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Variety Management in Manufacturing. Proceedings of the 47th CIRP Conference on Manufacturing Systems
Evaluation of Complexity Management Systems – Systematical and Maturity-Based Approach Andreas Klutha*, Jens Jägera, Anja Schatza, Thomas Bauernhansla,b a
Fraunhofer Institute for Manufacturing Engineering and Automation - IPA, Nobelstraße 12, 70569 Stuttgart, Germany b Institute of Industrial Manufacturing and Management – IFF, University of Stuttgart Nobelstraße 12, 70569 Stuttgart, Germany
* Corresponding author. Tel.: +49-711-970-1942; fax: +49-711-970-1927. E-mail address:
[email protected].
Abstract The way to deal with the strongly increasing complexity of the company itself and its environment has become a key competitive factor. The complexity within a production company is characterized by the challenges encountered in daily business processes and can be described by the four dimensions of complexity: variety, heterogeneity, dynamics and non- transparency, as well as their interrelationships. Despite this increasing importance, only few companies have access to adequate tools for complexity management. Most companies have not introduced or implemented yet a complexity management system/approach or they do not know, if the used complexity management methods are efficient and adequate. Therefore, the question rises: How can a company be reviewed and evaluated regarding its complexity management skills? Maturity models can be used to support the analysis and assessment of skills and development-levels of products, processes or organizations by defining different levels of maturity, in order to assess the extent to which an object fulfills defined qualitative requirements. The various levels of maturity within such models can be used to describe the different achievable skill levels. Maturity models not only include methods for the assessment of skill levels, but also provide incentives and measures to increase the degree of maturity. After the introduction of measures to increase the skill level of maturity these models are also suitable to measure and evaluate the progress made. This paper presents an approach for an evaluation model of complexity management systems. First, the basics of the so-called advanced Complexity Management are given, highlighting the difference between complexity and complicacy as well as the comparing external and internal complexity. The fields and dimensions of complexity are presented as well. After that, maturity models fundamentals are presented by showing state-of-the-art maturity model approaches. Furthermore, the overall maturity-based approach for evaluation of complexity management systems, especially the maturity of their functionalities and capabilities regarding the needs and purposes of manufacturing enterprises, is presented by adapting and combining existing methods and models. The maturity-based approach describes different levels of complexity management systems within a production company, also taking into account recommendations and measures to increase the degree of maturity.
© 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license © 2014 The Authors. Published by Elsevier B.V. (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the International Scientific Committee of “The 47th CIRP Conference on Manufacturing Selection and responsibility of the Hoda International Scientific Committee of “The 47th CIRP Conference on Systems” in thepeer-review person of theunder Conference Chair Professor ElMaraghy. Manufacturing Systems” in the person of the Conference Chair Professor Hoda ElMaraghy” Keywords: Complexity management, Evaluation, Maturity Model
1. Introduction and problem statement The trend of increasing digitalization and current developments towards the so-called fourth industrial
revolution show that - in the near future - an enormous flexibility and adaptability of companies will be required [1]. The corresponding significant increase of complexity is already perceived by industrial companies worldwide. The way of dealing with the strongly increasing complexity of
2212-8271 © 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the International Scientific Committee of “The 47th CIRP Conference on Manufacturing Systems” in the person of the Conference Chair Professor Hoda ElMaraghy” doi:10.1016/j.procir.2014.01.083
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both the company itself and its environment has become a key competitive factor [2]. In order to face complex problems or complex situations in general, humans have usually various options. The simplest way is to use so-called “trial and error”, which means try one solution and if this does not solve the problem, try the next solution. Another simple option is to fade out the complex problem. Both options are no learning strategies and do not lead to suitable solutions. More successful strategies for identifying and quantifying complexity are “intuitive review” (reduction of complexity by pattern creation on the basis of acquired knowledge and using diversity of knowledge from heterogeneous groups), “rational understanding” (understanding in detail by prioritizing the level of detail in terms of 80/20 rule), as well as “focussing on individual factors” (trivialization by dividing the main complex problem into single minor problems). Therefore, also industrial companies have to consider different complexity issues and strategies. Today´s companies can face the progressively increasing external complexity in global markets with an appropriate "healthy" internal complexity [3]. The complexity within the company is embossed by difficulties encountered in daily business processes (e.g. number of products, variety of production processes, short-term customer change requests, unclear workflow, etc.) and can be described by the four dimensions of complexity: variety, heterogeneity, dynamics and non-transparency, as well as their interrelationships. Internal complexity can occur in different ways. If sales targets cannot be achieved due to "exotic" customer requirements, new product variants will be developed and produced, leading to an increasing product-complexity. Based on that, the interconnected process- and also organizationcomplexity will also increase. This interrelationship will lead to a higher cost-level [4]. Current complexity management approaches are mostly focused on the complexity of products and especially on product modularization and variant management. The meaning of ideal complexity, of product profitability in terms of product complexity related to complexity in process and organization is mostly ignored. Based on an empirical study “advanced Complexity Management – the new management discipline” performed in 2013 by the Fraunhofer Institute for Manufacturing Engineering and Automation IPA in Stuttgart, 82% of the respondents (n=158) appraise, that the overall topic of complexity will gain in importance [5] . Despite this increasing importance, only few companies have access to adequate tools for complexity management [2].
Availableness of met hods and t ools t o syst emat ically assess and evaluat e complexit y Percent age dist ribut ion
16% complet e methods
4%
largely suit able met hods
exist ing 28%
12%
part ial suit able meht ods
Part ially exist ing
28%
marginal suit able…
56%
19% 0%
Not exist ing
37%
no exist ing met hods 10%
20%
30%
40%
Fig. 1: Availability of methods and tools to systematically assess and evaluate complexity [5]
Only 16% of the consulted companies state, that they have suitable methods or tools to systematically assess and evaluate complexity (see Fig. 1). Most companies have not introduced or implemented a complexity management system/approach yet or they do not know, if the used complexity management methods are efficient and adequate. Therefore, the question rises, how can a company be reviewed and evaluated regarding its complexity management skills? 2. Advanced Complexity Management What is the right level of complexity in order to be successful on the market and react optimally to external complexity? In order to answer this essential question, strategies of advanced Complexity Management can be applied. In this overall context, advanced Complexity Management is the target-oriented and value-added utilization of available resources in order to hamronize internal and external complexity, using appropriate manipulating, coping or pricing strategies. 2.1. Complicacy vs. complexity When dealing with complex problems and situations, and before developing specific strategies, it is important to distinguish between several terms, which are often used in the same content, although they have different meanings and definitions. In this case the terms complicacy and complexity are often used in the same way [6]. Nevertheless each term and definition has specific characteristics and different meanings (see Table 1). Table 1: Comparison complicacy vs. complexity
Complicacy
Complexity
- Causal interrelationships
- Surprising interrelationships
- Calculable and predictable
- Not calculable and not predictable
- Controllable - Objectively describable - Characterized by just the two dimensions variety and heterogeneity
- Not controllable, just observable and influenceable - Subjectively perceptible - Characterized by all dimensions, including dynamics and nontransparency
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As presented in Table 1 complicated issues can be described and controlled by causal interrelationships between the corresponding objects. Contrary to that, complex issues and problems cannot be predicted or controlled in that context, because such problems also include non-causal, but surprising interrelationships. Therefore complex issues just can be influenced or manipulated in certain ways. The main difference between complicacy and complexity is the characterization by so called dimensions of complexity (see chapter 2.3). Complicated issues are described just by the two dimensions variety and heterogeneity [7], whereas complex issues include also the dimensions dynamics and non-transparency [8]. That means, as soon as dynamic aspects or factors concerning non-transparency are involved, the problem/issue is related to complexity. Although there is no academic consensus about a consistent definition, within this paper it can be summarized, that complexity can be seen as the combination of a various, heterogenic system elements and their interrelationships that are changing dynamically and not clearly comprehensibly. 2.2. External vs. internal complexity The complexity of the external system environment can only be met with an equally strong internal system complexity [3]. External complexity describes the market perspective, which is characterized by so-called changeability and flexibility drivers (e.g. population growth and demographic change, increasing consumption of resources or digitalization). Internal complexity describes the company`s perspective, which is characterized by the complexity fields and the occurrence of complexity dimensions. Internal complexity is influenceable directly and cannot be considered isolated, because - as stated before - it inevitably has to be adapted to the external complexity demanded by the market [3]. Internal complexity is exactly ideal when it counters the external complexity equivalently [9]. If internal complexity is too low, external complexity cannot be coped sufficiently. The complexity management in the company is, therefore, not effective. If internal complexity is too high, the company thus has unnecessary efforts and the complexity management in the company is not efficient [8]. Complexity Dimensions
Ext ernal Com plexit y Drivers
Fields of Com plexit y Variety Heterogeneity Dynamics
Process
Product
Organisation
2.3. Fields and dimensions of advanced Complexity Management A first step to identify internal complexity and to improve its transparency is the systematic subdivision into complexity fields. These are those divisions in which complexity arises [10], such as order-processing, production network, productportfolio or the IT system landscape (see Fig. 2). The complexity fields are used to analyze and structure the existing internal complexity of a company. Internal complexity can be described by the three main complexity fields product (including services), processes and organization. These main fields can be further subdivided into more specified fields as shown in Fig. 2. Each complexity field has its own complexity, but in order to describe the overall internal complexity of the company, the existing interrelationships and interdependencies between the single complexity fields have to be considered as well. Complexity can in principle refer to elements of a system or their interrelationships. As mentioned before, internal complexity (company perspective) can be described in general by the four dimensions of complexity: variety, heterogeneity, dynamics and non-transparency. Variety describes the number of distinguishable states and configurations / distinguishable elements and relations of a system. Heterogeneity describes the diversity of the system`s elements and the divergence of their interrelations. The complexity dimension dynamics describes the changeability over time as well as possible turbulence effects of the system. Non-transparency is characterized by the knowledge about the system and its interdependencies in terms of lack of definitions or fuzziness. The less a company knows about the overall system, the higher is the non-transparency. In general it can be stated that higher degrees of each single dimension lead to an increasing complexity of the overall system. 2.4. Strategies of advanced Complexity Management In order to react on existing complexity within the mentioned complexity fields, different strategies were developed and can be applied. These strategies can aim either at manipulating the complexity or at coping with the existing complexity. Within this context five different strategies of advanced Complexity Management can be distinguished: x
Avoiding complexity
x
Reducing complexity
Technologies
Cust om erport f olio
Net w ork
x
Generating of complexity
Order processing
Product port f olio
Product ion
x
Dealing with complexity
x
Pricing complexity
IT-Syst em s
M at erials
NonͲTransparency
Personnel
M arket s
Fig. 2: Complexity fields and complexity dimensions
The avoiding of complexity follows the approach of prophylactic prevention of the emergence of complexity. The reappearance of over-complexity has to be prevented by proactive use of instruments. These include, for example, the modularization or standardization of products, processes or organizational structures [8].
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Complexity reduction is about to reduce identified existing complexity target-oriented. This can be achieved by the reduction of variety and heterogeneity, this means by the simplifications in the various fields of complexity. This includes, for example, the elimination of unprofitable product variants, the reduction of non-value added process steps, as well as the reduction of interfaces, both on the side of the ITsystems as well as from an organizational perspective [8]. Also specific resetting mechanisms can be used, in order to reduce complexity and to restore the desired state of operation of a system [11]. As described before, in some cases internal complexity within the company is lower than the corresponding external complexity on the market (internal complexity is not effective). Therefore, the generation of complexity is needed to increase and to adjust the internal complexity of the company. For example, if a company produces products with low complexity, which are not “state-of-the-art” in terms of market demands, then these products are not marketable. The dealing with complexity is aiming at the efficient coping with unavoidable internal complexity. This includes the adaptation of organizational structures, the increase of transparency in order processing or transformation of the process interfaces [8]. Pricing of complexity describes the reasonable pricing of products and complexity. Companies have to analyze with what products they make money and with what products they lose money. After it is identified, which complexity affects enhancing / lowering in terms of profitability and which complexity promotes / disables the asset management, companies can allocate this arising complexity to their product prices for example, if customers are willing to pay for that. This is not always suitable and easy to implement.
depending on the model, different stages of "maturity" of business processes are described." [17] "Maturity models are using a staging system, which represents the performance of a specific area of a company. These stages are pre-defined by the maturity model." [18] In literature as well as in practice different existing maturity models have been established in different fields of application: x
Maturity models in the fields of project- and process management;
x
Models based on quality management and tools from the field of (SW) development;
x
Maturity analysis models to check status of business processes.
The most prevalent approach for measuring the maturity level is the Capability Maturity Model (CMM) of the Software Engineering Institute (SEI) of Carnegie Mellon University [19]. The Capability Maturity Model is the oldest and best known model applied for the improvement of software processes. Its five-step evaluation scheme was originally intended to evaluate the quality of software processes of software suppliers of the U.S. Department of Defense [20]. The maturity levels of CMM are used as an indicator for the capability of an organization in terms of developing and providing software with the required quality and financial requirements within specified time frames [21]. In subsequent years this model has been enhanced and several upgraded versions were released. Finally the successor model, the Capability Maturity Model Integration (CMMI) was developed. The CMMI consists of five basic different maturity levels (see Fig. 3). 5
3. Maturity models fundamentals
Optimizing 4
Maturity models are based on the assessment of competency objects aiming at consistent and verifiable statements about these objects` status and quality of their execution. Frequently used objects are organizations and their processes [12, 13, 14]. Over the past years different maturity models have been used in different fields of application. The different levels/stages of maturity within such existing models are used to describe the different achievable skill levels. Therefore, on the one hand maturity models include methods for the assessment of skill levels, on the other hand they provide measures to increase the degree of maturity from one level to the next one. After the introduction of such measures in order to increase the maturity level, these models are also suitable for measuring and evaluating the progress made [15]. Maturity models can be used for different purposes. Maturity models may be limited to a competency measurement or can be part of a skills analysis. Additionally they can provide information about causes of the maturity level deficits or can propose instructions for solutions to improve the maturity level [16]. Different definitions of maturity models can be mentioned: "A maturity model is a (simplified) representation of reality to measure the quality of business processes. Here,
3
Quantitatively Managed
Focusoncontinuous process improvement
Process measured and controlled
Process characterized for organizations and is often proactive Process characterized for projects and is often reactive
Defined 2
Managed 1
Initial
Process unpredictable, poorly controlled and reactive
Fig. 3: CMMI maturity levels [22]
In CMMI several previous models with the same basic ideas and goals, but different in structure and field of application, are integrated. The main fields of application of the CMMI Model are [23]: x
Software Engineering
x
System Engineering
x
Integrated Process and Product Development
Another validation model is the so called EFQM Business Excellence Model, which is not a classic maturity model, but often used as a basis. EFQM stands for European Foundation for Quality Management and describes the merger leading
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from the top European companies with the aim of developing and providing its own model to increase their competitiveness in global markets [24]. The EFQM Business Excellence Model is a model for the integrated quality management and it is based on the simultaneous consideration of people, processes and outcomes. It consists of three main pillars of leadership, processes, and business results and is supplemented by specific implementation areas (people, policy and strategy, resources, etc.). In addition to the three main pillars and their subdivisions, that are individually highlighted and weighted in relation to the overall model, the EFQM Model is divided into the areas of enablers and results. All input factors, which are used to achieve the desired results, can be seen as enablers [24]. If the EFQM Business Excellence Model will be compared to the former described CMMI model, then the commonality of definition and improvement of processes is visible. The other aspects of the EFQM Model are only considered rudimentary in the CMMI model [23]. Another Model is the so called SPICE (Software Process Improvement and Capability Determination), the international standard for process evaluation [25]. It was initiated in 1993 In order to support the development and validation of a practical international standard for software process improvement. The initial versions focused exclusively on software development processes. In later versions, it was enhanced to cover all processes related to software life cycle, project management, configuration management and quality assurance [26]. The approach of the SPICE Model can be used for process improvement as well as for capability determination [27]. The SPICE model enables organizations to use the standard for process capability determination mode, process improvement mode and self-assessment mode [28]. As other international standards and models, SPICE takes into account the evaluation of the capability, effectiveness and quality of processes and organizations. 4. Overall maturity based approach for evaluation of complexity management systems The following approach is based on the assumption that predictable patterns exist in the development of complexity skills. These development patterns are conceptualized as evolutionary stages or levels and represent the mutually defined maturity levels. The maturity implies evolutionary progress in demonstrating specific skills or achieving targets, from an initial state where few skills regarding complexity management are considered, to a final state, which is complete, optimizing the company`s resources to achieve the goals of harmonizing internal and external complexity [29]. Each level describes different degrees of maturity regarding the complexity management system. Each maturity level is defined by specific characteristics and also predefined requirements that are necessary to achieve the next level of maturity. In general, it can be assumed that a higher degree of maturity shows a better expression of the rated processes and thus the underlying complexity management capabilities. This approach follows the basic structure of CMMI and has a total of seven maturity levels (see Fig. 4):
6 5 4 3 2 1 0
Harmonized (internal and external complexity are harmonised)
Managed (measures are defined and initialized)
Analyzed (complexity patterns are generated)
Quantitativ (quantitativKPIsare elaborated)
Qualitativ (complexity qualitatively evaluated)
Defined (complexity fields are defined)
Initial (no complexity understanding)
Fig. 4: Maturity levels for advanced Complexity Management systems
0) Initial: No understanding of complexity The company has not yet concerned or recognized any complexity problems or strategies 1) Defined: Complexity fields are defined The company has identified external complexity drivers and has defined the internal complexity fields. 2) Qualitative: Complexity is qualitatively evaluated The company uses methods to evaluate existing complexity within the different complexity fields in a qualitative way. 3) Quantitative: Quantitative KPIs are elaborated The company has elaborated specified Key Performance Indicators (KPI), in order to quantify the existing complexity in terms of the four complexity dimensions. 4) Analyzed: Complexity patterns are generated The company has analyzed the existing internal complexity and generated so-called complexity patterns by detailed analysis of the complexity fields and dimensions based on the correlation of specific, selected indicators. 5) Managed: Measures are defined and initialized The company has defined and initialized specific complexity cultivation strategies in order to adapt or master the existing internal complexity. 6) Harmonized: Internal and external complexity are harmonized The company has optimized their internal complexity according to the external complexity on the market and the company is able to dynamically adapt and adjust it permanently. Each defined maturity level as part of the advanced Complexity Managemet addresses deficits in existing complexity management approaches: General complexity fields are known, but not defined in more depth and formulated in detail. Various evaluation approaches exist, but generally related to product complexity. Specific measurement of complexity is rather rare. Mostly the cost considerations are in focus. Usually only general strategies (avoidance, reduction) are used, but no combinations or new strategies are introduced. There are no concrete approaches to measure external complexity.
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The determination of the maturity level will be carried out by using assessment methods. For this purpose, the predefined requirements and characteristics will be analyzed and validated (e.g. by means of questionnaires, checklists, and rules for its application). The assessment provides a condition record of the status of the complexity management situation. Based on that actual status determined by the assessment, finally suggestions and recommendations for improvement can be derived. These recommendations aim at improving the current status and to achieve the next level of maturity. 5. Conclusion and future work This paper presents the foundations and the first steps aiming at the development of a scalable maturity based approach for the evaluation of complexity management systems for industrial companies. The basics of the so-called advanced Complexity Management are given, highlighting the difference between complexity and complicacy as well as comparing external and internal complexity. The fields and dimensions of complexity are presented as well. Maturity models for the purposes of evaluation issues have several benefits such as finding vulnerabilities and identification of improvement measures, a better control over costs and time or an earlier and more accurate predictable release and introduction of complexity management activities. Further, the companies get the capability for self-assessments and comparison with other companies by getting transparency of the organizational, technical and operational status as well as the early identification of deviations from targets and risks. As work on the maturity model is still ongoing, this paper focuses on the foundations and the procedure for evaluation of complexity management. The definition of the different maturity and capability levels is still in progress and will be presented at a later stage. Also, specific examples of fields of application, implementation aspects (best practices) or requirements will be addressed in future work. After the maturity model has been defined and the evaluation criteria have been set, an instrument to measure the maturity as well as suitable strategies for the increase of the maturity will be developed. References [1] Bauernhansl, T.: Industry 4.0: Challenges and limitations in production: Keynote. In: A.T.Kearney: The Factory of the Year 2013: Global Excellence in Operations; Meet the best at the Congress for competition; Leipzig, 18th-19th February 2013.Süddeutscher Verlag, Landsberg 2013 [2] Shey, V.; Roesgen, R.: Mastering Complexity. In: Packowski, J.; Kotlik, L. (Pb.): Focus Topic Paper. Camelot Management Consultants AG, 2012 [3] Asby, W. R.: An introduction to Cybernetics. 5. Aufl., Champman & Hall Verlag, London 1970 [4] Wildemann, H.: Complexity management in sales, procurement, product development and production. 13 Ed, TCW Transfer Center for Logistics and Production Technology Management GmbH&Co. KG, Munich 2012 [5] Bauernhansl, T.: Fraunhofer IPA. Advanced Complexity Management – The new management discipline. Empirical study performed in 2013, Stuttgart 2014 [6] ElMaraghy, W., ElMaraghy, H., Tomiyama, T., Monostori, L.: Complexity in engineering design and manufacturing. CIRP Annals Manufacturing Technology 61; 2012. p. 793–814.
[7] Denk, R.; Pfneissl, T.: Complexity Management. Linde Verlag, Vienna, 2009. [8] Jäger, J.; Kluth, A.; Sauer, M.; Schatz, A.: Advanced Complexity Management – The new management discipline in production and Supply Chain. In: ZWF Journal of economic Factory Operation: 108 (2013), No.5, pp.341-343 [9] Kappelhoff, P.: Complexity theory: a new paradigm for management research? In: Schreyögg, G.; Conrad, P. (ed.): Theories of management, Management Research 12: Theories of management. 1 Edition, Gabler Verlag, Wiesbaden 2002 [10] Scheiter, S.; Scheel, O.; Klink, G.: How much does complexity really cost? In DAX companies slumber EBIT reserves of more than 30 Billion euros. A.T. Kearney, 2007 [11] Meselhy, K. T., ElMaraghy, W. H., & ElMaraghy, H. A. (2010). A periodicity metric for assessing maintenance strategies. CIRP Journal of Manufacturing Science and Technology, 3(2), 135-141. [12]de Bruin, T.; Rosemann, M.; Freeze, R.; Kulkarni, U.:, Understanding the main phases of developing a maturity assessment model. In: Proceedings of the 16th Australasian Conference on Information Systems (ACIS). Sydney, 2005. [13] Mettler, T.: A Design Science Research Perspective on Maturity Models in Information Systems. Work Report of the Institute of computer science, Nr. BE IWI/HNE/03, University of St. Gallen. [14] Mettler T., Rohner P.: Situational Maturity Models as Instrumental Artifacts for Organizational Design. In: Proceedings of the DESRIST'09. [15] Wochinger, T.; Münzberg, B.; Kennemann, M.: To review the quality of the production logistics maturity oriented. In: ZWF Journal of economic Factory Operation. 105, 2010, Nr. 3, pp. 222-226. [16] Ahlemann, F.; Schroeder, C.; Teuteberg, F.: Competence and maturity models for project management: foundations, comparison and use. ISPRI Working Report, Nr. 01/2005 [17] Fritz, P.: Maturity models in process management. In: Jahooda - The platform for project and process management. Available at: http://www.jahooda.org/reifegradmodelle-im-prozessmanagement-888/ (2013-11-03) [18] Bürgin, C.: Maturity model for the control of the innovation system of enterprises. Dissertation, Swiss Federal Institute of Technology ETH Zürich, Nr. 17390, 2007 [19] Berg, P.: Benchmarking of quality and maturity of innovation activities in a networked environment. In: International Journal of Technology Management, Vol. 33, No.2/3, 2006, S. 255–278. [20] Glinz, M.: A guided tour through the landscape of software processes and process improvement. In: Informatik/Informatique 6/1999. [21] Paulk, M..: The Capability Maturity Model – Guidelines for Improving the Software Process. Addison-Wesley, New York, 1995. [22] Carnigie Mellon University: Capability Maturity Model Integration(CMMI) Overview. Software Engineering Institute, Pittsburgh, PA 15213-3890; available at: http://pesona.mmu.edu.my/~wruslan/SE1/Readings/detail/Reading49.pdf (2013-11-03) [23] Kneuper, R.: CMMI – Improvement of software processes with Capability Maturity Model Integration. 1 Ed, dpunkt.verlag GmbH, Heidelberg, 2003. [24] Kirstein, H.: Foundations of EFQM-Model. Avalable at: http://www.deming.de/Deming/EFQM_Modell_2010_Grundlagen.html (2013-11-03) [25] Duncan, S.: Making Sense of ISO 15504 (and SPICE),” Quality/Process Improvement Consultant. SoftQual Consulting. Available at: http://www.westfallteam.com/Papers/Making_Sense_of_15504.pdf (2013-11-03) [26] Rout T. P.; El Emam K.; Fusani, M.; Goldenson, D.; Jung H. W.: SPICE in retrospect: Developing a standard for process assessment. In: Journal of Systems and Software, vol. 80, no. 9, pp. 1483–1493, 2007 [27] Dorling, A.: SPICE: Software process improvement and capability determination. In: Software Quality Journal, vol. 2, no. 4, pp. 209–224, 1993. [28] Konrad, M.; Paulk, M.; and Graydon, A.: An overview of SPICE’s model for process management. In Proc. 5th International Conference on Software Quality, Austin, TX, 23-26 October 1995, pp. 291-301. [29] Mettler, T.; Rohner, P.: Situational maturity models as instrumental artifacts for organizational design. In DESRIST, 2009: Malvern, p.1-9
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