufacturing dynamics elements)
status. During the construction of the indicators we also processed feedback and suggestions from two
Dutch organizations, namely Bosch Scharnieren en Metaal and Larsen Premium Precision Parts. Later in
section 4.2.1 will be explain in more detail how each indicator has been established.
The questionnaire was almost totally based on closed questions or statements. Participants needed to
answer each question or statement on two Five-point Likert scales, see Table 4.1.
The first scale refers to the degree of
implementation (current level of implementation).
The second scale refers to the degree of
importance for the participating organization.
Table 4.1 Implementation and importance Five-point Likert scale
By using these two scales we were able to provide an ''urgency matrix'', see Figure 4.1. In this matrix, the y-
axis represents the degree of implementation (first scale) and the degree of importance is placed on the x-
axis. This kind of matrix is able to make elements visible that require attentions. An element that scored
high on importance, but whose degree of implementation is limited, can be seen as an urgent element that
requires priority above other elements. These elements are located in the lower right corner of the matrix
(Slomp, et al., 2009). For example,
Figure 4.1, which focuses on
manufacturing dynamics, shows
that ''Information & feedback'' is
the most urgent element (large GAP
between degree of implementation
and importance). Though, the other
elements are located in the green
area, which represent the correct
level. The scores included in the
urgency matrixes represent the
average scores of the respondents.
The second part of the questionnaire was developed to generate a profile of the organizations and required
ten minutes from just one person of each organization. The second part was mainly based on open
questions and the outcomes were not connected to the QRM maturity level scoring process.
Scale 1 - Implemented Scale 2 - Importance
1 = None 1 = Totally unimportant 2 = Some 2 = Unimportant 3 = Partial 3 = Neutral 4 = Profound 4 = Important 5 = Complete 5 = Extremely important
31
4.1.1. Reliability and validity
Before spreading the questionnaire to the large sample, we pre-tested the reliability and validity of the first
concept questionnaire by circa five leading experts in the area of QRM. We sent the concept questionnaire
to each expert whom had the possibility to suggest changes in the definition as well as to keep, drop, or
modify questions. We gave the (QRM) experts also the possibility to suggest new items if they felt that
existing ones did not cover the domain of one of the theoretical constructs.
Furthermore, two pilot tests were performed to insure content validity and reliability. To detect if the
questions were clear and understandable for people in the industry, we tested the questionnaire by two
different companies that were in different phases of the QRM concept. First test took place at Larsen
Premium Precision Parts who just started with QRM and was not that familiar with the QRM concept. The
second pilot test took place at Bosch Scharnieren end Metaal, which is known as the first company in
Europe that implemented QRM principles.
We processed the feedback and suggestions from the two test companies, by changing and adding some
questions. With the prior knowledge of the two test companies we also analyzed the reliability of the
outcomes of the questions and their scores on the QRM Maturity Model. Finally, for the aim to ask not
more than thirty minutes from our respondents, we measured also the time during the pilot-tests. To fill in
part one took approximately twenty minutes and just ten minutes were needed to fill in part two of the
questionnaire.
To guarantee the reliability and value of the questionnaire’s output, respondents were only allowed to
answer a question when it was applicable for them. When a question (statement) was not applicable for a
particular respondent, they had the option to either skip the question (statement) or select ''not
applicable''.
4.2. Final Questionnaire
The original English version of the final questionnaire can be found in Appendix 4.1. The Spanish, German
and Dutch translations can be found respectively in Appendices 4.2, 4.3 and 4.4. We will first start to explain
in more detail how each indicator within the first part of the questionnaire (assessing maturity level) has
been established, followed by the explanations of the second part of the questionnaire (organizational
profile). Lastly, the method of the questionnaire’s execution will be described.
32
4.2.1. Part one - Assessing maturity level
Part one started with five open questions:
Name respondent? (optional)
Name organization?
What is your business function?
Where is your company located? (Country, City)
Within what industrial sector is your organization active?
These questions were necessary during the processing of the questionnaire’s output. To respect their
anonymity the name of the respondent was optional and not mandatory. The name of the organization was
important so that we could combine the results from different people from the same organization. Further,
the business function of each respondent was required, so that we were able to compare the results from
different business functions within one organization. For benchmark purposes the company’s location and
industrial sector were necessary.
Now we will explain in more detail how the indicators (questions or statement), within each of the six
theoretical constructs (Vision, Organizational structure, Manufacturing dynamics, Internal scope, External
scope and Product development / engineering), have been established.
Vision – What is the company’s current vision?
Most commonly used key performance indicators (KPIs) are: Cost, Speed, Reliability, Quality and Flexibility
(Figure 4.2). We asked different persons from each company about their KPIs, so we could compare the
results and identify their vision and find out if the
vision was shared within multiple layers of the
organization. The main goal was to identify the role of
''time'' as a performance criterion. Table 4.2 shows
the questions (indicators) per KPI, that we used to
identify the organization's ''Vision''.
The questions (Table 4.2) to identify the vision are largely based on a study of Ward et al (1998). Ward and
his colleagues developed a survey to identify competitive priorities in operations management. The
commonly accepted competitive priorities are described as follows:
vision KPIs
Cost
Quality
Delivery-time
Speed
Reliability
Flexibility
Figure 4.2 Most commonly used key performance indicators
33
Cost importance; based on: production costs, productivity, capacity utilization, and inventory
reduction.
Quality importance; based on the first six of Garvin’s (1987) quality dimensions: performance,
features, reliability; conformance, durability, serviceability.
Delivery-time importance; combination of speed & reliability
Flexibility importance; based on the first four of Gerwin’s (1993) dimensions of flexibility: product
mix, volume, changeover, and modification.
Their questions have been assessed by 114 manufacturing plants in the US and their results proved the
reliability and validity of their survey questions. From the questionnaire of Ward et al (1998) we have used
the questions that were proved to be reliable and valid, but we slightly adjusted the questions. We changed
the syntax of the questions to make it possible to answer the questions on our two scales (importance and
implementation).
For example:
- Original: ''Importance of productivity as criterion in evaluating line managers’ performance''
- New: ''We use productivity as criterion in evaluating line managers’ performance''
Originally the questions for the ''quality'' section existed of six questions, but we reduced the amount of
questions to a number of four questions. During the pilot test we used the six original questions. However,
the pilot companies suggested to clarify and combine some of the questions.
- Original: ''We deliver a high product performance'' and '' We deliver high product quality reliability''
- New: ''We deliver a high product quality performance / reliability''
34
Table 4.2 Indicators vision
Organizational structure - What kind of organizational structure does the company have?
Does the organizational structure support lead time reduction and flexibility? Is the organizational structure
organic or mechanic? In a stable environment mechanic structures are common and in an unstable and
changing environment organic might be the best structure (Burns & Stalker, 1961; Lawrence & Lorsch, 1979)
(Figure 4.3).
To identify if an organizational structure was mechanic, organic or something in between, we came up with
the questions mentioned in Table 4.3. These questions are highly based on a study by Nahm et al (2003).
Nahm et al (2003) developed an instrument (survey questions) to identify the impact of an organizational
structure on time-based manufacturing and plant performance. Time-based manufacturing and QRM, they
both have the aim to achieve a fast response to customer needs. According to Namh (2003), organizations
need an organic structure to be successful in post-industrial environment with low volume and high product
variety. To identity if the ''Organizational structure'' is organic or inorganic (mechanic), Nahm et al examines
the following structural dimensions:
Elements Reference Indicators
Cost
(Ward, et al., 1998)
-Production cost is one of our management priorities in manufacturing -Labor productivity is one of our management priorities in manufacturing -Full capacity utilization is one of our management priorities in manufacturing -Reducing inventory is one of our management priorities in manufacturing -We use cost as criterion in evaluating line managers’ performance -We use productivity as criterion in evaluating line managers’ performance
Delivery-time (Speed & Reliability)
-We have a short delivery time -We deliver on due date -We continuously reduce production lead time -We use on-time delivery as a criterion in evaluating line managers’ performance -We use production cycle time as a criterion in evaluating line managers’ performance
Quality
-We deliver a high product quality performance/reliability -We deliver a high product durability/lifetime -We are able to rapidly solve customer complaints -Conformance to design specifications is one of our management priorities in manufacturing
Flexibility
-We offer large number of product features or options -We are able to quickly introduce a new-product -We are able to rapidly adjust the capacity -We have the ability to make design changes
Low Environmental uncertainty High
Figure 4.3 Relationship between environmental uncertainty and organizational structure
Mechanic structure
Organic structure
35
Locus of decision-making
Are decisions made high in the organization (centralized decision-making) or are decisions made low in the
organization (decentralized decision-making). An organization's structure is organic when decisions are
made low in the organization (Lawrence and Lorsch, 1967). The indicators of the first dimension, mentioned
in Table 4.3, are all original questions from Nahm et al (2003).
Nature of formalization
Are workers provided with rules and procedures that encourage or discourage flexible/creative work and
learning? Nature of formalization is organic when the workers within the organization have flexible work
rules (Koufteros, et al., 1998). The indicators of the second structural dimensions are based on the original
questions from Nahm et al (2003) and combined and adjusted by experts till three questions with the same
aim.
Number of layers in hierarchy
Does the organization have few or many management layers in the organizational hierarchy? Organic
organizations have a low (less than four) number of hierarchical layers (Burns & Stalker, 1961). In the
original study of Nahm et al (2003) they define low number of layers at four or less layers. However, for our
research we focus on SMEs where the amount of layers are generally much lower. So for the purpose of our
questionnaire we changed the definition of low number of layers to less or equal to four layers of hierarchy.
Level of communication
Is the horizontal and vertical communication within the organization slow, difficult and limited or on the
other hand fast, easy and rich? Within an organic organization communication is fast, easy and rich (Doll
and Vonderembse, 1991). All five questions are the original questions from Nahm et al (2003). However,
after the pilot test we made some adjustment to overcome some ambiguities.
Level of horizontal integration (Joint specialization)
To identify if departments and workers are functional specialized (low level of horizontal integration) or
joint specialized (high level of horizontal integration), we constructed three questions. Within an organic
organization high levels of horizontal integration exist (Davenport & Nohria, 1994). Only two of the original
six questions from Nahm et al (2003) are used. After feedback from experts and pilot companies we decided
to remove comparable questions, whit the goal to keep the survey short.
36
Cross-functional training (Extra / addition)
We add an extra dimension ''cross-functional training'' which builds on the structural dimension ''level of
horizontal integration''. Workers that receive cross-functional training will increase his or her understanding
of the entire organizational processes. So they become more multi-functional which is useful in a post-
industrial industry, which deals with high product varieties and low product volumes. The questions to
identify cross-functional training are based on a study of Cua et al (2001), which later on were also used by
Ketoviki and Schroeder (2004). Cua et al (2001) developed an instrument to simultaneously measure the
influence of total quality management (TQM), just in time (JIT) and total productive maintenance (TPM)
practices on manufacturing performance.
The original, modified and added questions have been (again) tested on their validity and reliability by
experts and pilot tests.
Elements Reference Indicators
Locus of decision-making
(Nahm, et al., 2003)
-Our workers have the authority to correct problems when they occur -Our work teams have control over their job -Our supervisors or middle managers are supportive of the decisions made by our work teams -We encourage workers to be creative in dealing with problems at work
Nature of formalization
-We have written rules and procedures that show how workers can make suggestions for changes -Our workers have their own space and time to experiment with their job -We have written rules and procedures that guide quality improving and creative problem solving
Number of layers in hierarchy
-There are few layers in our organizational hierarchy (less than four)
Level of communication
-Communications are carried out among managers frequently -Communications are easily carried out among workers -Strategic decisions are quickly passed on to relevant work groups -Communication between different levels in hierarchy is easy -Workers can easily meet and communicate with upper management
Level of horizontal integration
-Our tasks are done through cross-functional teams -Our managers are assigned to lead various cross-functional teams
Cross-functional training
-In our organization employees receive training to perform multiple tasks -In our organization employees are cross-trained so that they can fill in for others if necessary -At our organization employees learn to do only one job / task (inverse)
Table 4.3 Indicators organizational structure
37
Manufacturing dynamics - How do people, machines and products
interact with each other, and does this support lead time reductions?
How is the capacity planned among the workers and machines? What kind of
batch size policy do they follow? To give answers to these and more
questions we constructed the following indicators, Table 4.4:
We measured two things. Firstly, we measured how people, machines and products interact with each
other. Secondly, we measured if the type of interactions supported lead time reductions. To measure these
two things we used a mix of existing metrics from Tu et al (2001), Shah & Ward (2007), and Cua et al (2001).
Tu et al (2001) developed an instrument to identify the relationship among time-based manufacturing
practices (which has similarities with QRM) and value to customer. Tu et al (2001) paid attention to the
following interesting activities: Shop floor employee involvement in problem solving, Reengineering setups,
Cellular manufacturing, Preventive maintenance, Quality improvement effort, Dependable suppliers and
Pull production.
Shah & Ward (2007) developed a list of 48 measurement items divided over ten distinct dimensions that
represent lean production. The 48 measurement items form a tool that can aid managers to self-evaluate
their progress in implementing lean production. Shah & Ward (2007) focused on the following interesting
activities: Pull, Continuous flow, Setup, Total productive/preventive maintenance, Statistical process
control, Employee involvement. They focused also on Supplier feedback, JIT delivery by suppliers, Supplier
development, Customer involvement, but those activities would be included in later constructs.
Cua et al (2001) developed an instrument to simultaneously measure the influence of TQM, JIT and TPM
practices on manufacturing performance. Cua et al (2001) focused on the practices such as: Setup time
reduction, Pull system production, Equipment layout, Autonomous & planned maintenance, Committed
leadership, Employee involvement, and Information and feedback.
Based on the literature we devided ''Manufacturing dynamics'' into the following dimensions:
Employee involvement
Till what degree are employees involved during problem solving? A high level of employee involvement will
usually result into a more effictive organization and quicker response to customers demand (Tu, et al.,
2001). The indicators within this dimension are based on studies from Shad & Ward (2007) and Cua et al
(2001).
People
Products Machines
Figure 4.4 Manufacturing dynamics
38
Setup
Till which extent are process downtimes between changeovers reduced till the minimum? Organizations
that work with relative short set-up times are usualy more flexible. This allows them to quickly adapt to a
diverse customer demand (Ohno, 1988). To measure the effort put into the setup time reduction, we
constructed indicators which are based on a mix of (QRM) experts and studies of Shad & Ward (2007) and
Cua et al (2001).
Cellular manufacturing
Is the organization working with cells and does it apply group technology principles? If yes, till which extent?
When a company is eligible for manufacturing cells it generally leads to less material handling, less work-in-
process, and shorter throughput times (Hyer, 1984). To answer this dimension, we came up with indicators
based on metrics from Tu et al (2001) and Cua et al (2001).
Maintenance
Till which extent are total productive, preventive and/or autonomous maintenance carried out? Good
maintenance normaly increases an organization's machine(s) and process reliability. The increasing
equipment availability will lead to shorter throughput times, higher product quality, lower production costs
(Tu, et al., 2001). The constructed indicators are based on the metrics of Shah & Ward (2007) and (QRM)
experts.
(quality) Information & feedback
Till which extent is information concerning quality and lead times directly available to everybody? When
several stations or cells are tightly linked with each other, it will become important that information and
feedback are available to determine production lot sizes and schedules. Information and feedback are also
part of the total productive maintance. The indicators are based on the metrics of Shah & Ward (2007), Tu
et al (2001) and Cua et al (2001).
Flow / pull
Till which extent does the production system run on signals that are based on the capacity of the next
station(s)/cell(s)? Pull or a hybrid push / pull systems, limit the amount of work in process that can be in the
system. This will reduce the work in process, cycle times and cost and improves the quality (Hopp &
Spearman, 2004). The indicators are based on the metrics of Shah & Ward (2007), Tu et al (2001). The
39
questions from Shah & Ward are only focusing on lean (KANBAN). With support from the QRM center and
the available QRM literature we came up with several QRM (POLCA) focused questions.
Capacity utilization
Is the goal to put the capacity utilization on 100% (effiency)
or 70 or 80% (flexibility)? A 20 or 30% reserve capacity will
increase the organization’s flexibility and quickness of
response by an extreme decline of lead time, see Figure 4.5
(Suri, 2010). The indicators are based on QRM literature
and knowledge from (QRM) experts.
Variability
Does the organization remove disfunctional and product variability or do they recognize strategic (product)
variability? When organizations are able to deal with a high product variety they might exploit it as their
strategic advantage against those organizations that are not able to deal with high product varieties. The
indicators are based on QRM literature and knowledge from (QRM) experts.
Extra
Are organizations creative to implement their own tools or are they capable to enhance excisting tools?
Pilot tests and interviews have revealed that some companies took their own initiatives by creating their
own tools or additions to QRM or POLCA. For example:
-Bosch Scharnieren en Metaal: PROPOS (virtual POLCA cards)
-Variass Electronics: cutting the POLCA card into two seperate cards
Figure 4.5 Capacity utilization vs. Throughput time
40
Elements References Indicators
Employee involvement
(Shah & Ward, 2007)
-Shop-floor employees are key to problem solving teams -Shop-floor employees drive suggestion programs -Shop-floor employees lead product/process improvement efforts
(Cua, et al., 2001)
-During problem solving sessions, we make an effort to get all team members’ opinions and ideas before making a decision
Setup
(Cua, et al., 2001; Shah & Ward, 2007)
-We are working to lower set-up times in our plant -We reduced the set-up times of equipment in our plant to the minimum -Our crews practice set-ups to reduce the time required
(Self) -Short set-up times enables us to use relative small batch sizes
Cellular manufacturing
(Tu, et al., 2001)
-Products are classified into groups with similar processing or routing requirements -Equipment is grouped to produce families of products -Families of products determine our factory layout
(Cua, et al., 2001) -Our processes are located close together so that material handling and part storage are minimized.
Maintenance
(Shah & Ward, 2007)
-We dedicate a portion of everyday to planned equipment maintenance activities -We maintain all our equipment regularly -We maintain excellent records of all equipment maintenance related activities -We post equipment maintenance records on shop floor for active sharing with employees -We emphasize good preventive maintenance
(Expert, Mussons) -Our operators perform certain equipment maintenance activities (such as lubricating, cleaning machine parts)
Information & feedback
(Tu, et al., 2001; Shah & Ward, 2007)
-We use fishbone type diagrams to identify causes of quality problems
(Cua, et al., 2001)
-Charts showing defect rates are posted on the shop floor -Charts plotting the frequency of machine breakdowns are posted on the shop floor -Information on quality performance is readily available to employees -Information on lead times is readily available to employees
Flow (pull, hybrid-push/pull)
(Tu, et al., 2001; Shah & Ward, 2007)
-Production at stations is ''pulled'' by the current demand or available capacity of the next stations -Production is “pulled” by visual/virtual cards or bins -We use a “pull” or combination of “push” and “pull” production system -Production is “pulled” by the shipment of finished goods
(Self/Experts/Pilots)
-We use a production planning system, but only to authorize/control the first workstation of the production line -Production at a workstation starts only when both authorization, material and capacity at the required workstations are available -Our production system enables us to reduce the work on the shop floor
Capacity utilization
(Self/Experts/Pilots)
-We do not aim for maximum utilization, so that we gain flexibility/robustness -Variability can be buffered by: time, capacity or inventory. Our buffers exist mainly of idle capacity -We can handle ''rush orders'' without disturbing our average delivery time -We work with short and accurate planning horizon
Variability
(Self/Experts/Pilots)
-We eliminate bad variability out of our process -We recognize strategic variability and try to exploit it (Might be their strategic/competitive advantage)
Extra (Experts/Pilots) -We created our own tools to improve lead time reductions
Table 4.4 Indicators manufacturing dynamics
41
Internal scope - Till which extent are actions to reduce lead times, penetrated throughout the company?
In this theoretical construct we wanted to answer the two questions. Firstly,
in which departments in the organization are firms working on lead time
reductions and till which degree? Secondly, did firms implement such a
strategy as QRM? If yes, in which phase of QRM implementation are they
right now?
To answer these two questions we constructed the questions illustrated in Table 4.5.
QRM is not just for the shop-floor, it applies to the entire organization including disciplines such as: Sales,
Purchase, Finance, Engineering, Design and Research & Development (R&D). Actions to reduce lead times
can be implemented throughout the entire organization, especially for those departments where time
reduction is important and many benefits can be achieved. In some companies, it happens that the office
operations consume for more than half of the lead time. For example, quicker responding in office
operations can be achieved, in calculating and tendering, engineering, planning and order processing by
implementing QRM principles (Suri, 2010). With our questions we identified for each discipline the degree
of importance and implementation of lead time reduction practices.
To identify the phase of the organization’s QRM implementation we described six phases which were based
on both ''how to implement QRM step-wise procedure for managers'' written by Suri (2010) and a step-wise
procedure for successful change management by Kotter et al (2006).
References Indicators
(Self) Select one or more areas where time reducing activities are present; please indicate the percentage of expansion within each area:
-Sales -Purchase -Finance -Engineering -Shop-floor -Design -Research & Development
(Self; Kotter, 2006; Suri, 2010)
Select one the phases in which you can locate your organization right now:
-We do not have urgency of taking time compression actions -We recently discovered the power of time -We search for the right area/segment within our organization to start a lead time reduction pilot -We need to successfully succeed a pilot test to convince the rest of the organization -We are reducing lead times in a couple of departments within the enterprise -We are actively reducing lead times throughout the entire enterprise -Not applicable
Table 4.5 Indicators internal scope
Figure 4.6 Internal scope
42
External scope - Till which extent are actions to reduce lead times, penetrated outside the organization
boundaries?
To answer this question we constructed indicators that measured both the
degree of integration with the supplier(s) as with the customer(s), illustrated
in Table 4.6. So, we divided the external scope into the following two
dimensions:
Supplier(s)
To identify the type of relation between the organization and their supplier(s), we used indicators which are
based on studies from Tu et al. (2001) and Shah & Ward (2007), interviews with experts and QRM literature.
SMEs that operate under time pressure cannot afford shortages and quality problems with supplier parts,
because this will generate a large delay. It is also proven that dependable suppliers can help to reduce lead
times, increase quality, and improve manufacturing competitiveness (Blackburn, 1991). So it is wise for
SMEs, which work under time pressure, to have a strong relationship with (local) suppliers that are reliable
and have short delivery times. On the other hand, organizations that are working under less till no time
pressure, will focus on costs and efficiency and their relation with the supplier will be more focused on
infrequent shipping to gain quantum discount.
Mature QRM organizations can train their suppliers to reduce the lead time throughout the supply chain.
However, we expect that most of the SME's are too small to influence/train the (larger) supplier(s).
Therefore we paid also attention to the customers which can be found at the other side of the supply chain.
Customer(s)/user(s)
To identify the type of relation between the organization and their customer(s) or end-user(s), we used
questions which are based on metrics of Cua et al (2001), interviews with experts and QRM literature.
''Customer involvement'' is one of those practices which was interesting for our study. An organization
wants to produce the product right the first time, in order to avoid delays and rework and achieve a
maximum customer's compliance service rate. To achieve this maximum rate and short lead times, the
organization needs to have a rich relation with their customers and be sure about customer's requirements.
To support the QRM production it is also important that companies encourage their customers to place
frequently small batch orders.
Figure 4.7 External scope
43
Elements References Indicators
Delivery-time & reliability of supplier(s)
(Tu, et al., 2001)
-We receive parts from suppliers on time -We receive the correct number of parts from suppliers -We receive high quality parts from suppliers -We receive the correct type of parts from suppliers
(Shah & Ward, 2007) -Our key suppliers are located in close proximity to our plants
(Self/experts/pilots)
-We receive small-quantity frequent deliveries from our suppliers -To gain quantum discount we have infrequent shipping of large quantities -We train suppliers to improve lead time reduction -Most of our suppliers are too large to influence -Our suppliers are aware about the power of time -We are aware about the suppliers lead times -Our suppliers have a short delivery time -We are able to work without stocks, due to the short delivery time(s) of our supplier(s) -We consider delivery time as crucial criterion in selecting suppliers -In some cases we are willing to pay more for a shorter delivery time
Communication with supplier(s)
(Shah & Ward, 2007) -We frequently are in close contact with our suppliers
(Expert, van der Stoel) - We share our forecast / demand information with the supplier(s)
Customer(s)/User(s) compliance service rate
(Cua, et al., 2001) -Our customers give us feedback on quality and delivery performance -We regularly survey our customer/user's requirement
(Self/experts/pilots)
-We encourage our customers to place frequently low volume orders -We have a maximum customers compliance service rate -Our customers experience short lead times
Communication with customer(s)/user(s)
(Cua, et al., 2001) -We frequently are in close contact with our customers/users -We share our forecast/demand information with the customer(s) -We strive to be highly responsive to our customer/user's needs
Table 4.6 Indicators external scope
Product development / engineering - What is the company’s current product design / engineering time
(time-to-market)?
Nowadays with the rapid changing in technology, markets and customers, a rapid time-to-market can form
a strategic advantage for companies. For SMEs under time pressure it will be necessary that decision making
during the (new) product introduction (development/engineering) needs to be based on time-thinking
instead of cost-thinking (Suri, 2010; Smith & Reinertsen, 1991). Companies in the computer industry are
taking the lead in quick product development. Accelerating the time-to-market has many benefits, but to
achieve those benefits a shift from a cost to a time mindset is necessary. Companies must put more effort
on time reducing strategies and techniques (Smith & Reinertsen, 1991). There are multiple techniques that
can be used to reduce the time-to-market. For our study we focused on the following techniques:
Concurrent engineering, Customer integration, Supplier integration and Project Management. To identify if
firms are working on lead time reduction in the development / engineering phase, we constructed the
indicators illustrated in Table 4.7.
44
Concurrent engineering (internal integration)
Are design/engineering and manufacturing two separate functional areas with relatively little interaction or
are designers/engineers and producers working together from the earliest stages of product
design/engineering (also known as concurrent engineering)? To reduce quality problems, production costs
and time-to-market concurrent engineering has proven to be a successful technique (Nicholas, 2008). To
identify if engineers and producers were working simultaneously we came up with indicators which are
based on metrics from Koufteros et al (2005). The term concurrent engineering is not just simultaneously
working between engineering and producers, but regards also to sales, marketing, purchasing, finance, and
quality.
Effective product development/engineering requires unifying with internal and external participants
(Koufteros, et al., 2005). With concurrent engineering we focus on the internal integration. However,
Koufteros et al (2005) proved that external integration is also an important element. Therefore, we used
also questions to identify the organization's level of external (both customer and supplier) integration with
regard to product development or engineering.
Customer(s)/user(s) (external integration)
Till what degree are customers/users involved during the product development or engineering process?
Time reduction and quality improvements can be achieved by combining the interests from the customer
with the development/engineering process from the start, so that customer requirements are identified
early. The indicators are based on existing metrics (Koufteros, et al., 2005; Ketoviki & Schroeder, 2004; Li, et
al., 2005).
Supplier integration (external integration)
Till what degree are suppliers involved during the product development/engineering process? Organizations
can allocate several developing/engineering tasks to their suppliers and capitalize on the engineering
expertise and background of suppliers. Suppliers can work simultaneously on various components and
subassemblies, which will accelerate the development/engineering process (Koufteros, et al., 2005).
According to Bonaccorsi and Lipparini (1994), early supplier involvement results into lower development /
engineering costs, consistency between design and suppliers capabilities, higher quality with fewer defects,
availability of detailed process data and reduction in time to market. The indicators are based on existing
metrics from Koufteros et al (2005).
45
Project Management
How flexible is the (new) product development / engineering? Flexibility is high when an organization is able
to make changes late in the development / engineering phase, without excessive disruption or costs. When
the flexibility is high, the time-to-market will be short. However, there are companies that are using an
inflexible pre-determined planning, also known as ''phased development systems'' (e.g. state-gate model,
six-sigma, project office). These systems discourage flexibility by rewarding and encouraging rigidity.
Though, for SME's flexibility, being able to make decisions at the latest moment is important to survive in
their unstable environment (Smith, 2007). The questions are mainly based on Smith (2007) and on expert
feedback.
Elements References Indicators
Concurrent engineering (simultaneous engineering)
(Koufteros, et al., 2005)
-Product development / engineering activities are parallelized (performing tasks concurrently) -Various disciplines are involved / integrated in product development/engineering from the early stages
(Self) -We apply tools and techniques that will shorten or integrate steps
Customer integration
(Koufteros, et al., 2005)
-We visit / listen to our customers to discuss product development / engineering issues
(Ketoviki & Schroeder, 2004)
-Our customers / users are actively involved in the product design process
(Li, et al., 2005) -Customer / users experience our time-to-market as quickly
(Self)
-During development / engineering we are still able to execute customers feedback -We have rapid prototyping techniques
Supplier integration
(Koufteros, et al., 2005)
-Our suppliers develop component parts for us -Our suppliers are involved in the early stages of product development / engineering -We make use of supplier expertise in the development / engineering of our product
Project management
(Self)
-We use tools and techniques to cut decision-making time -We follow an upfront planning and phased development plan (states-gate model) -Our new product development/engineering process is flexible so that we can quickly response to customer specific product wishes -During development/engineering we have the ability to make changes, without being too disruptive -We measure time-to-market from the last change in requirements until the product is delivered
Table 4.7 Indicators product development / engineering
4.2.2. Part two - Organizational profile
As an addition to the previous indicators of the first part of the questionnaire (assessing the maturity), we
added a second part to the questionnaire that deals with technical indicators which were necessary to
analyze the interview outcomes and generate profiles of the organizations. The duration of the second part
of the questionnaire was approximately 10 minutes and required only one person of the organization.
46
Technical variables - What kind of companies filled in our questionnaire?
We developed a mix of open and closed questions to generate a profile of the organizations, see Table 4.8.
Organizational profiles were used for benchmarking purposes. It made it possible to compare companies
with each other. Furthermore, questions were asked about the production characteristics of the
participating companies. We expected that for example, companies that are characterized by ''low volume
production, high product variety'' or ''make-to-order'', score higher on the importance
of QRM principles, than companies that are characterized by ''high volume production,
low product variety'' or ''make-to-stock''. Since, QRM has a better answer on the
product variety than Lean (Suri, 2010).
The questions are based on the following sources:
A lean monitor that was developed in 2009 by the University of Groningen with the purpose to identify the
level of implementation and importance of lean principles within the Dutch industry (Slomp, et al., 2009).
Their monitor consists of 41 statements that need to be answered by participating organizations. Next to
the 41 statements concerning lean principles, several additional questions that generate a profile of the
participating organization(s) are included. For the purpose of our study, we compared and include a couple
of those questions.
During the test phase of the questionnaire, we gained feedback from Mussons a QRM expert in Spain and
professor ''Management and optimization of industrial plants'' at the Universitat Politecnica de Catalunya
(Spain, Barcelona). At the moment Mussons is working on a questionnaire that aims to find a big index
which includes all the operations competitiveness issues in an industrial company. Instead of us focusing on
QRM, Mussons tries to keep his focus broader. There is some overlap between our two questionnaires, so
we made a mutual agreement to include some of each other's questions.
Members of the QRM center were able to give feedback, suggestions and had the possibility to add
questions to the questionnaire.
Finally, we used the feedback that we received during the pilot tests to refine and simplify the questions.
For example, the companies suggested to create dropdown answering options. This had as a result that
questions became more simple and less time consuming to answer.
Figure 4.8 Organizational profile
47
Indicators
-Name organization -Is your organization part of a multinational organization? -Where is your company located? (Country, City) -Age of the organization? (in years) -Within what industrial sector is your organization active? -What kind of product(s) does your organization provide? -Number of product types / items? -How many client groups? -Who are your main client groups? -Number of orders per year? -Does your organization have easily predicted sales? (yes / no, other___) Number of employees within your organization’s location? -Organization’s turnover? -What do you think is your organization’s most decisive competitive advantage? -Which competitive factor do you want to improve the most? -Has your organization achieved lead time reduction in the past? If yes what percentage? -Have you implemented concepts such as LEAN or QRM? If yes when did you started (starting date) -Indicate your plant’s production orientation (make to stock, assemble to order, make to order, engineer to order, Other) -I would characterize my plant as
- High volume production, low product variety - Average volume production, average product variety - Low volume production with high product variety - Not applicable
-In relation to the total sales what is the percentage of custom products (customer specific products) that your organization sell? -How many different products does your organization sell each month? -How long is the planning horizon? (in days) -Indicate how the stock in your organization are divided Fill in what percent of sales falls into each category (percentage must sum 100%)
- Finished products stock ( sales % ) - Work in progress stock ( sales % ) - Raw material stock ( sales % )
-The production process in our plant is best characterized as follows. Fill in what percent of product volume falls into each category (percentages must sum 100%)
- One of a kind ( product volume % ) - Small batch ( product volume % ) - Large batch ( product volume % ) - Repetitive / line flow ( product volume % ) - Continuous ( product volume % )
Table 4.8 Technical questions
4.2.3. Questionnaire's execution method
The purpose was to collect data from over five companies from each a different region. The questionnaire
was accessible for everyone via the official European QRM website1, since May 2012. To prevent language
problems or misinterpretations, we have translated the questionnaire, next to English, into three more
languages (Spanish, German and Dutch), with assistance from the Groningen University Language Center.
1 http://survey.qrm-centrum.nl
48
To increase the response rate, we contacted the European QRM center. Via the QRM center and their global
network partners we were able to invite companies from the following regions: USA, Belgium, Germany,
Norway, Spain, Denmark, Austria, Mexico, Chile and the Netherlands. These network partners consisted
mostly of member of local QRM centers, which had again relations with companies in their region. We first
mailed an announcement followed by a detailed instruction letter to about twenty network partners, with
the request to help us by spreading the questionnaire to at least five companies in their region. To gain the
interest of the companies and in exchange for their effort, we included a draft customized report within the
invitations, which each company will receive afterwards.
Almost all the contacted network partners indicated to be interested and willing to help us spreading the
questionnaire, but due to a lack of time, not every partner was able to invite companies in their region
before the QRM conference held on June 2012, see Table 4.9. Hence, Table 4.9 shows there is plenty of
support for further research.
Table 4.9 Global network partners
Region
Nu
mb
er
of
par
tner
s th
at
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nce
d
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at
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re w
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at
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ith
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(be
fore
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ne
20
12
)
Austria 1 1 1 Belgium 3 1 Chili 1 1 Denmark 2 2 Germany 3 3 Mexico 3 2 The Netherlands 3 3 3 Norway 1 1 1 Spain 2 2 USA 1 1
Figure 4.9 Impression of the on-line questionnaire
The tool which has been used for the on-line questionnaire, was able to automatically combine the results
of the respondents into one document per language. We could combine the results from the four different
languages into one data base, without the need for one or more translators, because the questionnaire's
outputs were largely based on the numerical scores of the Five-point Likert scales.
We will start to analyze the collected data in more detail in the next section.
49
5. Results & analysis In this section we will address the preliminary results that are part of a larger research which is still in
progress. The questionnaire is still accessible via the official European QRM website2 and the global network
partners are still spreading invitations to organizations in their regions. The aim was to make a quantitative
study from the data of at least five companies per region and per company multiple persons from different
business processes. At the QRM conference held on June 2012, we presented our first results. The number
of respondents was limited, so we did not statistically analyze the results. Nevertheless, we have examined
the applicability of the QRM Maturity Model on a qualitative approach. We applied a multiple case study
research methodology, since case studies are based on analytic generalization instead of statistical
generalization (Yin, 2009).
The multiple case study is based on the data, which was gathered by our on-line questionnaire. At the
beginning of June 2012 the questionnaire was filled in by eleven companies from three different countries.
We have summarized the main characteristics of the eleven companies in Table 5.1 The companies are
located in Europe (the Netherlands, Norway and Austria) and can be classified as SMEs. To be able to
analyze each questionnaire's output, at least two or more respondents per company were required. Four
companies of our sample failed to meet this requirement, which reduces the number of cases to seven
companies. Variass Electronics, Bosch Scharnieren en Metaal, Kaak Bakeware, AS Trøndelag
Industrielektronikk, Brakel Aluminium, Larsen Premium Precision Parts and Euro-Bis Poedercoating, form
the case studies that we analyzed. These companies can be characterized as make-to-order (MTO) or
engineer-to-order (ETO) organizations, which work with ''low or high volume production and high product
variety''. With the exception of one company, all companies had indicated that they have implemented
concepts such are lean or QRM.
5.1. Case studies
We will now discuss the seven case studies to which we applied the QRM Maturity Model. Each case will be
analyzed separately. First, each case will be shortly introduced. Thereafter, the company's QRM maturity
level will be argued and explained based on the maturity scores that have been dedicated to each of the six
theoretical constructs. The maturity scores on the theoretical constructs were automatically calculated by a
special developed and tested calculation model which used the data output from the questionnaires. So,
companies will be scored on each of the six construct separately and the average score state the overall
QRM maturity level of the particular company.
2 http://survey.qrm-centrum.nl
50
Case Par
t 2
Par
t 1
Nr
resp
on
de
nts
Bu
sin
ess
fun
ctio
ns
of
the
resp
on
den
ts
Nu
mb
er
of
em
plo
yee
s
Turn
ove
r
Ind
ust
rial
se
cto
r
Loca
tio
n
Kin
d o
f
org
aniz
atio
n
1
3
-Project leader -Operations manager -Production manager
>100
€25.000.000 Electronics Netherlands,
Veendam MTO
2
3
-CEO -Operations manager -Production optimization consultant
20 - 50
€4.000.000 Metal Netherlands, Doetinchem
ETO
3
3
-Engineer process development -Production leader -CEO
20 - 50 €10.000.000 Machine
construction Netherlands,
Terborg
ETO (30%) MTO (70%)
4
3
-CEO -Project leader -Quality Assurance
50 - 100 €9.730.000* (73,9MNOK)
Electronics Norway,
Selbu MTO
5
4
-CEO -Product manager -Operations manager -Engineer
> 100 €15.500.000 Construction
and large metal Netherlands,
Uden ETO
6
2
-CEO -Student (intern)
20 - 50 €4.850.000
Medical industry,
aerospace, semiconductors
Netherlands, Zeewolde
MTO
7
2
-Student (intern) -CEO
10 - 20 €1.500.000 Powder coating
Surface treatment
Netherlands, Oudenbosch
MTO
8
1**
-Operations manager >100 €20.000.000 Metal &
electronics Netherlands,
Assen ATO
9
1**
-Operations manager >100 €40.000.000 Consumer
goods Austria,
Mittersill MTS
10
1**
-Operations manager 50 - 100 €11.000.000 Electronics
Manufacturing Services (EMS)
Norway, Trondheim
MTO
11
1** x 50 - 100
€19.740.000* (150MNOK)
Oil & gas technology
Norway, Stavanger
MTO
Table 5.1 Summary of the main characteristics of the seven cases * Currency Norway Krone vs. Euro: 1,00 NOK = 0,131625 EUR (XE.com, 2012) **These company is not part of the case study research, because more than one respondent per company was required.
51
Case one – Variass Electronics
Variass Electronics is located in the Netherlands and is a system supplier of integrated electronic and
mechatronic equipment for industrial, medical, military and water applications. They are classified as a SME,
due to the fact that their turnover of €25.000.000 and their 120 employees stayed below the SME
classification boundary (turnover < €50.000.000 and number of employees <250). Their plant can be best
described as ''low volume production with high product variety'' and a make-to-order (MTO) production
orientation. In 2006 they started to implement concepts, such as lean and QRM and in 2011 they
implemented POLCA, which altogether resulted already in a 20 percent lead time reduction. At this moment
quality and reliability form the organization's most decisive competitive advantage. For the future, flexibility
has the main priority to be improved. The average planning horizon amounts to 80 days. The stock
distribution and the production characteristic are respectively illustrated in Tables 5.2 and 5.3.
Finished products
Work in progress
Raw Material
15% 20% 65%
One of a kind
Small batch
Large batch
Repetitive Continuous
10% 65% 20% 5% -
Table. 5.2 Type of stocks (sum 100%) Table 5.3 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part was filled in by three persons (Project leader, Operations manager and Production manager). The
average scoring difference between the three respondents amount 0.66 per question, this is almost
equivalent to the sample's average (0.72). The lower this number is, the more the respondents agree with
each other on their given scores. Variass can be located on the third maturity level, Table 5.4 explains the
scores on each construct. For a more detailed overview of the scores and insights see Appendix 2.1.
Construct Score Arguments / explanation
Vision 2 They are aware about the importance of delivery-time (4.12). However, cost (4.28) and quality (4.33) are still playing a more important role as key performance indicators than delivery time and flexibility. Flexibility (3.75) scores even below the average sample score (3.92).
Organizational structure
3 The organization is semi-organic and needs to become more flexible to score higher. The level of horizontal integration (2.50) scored for example below the sample average (2.85), but we think this will increase soon, due to their high level of cross-functional training (4.33).
Manufacturing dynamics
4 Manufacturing dynamics scores as a construct, higher than the average sample score (2.99). This is largely attributable to successful maintenance (4.33), cellular manufacturing and their (POLCA) production control system which reduces lead times and work in process.
Internal 3 Time reducing activities are implemented throughout the entire organization. However the departments R&D(2.33), design(2.00), finance(2.00) and sales(2.33) are lagging behind purchase(4.33), engineering(3.67) and the shop-floor(3.67).
External 4 The QRM principles are implemented throughout the supply chain. There is a good integration with the suppliers and customers / users. Especially the communication with the suppliers (4.33) scores above average (3.33). The speed and reliability of the suppliers should be further optimized.
Product development
3
The last construct scores on an average scale. It has also has a large GAP (-0.57), which indicates that they need to improve their QRM elements in this construct. For example concurrent engineering has the main priority for improvement, and will result in a reduction of quality problems and less production cost and quicker time-to-market.
Table 5.4 Scores per theoretical construct (Variass Electronics)
52
Case two – Bosch Scharnieren en Metaal
Bosch Scharnieren en Metaal is located in the Netherlands and is a manufacturer of custom-made hinges
and metal constructions for a large variety of industries (metal industry, marine, railway, etc). They are
classified as a SME, due to the fact that their turnover of €4.000.000 and their 30 employees stayed below
the SME classification boundary. Their plant can be best described as ''low volume production with high
product variety'' and they have an engineer-to-order (ETO) production orientation. In 2004 they started to
implement lean, however this was not a success, so in 2007 they implemented QRM principles such as
POLCA, which already resulted in a 50 percent lead time reduction. Recently they developed PROPOS
(Production and POLCA Observation System), which is a virtual version of the visual polca-cards. Custom-
made service, reliability and short delivery times, form the most decisive competitive advantage. For the
future improvements, shorter delivery times have the main priority. The production characteristic is
illustrated in Table 5.5. The average planning horizon amounts to 10 till 20 days.
One of a kind
Small batch
Large batch
Repetitive Continuous
15% 60% - 25% -
Table 5.5 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part is filled in by three persons (CEO, Operations manager and an Intern master student). The average
scoring difference between the three respondents amount 0.65 per question, this is underneath the
sample's average (0.72). The lower this number is, the more the respondents agree with each other on their
given scores. Bosch Scharnieren en Metaal is located on the fourth maturity level, which is explained in
Table 5.6. For a more detailed overview of the scores and insights see Appendix 2.2.
Construct Score Arguments / explanation
Vision 4 There is a significant difference visible between the importance for cost (3.29) and delivery-time (4.28). Speed and reliability (3.65) are playing a more important role as key performance indicators than cost (2.95). This vision is shared among the employees.
Organizational structure
4 Their organizational structure is quite organic and is able to react on their changing environment. One of the reasons, is that their employees are multi-functional (4.00) and we expect this will be further optimized due to the high score on cross-functional training (4.56).
Manufacturing dynamics
4 Setup time reductions (3.81), cellular manufacturing (5.00) in combination with a hybrid push/pull system reduced the amount of work in process and decreased the lead times. Before reaching the highest level they need to involve their employees more and share richer information and feedback.
Internal 4
The time reducing activities are implemented throughout the entire organization Also at design (4.00) and R&D(4.50), which are usually the last departments to implement QRM principles and therefore they score way above the average sample(3.26). Though, for design the respondents opinions related to the degree of implementation were strongly divided (1.41).
External 4 They just score a four (3.57) thanks to their high customer(s) compliance service rate (4.44). To become more mature they need to integrate even more with their supplier(s), customer(s) and user(s).
Product development
4
Employees work simultaneously from the earliest stages of product designing or engineering to meet the customers' requirements. This reduces the number of quality problems and production costs and created a faster time-to-market. To become even more flexible in the engineering/development, they should increase their degree of integrated with their suppliers and use a tool that makes it possible to make changes late in de process.
Table 5.6 Scores per theoretical construct (Bosch Scharnieren en Metaal)
53
Case three – Kaak Bakeware (Kaak Group)
Kaak Bakeware is part of the Kaak Group and is located in the Netherlands. They are classified as a SME, due
to the fact that their turnover of €10.000.000 and their number of employees (20-50) stayed below the SME
classification boundary. Kaak Bakeware is a worldwide supplier of customized trays and molds for the
production of baked goods. The product range comprises a large variety of cake tins, different types of plain
and shaped baking trays, bread pans and strapped pans. For the baker they produce in low volumes, but for
the industrial baker they produce also large volumes. Their production orientation is divided into engineer-
to-order (30%) and make-to-order (70%). Kaak Bakeware reduced their lead time already by 70 percent,
since they started with QRM in the end of 2008. Kaak Bakeware's competitive advantage is their ability to
deliver custom specific products within a short lead time. The planning horizon amounts 30 days. The stock
division and the production characteristic are respectively illustrated in Tables 5.7 and 5.8.
Finished products
Work in progress
Raw Material
20% 50% 30%
One of a kind
Small batch
Large batch
Repetitive Continuous
10% 30% 60% - -
Table. 5.7 Type of stocks (sum 100%) Table 5.8 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. The
questionnaire has been filled in by three persons (Process development engineer, Product leader and the
CEO). The average scoring difference between the three respondents amount 0.78 per question, this is
slightly above the sample's average (0.72). The lower this number is, the more the respondents agree with
each other on their given scores. Kaak Bakeware is located on the third/fourth maturity level, due to the
reasons mentioned in Table 5.9. For a more detailed overview of the scores and insights see Appendix 2.3.
Construct Score Arguments / explanation
Vision 3 There is a significant difference visible between the importance for cost (3.39) and delivery-time (4.33). Speed and reliability (4.67) are playing a more important role as key performance indicators than cost (3.72). However this vision is not shared among all the employees.
Organizational structure
4 Organizational structure is quite organic and able to react on changing environments, but to reach the highest level they should give the employees low in the organization more rights to make decision. Further the employees should become more joint specialized.
Manufacturing dynamics
3 They do not 100% utilize their capacity and they reduce set-up times and perform (preventive) maintenance. Though cellular manufacturing is implemented far below the average of the sample and they also don't see the urgency to change it.
Internal 4
The time reducing activities are implemented throughout the entire organization Also at design(4.00) and R&D(4.00), which are usually the last departments to implement QRM principles and therefore they score way above the average sample (+1.71 & +1.67). The finance department has still to make a large improvement.
External 4 The QRM principles are implemented throughout the supply chain. There is a good integration with the suppliers and customers / users.
Product development
4
Employees work simultaneously from the earliest stages of product designing or engineering to meet the customers' requirements (4.22). This reduces the number of quality problems and production costs and created a faster time-to-market. To become even more flexible in the engineering / development, Bosch should increase their degree of integrated with their suppliers and use a smarter tool that makes it possible to make changes late in de process.
Table 5.9 Scores per theoretical construct (Kaak Bakeware)
54
Case four - AS Trøndelag Industrielektronikk
AS Trøndelag Industrielektronikk is located in Norway and is a manufacturer and assembler of electronic
customized components for the electronic industry. They are classified as a SME, due to the fact that their
turnover of €9.730.000 and their number of employees (50-100) stayed below the SME classification
boundary. Their plant can be best described by ''low volume production with high product variety'' and they
have a make-to-order (MTO) production orientation. In contrast with the other cases, AS Trøndelag
Industrielektronikk indicates that they do not have implemented concepts such as lean or QRM, and they
did not achieve lead time reductions in the past. They have a long planning horizon of more or less 180
days. Nonetheless, they indicate that delivery-times as a competitive factor has the main priority to be
improved. Lead time reduction will increase their flexibility, which forms their most decisive competitive
advantage. The stock division and the production characteristic are respectively illustrated in Tables 5.10
and 5.11.
Finished products
Work in progress
Raw Material
- 50% 50%
One of a kind
Small batch
Large batch
Repetitive Continuous
5% 95% - - -
Table. 5.10 Type of stocks (sum 100%) Table 5.11 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part has been filled in by three persons (Quality Assurance, CEO and the Project leader). The average scoring
difference between the three respondents amount 0.58 per question, this is below the sample's average
(0.72). The lower this number is, the more the respondents agree with each other on their given scores. AS
Trøndelag Industrielektronikk is located on the third maturity level, because of the reasons mentioned in
Table 5.12. For a more detailed overview of the scores and insights see Appendix 2.4.
Construct Score Arguments / explanation
Vision 2 Cost and time score equal on the degree of importance (4.2), but to measure the performance they still focus more on the cost and efficiency (3.61) instead to focus the measurements on speed and reliability 3.13). Also the visions vary among the employees.
Organizational structure
4 Communication is easy and fast (4.44) and the organizational structure is flexible, but not flexible enough yet. Therefore the employees need to become more multi-functional (3.17), so that employees can fill in for each other if necessary.
Manufacturing dynamics
3 As a construct manufacturing dynamics (2.86) scores quite equal to the sample's average (2.99). But to increase their flexibility they need to improve al included elements. Especially, the process downtimes between changeovers and the capacity utilizations.
Internal 4
Within several departments (sales, purchase, finance, engineering and shop-floor) time reducing activities are actively present. However within the R&D and Design functions time reduction activities are not present. Also AS Trøndelag Industrielektronikk does not see the urgency to reduce time in the R&D and Design departments.
External 4 The QRM principles are implemented throughout the supply chain. There is a good integration with the suppliers and customers / users. Not all their suppliers have a short delivery time, but they are willing to change supplier(s) and pay more for a shorter delivery time.
Product development
1
Both the implementation (1.30) as the importance (1.30) of product development / engineering score low, this might indicate that product development does not play an important role within AS Trøndelag Industrielektronikk. (Also if we don't account this construct in the total maturity level, it will stays 3)
Table 5.12 Scores per theoretical construct (AS Trøndelag Industrielektronikk)
55
Case five - Brakel Aluminium (Brakel Group)
Brakel Aluminium is part of the Brakel Group and is located in the Netherlands. They are supplier of
customized smoke and heat control products and skylight constructions for the metal and construction
industry. They are classified as a SME, due to the fact that their turnover of €15.500.000 stays below the
SME classification boundary. Their plant can be best described by ''low volume production with high
product variety'' and they have an engineer-to-order (ETO) production orientation. In 2008 they started to
implemented concepts such as lean and QRM, which resulted already in a 50 percent lead time reduction.
Customized production and flexible solutions form the organization's most decisive competitive advantage.
Further reduction by again 50 percent of the lead times has their main priority and by realizing this they
hope to decline the total costs by 25%. The average planning horizon amounts 30 days. The production
characteristic is illustrated in Table 5.13.
One of a kind
Small batch
Large batch
Repetitive Continuous
35% 50% 15% - -
Table 5.13 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part has been filled in by four persons (CEO, Project manager, Operations manager and a Staff engineer).
The average scoring difference between the four respondents amount 0.72 per question, which is
equivalent to the sample's average (0.72). The lower this number is, the more the respondents agree with
each other on their given scores. Brakel Aluminium is located on the third maturity level, which is argued in
Table 5.14. For a more detailed overview of the scores and insights see Appendix 2.5.
Construct Score Arguments / explanation
Vision 3 There is a significant difference visible between the importance for cost(3.54) and delivery-time(4.80). Speed and reliability (4.30) are playing a more important role as key performance indicators than cost (3.04), but this vision is not shared among all the employees.
Organizational structure
4 Their organizational structure is quite flexible and therefore able to adapt to their changing environment. To become more mature, the level of multi-functional employees (3.63) should increase and therefore cross-functional training (3.58) needs to be improved as well.
Manufacturing dynamics
3 Cellular manufacturing (4.38) is implemented well, which reduce the lead times and the work on the shop-floor. Setup time reduction, (preventive) maintenance and information sharing is limited and should have the priority above the rest to be improved.
Internal 3 Time reducing activities are implemented on a low level throughout the entire organization. Except on the shop-floor, which is actively working on time reduction (4.50). With the exception of the financial department, the other departments all indicate the importance of time compression.
External 3 All the four elements have an average score of three out of five. To increase the maturity level they should improve all elements. They should give priority to the level of integration with their suppliers before starting to increase the integration level with their customers.
Product development
3 The last construct scores on an average scale. They should encourage concurrent engineering and integrate suppliers and customers to achieve further time reductions.
Table 5.14 Scores per theoretical construct (Brakel Aluminium)
56
Case six – Larsen Premium Precision Parts
Larsen Premium Precision Parts is located in the Netherlands and is technologically supplier of advanced
turning and milling work for the aerospace, semiconductor and medial industry. They are classified as a
SME, due to the fact that their turnover of €4.850.000 and their number of employees (20-50) stayed below
the SME classification boundary. Their plant can be best described by ''low volume production with high
product variety'' and they have a make-to-order (MTO) production orientation. In 2008 they started to
implemented concepts such as lean and QRM, but this did not result in any time reductions. The average
planning horizon amounts to 60 days. The production characteristic is illustrated in Table 5.15.
One of a kind
Small batch
Large batch
Repetitive Continuous
- 30% - 70% -
Table 5.15 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part has been filled in by two persons (CEO and an Intern master student). The average scoring difference
between the two respondents amount 0.83 per question, which is above the sample's average (0.72). The
lower this number is, the more the respondents agree with each other on their given scores. Larsen
Premium Precision Parts is located on the second maturity level, which is argued in Table 5.16. For a more
detailed overview of the scores and insights see Appendix 2.6.
Construct Score Arguments / explanation
Vision 2 They are aware about the power of time ( 3.70). However to measure their performance, cost (2.33) criteria still plays a bigger role than speed and reliability (1.70) criterion.
Organizational structure
2 Employees are not multi-functional (1.00) and they do not receive enough training to become multi-functional (2.33). To reach a higher level the organization must start to create a more organic organizational structure.
Manufacturing dynamics
1 Their system dynamics are cumbersome and slow. All the elements within this construct score far below the sample's average. Employees are badly involved, working with long setup times and less (preventive) maintenance are just some examples. The biggest improvement needs be made in this construct.
Internal 2
Several departments (sales, purchase, finance, engineering and shop-floor) are working a little on time reduction. On the other hand the R&D (1.00) and Design (1.00) department are not busy with time compression at al. Time reducing activities within the engineering and shop-floor departments have the main priority to be improved.
External 2 All the elements of the external construct score below the sample's average. This is due to the lack of communication with both the suppliers and customers or users. In most cases they are not willing to pay more for a shorter delivery time.
Product development
2
They are aware about the benefits of integrating their customers and suppliers, but they are not strongly integrated yet. Also are different functions not working simultaneously, which results in rework and longer lead times.
Table 5.16 Scores per theoretical construct (Larsen Premium Precision Parts)
57
Case seven - Euro-Bis Poedercoating
Euro-Bis Poedercoating is located in the Netherlands. They are classified as a SME, due to the fact that their
turnover of €1.500.000 and their number of employees (10-20) stayed below the SME classification
boundary. Euro-Bis provides services in the surface treatment (powder coating) of metal objects. Their plant
can be best described by ''low volume production with high product variety'' and they have a make-to-order
(MTO) production orientation. Euro-Bis achieved already lead time reductions (percentage unknown), since
they started with lean/QRM concepts in 2010/2011. Their competitive advantage is formed by their quality,
knowledge and quick delivery. Currently they are searching for the right balance between delivery-time
improvements and costs. The stock division and the production characteristic are respectively illustrated in
Tables 5.17 and 5.18.
Finished products
Work in progress
Raw Material
30% 33% 37%
One of a kind
Small batch
Large batch
Repetitive Continuous
- 90% 10% - -
Table. 5.17 Type of stocks (sum 100%) Table 5.18 Type of production process (sum 100%)
The location in the QRM Maturity Model is based on the output of the first part of the questionnaire. This
part has been filled in by two persons (CEO and an Intern master student). The average scoring difference
between the two respondents amount 0.88 per question, which is above the sample's average (0.72). The
lower this number is, the more the respondents agree with each other on their given scores. Euro-Bis
Poedercoating is located on the third maturity level, which is argued in Table 5.19. For a more detailed
overview of the scores and insights see Appendix 2.7.
Construct Score Arguments / explanation
Vision 3 Delivery-time plays a more important role as performance criteria than (production) cost, but the employees are not totally on the same line of time-thinking.
Organizational structure
3 Employees receive multi-functional training (3.83), but they are not highly multi-functional (2.00) yet. Also they have less space to experiment with their jobs (1.67). However at the bottom of the organization they have much authority to correct problems.
Manufacturing dynamics
3 Manufacturing dynamics just scored a three (2.55). They are aware about reducing lead times, but compared to the other constructs system dynamics needs to be improved on all elements (biggest GAP -0.79).
Internal 3 Within several departments (sales, purchase, finance, engineering and shop-floor) time reducing activities are actively present. However within the R&D and design departments time reduction activities are not present. Also does Euro-Bis not see the urgency to reduce time in the R&D and design departments.
External 3 Euro-Bis has an average relation with their suppliers and customers, but it is difficult to give an advise due to the fact that the respondents answers were varying a lot (1.24)
Product development
2
Product development has the lowest score by just scoring a two (1.53). Within Euro-bis they integrate process steps, but still on a low level. Customers are integrated into the development / engineering process on a small level, but the suppliers are not integrated at all. However they indicated also that this construct is less important for them (2.19). (Also if we don't account this construct in the total maturity level, it will stays 3)
Table 5.19 Scores per theoretical construct (Euro-Bis Poedercoating)
58
Now that we have assessed and generated insights into the QRM status of the seven cases, we can indicate
that not one of the cases reached the fifth maturity level. Case two of Bosch Scharnieren en Metaal was
coming nearby, which achieved the fourth maturity level. Next, was Kaak Bakewere which achieved a
maturity somewhere between the
third and fourth level. Variass
Electronics, Brakel Aluminium, AS
Trøndelag Industrielektronikk and
Euro-Bis Poedercoating achieved
the third maturity level. Larsen
Premium Precision Parts got no
further than the second maturity
level. None of the cases was
totally unaware about the power
of time and was located at level
one. Table 5.20 gives a clear
summary of the achieved maturity
levels achieved per theoretical
construct and it shows also the
average maturity level per
organization.
Company Constructs Maturity level Total maturity 1 2 3 4 5
Var
iass
Ele
ctro
nic
s
Vision
Level 3
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development B
osc
h
Sch
arn
iere
n
Vision
Level 4
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
Kaa
k B
ake
war
e Vision
Level 3/4
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
AS
Trø
nd
ela
g
Ind
ust
ri-
ele
ktro
nik
k
Vision
Level 3
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
Bra
kel
Alu
min
ium
Vision
Level 3
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
Lars
en
Pre
miu
m
Pre
cisi
on
Par
ts Vision
Level 2
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
Euro
-Bis
Po
ed
erc
oat
ing
Vision
Level 3
Organizational structure
Manufacturing dynamics
Internal scope
External scope
Product development
Table 5.20 Summary of the achieved maturity level per organization
59
5.2. Cross-case analysis
To analyse the multiple cases as a whole we used the cross-case analysis. We created word tables that
display the data from the seven individual cases. These tables were able to go beyond the single features of
a case and array a whole set of features on a case-by-case basis (Yin, 2009). This is insightful and improves
the understanding and explanation, and increases the generalizability of your findings (Powell, et al., 2012).
The cross-case analysis relies strongly on argumentative interpretation, not on statistic calculations (Yin,
2009). We must remark that the amount of data within each case was abundant, but the number of cases
was too limited to draw firm conclusions about the relation between (QRM) principles and the case location
in the QRM Maturity Model. Nevertheless, we came up with several relations and insights, which we are
going to present you now.
To start, for the first construct (vision) we expected (section 4.1. p29) sales and marketing people to score a
higher priority for Timely delivery, Quality and Flexibility than the operators or engineers. We expected that
operators and engineers would score a higher priority for Costs. None of the cases was filled in by a
sales/marketing person in combination with an operator/engineer, see Table 5.1. Therefore we couldn't
examine our expectation. However, recently (end of June 2012) a company out the USA (Nicolet Plastics,
Inc) filled in the questionnaire through their CEO, Finance, Engineer and Sales. This company was not
included in the multiple case analyses, because their data was received after the QRM conference
(beginning of June 2012). Nevertheless, we decided to analyze this case, because of the interesting mix of
respondents. The visions of the four respondents are illustrated in Figure 5.1. We can conclude that the
Engineer actually pays more priority to costs than Sales. Sales instead, scores relatively higher on delivery-
time, quality and flexibility as performance criteria. This conclusion is consistent with our expectations.
However, this conclusion is not firmly supported, due to the limited amount of appropriate cases.
Figure 5.1 Vision of Sales vs. Engineer (within Nicolet Plastics, 22-06-2012)
1
2
3
4
5
Cost Delivery-time Quality Flexibility
Deg
ree
of
imp
lem
enta
tio
n
Finance CEO Engineer Sales
60
For construct two, three, five and six we examined the relations between each principle with the company's
overall maturity level. For each principle we made a scatter diagram with the cases overall maturity level on
the x-axis and the cases implementation scores of the particular (QRM) principle on the y-axis. We used a
trend line ((non)linear regression) function in Office Excel's scatter diagram to calculate the coefficient of
determination (R2) for both linear and nonlinear functions (exponential, 2th order polynomial, and power).
The R2 showed us the goodness of fit of a curve with the data points. R2 ranges from zero till one, the higher
the value the better the curve fits with the data points. We used the R2 together with our own evaluation as
a criterion for whether a fit was reasonable.
The analysis between the implementation scores of each principle from the second construct
(organizational structure mentioned in section 4.2.1) with the case's overall maturity level brought several
insights. The strongest fit was found between the overall maturity level and the degree of horizontal
integration (joint specialization), see Table 5.21. Figure 5.2 clearly illustrate that the more mature the
organization the higher the degree of horizontal integration. The rest of the organizational structure
principles and their relations can be found in Appendix 3.1.
When concentrating on the results of the third construct (manufacturing dynamics) it revealed some
relations. The strongest relations were found between the overall maturity level with the level of variability
recognition and with the level of setup time reducing effort, see Table 5.22. Figure 5.3 illustrates a (linear)
relation between the degree of variability recognition and the organization's level of maturity. The more
mature the organization the more they recognize the variability as an opportunity and the more they are
able to exploit it. The other relation, Figure 5.4 shows is a (power) relation the more mature the
Principle Type of relation R2*
Level of horizontal
integration Exponential 0.843
Cross-functional training Polynomial (2) 0.833
Locus of decision-making Polynomial (2) 0.811
Level of communication Power 0.631
Nature of formalization Power 0.594
Number of layers in
hierarchy N/A N/A
Table 5.21 Relation overall maturity level with each element of the organizational structure *R2 is the degree to which a model approximates the actual data. When R2=1 model exactly the same as actual data.
Figure 5.2 (exponential) Relation maturity level & degree of horizontal integration (joint specialization)
y = 0,3047e0,7038x R² = 0,8428
1
2
3
4
5
1 2 3 4 5
Deg
ree
of
ho
rizo
nta
l in
tegr
atio
n
Level of maturity
61
organization is the more effort is put into set-up time reduction. The rest of the manufacturing dynamics
principles and their relations can be found in Appendix 3.2.
Table 5.22 Relation overall maturity level with each principle of the manufacturing dynamics
Principle Type of relation R2
Variability Linear 0.977
Setup Power 0.959
Flow Power 0.882
Capacity Utilization Linear 0.861
Employee involvement Polynomial (2) 0.854
Maintenance Power 0.726
Cellular Manufacturing Power 0.674
Information & feedback Power 0.296
Extra N/A N/A
Figure 5.3 (linear) Relation maturity level & recognition of variability
Figure 5.4 (power) Relation maturity level & setup time reduction effort
When looking closer at the results of the
''Internal scope'' (fourth construct), it tells
us that within the R&D and Design
departments, time reduction activities are
only implemented at the more mature
organizations starting at level three, see
Table 5.23.
Leve
l of
mat
uri
ty
Company R&D Design
Level 2 Larsen Premium Precision Parts
Level 3
Euro-Bis AS Trøndelag Industrielektronikk
Brakel Variass
Level 4 Kaak Bakeware Bosch Scharnieren
Table 5.23 Relation maturity level & Internal scope (R&D and Design)
y = 0,4257x1,6905 R² = 0,9589
1
2
3
4
5
1 2 3 4 5
Deg
ree
of
set-
up
tim
e re
du
ctio
n
Level of maturity
y = 1,6662x - 1,9962 R² = 0,9722
1
2
3
4
5
1 2 3 4 5
Deg
ree
of
vari
abili
ty r
eco
gnit
ion
Level of maturity
62
The fifth construct (external scope) showed one strong relation between the overall maturity level and the
customer(s) compliance service rate, see Table 5.24. Figure 5.5 illustrates a (Polynomial, 2th order) relation;
the more mature the organization the higher the customer(s) compliance service rate. The rest of the
external scope principles and their relations can be found in Appendix 3.3.
The last construct (product development / engineering) showed four weak relations, see Table 5.25. One of
those is the relation between the overall maturity level and the degree of concurrent engineering. Figure
5.6 illustrates a (Polynomial, 2th order) relation; the more mature the organization, the more employees
within the organization work together and simultaneously from the earliest stages of product development
or engineering. The rest of the product development / engineering principles and their relations can be
found in Appendix 3.4.
Principle Type of relation R2
Customer(s) compliance service rate
Polynomial (2) 0.824
Communication with supplier(s)
Polynomial (2) 0.666
Delivery-time and reliability of supplier(s)
Power 0.547
Communication with customer(s)/user(s)
Polynomial (2) 0.048
Figure 5.5 (polynomial) relation maturity level & customer(s) compliance service rate
Table 5.24 Relation overall maturity level with each principle of the external scope
Principle Type of relation R2
Concurrent engineering Polynomial (2) 0.783
Customer integration Polynomial (2) 0.730
Project management Polynomial (2) 0.665
Supplier integration Polynomial (2) 0.660
Table 5.25 Relation overall maturity level with each principle of the last construct (product development / engineering
y = -0,3869x2 + 3,3265x - 2,8692 R² = 0,8238
1
2
3
4
5
1 2 3 4 5Cu
sto
mer
(s)
com
plia
nce
ser
vice
ra
te
Level of maturity
y = 0,6484x2 - 1,9536x + 2,2403 R² = 0,7827
1
2
3
4
5
1 2 3 4 5
Deg
ree
of
con
curr
ent
engi
nee
rin
g
Level of maturity
Figure 5.6 (polynomial) Relation maturity level & Concurrent engineering
63
When referring to Table 5.26 we might conclude that low maturity levels do not enable working with small
batch sizes. Larsen Premium Precision Parts is the case which scored the lowest maturity level and has
relative low percentage (30%) of small batches and high percentage of line production (70%). Table 5.26
shows the production process characteristics of the other cases and this illustrates that most of the cases,
which are more mature, are able to work with small batch sizes or even with one of a kind production.
However, Bosch Scharnieren en Metaal, who is rather mature, works mostly with small batches (60%), but
also with repetitive production (25%). So, we might consider there is a relation between the level of
maturity and type of production process, but we cannot form a strong conclusion.
Leve
l of
mat
uri
ty
Company One of a kind
Small batch Large batch Repetitive production
Continuous
Level 2 Larsen Premium Precision Parts
- 30% - 70% -
Level 3
Euro-Bis - 90% 10% - - AS Trøndelag Industrielektronikk
5% 95% - - -
Brakel 35% 50% 15% - - Variass 10% 65% 20% 5% -
Level 4 Kaak Bakeware 10% 30% 60% - Bosch Scharnieren 15% 60% - 25% -
Table 5.26 Relation maturity level & types of production processes (per company the sum of percentage counts 100)
Further, after analyzing the gaps between the degree of implementation and importance of all (QRM)
elements, we generated insights in the (QRM) elements that require (urgent) improvements. Table 5.27,
illustrates the average gap size for each particular construct and their elements. The average cap sizes are
based on the first seven cases of Table 5.1. The numbers in Table 5.27 tells us that from the constructs
''manufacturing dynamics'' require the highest priority for further improvement. When looking to the
elements, the top three of elements that require the most urgent action for future improvements are:
1. Supplier integration within the product development / engineering (-1.49)
2. Set-up time reduction (-1.27)
3. Employee involvement (-1.19)
64
Constructs / Elements GAP (implementation – important)
Constructs / Elements GAP (implementation – important)
Vision -0.14 Internal scope -0.55
Cost -0.35 Sales -0.76
Time -0.68 Purchase -0.69
Flexibility -0.30 Finance -0.64
Quality -0.44 Engineering -0.86
Shop-floor -0.88
Design -0.62
R&D -0.55
Organizational structure -0.44 External scope -0.58
Locus of decision-making -0.68 Delivery-time and reliability of supplier(s) -0.66
Nature of formalization -0.65 Communication with supplier(s) -0.47
Number of layers in hierarchy 0.33 Communication with customer(s)/user(s) -0.62
Level of communication -0.37 Customer(s) compliance service rate -0.58
Level of horizontal integration -0.74 Cross-functional training -0.52
Manufacturing dynamics -0.85 Product development / engineering -0.54
Employee involvement -1.19 Concurrent engineering -0.58
Setup -1.27 Customer integration -0.49
Cellular manufacturing -0.47 Supplier integration -1.48
Maintenance -0.70 Project management -0.68 Information and feedback -1.00 Flow -0.54 Capacity utilization -0.79 Variability -1.00
Extra -0.60
Table 5.27 Average gap sizes from the seven cases
Lastly, in section 4.2.2 we expected that companies that are characterized by ''high volume production, low
product variety'' or make-to-stock (MTS) will score relative low on the importance of the QRM principles.
We cannot confirm neither deny this expectation, because of limited data. From all the cases including the
most recent once, there was no case that could be characterized by ''high volume production, low product
variety''. Hence, there was one company that could be characterized by MTS (Blizzard Sport), see Table 5.1.
Contrary to our expectations, the MTS organization scored relatively high on the importance for the QRM
principles, see Appendix 2.8. This is might be explained by the fact, that the organization works with a high
volume production and low product variety and they mentioned the need to change from a MTS to a MTO
production to become more flexible.
65
6. Discussion In this section we discuss the results of the previous section and evaluate the in chapter three proposed
QRM Maturity Model. The discussion includes also the project limitations and proposals for further
research. We stated that from an academic perspective, the QRM Maturity Model should generate both
insights in what SMEs have implemented to increase their quickness of response and insights into their
priorities in setting the next step towards a more quickly responding organization.
From a practical standpoint, we stated the QRM Maturity Model should be simple and useful for companies
to assess themselves on their degree of response quickness. The results of the self-assessment should
provide organizations understanding of the evolution of becoming a more quick responding company, by
providing guidance on how to move towards a more mature quick responding organization.
We will now start to discuss, whether the QRM Maturity Model has achieved its predefined goals.
First, we can state that the studied cases generated (new) insights in what SMEs have achieved till
so far with regard to their level of quick response. During the data collection multiple persons per company
scored (QRM) elements on a degree of implementation, which resulted in abundance of objective data.
Since we have divided the (QRM) elements in six focused areas, it was less complex to understand and
explain the scores of the elements. The Annexes 2.1, 2.2, 2.3, 2.4, 2.5, 2.6 and 2.7 illustrate for each case in
a clear way the current status per focused area, by using simple informative figures and diagrams. The
detailed insights into the status of each focused area, resulted in a better understanding of the status of the
organizations as a whole.
Within the multiple-case study none of the seven cases was totally unaware about the power of time (level
one), but also none of the cases was totally aware about the power of time (level five), see Table 5.20. Just
one case reached the fourth maturity level. Most of the companies (five cases) are located at the third level
and only one case scored a second maturity level. The most mature case distinguished itself from the less
mature case by having first of all a more organic organizational structure, which made them more flexible to
react on unexpected changes. For example the workers at the mature case were more multi-functional than
the immature case and were able to fill in for each other if necessary. Figure 5.2 clearly illustrates ths
(exponential) relation between the level of maturity and the degree of horizontal integration. Secondly, the
mature case had a more agile and dynamic system, which was partly due to a higher degree of variability
recognition as a strategic advantage, shorter set-up times and the use of smaller batch sizes. The Figures 5.3
and 5.4 from the results section clearly illustrates the relation between the level of maturity and degree of
66
variability recognition and set-up time reduction. With regard to the batch sizes Table 5.26 illustrates that
the high mature case was using relatively smaller batch sizes than the low mature case. Thirdly, actions to
reduce lead times were deeper penetrated throughout the entire enterprise. In contrast to the low maturity
case, the high mature case even implemented time reduction efforts in the R&D and Design departments,
see Table 5.23. Further, the mature case had a higher customer(s) compliance service rate, see Figure 5.5.
Lastly, their time-to-market was quicker, since process steps were relatively more combined and performed
simultaneously (Figure 5.6).
We can conclude that most of these differences per focused area between the mature and immature case
were strongly consistent with the theoretical construct descriptions of section 3.1.
Companies scored the (QRM) elements also on a degree of importance. These gave insight into the
company’s degree of importance for particular ''focused areas'' or, in more detail, for each (QRM) element.
After analyzing the difference between the degree of implementation and importance (GAP analysis) we
created understanding into the companies priorities for future improvements. The Annexes 2.1, 2.2, 2.3,
2.4, 2.5, 2.6 and 2.7 clearly illustrate the gaps for each case. Table 5.27 of the results section shows the
results of the average GAP sizes. It tells us on an average base which focused area, or in more detail which
(QRM) element, had the greatest priority to get improved. When comparing the focused areas,
''Manufacturing dynamics'' claim the most priority for improvements. So, the companies indicate that they
want to become more agile and fast regarding to their system dynamics. If we look in more detail on
element level, it tells us that the top three of elements that require the most urgent action for future
improvements are:
1. Supplier integration within the product development / engineering
2. Set-up time reduction
3. Employee involvement
The first element, ''supplier integration'' refers to the company’s need for higher degree of integration with
their suppliers, with regard to the development and/or engineering of a (new) product. According to
Nicholas (2008) supplier integration is quite important and will lead to lower lead times, lower costs and
higher quality. The second and third most urgent elements are both part of the most urgent focused area
''Manufacturing dynamics''. Companies showed their need for shorter downtimes between changeovers in
return for an increase of flexibility and quickness of response to changing customer’s needs. This is
interesting, because there is also a strong relation between the overall maturity level and the degree of
setup time reducing effort (Figure 5.40). Further, to quickly solve problems (e.g. long set-up times) and
response on customers requests, it’s important for companies to involve their employees. Koufteros et al
67
(1998) agrees with the high priority on employee involvement and mentioned that involvement is an
antecedent to reengineering setups, cellular manufacturing, preventive maintenance, quality improvement
efforts, dependable suppliers, and pull production.
Further, the QRM Maturity Model has proven its functionality as a simple and useful self-
assessment tool to determine the current degree of response quickness. The questionnaire is accessible
via the website of the European QRM Center and is available in at least for languages (English, Spanish,
German and Dutch). The respondents did not experience problems with answering each question on two
Five-point Likert scales. Though, some companies (Larsen Premium Precision Parts, Bosch Scharnieren en
Metaal and Variass Electronics) experienced the questionnaire as long, but they also indicated that
shortening the questionnaire might probably decrease the quality of the output. We recognize this
feedback, but we had to find the right balance between a simple questionnaire and the complex reality of
identifying the maturity level of the entire system. Therefore we couldn’t reduce the amount of questions.
Though with closed-questions and with predefined answer options, we made it easier and less time
consuming to fill in the questionnaire. Even AS Trøndelag Industrielektronikk, which was the only case that
indicated that concepts such as lean or QRM were not implemented within their organization, could be
located in the QRM Maturity Model. This indicates that also companies that are unfamiliar with the QRM
concept, but work unnoticed according to the (QRM) principles, can be accessed by the QRM Maturity
Model and receive guidance towards a more quick responding organization.
With the aim to make the abundance of data understandable for the companies and ourselves, the outputs
of the questionnaires were automatically transformed into the tables and figures (for example see Appendix
2.1). Also the determination of the maturity levels was fully automated in order to avoid the intervention of
a third person. The formula to automatically identify the maturity levels was tested on its reliability by two
pilot companies (Larsen Premium Precision Parts and Bosch Scharnieren en Metaal). In advance assigned
scores, based on experience of local employees and external QRM experts, were proven to be consistent
with the outcome of the designed formula.
Lastly it can be stated that besides the fact that the QRM Maturity Model was able to determine a
company’s current status, it was also capable to identify opportunities for improvements and serve as a
guide towards a more mature quick responding organization. In the near future, participating companies
will receive a customized report with their results; see for a sample customized report Appendix 1. To
provide a better understanding the results will be divided among the seven focused areas and will be
visualized into gap-analysis (urgency matrices section 4.1), which also indicates the degree of urgency for
68
each improvement opportunity. Also the companies will be able to benchmark their results, which will
generate a better understanding of the results. The tested companies (Larsen Premium Precision Parts and
Bosch Scharnieren en Metaal) showed serious interest after seeing a draft version of their customized
report. Some companies even mentioned to repeat the assessment once in a well to measure their
improvements and to identify if they are on the right road to a more quickly responding organization. Also
during a presentation of the QRM Maturity Model at the first European QRM conference we received many
positive comments from companies as well as from consultancies.
Limitations & Further research
There are still some limitations. First, due to the limited amount of data we cannot guarantee a hundred
percent accuracy of the QRM Maturity Model. More data from companies is required to be able to
statistically analyze the correlation between the questions of the questionnaire and the allocated scores.
For further research it might be interesting to examine the accuracy of the QRM Maturity model in more
detail and study the feasibility of assigning any weights to particular elements that earn a larger influence
rate on the maturity score.
Second limitation; we were not strict enough towards companies, with regard to the selection of their
respondents. To test our expectations with regard to the difference in vision between the sales and the
engineers, the number of financial or sales respondents was too limited to make a strong conclusion.
Further, we risked that only the "fans" of QRM took the time to fill in the questionnaire. The exclusion of
the haters of QRM concept might have negatively influenced the objectivity of the questionnaire’s output.
Third limitation; we still need a third person to build a customized report for the companies. This is in
contrast with our ultimate goal that companies complete the questionnaire on the website of the QRM
center and then immediately receive their customized report. Furthermore, a central database available for
the QRM Center and its knowledge partners is still lacking.
Lastly, we had some limitations with regard to the customized report. Due to a limited amount of
companies it was not possible to benchmark between industrial sectors, countries or other categories.
Another limitation was the fact that we cannot guarantee whether the steering function of the customized
report works in practice. Because we did not had the opportunity to examine any company that used our
customized report as a guide toward a more mature quick responding organization. For further research it
might be interesting to study the functionality of the customized report as guide and when necessary
optimize the guidance function to avoid that it leads companies into the wrong direction.
69
7. Conclusion We can conclude by stating that the QRM Maturity Model forms a major win-win-win contribution between
academia, companies and education.
For the academia, the QRM Maturity Model and its cases generated (new) insights into the SMEs and their
current implementation rates of QRM principles and their priorities. Also, more understanding is generated
among the relations between the QRM principles and a company's location in the QRM Maturity Model.
These (new) insights developed by the academia will become accessible for the industry, which will put it
into practice. Putting practice into theory and theory into practice forms a wining situation of continuously
generation of (new) insights.
Our experience with the industry tells us, that firms are enthusiastic about the possibility to self-assess their
organization. The companies stated they are interested in the results of their customized report, which they
can use as a guide for their future improvements. The companies are also thinking to repeat the assessment
once in a while to assess their progress in achieving a state of quickly response. Also the European QRM
Center was enthusiastic and wants to continue with the project. We are proud to mention that the QRM
Maturity Model is still accessible via the official European QRM website. Though, for further research the
QRM Maturity Model and the customized report should be statistically tested and improved in order to
avoid misleading results.
Last but not least the research established cooperation between knowledge centers, which are specialized
in the QRM concept (University of Groningen, Leuven, Madison, Universitat Politecnica de Catalunya and
HAN University of Applied Sciences). Which resulted in the benefits of enhances mutual exchange of (QRM)
knowledge.
70
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