QFD for Cloud Computing Georg Herzwurm1, Wolfram Pietsch2, Sixten Schockert1, and Tobias Tauterat1 1
Universität Stuttgart, Chair of Information Systems II (Business Software) Keplerstraße 17, 70174 Stuttgart, Germany {herzwurm, schockert, tauterat}@wi.uni-stuttgart.de
2
Aachen University of Applied Sciences, Department of Economic Sciences Eupener Str. 70, 52066 Aachen, Germany
[email protected]
Abstract The introduction of the client-server model in the 80s had a huge impact on the information technology used in manufacturing industry as well as within IT organizations (e.g. concerning the operation and the development of applications). Just like that, cloud computing will have a severe impact on almost all industries. This paper describes how QFD can be used to define specifications for cloud based IT solutions. Starting with the global mega trends we will explain the characteristics of cloud computing and their impact on the application of QFD, especially on the collaboration of all involved stakeholders. From this analysis and a conducted case study with a German information technology service provider we derive several recommendations on how to execute QFD for cloud computing.
Keywords Cloud Computing, manufacturing, megatrends, fuzzy development tasks, Continuous QFD, information technology
1 Motivation Industrial countries all over the world such as Germany, Japan, or the United States of America have to come face to face with the fact that their industries have to consider changes in the future. According to Westkämper these changes can be described by the eight megatrends; ageing, finance, globalization, individualism, knowledge in the global information and communication technology (ICT), public debt, sustainability and urbanization. Due to the fact that the manufacturing industry has major importance to the economic growth of all industrial countries in recent decades, these eight megatrends also have a major influence to the manufacturing industry. Figure 1 represents an example, how companies conceptual can handle global megatrends to receive a factory of the future, which will take the global megatrends into account. For instance the manufacturing industry has to consider how to manufacture in urban environment or how factories can be modified to receive a lean, clean and green factory. [1]
• Innovative products and processes • Dematerialization • Innovative materials
• Knowledge-based manufacturing engineering • Service engineering
Factory as good neighbor Manufacturing in urban environment
Volume production back to Europe
Impact of global megatrends
Factories of the future Factory and nature Lean, clean, green factories
• New business models in the life cycle of products
Next generation ICT for factories Digital factory • Infrastructure and education • E-learning
Fig. 1. Contributions to manufacturing of the future (based on [1])
To realize these global megatrends in order to generate factories of the future, ICT is needed on a large scale and must be established as an enabler for (almost) ever megatrend in the manufacturing industry. Because of the fact that ICT is needed to enable the eight megatrends, traditional manufacturing companies have to build up ICT-resources and -knowledge, which will support manufacturing to make a more effective and more efficient manufacturing possible. ICT-knowledge is needed to use ICT-resources optimal, to handle all difficulties, and to adjust them to support the manufacturing in an effective way. Software, platforms, and infrastructure can be classified as ICTresources. Software is needed for future factories to control all manufacturing machines and the entirely process of manufacturing to handle the advanced manufacturing. Some examples for complex systems which need more and more software support are; manufacturing execution systems, supply chain management systems, knowledge management systems or systems like the digital factory, which stands for digital models and methods to plan, realize, control and improve manufacturing processes and resources. Platforms in this context represent the opportunity to network with other factories and/or construct the manufacturing in a modular way. For example, the common tendency to plug and play products (for a detailed description see [2] and [3]) within the information technology (IT) domain can be taken into account as an concept to develop parts of the manufacturing with the help of ICT towards manufacturing that can be named as plug and produce. Plug and produce means: if a factory needs no matter what kind of manufacturing machine, that this machine can easily be added by a standardized interface. Even in this case software is needed to enable, provide, and coordinate this concept of plug and produce. To meet the requirements of a software intensive manufacturing and to realize platform manufacturing, a huge demand of hardware is necessary such as servers or storage. The conventional approach to cover the demand of software, platforms and/or hardware is to buy the components needed. With the evolution of the Internet technology it is possible to rent these ICTresources on demand and it is not necessary to buy them. An advantage of renting ICT-resources is that customers do not have to invest a lot of money for these resources and so they have no high fixed capital. The possibility to rent ICT-resources through the Internet technology on demand is called cloud computing.
2 Cloud Computing In reference to the United States National Institute of Standards and Technology (NIST), cloud computing will be defined as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” [4] Because of the fact, that cloud computing is a complex topic, the cloud model of the NIST “is composed of five essential characteristics, three service models, and four deployment models” [4]. In our opinion just three deployment models exist because the deployment model “community cloud” can be subordinated to hybrid cloud. The result of our concept can be seen in figure 1.
Service Models and areas of application
Software as a Service (SaaS) (E.g., HR, CRM, ERP, FI, …) Platform as a Service (PaaS) (E.g., tools, operating system, database, middleware, …) Infrastructure as a Service (IaaS) (E.g., network, server, data center structure, storage, …)
Deployment Models
Essential Characteristics
Private cloud
Hybrid cloud
Rapid elasticity On-demand self-service
Public cloud
Measured service
Broad network access
Resource pooling
Fig. 2. Models and Models and characteristics of cloud computing (based on [4] and [5])
The five essential characteristics of all cloud computing service and deployment models are: ondemand self-service, broad network access, resource pooling, rapid elasticity and measured service (for a detailed description see e.g. [4]). “Deployment models broadly characterize the management and disposition of computational resources for delivery of services to consumers, as well as the differentiation between classes of consumers.” [6] Deployment models can be differentiated into private cloud, hybrid cloud and public cloud. A private cloud is one in which the access is limited to employees of the same company or authorized business partners, customers and suppliers. [7] In reverse a public cloud is open to everyone who wants to use a cloud solution for example via web-portal and so the provider allows the customer to define their own scope of service, which is charged on the actual operating life. A hybrid cloud is a mixed form of private and public cloud. [7] Another differentiation is based on the service models. In this case Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) can be differentiated. All three models have in common, that IT-resources are provided as services. [8] In the case of SaaS customers are able to rent applications and to use them over different client devices. For example by using a web browser or a program interface. One advantage of this service model is, that “the cloud consumer does not manage or control the underlying cloud infrastructure or individual applications, except for preference selections and limited administrative application settings.” [4]. Through PaaS runtime environment and development environment are provided by cloud providers. The platform offer contains a framework for the program language and the different development tools of the provider to develop a software solution, which is based on the providers’ platform. [9]
The last service model is IaaS. IaaS involves infrastructure components such as storage or computing power. Users can book the components they require and will receive direct access to these virtual resources. For companies in the manufacturing industry cloud computing can be used in two ways: to use ICTresources and to extend the existing business model of the company. Cloud computing to use ICT-resources can be represented by cloud computing thru covering the demand for IT services, which will be needed to develop factories of the future. For example a manufacturing company might rent servers or storage from a cloud computing service provider to satisfy their hardware needs. If all needs are satisfied they just stop renting the IT-resources and won’t have to pay any longer for them. Or if a specific software is required for a period of time, the company rents the software solution from a cloud computing provider. In those cases the manufacturing company is cloud computing customer. Cloud computing as extension of the existing business model can be represented by cloud computing, if manufacturing companies provide cloud computing solutions in addition to their normal business as a cloud computing service provider. This case would be possible, if a manufacturing company invests in hardware components needed to cover the demand of ICT, which is required to enable the advanced manufacturing, and if the company has an unsteady workload of this hardware. By using cloud computing as business model manufacturing companies may be able to rent out idle IT-capacity to increase their sales. Probably the most famous example in this context is Amazon. Amazon started as retail website for books and later on as retail website for nearly everything. [10] Because of the fact that Amazon provides an enormous number of IT-resources (e.g., servers or storage), which were not be fully stretched to handle the traffic of their website, they decided to launch a cloud computing solution named Amazon Web Services in the year 2006 to rent out the not needed It-resources. Nowadays the business models of Amazon are to sell real objects as well as to rent out IT-resources by cloud computing solutions. [11] It also would be possible to rent out software solutions or to allow other companies to use a special platform for their manufacturing by paining for it.
3 QFD for cloud computing Cloud computing as a new domain for the application of QFD has to consider some specifics. There are three characteristics of cloud computing which have major implications on the application of QFD:
The novelty of the cloud computing concept The novelty of the cloud computing business model The service providing nature of cloud computing
Most implications on a QFD application are caused by the novelty of the cloud computing concept. From a technical as well as a customer oriented viewpoint there is a latent uncertainty about the potential of cloud computing in the future. In the case of such entirely new products customers have problems identifying benefits since comparing new solutions with existing products is rather complicated. E.g. how to compare the billing concept based on actual usage of storage, processing, memory and so on with the payoff of an investment in a dedicated server? Likewise, developers from the service providers’ side have difficulties in determining potential solutions as the feasibility of the new technology is not certain. E.g. how to know in advance if the operation in form of pooling dynamically all computing resources to serve multiple customers according to their demand will work smoothly or not? For all involved stakeholders it is not clear what to demand from a cloud computing solution. The lack of experience in this application domain on customers’ as well as service providers’ side results in unclear customer requirements and solution characteristics.
Under such circumstances the “classical” QFD concept is less suitable. The “classical” QFD concept relies on well-known requirements “only” to be elicited, structured and prioritized by the customer on hand and transferred in solution characteristics. For such a rather fuzzy development task like the one described above a QFD variant called Continuous QFD [12, pp. 89-115] has been designed. In essence, it consists on incremental planning and implementation cycles supported by the extensive employment of information technology.
Fig. 3. Characteristics of fuzzy development tasks and the corresponding specifics of Continuous QFD [12, p. 93]
A QFD project is always a joined team effort of the customers’ as well as the developers’ side. QFD always aims at improving communication by establishing cross-departmental, interdisciplinary teams within the company and with the customers. Furthermore, as fig.3 shows, the lack of experience and clarity in customer requirements as well as solution characteristics calls for an even closer and increased collaboration of all involved stakeholders (primarily indicated by the demand for a larger number of meetings and a simultaneous collection of requirements and solutions). But unfortunately, the other two relevant characteristics of cloud computing do have implications which make the cooperation between all stakeholders more challenging. For the first, there exists a natural uncertainty on customers’ as well as service providers’ side regarding the consequences of the cloud computing business model. From providers’ viewpoint new cloud services could conflict with traditional business fields like the operation of a data center. Even an internal competition between departments could arise, which can of course be beneficial, but is more likely to lead to less willingness of joining the interdisciplinary QFD team. Customers could have doubts and moreover only little motivation to work within a QFD team because by using external services current internal information technology resources and staff could become obsolete. Therefore a certain degree of skepticism and acceptance problems could exist regarding the application of QFD for cloud computing. Likewise, the service providing nature of cloud computing with focus on little direct interaction with the customers but more loose virtual cooperation via web handicaps the need for close collaboration between all stakeholders. Cloud computing represents the modern “value in use” concept of services where customers individualize their personal solution on the basis of the offered services by themselves. But with so little direct interaction, how does a service provider know what to offer? So, on the one hand, cloud computing having the nature of a fuzzy development task demands for strong collaboration between all stakeholders. But on the other hand, the impacts of the cloud computing business model as well as the specific service character make the cooperation more difficult. To tackle this central problem we came up with several adjustments of QFD for cloud
computing. These recommendations incorporate lessons learned in a case study with a German information technology service provider as well as theoretical considerations.
When real customers are hard to motivate for a QFD application, internal marketing and sales people have to be involved in the QFD application more strongly. They even have to prioritize the customer requirements for the most part, even though this could of course lead to misjudgments. In this context, the project will benefit somewhat from the fact, that the time schedule is mostly not that tight because of the openness and newness of the cloud computing market. It is e.g. possible to change the service provider rather easy and fast when the offerings are comparable, especially regarding infrastructure as a service. The lack of time pressure is also an essential difference to Continuous QFD.
When collaboration is difficult the simultaneous collection of requirements and solutions with all stakeholders as included in Continuous QFD has little prospect of success. The novelty of the cloud computing concept even calls for asking developers at first about their potential solutions before marketing and sales people are involved.
To enhance the communication with the (potential) customers which may even be distributed around the world it is necessary – like in Continuous QFD – to make extensive use of information technology concepts. Thus, the analysis of log files, reports, reviews etc. and even tool supported web collaboration in requirements negotiation software tools is an option for incorporating the voice of customer into the process. One could say IT tool support in the way of “QFD as a service” is needed.
Even though cloud computing is an IT resp. software topic its service providing nature leads to a higher importance of solution characteristics in form of quality attributes in favor of functional requirements. E.g. security, operational availability, and usability represent the performance side of the cloud services which outperform the process side of the services. On the other hand the resource side reflecting the potential to deliver a secure, highly available and user-friendly service is important in communicating the offerings on the market.
The determination of correlation values between requirements and solutions in a QFD matrix usually represent the central step of getting a sense of commitment between all stakeholders on the product to be developed. However, when dealing with such a demanding, complex matter in conjunction with the difficult access to customers the developers, supported by marketing and sales, are responsible for the linkage between requirements and solutions.
4 Conclusion This paper described the application of QFD for cloud computing. We derived specifics of QFD usage in this novel domain by taking the global mega trends as a starting point. After that the concepts of cloud computing were illustrated. Three characteristics of cloud computing were identified which have a strong impact on the execution of a QFD project, especially on the collaboration of all involved stakeholders. From this analysis and a conducted case study with a German information technology service provider we concluded several recommendations on how to tackle these challenges. During a QFD project dealing with such fuzzy development tasks continuously new insights are gained, the lack of clarity is reduced little by little. This is in the sense of Continuous QFD with its iterative and incremental procedure. In this context, we expect information technology collaboration concepts like requirements negotiation software tools to become more and more essential in the application of QFD.
References [1] Westkämper, E.: Next Generation Manufacturing. http://publica.fraunhofer.de/documents/N194503.html [2] TechTerms.com, http://www.techterms.com/definition/plugandplay [3] ZDNet: http://www.zdnet.com/news/plug-and-play-in-windows-2000/296578 [4] Mell, P., Grance, T.: The NIST Definition of Cloud Computing. National Institute of Standards and Technology, Gaithersburg (2011) [5] Herzwurm, G., Mikusz, M., Pelzl, N.: Vernetzte Produktionssysteme als softwareintensive Dienstleister. In: Management vernetzter Produktionssysteme, pp. 167-180 (2011) [6] Jansen, W., Grance, T.: Security and Privacy in Public Cloud Computing. National Institute of Standards and Technology, Gaithersburg (2011) [7] BMWi: Aktionsprogramm Cloud Computing. Aktionsprogramm des Bundesministerium für Wirtschaft und Technologie (BMWi), Berlin (2010) [8] BITKOM: Cloud Computing. Bundesverband Informationswirtschaft, Telekommunikation und neue Medien e. V. (BITKOM), Berlin (2009) [9] Durkee, D.: Why Cloud Computing Will Never Be Free. In: Commun. ACM 53 (5), pp. 62–69 (2010) [10] Brandt, R.L.: One Click. Portfolio Penguin, St. Ives (2011) [11] Amazon Web Services, http://aws.amazon.com/what-is-aws/ [12] Herzwurm, G., Schockert, S., Mellis, W.: Joint Requirements Engineering, QFD for Rapid Customer-Focused Software and Internet-Development. Vieweg, Wiesbaden (2000)
Biography Prof. Dr. Georg Herzwurm Prof. Dr. Georg Herzwurm is a Distinguished Full Professor and holds the Chair for Business Administration and Information Systems, esp. Business Software at the University of Stuttgart, Germany. He is founder and speaker of the board of the German QFD Institute (QFD-ID). Since 2009 he is director of the International Council for QFD (ICQFD). 2000 he received the international Akao-Prize for outstanding contributions to the further development and support of QFD. Certified QFD-Architect conferred by the QFD-Institute Germany. Prof. Dr. Wolfram Pietsch Prof. Dr. Wolfram Pietsch is currently serving as a senior professor in International Sales and Service Management at the Aachen University of Applied Sciences. He has earned a doctoral degree with works on software project management and has been consulting several companies concerning quality and process management as a senior consultant for ExperTeam AG for merely a decade. He is co-founder and member of the board of the QFD-Institut Deutschland. 2009 he received the international Akao-Prize for outstanding contributions to the further development and support of QFD. Certified QFD-Architect conferred by the QFD-Institute Germany. Dipl.-Wirt.-Inf. Sixten Schockert Dipl. Wirt.-Inf. Sixten Schockert holds a Master’s degree in Information Systems from the University of Cologne, Germany. Since 2003 researcher and lecturer at the department of Information Systems, esp. Business Software of Prof. Dr. Georg Herzwurm at the University of Stuttgart; founding member and since 2006 member of the board of the QFD Institute Deutschland (QFD-ID); Certified QFD-Architect conferred by the QFD-Institute Germany. Tobias Tauterat, M.Sc. Tobias Tauterat holds a Master’s degree in Information Systems from the Universities of Stuttgart and Hohenheim, Germany and a completed vocational training as IT Specialist for Systems Integration. Since 2011 he is researcher and lecturer at the department of Information Systems, esp. Business Software at the University of Stuttgart.
