Evaluation and optimization of Product/Service Systems within the development process

Transcription

1 Evaluation and optimization of Product/Service Systems within the development process Johannes Matschewsky LIU-IEI-R 13/00161-SE Department of Management and Engineering Division of Environmental Technology and Management Note: This report was submitted as a thesis to acquire the degree of Diplom-Ingenieur (FH) at the University of Applied Sciences Dresden (HTW Dresden). The research was conducted at Linköping University from March to September The degree was awarded on December 3, 2012.

2 We are not going to be able to operate our spaceship earth successfully nor for much longer, unless we see it as a whole spaceship and our fate as common. It has to be everybody or nobody. R. Buckminster Fuller

3 Contents Nomenclature List of Figures List of Tables VIII X XII 1 Introduction Background Objective of the Thesis and Research Questions Structure of the Thesis Product-Service Systems - An Introduction Introduction Products and Services - Definition Products Services Product Service Systems - Definitions Product-Service Systems and Environment Service Engineering and the move from Eco-Design Eco-Efficiency as a main focus of Product-Service Systems Factors influencing Environmental Performance Business Models in PSS Introduction Discriminating amongst the different models Product Development and PSS Introduction and Scope Locating PSS and Producer Value Assessment in product development Product development and PSS - a broad field New Product Development and PSS design Idea Generation: Brainstorming Idea Screening and Evaluation: Cost-Utility Analysis Quality and implications on PSS-Design IV

4 CONTENTS Quality Function Deployment - Introduction Quality Function Deployment and Product Service Systems Failure Modes and Effects Analysis - Introduction Failure Modes and Effects Analysis and PSS Life-Cycle Perspectives, PSS and Producer Value Introduction Life-Cycle Assessment - An Introduction Life-Cycle Perspectives in PSS research Life-Cycle Perspectives in Producer Value Assessment Producer Value evaluation and SPIPS Traditional approaches to Producer Value Introduction Producer Value in Literature Value Engineering Definition The focus-points of Value Engineering Value Engineering and Services Value Engineering and PSS evaluation Existing Research in the PSS-Field Costing and Producer Value evaluation Introduction The Experience Curve Definition and introduction Implications of the experience curve on the PSS evaluation Economies of Scale Definition and Importance to the topic Uncertainties in Producer Value evaluation in PSS Introduction General Definition and Scope of Uncertainty Definition The Nature of Uncertainty Uncertainty and Risk Classes of Uncertainty Uncertainty in relation to PSS optimization Reducing Uncertainty within the PSS optimization Categories of Service Uncertainty Implications of categories on PSS optimization Generation of uncertainty values Methodology to tackle uncertainty in producer value evaluation V

5 CONTENTS Motivation and Scope The NUSAP System to quantify qualitative information Reducing Uncertainty in PSS evaluation using NUSAP Results of the NUSAP-Based uncertainty-calculation Properties to determine producer value Introduction Categorization of value parameters Characteristics of Producer Value in PSS Introduction Knowledge as a criterion for PSS evaluation Relation to customers Time-to-market and its producer value Infrastructure State of the Market and its development Life-Cycle and Environment Scale of Scoring Derivation of an aggregate Producer Value Interdependencies in PSS assessment Introduction Design Structure Matrix and PSS components Introduction Definition and Scope Possible relations conveyed by a DSM How to read a DSM Optimization of a component-dsm Introduction, Cambridge Advanced Modeller DSM clustering Interpretation and results of DSM-based optimization Structure and operation of the Method Introduction Structure of the process Component Focused Assessment Step 1 - Enter/Load Components Step 2 - Enter/Load and select applicable types of Producer Values Step 3 - Assign Values to Producer Value Determinants Step 4 - Uncertainty Assessment Offering-Focused assessment Step 5 - Interdependencies Step 6 - Cost and Revenue VI

6 CONTENTS Step 7A - (Re-)Evaluation of Components Step 7B - (Re-) Evaluation of Offerings Iterative nature of the method Software automating the evaluation process Introduction General Structure Suggested design of the software Entry of Components Selection of Producer Values Uncertainty Assessment Incorporation of interdependency into the software Integration of Cost and Revenue Creation of Offerings Revenue Overview Application of the method to a set of data Introduction Evaluation Process and Results Display of Information in the thesis Variety among physical components and evaluation focus Component Catalog and component properties Assign Values to different components Uncertainty Assessment Interdependency and use of DSM Cost and Revenue Results, Combination and Reassessment Lessons learned Conclusion and Outlook Conclusion Outlook and further research Bibliography 97 Appendix Appendix 1: Component Properties Appendix 2: Cost and Revenue Appendix 3: Data produced during the evaluation VII

7 Nomenclature CAM CAPTOE CUA DfE Cambridge Advanced Modeller Commercial, Affordability, Performance, Training, Operation and Engineering Uncertainty Cost Utility Analysis Design for Environment DSM EOL Design Structure Matrix End of Life FMEA ISPE Failure Modes and Effects Analysis Integrated Product Service Engineering KPI NPD Key Performance Indicator New Product Development NUSAP PSS PV PVD QC QFD Numerical - Unit - Spread - Assessment - Pedigree Product-Service Systems Producer Value Producer Value Determinant Quality Control Quality Function Deployment QFDE Quality Function Deployment for Environment VIII

8 NOMENCLATURE SE SPIPS TRIZ VBA VE WTP Service Engineering Toward Solution Provider - Through Integrated Product and Service Development Theory of inventive Problem solving Visual Basic Application Value Engineering Willingness to Pay IX

9 List of Figures 1.1 Structure of this thesis Design Paradox: Freedom of action vs. product knowledge PSS Business Models Linear NPD model Eco-Design methodology Steps of the SPIPS-method Value Engineering and PSS Evaluation Experience Curve with 90% Slope (Dis)Economies of Scale Categorization-Pyramid for producer value parameters Parallel DSM relationship Sequential DSM relationship Coupled DSM relationship Example of a DSM with unaltered data in CAM Clustered component-based DSM Description of the evaluation process Shortened NUSAP process to reduce uncertainty Example of DSM optimization by clustering PSS illustrated by Tablet and Sales-Platform offering Mockup of the general structure of the software Dialog for entry of components Selection and connection of producer values Mockup of the Uncertainty-Assessment-Tab Integration of cost-related data in the software Creation of offerings in a software Interface for inserting revenue-related data Overview of the data entered X

10 LIST OF FIGURES 11.1 DSM matrix of woodchipper before clustering Clustered DSM matrix of the woodchipper XI

11 List of Tables 2.1 Specification of PSS Business Models Evaluation criteria used by Yoon et al Classes of Uncertainty Self-Assessment-Questions regarding uncertainty Example of Uncertainty assessment Pedigree Matrix for scoring uncertainties Color-codes for Pedigree scores Scoring Scale for Producer Value Assessment Example of the derivation of aggregate Producer Values Matrix of Components and PV-Scores Possible grouped components view Component Catalogue with product and service components Components with producer values assigned Uncertainty Assessment of example problem Experience Curve Data for Services Scale effects on Services Cost and Revenue for three and five-year contracts Components chosen for possible offering XII

12 Chapter 1 Introduction 1.1 Background We live in a world that is evolving and changing faster than ever. Paradigms are set, and revoked the next day. One of these paradigms, that have fueled the prosperity of market economies all around the world in most of the 20th century, is growth. More production leads to more consumption and an increased standard of living. Today, hardly anyone in academia or politics sees a future of prosperity through the growth of production and sales of physical products alone. Scarcity of resources is a fact we are faced with today and even more so when looking ahead to the next 30 years or so. Different ways of creating value without destroying the very base of our existence must be contrived while attempting to maintain the standards of living in the developed world and providing emerging countries with a fair chance for prosperity in the future. Product-Service Systems (PSS) are one possible way of creating added value and thus growth, but disconnecting this growth from an increase in material consumption and therefore resource depletion (as discussed e.g. by Manzini et al., 2001). This issue will be discussed further in chapter 2.4. By combining products and services, developing them in an integrated manner and approaching their design and operation from a life-cycle perspective, offerings can be conceived that reduce the strain on the environment through different effects but allow for new sources of revenue, growth and prosperity to be discovered. As mentioned by Meier et al. (2010), the portion of the GDP created through service activities in Japan (69%), Germany (70%) and the USA (75%) surpasses that of the industrial sector by a large margin. Combining the two and making use of the resulting synergies is a main objective of the research on Product- Service Systems in roughly the past decade. Current research will be examined in the following chapter to fully explain PSS and why it holds such great potential, both from an environmental as well as an economic perspective. One of the main focuses of research in the field of PSS is PSS development. Since an integrated approach of product and service development is the explicit aim of most PSS design strategies (e.g. Lindahl et al., 2006), traditional means of product development 1

13 Introduction known and successfully applied in engineering design do not apply to the world of PSS or must be altered and adapted to do so. This issue is discussed in detail in chapter 3 of this thesis. The PSS-design method SPIPS (Toward Solution Provider - Through Integrated Product and Service Development), introduced in Sakao et al. (2009) and extended in Sakao and Lindahl (2012) is one possible approach to PSS design that is introduced and related to this thesis in chapter 3.5. At this point, although possessing a verified method for consumer-value assessment (Sakao and Lindahl, 2012), the method is lacking an approach toward the assessment of the producer-value of PSS components and offerings. This thesis aims to fill this void. 1.2 Objective of the Thesis and Research Questions The primary aim of this thesis is to provide a structured method to assess the producer value (PV) of components and combinations of components (offerings) of Product/Service Systems. This goal is intended to be reached through answering the following sub-questions or completing these tasks: 1. Provision of an introduction to PSS and current research as well as definitions for the most important terminology 2. Discussion of traditional product development, interfaces with PSS and review of literature relevant to this 3. Review of methods of producer value assessment and extraction of useful issues 4. Discussion of uncertainty, interdependency and cost within the scope of producer value evaluation in PSS design, derivation of possible solutions and issues for further research 5. Finding a way to quantify producer value 6. Describing the structure of the method proposed 7. Outlining the possible realization of the method in a software environment 8. Applying the findings to an example of realistic nature 1.3 Structure of the Thesis The thesis is structured along the lines of the tasks and questions listed above and is illustrated in Figure

14 Introduction Review of research, examination in relation to PSS in general and Producer Value Assessment in particular 1. Introduction, Objectives 2. PSS Introduction, Definitions 3. Traditional Product Development 4. Traditional Producer Value Assessment 5. Uncertainty, Interdependencies and Cost Development and description of the method and its elements 6. Quantification Producer Value in PSS 7. Introduction of the Producer Value Assessment Method 8. Suggestion of Method-Use in a Software 9. Application of Method to an Example Figure 1.1: Structure of this thesis The thesis can be divided, as also shown in the illustration, into two large sections: In section one, the focus is on review of two types of literature: Either research directly referring to PSS is listed and examined, or other literature referring to traditional engineering methods is put in relation to PSS. Whenever appropriate, conclusions relating to the proposed method have been drawn or cross-references made. This is visualized by the connections of the different topics as shown in Figure 1.1. The second section explains the components of the method, how they were conceived and why they are intended for use in a certain way. 3

15 Chapter 2 Product-Service Systems - An Introduction 2.1 Introduction In the following sections, the most important terminology used in this thesis will be explained and defined in the light of current literature and leading research in the field. A short but comprehensive introduction to this interesting type of offering that has received much attention in various fields of research and the industry will be given. 2.2 Products and Services - Definition Products In the papers reviewed for this section, the product-portion does not receive special attention with respect to a particular definition of the term. It is mostly just assumed to be the tangible/physical part(s) of an integrated offering of products and services. Goedkoop et al. (1999) define a product as a tangible commodity manufactured to be sold. It is capable of falling onto your toes and of fulfilling a user s need Services With services, the situation is quite the opposite. Many definitions and descriptions are given, some of them, if they add to the understanding of the issues discussed, will be reproduced in the following. Meier et al. (2010) in their review of the state of the art in Industrial Product Service Systems, focusing on the business-to-business-perspective, cite a threefold definition of services as stated by McDonald et al. (2011): Intangibility: Services are intangible, as opposed to concrete products 4

16 Product-Service Systems - An Introduction Uno-actu-principle: Services are produced and consumed at the same time, storing them is not possible Direct contact between an external service provider and the customer is imperative Other authors such as Kim et al. (2011) solely refer to the tangibility-criterion in order to determine the property of a component as a physical or service component. 2.3 Product Service Systems - Definitions Within this section, different definitions and views of Product-Service Systems will be introduced. Eventually, a definition will be adopted for use in this thesis. Goedkoop et al. (1999) According to Kim et al.(2011a), Goedkoop et al. (1999) were first to introduce PSS as a reflection of both ecological and economic issues. They define a Product-Service System as follows: A Product Service system (PS system) is a marketable set of products and services capable of jointly fulfilling a user s need. The PS system is provided by either a single company or by an alliance of companies. It can enclose products (or just one) plus additional services. It can enclose a service plus an additional product. And product and service can be equally important for the function fulfillment. The researcher s need and aim determine the level of hierarchy, system boundaries and the system element s relations. The authors go on to restrict their definition of the term service to services that have a direct positive economic value in the market (excluding free services), services that benefit the end-user (consumer or business), and exclude common distribution and sales channels. It appears that publications referring to PSS agree to this definition without explicitly stating this. Meier et al. (2010) Meier et al. (2010), particularly focusing on the business-tobusiness aspect of PSS, refer to them as Industrial Product-Service Systems (IPS 2 ). Citing Meier et al. (2005), they define IPS 2 as follows: An Industrial Product-Service System is characterized by the integrated and mutually determined planning, development, provision and use of product and service shares including its immanent software components in Businessto-Business applications and represents a knowledge-intensive sociotechnical system. The authors proceed to refine their definition even more; this is suggested for further reading. 5

17 Product-Service Systems - An Introduction Baines et al. (2007) Baines et al. (2007) in their review of PSS firstly refer to the original definition introduced by Goedkoop et al. (1999). After reviewing a number of definitions found in Table 1 of their paper, Baines et al. (2007) come to the following conclusion with respect to finding a definition suitable to PSS: A PSS is an integrated product and service offering that delivers value in use. A PSS offers the opportunity to decouple economic success from material consumption and hence reduce the environmental impact of economic activity. The PSS logic is premised on utilizing the knowledge of the designer-manufacturer to both increase value as an output and decrease material and other costs as an input to a system. In their aggregation of a number of definitions, Baines et al. (2007) put stress on the environmental effects that are expected from the use of PSS. This stands in contrast to the aforementioned definitions focusing mainly on the economic aspects. In this thesis, PSS is to be understood with mainly two things in mind, that are part of Meiers and Baines definitions: Firstly, a Product/Service System is to be developed, offered and used in an integrated manner; secondly, environmental benefit, though achieved indirectly, is a major focus of the development and use of Product/Service Systems. 2.4 Product-Service Systems and Environment When research on PSS gained momentum, one of the main points of interest was the improvement of environmental performance of offerings Service Engineering and the move from Eco-Design Sakao and Shimomura (2006), for example, see Service Engineering (SE) as a further development of Eco-design (exemplary of this is Fiksels Design for Environment, 2011). The authors go on to criticize that even though Eco-design has succeeded in bringing environmentally friendly products to market, very few of those tools and methodologies have succeeded in incorporating the needs of consumers effectively. Sakao and Shimomura (2006) further introduce their concept of this engineering discipline and a newly-developed design tool, called Service Explorer. Cavalieri and Pezzotta (2012) have assumed service engineering to be a part of PSS design, as Sakao and Shimomura (2006) focus on combining customer requirements and value creation with environmental efforts. 6

18 Product-Service Systems - An Introduction Eco-Efficiency as a main focus of Product-Service Systems In Goedkoop et al. s (1999) introduction of PSS, environment and sustainability are, besides economy, the main focus of this major study on this type of offering. Results of this study go so far as to suggest a possibility of unlinking the toll on the environment that economic growth tends to take. In Baines et al. (2007), the shift in focus of PSS-oriented research becomes obvious. The main objective in achieving more sustainability is dematerialization. The idea here is to unlink the amount of value created for the customer from the amount of material delivered in order to create this value. Ehrenfeld (2001) states, though, that the objectives of dematerialization and sustainability should not be interpreted as synonymous. Baines et al. (2007) also point out that dematerialization is not part of any of the definitions of PSS reviewed in their paper. Manzini et al. (2001) clearly state a smaller environmental impact together with a higher added value as one of the main objectives of offering PSS Factors influencing Environmental Performance In this paragraph, a recent publication by Lingegård et al. (2012) addressing factors influential on environmental performance of PSS will be examined and critical issues discussed. Reference is made to Integrated Product Service Engineering (IPSE), which was first introduced in Lindahl et al. (2006). The concept was compared to common eco-designpractices (Design for Environment, DfE) in Lindahl et al. (2007). The conclusion drawn in this paper is that the environment-related requirements of DfE need to be intertwined with offering-related requirements. Further, an advantage is seen in the balance of focus between environmental and economic issues. The view of both products and services together with a Life-Cycle perspective are seen as a promising approach. In Lingegård et al. (2012), IPSE is regarded as a particular approach to PSS. As stated in Lingegård et al. (2012), IPSE attempts holistic optimization from the environmental and economic perspectives throughout the life cycle. In addition, not only design as the foremost engineering activity, but also maintenance, upgrade and remanufacturing are in focus. The biggest factors influencing environmental performance identified in this publication are: Theory of Product Development Product development is nowadays often focused on cost reduction. In many cases, this also leads to a reduced environmental impact, as e.g. material-consumption is reduced. Also, the design-paradox must be considered: The paradox is that when the general design information is needed, it is not accessible, and when it is accessible, the information is usually not needed (Lingegård et al., 2012 referring to Ullman, 2009). 7

19 Product-Service Systems - An Introduction Figure 2.1: Design Paradox: Freedom of action vs. product knowledge (Ullman, 2009) This relation is illustrated in Figure 2.1. Additionally, the implementation of an integrated approach between product and service development yields large opportunities to reduce the environmental impact of an offering. Information Asymmetric between Provider and User The asymmetry in knowledge about the use of a good for optimal energy efficiency, the best End-Of-Life (EOL)- treatment etc. are the main points made with reference to this issue. Economies of Scale Economies of scale will be discussed in more detail farther along this thesis in chapter 5.3. One example mentioned by Lingegård et al. (2012) is that the outsourcing of an identical process within a number of companies to a single one would increase the efficiency of production (Gao et al., 2009). Risk Risk and Uncertainty is a major factor not only regarding environmental performance, but the performance and profitability of a PSS-type offering in general. It is discussed in detail in chapter Business Models in PSS Introduction A new type of offering requires new business-models in order to properly and most efficiently market these offerings. In order to provide a broad introduction to PSS, the most common business models as listed in Meier et al. (2010) should be introduced and briefly explained in this section. Figure 2.2 gives an overview of the three main business-models present in current research: function, availability and result-oriented. 8

20 Product-Service Systems - An Introduction Figure 2.2: PSS Business Models (Meier 2010) Discriminating amongst the different models Meier et al. (2010) have developed an elaborate scheme to discriminate amongst the different business models present with respect to PSS-type offerings. The following table is taken from that publication and illustrates the responsibilities as they are divided between customer and supplier very well. A Function oriented PSS-type offering is the least servitized form of a business model based on Product-Service Systems. Meier et al. (2010) mention a maintenance contract, guaranteeing the functionality of an offering for a certain period of time. Ownership of the offering is transferred entirely to the customer and he is also the only one initiating servicing etc. It is very easy to confuse a traditional product-offering with a service-contract added on top with a function-oriented PSS. It must be kept in mind that the intention and aim of a PSS, especially as it is interpreted by IPSE, is simultaneous and co-supportive development of products and services. When looking at an Availability oriented PSS, the shift towards servitization and with respect to ownership becomes apparent. While production and the supply of the operating personnel still lie with the customer, the service initiative and the carrying out of the services, though, has shifted to the supplier. One example of this might be a remote maintenance program, which alerts the supplier of wear on one of his products, so that he is able to dispatch a service technician in advance of a possible failure, thus ensuring he meets the availability goals promised in the initial contract. The risks of operation are shared among the parties involved. 9

21 Product-Service Systems - An Introduction Table 2.1: Specification of PSS Business Models (Meier 2010) Function oriented Availability oriented Result oriented Production responsibility Customer Customer Supplier Supply of operating personnel Customer Customer Supplier Service Initiative Customer Supplier Supplier Ownership Customer Customer/ Supplier Supplier Supply of maintenance Customer/ Supplier Supplier personnel Service turnover model Supplier Pay on service order Pay on availability Pay on production The shift from a producer of a physical product to the provider of a service using a product is completed with the Result oriented PSS. Here, no transfer of ownership is realized at all, the offering stays entirely with the provider and the risk is borne by the provider alone. In many cases, the supplier will set up his apparatus within the premises of the customer. Payment is only transferred per item manufactured. According to Meier et al. (2010), the number of customers willing to completely outsource processes is limited, and even though compensation-payments will be made in case the supplier is unable to provide a sufficient number or quality of parts, customers risk delays with their own products that they will be held liable for as well. 10

22 Chapter 3 Product Development, PSS development and integration of the method 3.1 Introduction and Scope The producer value assessment that is the goal of the method proposed within this thesis is part of a larger PSS design method called SPIPS (Toward Solution Provider - Through Integrated Product and Service Development), that was introduced in Sakao et al. (2009) and modified and developed further in Sakao and Lindahl (2012), a paper of particular interest, since it proposes a evaluation method focusing on consumer value, whereas this thesis attempts to deliver the counterpart to this from the producers view. In this chapter, the positioning of the proposed method within the developmentprocess of an offering will be laid out. First, the design of PSS is located in the field of product development, then traditional engineering tools of evaluation and their impact on PSS are assessed, and lastly it will be explained, how this method integrates into SPIPS. Also, focus will be on quality, since this is a much-discussed field in PSS-related research. Namely, findings on using Quality Function Deployment (QFD) and Failure Modes and Effects Analysis (FMEA) in PSS-design will be briefly discussed. 3.2 Locating PSS and Producer Value Assessment in product development Product development and PSS - a broad field In order to put the method developed in this thesis into context and clarify its purpose and direction, it is important to shed light on the development of Product/Service Systems in relation to traditional product development in the engineering sector. In 11

23 Product Development and PSS Figure 3.1: Linear NPD model (Trott, 2012) this chapter, techniques and methods of product development will be briefly explained, interfaces with PSS-development examined and put in relation to the method as laid out in the following parts of this thesis. The reference for engineering design is Pahl et al. s Engineering Design: A Systematic Approach (2007, originally German: Konstruktionslehre: Grundlagen erfolgreicher Produktentwicklung ). Although of course only a few of the methods detailed in this book will be examined, focus will be on the most popular ones among engineering designers New Product Development and PSS design New Product Development in most cases affects a company in its entirety, whether it is a small business selling handmade goods or it is a multinational corporation selling a highly developed technological product. The actual design of the offering, and, as explained here, the decision making as to what components the offering will be comprised of, is done mostly in engineering. Figure 3.1 shows the linear model of NPD. Since this view is mostly utilized by managers and very business-focused, engineering is involved in only a few of the steps, especially when only PSS-design related tasks are considered. Mainly, the focus is on the following steps: Idea generation Idea screening 12

24 Product Development and PSS These points closely adhere to SPIPS as laid out in Sakao et al. (2009), of which the method proposed here will be a part. Starting from these very general points, traditional methods and tools of product development in the field of product engineering will be reviewed for interfaces with the goals of Product/Service System-design Idea Generation: Brainstorming Brainstorming is a method originating in the 1950 s and has been first formulated by Osborn (1957). Pahl et al. (2007) list it as a method with intuitive bias, and it is still one of the most popular methods of idea creation used today. In order to not unduly extend this part, only the most important factors in brainstorming will be listed: A group of 15 persons, possibly some of non-engineering background is formed The moderator interferes only very little with the discussion, may occasionally set stimuli etc. Nothing that can be imagined cannot be said, creativity is key, no criticism All proposals are recorded; the meeting should last no longer than 45 minutes Engineers review all proposals, evaluate their feasibility Other common methods include Method 635, Gallery Method and Delphi Method. On these and related topics Pahl et al. (2007) and references mentioned therein are suggested if further information is desired. Idea Generation, PSS Design and Producer Value Assessment Idea generation and brainstorming as a special incarnation of this is an essential step in designing PSS. Brainstorming is specifically mentioned in Sakao et al. (2009) as a creativity-tool within the SPIPS-method. There is no large discrimination to be made between components of physical products and their function, which is the aim of Pahl et al. (2007), and components of Product/Service Systems, whether they are physical or services. Creativity is especially key in the development of integrated products and services, since the inspiration engineers can take from existing offerings that have been built in an integrated manner from the ground up is still limited. Because of that, idea creation is an essential step that must be completed before components and offerings can be evaluated from the producer s viewpoint, as explained later in this thesis Idea Screening and Evaluation: Cost-Utility Analysis Pahl et al. (2007) discuss two techniques of selection and evaluation in detail: Evaluation according to VDI 2225 and the Cost-Utility-Analysis (CUA) (German: Nutzw- 13

25 Product Development and PSS ertanalyse), originally by Zangemeister (1976). Reichle (2006) has also given a short account of this type of analysis, the structure chosen here is along the same lines. Cost-Utility-Analysis was chosen, since it is the most complex of the evaluation methods generally used in engineering design. Very simple evaluation-lists are the basic form; they often offer no more than a yes/no/maybe for all of the possible entries. Lists with a weighted evaluation are already more complex, the next step being the evaluation according to VDI The most sophisticated method is the Cost-Utility- Analysis. The steps to follow are very similar for both methods (Pahl et al., 2007), with CUA reaching farther than the VDI-evaluation: 1. Isolation of objectives/evaluation criteria 2. Examination of the criteria and weighting of the criteria 3. Selection of applicable criteria for particular offering (not included in VDI 2225) 4. Assign values to criteria (VDI: 0-4, CUA: 0-10) 5. Calculate an aggregate value (VDI: Sum without weighting, CUA: weighted) 6. Compare offerings 7. Evaluate possible uncertainty (not included in VDI 2225) 8. Find weak points to improve selected offerings Idea Screening and Evaluation in PSS design It is clear, that this is the field this thesis is directly addressing, although, of course, only a very small portion of it is of particular interest in this case. Evaluation and selection is point 7 of the PSS-design method introduced by Sakao et al. (2009). It also includes data being fed back into idea creation, since evaluation may lead to a new view on the data present. As one part of this, Sakao and Lindahl (2012) have introduced a method to evaluate the consumer value of PSS components. This thesis is part of the efforts to provide a counterpart to this, focusing on the producer side of things. Some of the steps introduced below are naturally quite similar to the methods described by CUA and VDI 2225, while for the most part, the nature of PSS design compared to product-focused engineering design leads to different approaches and solutions. Cost-Utility Analysis remains, after many decades of use, a very powerful tool nonetheless. For the design of the components that make up a Product/Service System, it is one of the most productive tools for engineers. Since there are a number of commercial and open software programs aiding engineers in cost-utility analysis, including this into a comprehensive PSS-design tool does not seem necessary. 14

26 Product Development and PSS 3.3 Quality and implications on PSS-Design Quality Function Deployment - Introduction As said above, quality and the customer s perception of it are critical elements of the design of any product. PSS as a new type of offering requires a slight change of perspective to accommodate all elements of products and services. Quality Function Deployment (QFD) as a means of translating customer requirements to product design parameters and Failure Mode and Effects Analysis as a failure-assessment tool have been applied to PSS in the past and should serve as a short introduction within this thesis. Quality Function Deployment was originally introduced by Yoji Akao in 1966 (Akao, 2004). QFD provides specific methods for ensuring quality throughout each stage of the product development process, starting with design: [...] [It] is a method for developing a design quality aimed at satisfying the consumer and then translating the consumers demands into design targets [...]. (Akao, 2004). Quality Function Deployment is a set of techniques and methods that have evolved over almost half a century and produced tools that are crucial to modern day engineering. With regard to brevity, only the three major steps of QFD as Akao (2004) defined them will be listed and described, disregarding particular tools and incarnations such as the House of Quality. A comprehensive introduction to QFD may be found in Akao (2004) and literature referenced therein. Developing the Quality Plan and Quality Design This step involves the gathering of information regarding consumer demands, market characteristics, competition etc. Important quality elements to focus on must be isolated, quality assurance secured etc. Detailed Design and Preproduction (Subsystem Deployment) This step involves turning the product quality as identified above into quality characteristics that can be measured and quantified. Unit and component functions must be clarified and quality assurance items, function characteristics and safety characteristics need to be introduced and tolerances applied. Process Deployment Process techniques to optimize process capability need to be implemented and quality control (QC) processes must be planned and defined. Akao introduces QC process charts and includes subcontractors into the QC processes. 15

27 Product Development and PSS Quality Function Deployment and Product Service Systems In their current review of the state of the art in Product Service Systems Engineering, Cavalieri and Pezzotta (2012) attribute QFD to the following stages of PSS design: Requirements generation Requirements identification Requirements analysis This correlates to Step 5 in the SPIPS-method as shown in figure 3.3. Masui et al. (2003) have introduced a method for the application of QFD onto environmentally conscious design: QFDE (QFD for environment). The goal is to simultaneously focus on requirements of both customers and the environment in an integrated tool. This method states a number of parameters for designers to concentrate on in early stages of product design. This approach was extended in Sakao (2007a) through adding Life Cycle Assessment (LCA, ISO 14040, 2006) and TRIZ (Theory of inventive problem solving, see Altshuller and Altov, 1996) and is shown in figure 3.2 from that publication. TRIZ on its own and in combination with other methods has also been applied to PSS and has been the topic of extensive research. It is also discussed in Cavalieri and Pezzotta (2012) along with other methods that may be of interest if more information is desired. Figure 3.2: Eco-Design methodology proposed by Sakao (2007) 16

28 Product Development and PSS This procedure shown in figure 3.2 now has received ongoing development, being included in a service design method (Sakao, 2009) and now as a part of SPIPS as mentioned in Sakao and Lindahl (2012). As said by Sakao (2007, 2009) and Cavalieri and Pezzotta (2012), QFD and alterations thereof is a well-suited method to translate requirements from customers and the environment into design parameters. (Sakao, 2007). The method proposed within this thesis complements QFD within a larger set of methods. The focus on quality and its perception of the customer is crucial for the success of any offering and therefore also in the case of PSS. QFD sets the parameters for the components and offerings that will be evaluated in a later step of the SPIPS procedure as it is suggested in this thesis. It is conceivable that, after a PSS-type offering has been formed, the design team returns to the QFD step to re-verify the accuracy with which parameters and requirements have been met. Producer and customer value and quality are mutually dependent and therefore an essential part of a PSS design method Failure Modes and Effects Analysis - Introduction Failure Modes and Effects Analysis originates from procedures within the US Armed Forces Procurement with descriptions of procedures as early as 1949 (now-canceled procedure MIL-STD-1629, 1980). As stated by Pahl et al. (2007), FMEA is a means of systematically recording possible failures and an assessment of the associated risks. Performing this assessment before bringing a product to market can be essential in order to discover critical faults that place customers and subsequently also the company at risk. Should a closer look into the field of FMEA be desired or necessary, the literature mentioned and further references in Pahl et al. (2007) are suggested for further reading. Generally according to Pahl et al. (2007), the following steps are followed: 1. Risk Analysis and consideration of parts/process steps with regard to Potential failures Effects of these failures Causes for failures Planned measures for failures avoidance Planned measures for failures discovery 2. Risk Assessment: Assessment of likelihood of failure Assessment of the customer s perception of the error 17

29 Product Development and PSS Assessment of the likelihood of discovering the failure before delivery 3. Determination of the Risk-Priority-Number 4. Risk Minimization FMEA may be applied to a number of processes and products, the most common types of FMEA are: Design-FMEA dealing with optimal fulfillment of customer requirements, and Process-FMEA ensuring proper production processing. Other, more detailed types are mentioned in literature, Service-FMEA being of particular interest in the context of this thesis Failure Modes and Effects Analysis and PSS FMEA has received some interest in the service-engineering-world, although not as broad and exhaustive as QFD. Thomas et al. (2008) in their broad article on design and development with respect to PSS mention FMEA as a means of analyzing the present properties of the PSS. Schneider et al. (2006), along with discussing the morphological box, QFD, Cost-Utility-Analysis and Service-Blueprinting, have also examined the applicability of FMEA on Service Engineering. The authors explain FMEA and its application within the world of services and in conclusion find that FMEA is a mathematical-deterministic method of engineering that holds a high potential in the world of services. They further state that the application of FMEA in the servicesector is virtually identical to that of physical goods [...]. This statement is particularly helpful, since PSS is an integrated product. Concluding from this, one may say, that a Failure Modes and Effects Analysis may be performed on an integrated PSS offering without the split into physical- and service components. This further helps the process of integrating the development of products and services, blurring the divider between the two and moving closer to a fully integrated PSS development. Cavalieri and Pezzotta (2012) also incorporate FMEA into their review. They make reference to Luczak et al. (2007), who utilize a Service-FMEA as a means of assessing potential risks associated with [the] service delivery process. This view is still rather focused on the separation of products and services and the individual assessment of possible failures while in operation. A more integrated approach to this topic seems worthwhile for further research. Since FMEA is a mechanism that is applied very late in the development process on practically ready-for-market goods, the interconnections to the producer value assessment proposed here are scarce. There may possibly be feedback from early prototypes or predecessors fed back into the evaluation process. Nonetheless, FMEA can be a vital step of PSS development, especially if executed in an integrated manner. 18

30 Product Development and PSS 3.4 Life-Cycle Perspectives, PSS and Producer Value Introduction In this section, life-cycle perspectives in product design will be briefly introduced. Further will its relations to Product-Service Systems and PSS design be examined by discussing literature relating to the life-cycle perspectives of PSS. Lastly, the possible impact of life-cycle-related thoughts on the producer value assessment in PSS design will be discussed. One of the most well-known tools in Life-Cycle engineering is Life-Cycle Assessment (LCA). For that reason, it is briefly introduced and defined in the following subchapter. LCA is outlined in ISO 14040:2006 pp Life-Cycle Assessment - An Introduction Life-Cycle Assessment is one of the main approaches to measuring the environmental impact of an offering over its lifespan ( Cradle to Grave ). Since LCA is a very wellestablished method and is a method often used in relation to optimization of products with regard to the environment, it will be briefly introduced in this section, literature on service engineering and PSS relating to LCA will be presented and the relation to the producer value assessment discussed. The Life-Cycle Assessment-method is utilized mostly by producers for the sake of optimizing their offerings and also to facilitate marketing efforts. According to ISO 14040:2006, LCA is fit to assist in the following tasks: Identifying opportunities to improve the environmental performance of products at various points in their life cycle Informing decision-makers in industry, government or non-government organizations The selection of relevant indicators of environmental performance, including measurement techniques Marketing The definition of Life-Cycle Assessment in ISO 14040:2006 is: [A] compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle. Generally, the assessment is split into four sub-steps as listed in ISO 14040:2006: 1. The goal and scope definition phase 2. The inventory analysis phase 3. The impact assessment phase 19

31 Product Development and PSS 4. The interpretation phase Life-Cycle Perspectives in PSS research For obvious reasons, LCA is an integrate part of a number of environment-focused engineering research-activities. As mentioned above, the eco-design methodology proposed by Sakao (2007a) puts a large focus on Life Cycle Assessment, since it is seen as a main source for suggestions regarding the optimization of offerings with respect to environmental issues. Komoto et al. (2005) have performed a life-cycle simulation on PSS. The focus here was, rather than on the environmental impact of the offering in question, on isolating the required conditions for a PSS to function to its full capabilities. Lanza and Rühl have dealt with a major issue mentioned in chapter 2.5: Long term contracts and the associated uncertainties (see chapter 6). The particular focus was on the simulation of service costs throughout the lifetime of a production facility delivered and operated as a PSS. This is achieved through accruing deterministic and stochastic factors of facility operation and performing a Monte Carlo Simulation. Aurich has published a number of papers on the relation of PSS and life-cycle perspectives. In Aurich et al. (2006), a design methodology for PSS with particular focus on the life-cycle perspective was introduced. Sundin (2009) provided a summary of the state of the art in life-cycle perspectives on PSS. For that purpose, the life cycle was divided into the steps of manufacturing, usage, delivery, maintenance, recycling and remanufacturing. In conclusion, the author specifically stresses that providers should maintain a broad view of the entire life cycle to avoid sub-optimizing any specific life-cycle phase, which could put a strain on the other phases. An example of this could be streamlined manufacturing using adhesives instead of screws, which leads to adverse effects in recyclability. This would be a negative effect for the producer in case the ownership of the PSS still lies with him and he is therefore in charge of recycling Life-Cycle Perspectives in Producer Value Assessment The review of literature linking life-cycle perspectives to PSS indicated that life-cyclerelated considerations can provide great benefit to the environment, the user and the producer of a PSS. Especially the relation between better overall environmental performance and increased producer value becomes apparent: One major issue in this realm is marketing, as customers become increasingly focused and conscious of their ecofootprint. Additionally, improvements in recyclability, materials used or preparation for remanufacturing in the design stage can be addressed from a life-cycle perspective and provide a direct increase in producer value through the decision to include a higher-scoring component. 20

32 3.5 Producer Value evaluation and SPIPS Product Development and PSS As said above, the SPIPS-method is a comprehensive method for Product/Service- System design. The most recent published version of this method can be seen in figure Qualitative analysis of customers i) information of costumer value a) Importance of CV b) Satisfaction from the provider and competitors c) information for products/services 2. Customer Segmentation ii) Customer Segments 3. Extracting Customer Value (CV) iii) CV per Segment 4. Importance/Satisfaction Analysis on CV iv) Promising areas in CV 5. Translation to design parameters v) Importance of PSS charact. d) Existing PSS in the/other sectors Legend Step Input to Step Output from Step 6. Idea Creation vi) potential PSS Components 7. Evaluation and Selection vii) feasible PSS offerings Producer Value evaluation Figure 3.3: Steps of the SPIPS-method (modified from Sakao and Lindahl, 2012) The customer-focused PSS-evaluation method discussed in Sakao and Lindahl (2012) constitutes one part of step seven of this method. In order to provide a more complete view of the driving forces behind the selection of PSS components and the eventual decision to bring an offering to market, the method developed within this work will complement this part and serve as the second part of step seven of this design methodology. Producer value is an often overlooked part of product and service design and this method aims to fill this void in the SPIPS PSS design methodology. A focus of future work may be the integration of both producer and consumer value methods to create a tool capable of optimizing PSS offerings for both viewpoints. 21

33 Chapter 4 Traditional approaches to Producer Value and the relation to PSS 4.1 Introduction The goal of this chapter is to introduce and briefly discuss traditional approaches towards producer value and producer value improvement. Further, approaches to producer value assessment in literature regarding PSS will be reviewed. Value Engineering as a method has been used for more than half a century to increase producer value through alterations in the function/cost relation. This method will be discussed in depth as an example of a traditional approach towards the improvement of producer value. 4.2 Producer Value in Literature While traditionally the approach towards the consumer value has been multidimensional, producer value is, if at all, assessed by just a single measure: Profit. This is summarized by Fukuda (2011), saying: In the past, the producer developed products from their own perspective. Thus, value meant nothing other than profit to the producer [...]. Without pointing it out explicitly, methods such as cost-utility analysis (see chapter 3.2.4) address producer and customer value in parallel. Concurrent with what was said before, the side of the producer is mainly represented through optimizing the profit margin achieved through the sale of a good. Other possible non-monetary factors that might contribute to producer value are not discussed. More recently, a diversified approach to value assessment on the provider side is notable. Schäppi et al. (2005) note a list of factors that contribute to producer value, leaving the realm of just profit alone. Still, the direction of the factors mentioned is clearly and one-sidedly leaning to direct monetization (time-to-market, cost, strategic 22

34 Traditional approaches to Producer Value conformity, realization potential etc.). Herrmann (2009), assessing life cycle management, also refers to Schäppi et al. (2005) and the factors pointed out by them. Beyond mentioning factors contributing to producer value, a procedure to explicitly assess it and determine components to optimize producer value is not present. As stated before, it is a natural part of the assessments performed in design engineering, but a more focused and explicit approach is required. This thesis attempts to fulfill this task with special focus on Product-Service Systems. 4.3 Value Engineering Definition Since it was first developed by Lawrence D. Miles of General Electric during the Second World War, Value Engineering (VE) has been one of the major tools in product development and cost optimization. Due to the shortage of materials during times of war, Miles and his colleagues were forced to focus on the function of products and components and on how to create a functional product at minimal cost. In his book Techniques of Value Analysis and Engineering, Miles (1972) defines value analysis and engineering as follows: Value analysis [engineering] is a problem-solving system implemented by the use of a specific set of techniques, a body of knowledge and a group of learned skills. It is an organized creative approach that has for its purpose the efficient identification of unnecessary cost, i.e. cost that provides neither quality nor use nor life nor appearance nor customer features. The means of cost reductions that Miles points out include the use of alternative materials, process chances, and specialized suppliers. A more recent definition is given by Cooper and Slagmulder (1997): It is a systematic, interdisciplinary examination of factors affecting the cost of a product so as to find means to fulfill the product s specified purpose at the required standards of quality and reliability and at an acceptable cost. It accomplishes this objective by analyzing products to find ways to achieve their necessary functions and essential characteristics. In order to provide clarification with respect to terminology, it is necessary to mention that Miles coined the term Value Analysis. The term Value Engineering is used by Miles synonymously to value analysis (compare Miles 1972, 1), while he mostly refers to value analysis. As Fang and Rogerson (1999) point out, Value Analysis/Engineering is originally a re-engineering tool. Since this thesis is focused on the process of designing PSS, the term value engineering will be used to describe the implications of this method to the design of physical components and services, rather than improvement at a later stage. 23

35 4.3.2 The focus-points of Value Engineering Traditional approaches to Producer Value Miles and thus most authors referring to his work emphasize the relation between value, function and cost when examining a product from the provider s point of view. Miles (1972, p. 5) definition of value can be summarized using the following formula, as done by Kaufman (1997): V alue = F unction Cost Hence, there are two scenarios in which the value increases in the provider s perspective: 1. Decrease of costs 2. Increase of function The first point, Decrease of costs, is easily explained: Cost-reductions are in almost any case achieved by leaving something out or exchanging it for something more affordable. That might be material, labor, a certain property etc. Cost is a factor that is the easiest to influence for the producer of the good. On the contrary, the Increase of function is much harder to explain and also much harder to quantify. Usually, a customer expects a product to work in a certain way, or to possess certain properties: it serves its function. In order to illustrate this, an example from Miles (1972, 3) will be used and extended: An appliance knob, like they used to be installed on radios or televisions, has the function of de- or increasing the volume, depending on the direction, in which it is turned. In Miles example, the knob has a red indicator showing the volume currently set. By leaving out the red indicator, the cost of producing the knob was reduced by 75%. There would have been a way of increasing the function of the knob at the same time: If the knob was used not only to increase the volume, but also to turn the device on and off when turned all the way counterclockwise, its function would have increased dramatically. Additional cost-saving opportunities would arise, as the on/off-switch could be omitted. Still, the manufacturer cannot be sure, whether he made a wise decision: Maybe people like it much better to have their device set to the same volume at all times without the need for re-adjustment after turning it on? While cost-improvements are mostly easy to quantify, improvements in the perceived function of a product are not, as this factor is hard to quantify in general Value Engineering and Services The fundamental questions of value engineering The following five questions capture the main points of the value-engineering-process as laid out in Miles (1972), adapted from Kaufman (1990): 24

36 Traditional approaches to Producer Value 1. What is it? 2. What does it do? 3. What does it cost? 4. What else will do the job? 5. What does that cost? Value Engineering and Services Miles et al. and authors referring to him (Kaufman, Cooper etc.) have discussed at length the implications of value engineering on physical products. The focus of the discussion here is on how the five questions posed can be related to service engineering. Question one is quite easy to answer with respect to physical products. Technical terminology provides a clear and one-to-one description of parts or components, and in the case of entirely new developments, a new name is assigned. Since service engineering as a discipline has risen only in recent years (Sakao and Shimomura, 2007), terminology and definition is much more difficult with services. One-word-terms describing all facets of a service are hardly found. A clear definition and mutual understanding can nevertheless be easily achieved, so that this step in the value engineering process can be applied to services without troubles. To answer the question What does it do?, Miles proposes the paradigm of describing all function with two words, one being a verb and one being a noun. This description must be as broad as possible in order not to exclude any side-function and thus value the product might have. A lighter may be described using the words provide flame, since the description light cigarette would exclude the lighting of candles, stoves, wood etc. When examined closely, though, even in this broad description, not all function of a lighter is included. It may also serve as a bottle-opener, even though the engineer might not have intended this use. Since answering question two is already tough for physical components, it gets even tougher for services. Someone might argue, that virtually all services within a PSS may be correctly described with the term ensure operativeness, and this claim is hard to disprove. The approach of value engineering is insufficient with respect to service in this case. Again, the cost of a physical product is easy to determine. With services, though, there is much more uncertainty involved. This makes pre-contract costing very difficult (Erkoyuncu, 2011). Cost-determination is a major focus of PSS development and evaluation; therefore it must be examined thoroughly. In the world of physical products, there is almost always an alternative for the product currently used. In services, it requires much more work and research to isolate alternative solutions. The same is valid for costing alternatives: Without thorough examination and calculation, a meaningful solution is hard to achieve. 25

37 Traditional approaches to Producer Value It is also important to shed light on the way the questions above are posed and how this way of examining a task applies to service engineering. All questions are What -questions. This seems appropriate for physical products, since their existence is dependent on neither time, nor location nor means of use. Services, though, must be addressed in a different manner. As said above, services are dependent on several additional factors: Time is very important. The questions that must be asked here may be: 1. When will the service be executed? 2. How often is servicing needed? 3. How many persons are needed? 4. Are special skills required? 5. Is there a chance rush-servicing is necessary? Since these questions all have an impact on cost and producer value, they must, at least at the surface, be addressed by the evaluation-tool. Conclusion The questions posed in the process of value engineering may be helpful when trying to formulate and define the exact purpose of a service when its inclusion into a PSS is contemplated. Regardless, the depth of the method is insufficient with respect to the complex environment of services, especially when considering questions three, four and five. An engineer may have the principles of value engineering in mind when designing a PSS, but more sufficient and profound methods are needed, particularly with respect to cost Value Engineering and PSS evaluation As explained in the previous section, evaluations based on the value engineering technique are not sufficient for the assessment of product value. Products and services are increasingly offered in an integrated manner, rather providing functionality than mere ownership. It is clear, that the value and cost of such offerings must also be assessed in an integrated way. Furthermore, large companies of the manufacturing sector have high standards regarding documentation and traceability of decisions, so a computer-aided decision-making process can be of very high value through providing transparency. Still, it is important to ensure such tools do incorporate or leave room for decisions based on experience and skill of the engineer using it. Value engineering, by setting its focus entirely on the ratio between function and cost, omits other factors that may lead to the depletion or creation of value. Additionally, both factors are very hard to quantify in the field of service engineering. It is nevertheless vital to address cost and value in the decision-making process while 26

38 Traditional approaches to Producer Value designing a PSS. The decision-maker must be aided in his elaboration of possibilities by a fact-based support. The tool proposed in this thesis is intended for that purpose. By no means are the tools of value engineering obsolete in the efforts to optimize the value of modern PSS-type offerings, although support for decision-makers is needed to assess the cost and value of service-offerings as part of a PSS. Additionally, the offering must be evaluated as a whole, since an optimization of a single part with a subjective improvement in value may lead to a decreased value when the entire offering is considered from a life-cycle-perspective; e.g. through reduced maintainability. It is also important to note that value engineering, as Miles saw it, focuses very much on the smallest possible scale, in which changes lead to large scale-improvements due to the high quantities produced/bought, cp. Miles (1972; p. 33, 39). When discussing components of a PSS, these mostly consist of many parts themselves, which may be optimized using VE. When examining possible components of Product/Service- Systems, as illustrated in Figure 4.1, this approach is in most cases no longer feasiblehence a different method must be developed. Figure 4.1: Value Engineering and PSS Evaluation It must again be noted, that value analysis as intended by Miles is focused on re-engineering. This is especially true with services in mind. Once the process of quantifying a service has been completed in its entirety and there is data from a working PSS available to the supplier, it is much easier to identify weak links and opportunities for improvement. The tool proposed, through its ability to re-cycle through the process with changed figures, may help identify critical factors in advance and spare some trial and error, that value analysis generously accepts as part of the improvement process. The focus of the tool is nevertheless on the design stage of the product development process. As shown in Figure 4.1, rather than improvement and optimization, the focus 27

39 Traditional approaches to Producer Value is on deciding what will be a part of the eventual offering, be it physical products or, even more so, services. While value engineering has its place in development and improvement of components and products, a tool to help evaluate which services and physical components to include in order for the provider to optimize his cost and value is needed. 4.4 Existing Research in the PSS-Field After a review of current literature, only Yoon et al. (2012) have investigated the issue of producer-value within the area of Product-Service Systems. When evaluating a PSS from the provider s viewpoint, Yoon et al. focus on finding the potential risk in the designed PSS model when it is applied in the market [...]. The focus of said paper is thus the evaluation of the entire PSS, compared to the investigation of all of its components, as proposed by this thesis. Further, Yoon et al. take a more qualitative approach to the evaluation of PSS with respect to producer value. The criteria used in the article are shown in Table 4.1. Criterion Macro effects Economic feasibility Technological feasibility Political-legal feasibility Relationship to current competitive providers Table 4.1: Evaluation criteria used by Yoon et al. Evaluation Environment effect Service location, scale of investment, market size, market growth Field test Trend survey of government regulation etc. Simulation Nevertheless, some of the evaluation-measures used may be helpful also on the component-level- in particular these related to economic feasibility (see Table 4.1). In contrast to Yoon et al. s approach, the methodology proposed here focuses on quantitative data supplied by the PSS-engineer directly rather than a measurement of the effects induced by the PSS once it is brought to market. The focus is to directly assess and measure the potential benefit for the provider through including a certain set of components in a PSS. In that sense, both approaches complement rather than substitute one another, since they are also applied in different phases within the design process. 28

40 Chapter 5 Cost Calculation Parameters as part of the Producer Value evaluation 5.1 Introduction The input of provider cost for the components and services included into an offering is an important step within the process in the PSS-evaluation tool. Retrieving the costs is, at first sight, simple: For buying parts, just put in the cost of a single component and the number of components, for self-produced parts, just add labor- and materialrelated costs and multiply them by the number of components used. For services, the calculation is much harder, since many factors such as labor, education, transport, response time etc. must be addressed. Additionally, there are various uncertainties, concerning how often a service will be used, how high future costs will be, and if supplier costs might rise while the initial contract is still in place. Even in the environment of reduced information, for which the evaluation tool is intended, some important effects of cost-calculation must be taken into account. Two ways of gathering and processing cost-related information will be discussed out in the following sections, whereas the exact implementation of these methods will be laid out in chapter 9. It must again be stressed, that the factors discussed and examined here all serve as factors for the evaluation of components of PSS. Even just considering the factors mentioned within the process of design and development may unknowingly lead to an improved result without the assistance and the possible restrictions of an automated software or spreadsheet. 29

41 Costing and Producer Value evaluation 5.2 The Experience Curve Definition and introduction The Experience Curve is a way of illustrating the decline of per unit costs as production increases. Every time the cumulative production doubles, the costs are reduced by a certain percentage (Nagle and Holden, 2002). This decline is, in this case, attributed to the experience gained by workers; for example in the utilization of machinery. Other names of this theory, all bearing slightly different notions, are productivity improvement curve, progress curve, time reduction curve and so on (Stewart, 1995 pg. 212). The experience gained doing a repetitive task corresponds directly to a cost reduction, because of working hours saved (Stewart, 1995). If a 90% slope is assumed for the experience curve, and a task takes 100 hours to execute for the first product, then the same task will only take 90 hours for the second product, 81 hours for the fourth and so on (compare Figure 5.1, Stewart 1995) , , , , , , Hours Units Produced Figure 5.1: Experience Curve with 90% Slope Generally, the slope of the experience curve lies between 80-96% (Stewart 1995, Cyr 2007). Using these two extremes, after the production of 128 units, the time it takes to manufacture the product using the example set above is 21 and 75 hours, respectively. Assuming a working hour generates costs of 50 in total, and only one person is required to complete the necessary tasks, the labor-costs associated with manufacturing the product range from 1050 to Hence, it very much depends on the slope of the experience curve associated with a task, whether or not gathering and entering the respective information is worthwhile in the context of evaluating PSS. The following formula allows the engineer to easily calculate the cost of the current unit (Chase et al., 2006). 30

42 Y x = K x log 2b Costing and Producer Value evaluation Y x K x b Expected Cost of the current unit Cost of the first unit Current unit number Slope of the learning curve Implications of the experience curve on the PSS evaluation Since the effects are significant, especially during the ramp-up phase of the production of a new product or component, within the evaluation, reference must be made to the related issues. It is advisable to gather the related data from the sales and purchasing departments. This might include, but is certainly not limited to, an initial cost and a decline-rate over the number of components included. Services Experience curve effects commonly arise; this is especially true with services in mind. When designing a Product/Service System, the engineer might not have this factor in focus. Particularly when considering that Service Engineering (Sakao and Shimomura, 2007) has not yet received much attention (Baines et al., 2007) and dedicated service engineers are still rare. A design engineer might not consider the experience curve effect when drafting a maintenance schedule or similar activities for a PSS he is setting up. Should the data be retrievable by the measures stated above, estimation to the slope of the experience curve needs to be made, potentially by again retrieving knowledge from other departments of the company. If no increased knowledge in the field is available, even very conservative estimations will lead to the ability to offer a reduced price, increasing the customer value and this his willingness to pay (WTP) for a PSS including the particular service, or leaving the price as is and calculating with increased profits. Actual WTP-calculation is obviously far beyond the scope of this thesis, since an entire branch of economics is focused on the problems revolving around this. It is assumed, that the design engineer constituting the PSS has some historical data indicating acceptable price-levels. Further information regarding experience curve calculation can be found in Cyr (2007, publicly available calculator provided by NASA), Steward (1995) and Ostwald (1992). Products The effects of the experience curve also become apparent with respect to physical components. The following example may illustrate this: If a PSS is tailored and its components designed to fit one customer, in production and assembly the effects of the experience curve will not arise. Should, e.g. by going through the evaluation process illustrated here, the engineer notice possible fields of improvement and slight modifications, which would make the PSS suitable for a much larger number 31

43 Costing and Producer Value evaluation of customers, this could lead to significant cost reductions and thus flexibility in price. This may help the No.1 customer accept a less tailor-made PSS and provide him with increased value. 5.3 Economies of Scale Definition and Importance to the topic Economies of Scale is a principle closely tied to the aforementioned experience curve. Some argue, that it is hard to impossible to separate the two effects, thus rendering one of them pointless (Berndt, 1991). Further, King et al. (2011) assign a large portion of the economies of scale-effect to increased skill in labor - though higher buying power and thus lower prices must also be discussed. Hence, the effects of economies of scale are significant, especially when buying parts or components. Economies of scale are much discussed in literature, such as McEachern (2011) and Mankiw (2006). Both point out, that the effects of economies of scale are very significant at low levels of output (Mankiw, 2006). Since PSS are mostly custom fit, its components are sold and executed on a rather small scale, where large improvements due to economies of scale are possible. Figure 5.2 illustrates qualitatively the dependency of the per-unit cost to the number of units produced (adapted from Mankiw, 2006). Especially notable is the incline of the function at the end of the x-axis in Figure 5.2. This effect is only present in a case where a market is permeated in its majority by a product, and reaching the actors of the market that are yet to come in contact with the product gets increasingly expensive and is not advised. Cellphone-coverage in a sparsely populated country like Sweden is a great example for this effect. A very large portion, say 90%, of the population can be reached by providing coverage in about 30% of the country. Reaching the rest of the population is increasingly costly and reaching everyone is certainly not economically feasible and likely impossible Cost 5 4 Economies of Scale Diseconomies of Scale { Constant Returns to Scale Quantity Figure 5.2: (Dis)Economies of Scale 32

44 Costing and Producer Value evaluation Products The approach here is very much alike the one discussed in the servicesection with respect to the experience curve. Relevant data must be gathered or supplied by different departments of the company. Scale-effects are easily observed with physical products, at least at the surface. In order to be able to find a higher or lesser value of any given component, the slope of the Economies of Scale curve would be helpful. The first section of the declining part of the curve can ideally be seen as a binary logarithmic function, as seen above with the experience curve. With this in mind, it would suffice to enter an initial cost, the number of components included and the decline per additional unit. Thus, basic calculations are possible with just a very small data base. Services While qualitatively including the effects of economies of scale with respect to physical products in the PSS evaluation, the case with services is more complex. The effects of scale are most obviously visible where the costs of a service are fixed. This is easy to observe in software programming and sale. Software may be programmed once but sold many times, generating large scale effects. These are obviously diminished by the additional need for maintenance and support, which every customer requires. This type of service could easily be part of a PSS; therefore scale effects must be also taken into consideration in the case of services when evaluating parts of a Product/Service-System. Since it is not the goal of this thesis to determine, whether or not scaling effects apply for a certain kind of service, this must be done by the engineer. Should this not be possible, this part of the evaluation will be omitted, narrowing the base for decision-making but certainly not making it obsolete. There are other areas of service engineering, where scaling effects do not have an effect significant enough to be mentioned and included in evaluation of PSS. This is the case especially with services that include workers visiting the site in order to perform any task concerning the PSS, or PSS-components being shipped back to the supplier in order to perform any necessary tasks. In general, it can be said that scale effects do not apply where a large amount of the cost-factors appear every time a service is used. Some might argue that in these cases, effects of the experience curve apply. These are discussed in section

45 Chapter 6 Uncertainties in Producer Value evaluation in PSS 6.1 Introduction When examining and determining cost, uncertainties play a large role. This is especially true for the estimation of service costs, as there are many dimensions to service uncertainty (Erkoyuncu et al. 2011). Further, Erkoyuncu et al. have extensively covered service uncertainties in the PSS environment. Therefore, their work serves as base and outline of this section. On the following pages, the challenges of uncertainty in cost and value estimation will be discussed and possible ways of mastering these challenges will be shown. The implementation of the findings within this chapter into the PSS-evaluation tool may be found in chapter General Definition and Scope of Uncertainty Definition Walker et al. (2003) give the following definition of uncertainty: [Uncertainty is] any deviation from the unachievable ideal of completely deterministic knowledge of the relevant system. This definition is obviously not the only definition that may be found, as there are more simplistic approaches, merely defining uncertainty as the absence of information (Rowe, 1994). Walker et al. s definition serves as a base of future argumentation and the term will be used in the sense stated above The Nature of Uncertainty Commonly, uncertainty is referred to in two dimensions: Aleatory and epistemic. Parry (1996) describes the aleatory nature of uncertainty as a term characterizing a random 34

46 Uncertainties in Producer Value evaluation in PSS or stochastic occurrence that may be described by probabilistic models. Epistemic uncertainty refers to uncertainty that is due to inaccurate data, measurement error[s], incomplete knowledge, imperfect models [...] etc. (Walker et al. 2003, 9). The connection between the two forms of uncertainty is illustrated in the following example, adapted from Parry (1996, pg. 120): When approximating the amount of coffee consumed by an average college student, the probabilistic model needed to do that reduces the aleatory uncertainty with reference to college student coffee habits. The epistemic uncertainty refers to the accuracy of the model used and is reduced by improving the base of the model, e.g. by increasing the size of the sample Uncertainty and Risk The terms risk and uncertainty have first been differentiated by Knight (1921). The general understanding is that while risk is based on measurable probabilities, with uncertainty, this is not the case. It often occurs that uncertainty directly affects risk: When entering a car, based on statistics, one is able to determine the risk of encountering an accident during the journey. Still, the uncertainty as to when and where a crash is going to occur renders this risk assessment almost pointless. The occurrence of car accidents is aleatory, though some might argue that there are spots where accidents occur frequently, with this knowledge reducing uncertainty and making risk-assessment more fruitful. As Erkoyuncu et al. (2011) state, even though distinctions can be made, both terms refer to a similar situation, in which some aspect of the future cannot be foreseen. Since uncertainty significantly determines individual s ability for risk-assessment, the focus here will be on uncertainty and how it can be assessed by functions of the proposed tool Classes of Uncertainty When examining uncertainty and the forces that drive it, it can be helpful to decompose the term and its implications in order to arrive and a better understanding. Rowe (1994) has proposed and defined four classes of uncertainty: Table 6.1: Classes of Uncertainty (adapted from Rowe, 1994) Class Explanation Temporal Uncertainty in future states Uncertainty in past states Structural Uncertainty due to complexity, including models and their validation Metrical Uncertainty in measurement Translational Uncertainty in explaining uncertain results 35

47 Uncertainties in Producer Value evaluation in PSS Rowe further states: All four classes occur in any situation, but depending on the situation, one or more dominate. 6.3 Uncertainty in relation to PSS optimization Reducing Uncertainty within the PSS optimization Within this work, there are two completely different areas, in which effects related to uncertainty occur: Firstly and more obviously, uncertainty applies to the area of service costing. There are many factors affecting the determination of costs of services in a long term contract, which remain uncertain. This is especially true for long running contracts and when designing a product-service system in an early stage of development. Secondly, the eventual effect of the properties assigned to physical components or services is hard to determine. The user of the evaluation tool does, in most cases, not have access to substantial data indicating the effect of a certain component upon the producer value of the entire offering. Still, the tool s purpose is, within an environment lacking information, to enable the engineer using it to make a fact-based decision that serves for documentation and future reference and, much more importantly, is superior to the one just based on gut-feeling Categories of Service Uncertainty In order to determine, which measures regarding the management of service uncertainties lie within the scope of this work, the main categories of service uncertainty as stated and explained by Erkoyuncu et al. (2011), in Erkoyuncu (2011a) referred to as CAPTOE, will be introduced: (1) Commercial (Contractual) Uncertainties Within the service sector, two types of contracts have received increased attention (Ng, 2009): One the one hand, a fixed price contracts with defined KPIs and pain- and gain-share mechanisms. In this case, assuming no unlikely events occur, the uncertainty is owned by the producer. Another approach is associating the requirement for maintenance rising and falling with the use of the equipment. In this case, the customer may bring some uncertainty into the relation to the producer, but he also mostly bears the risks arising from this, since he is being held responsible for a sudden increase in usage and thus the higher need for maintenance. (2) Affordability Uncertainty According to Erkoyuncu et al. (2011), this factor of service uncertainty refers to the ability to estimate possible monetary constraints 36

48 Uncertainties in Producer Value evaluation in PSS of the customer (ability to pay) as well as the perceived value of the service offered (willingness to pay). (3) Performance Uncertainty This factor influences the ability of the provider to meet the performance requirements set in the initial contract. (4) Training Uncertainty Training Uncertainty considers factors affecting the delivery of training requirements set in the contract. (5) Operation Uncertainty This type of uncertainty refers to activities directly liked to maintenance activities as detailed in the contract. (6) Engineering Uncertainty This category considers factors associated with providing indirect activities to meet maintenance goals Implications of categories on PSS optimization Within this section, the implications of the different categories of services on the PSS optimization will be discussed and ideas and approaches to reducing uncertainty are proposed. Although the proposed uncertainty-categories are focused on services, some elements might also apply to products. The person performing the evaluation and optimization may also consider uncertainty when dealing with these physical products. In a possible future software-tool, all categories should be available for evaluation, although not all may be applicable. (1) Commercial Uncertainties In most cases a company will sell a PSS in its entirety and therefore, the same contract is valid for all components. Should this be the case, there is no effect of the contract on the function of individual parts of the PSS, as all must operate under the same contract. Should the provider aim to reach individual agreements with respect to parts of the PSS, then this may be a factor affecting the uncertainty associated with parts of the PSS. Thus, when composing a Product/Service System, the type of contract and the associated uncertainty must be considered and evaluated entering data with respect to services. (2) Affordability Uncertainty This is a very important factor, not only in the area of services, but also, though on a smaller scale, with physical components. When trying to decide, which products and services to include in a PSS, it is important to consider whether individual parts of the system may throw the customer off due to a relatively low price/value ratio. Even though this thesis focuses on the producer side of the evaluation problem, this factor must be taken into account. Therefore, as a first step, products or services with similar functions must be grouped. The easiest way 37

49 Uncertainties in Producer Value evaluation in PSS to quantify the differences between the components can be assessed qualitatively in terms of better/worse. Data from the sales-department might help with this. This must be done cautiously, though, since some users may jump to the conclusion that the product that they think is superior on this individual field, may be superior in all fields, possibly leading to the exclusion of options that might have fared way better on other areas of evaluation. Tackling affordability uncertainty is one of the major focuses of research in business. In order to significantly reduce uncertainty in this area, further research is certainly needed; the research at Cranfield University (Roy, Erkoyuncu et al.) is of particular importance here. (3) Performance Uncertainty This factor is very hard to estimate upfront, a risk reduction in this field will be very hard to achieve. It must be assumed, that all contractual provisions are carefully examined and adjusted to the individual capabilities of the provider. This factor should not be part of the evaluation of the PSS, as it would not lead to a profound improvement of the decision-making background. (4) Training Uncertainty The question that must be asked regarding this type of uncertainty is: Does the respective service include training efforts at the customer s production facility? Additionally, the likelihood of disruptions in this training process must be assessed. Most engineers will be able to gauge these factors by examining historical experience in the company s previous sales. (5) Operation Uncertainty Within the scope of this category, uncertainties in relation to the performance of tasks directly at the PSS sold may be discussed. In this iteration of the method, it can be assumed that the assessment with open questions and values assigned by the user is sufficient. (6) Engineering Uncertainty The same that has been said in category 5 is also applicable here. The assessment of this uncertainty as explained above will, at this early stage, will also be done by assigning a discrete value at the will of the user Generation of uncertainty values All of the factors under section should be considered when assigning values to individual components that might be used within a PSS. In order to simplify this process, the factors mentioned above are summarized in abbreviated form in Table 6.2. At this phase of developing a PSS evaluation methodology, it is sufficient for the engineer to self-assess his entries and guesses with respect to the uncertainty-factors stated above. He then should assign an uncertainty to every individual component, basing all of them on the same ground in order to make them comparable. A simplified method of dealing with this is presented below. 38

50 Uncertainties in Producer Value evaluation in PSS The questions have been derived from Erkoyuncu et al. (2011) as explained above. They are not exhaustive or all-encompassing. The intention is to make a first step towards reducing uncertainty within this approach to the problem that may be extended in future work building on the base that this thesis aims to set. Erkoyuncu et al. (2011) focused on the uncertainty in cost estimation, but a more general approach is called for here. Table 6.2: Self-Assessment-Questions regarding uncertainty Type of Uncertainty Examples of Self-Assessment-Questions Commercial Uncertainty Is individual contracting required for this component? Affordability Uncertainty Are there components similar to this one? May the value/price-ratio be off-putting for the customer? Training Uncertainty Are training efforts at customer facilities necessary? May there be difficulties with training (e.g. steep learning curve)? Operation Uncertainty May disruptions in the field of maintenance (etc.) arise? Engineering Uncertainty Will maintenance-goals be met? When answering these questions, the user must self-assess the uncertainty associated with answering. Should a solid base for this information be obtainable, it must definitely be used. This might be expert opinion within the company, knowledge gained from previous transactions etc. If a more profound evaluation is sought, all elements stated under should be carefully assessed. The information used here and how it was obtained should be noted and saved, as it will be reused later in efforts to reduce uncertainty. Assigning values to uncertainty-types When trying to assign a certainty to ones assessment of a component, the following procedure is proposed: A scale of 0% to 100% is given. 100 percent means that there is full certainty in the respective type of uncertainty. At 0 percent, the assessment made with respect to a type of uncertainty is essentially worthless, the uncertainty is not assessed. All values in between hence indicate a varying level of certainty when assessing the differing 39

51 Uncertainties in Producer Value evaluation in PSS Table 6.3: Example of Uncertainty assessment Uncertainty Evaluation Explanation Commercial 100% One contract for the entire PSS will be in place Affordability 75% New component on the market, customer value undetermined Training 80% Training is necessary, is expected to go smoothly Operation 70% New component, maintenance may cause disruptions Engineering 90% Maintenance goals set pessimistically in advance, meeting them is very likely Arbitrary Average 80% uncertainties as stated above. Table 6.3 gives an example of what this assessment may look like. Lindahl (2005) stresses the ease of implementation as one of the most important factors for a tool to be adopted and used by engineers. Overcomplexity would hinder this, even though slightly more significant results may be achieved. Therefore, a single uncertainty value may be used at this stage of the method s development. Again referring to Table 6.3, the indication would be that the parameters describing a particular component (details on this in chapter 7) bear a certainty of 80%. Weighting among the different uncertainties may vary with every component, hence simply calculating an average (83% in this case) would not do justice to the complexity of the problem. Balancing all uncertainties would be an interesting challenge in the future, since obviously, assessing uncertainty is associated with lots of uncertainty itself. For this reason, the single, arbitrary uncertainty is used in the method proposed here, in all due awareness of the difficulty of the assessment. Erkoyuncu et al. (2011) have developed a framework to tackle costing uncertainty, which might be interesting for further reading. The categories provided within this section focus mainly on service uncertainty, although most of them can be extended to physical components as well. Also, the classes given in section serve as additional implications as to which areas bear high uncertainty. Through the iterative process of obtaining information to reduce uncertainty, the engineer using the method or the software will gain additional knowledge about the components and therefore make more educated decision, even though most of them will still be located in the field of guessing. 40

52 Uncertainties in Producer Value evaluation in PSS 6.4 Methodology to tackle uncertainty in producer value evaluation Motivation and Scope Gathering substantial data when trying to reduce uncertainty is a difficult task. In most cases, only a qualitative assessment of the present uncertainty in several products/services is possible. Measures to validate the findings made and to quantify qualitative information have been proposed in literature. In order to provide practitioners with some insight into this field, one possible strategy is laid out in short within this subsection. The main focus is to motivate the engineer working on the reduction of uncertainty to rethink and evaluate his assumptions and to provide him with a more firm basis for cost estimation and thus product and service evaluation. Also, the comprehensibility and traceability of the decisions made is improved. In order to quantify the decision-making base for uncertainty-related assumptions, the NUSAP system will be utilized. The base of this is the research of Erkoyuncu et al. (2011). Additionally, Erkoyuncu et al. offer a more sophisticated framework including agent-based modeling. Including this does not match the target of this thesis, but examining it in future research may yield more reliable data. As a first step, NUSAP is sufficient The NUSAP System to quantify qualitative information Van der Sluijs et al. (2005) define the NUSAP-System as follows: NUSAP is a notational system proposed by Funtowicz and Ravetz (1990), which aims to provide an analysis and diagnosis of uncertainty in the knowledge base of complex policy problems. Thus, the aim of the NUSAP-System was very narrowly aimed at reducing uncertainty in public policy, especially regarding environmental policy (Van der Sluijs et al., 2011). Erkoyuncu et al. have incorporated these findings into their efforts in reducing service uncertainty with PSS offerings (2011). The approach is adopted here is to provide practitioners with a base for transforming qualitative data such as expert opinion, historical knowledge and educated guessing into quantitative, numeral values. This transformation is a vital support for enhanced decision-making in the situations discussed. Even though Erkoyuncu et al. (2011) propose a complete framework for reducing uncertainty in service cost estimation, a less far-reaching approach will be taken in this multi-focused thesis. Expanding this may be the focus of future research. NUSAP is an acronym conveying all five qualifiers of the system as described in van der Sluijs (2005), which are introduced as follows: 41

53 Uncertainties in Producer Value evaluation in PSS (1) Numeral A number is assigned in order to later allow for grouping of the individual components. The scale is no issue here, although among each other, there should be a reliable connection between these numeral values. (2) Unit Any unit may be chosen here, although in many cases, where only scoring is of interest, this may be omitted. Additional information will be conveyed, such as the date in case of monetary units etc. (3) Spread This category includes the randomness of the assessment. This may be an assumed random error or the variance of statistical data. It may be conveyed as a number and a respective indicator showing the tendency of the assessment (±, %, etc.). Using this tendency, the numeral assigned in (1) may be assessed using statistical and mathematical techniques such as sensitivity analysis. (4) Assessment Van der Sluijs et al. (2005) describe this category in relation to the aforementioned spread: When spread is seen as the random error, assessment may be viewed as the systematic error. Other uses of the assessment category are, if used in the field of statistical testing, the significance level, or, in the case of numerical estimation, indicators such as positive or negative. This would correspond to the factor of expert judgment, which will supposedly often be used in PSS evaluation. (5) Pedigree Within this section, the process of acquiring the information above will be evaluated. A set of criteria will be given to assess the way information was produced, each referring to a numeral value. These pedigree-matrices differ greatly, depending on the type of information referred to Reducing Uncertainty in PSS evaluation using NUSAP The NUSAP system will be the primary measure used to reduce uncertainty within the PSS evaluation process proposed within this thesis. In this section, it will be explained how the factors of the system relate to the data gathered in the evaluation process and what steps should be followed in order to achieve meaningful results. As explained in Chapter 7, numeral values will be assigned to the different properties by the engineer. Indications as to how this data will be obtained have been given. It is these factors, that eventually lead to the assessment of the producer value of different components, whether physical or services, and thus the uncertainty within this assessment is sought to be reduced. Hence, these numeral figures will correspond to the Numeral section within the NUSAP system. They are the base on which all else is built. With reference to Unit, significance to the assessment is not apparent. It is left to the engineer, whether or not he wants to assign units to different entries. 42

54 Uncertainties in Producer Value evaluation in PSS Table 6.4: Pedigree Matrix for scoring uncertainties (Erkoyuncu et al., 2011) Score Basis of Estimate Rigor in assessment Level of validation 1 Best possible data, large sample, use of historical field data, validated tools and independently verified data 3 Small sample of historical data, parametric estimates, some experience in the area, internally verified data 5 Incomplete data, small sample, educated guesses, indirect approximate rule of thumb estimate 7 No experience in the area Best practice in well established discipline Sufficiently experienced and benchmarked internal processes with consensus on results Limited experience of applied process with lack of consensus on results No established assessment processes Best available, independent validation within domain, full coverage of models and processes Internally validated with sufficient coverage of models, processes and verified data. Limited independent validation Limited internal validation, no independent validation No validation The Spread category makes use of the uncertainty-values given as explained in Datta and Roy (2010) have mentioned that Monte Carlo simulation is effective when evaluating three-point estimates in uncertainty evaluation, mainly when assessing the factor of cost in long-term service contracts. Datta and Roy (2010) also make reference to Lanza and Rühl (2009), who have developed a comprehensive method to calculate service costs of production facilities throughout their life-cycle. Erkoyuncu et al. (2011) do not suggest any definitive method to be used in this step of the NUSAP assessment. To include a contemporary technique to tackle cost-uncertainty in the method presented here is a next step in improving the value of the method presented and a focus for future research. Should any systematic errors occur, which are supposed to be addressed within the Assessment-section of the NUSAP-process, these should be handled before entering the evaluation-phase of the PSS development. Therefore, this category will be omitted in the evaluation process proposed here. The Pedigree- assessment is a very important and valuable part of the process of assessing uncertainty. Not only because of the information conveyed, but also because of the reviewing and rethinking it forces the designer to do: When trying to locate his estimates within the pedigree-scale, he must thoroughly assess the estimations, guesses and data that lead to the resulting values. This process may lead to an improvement of the quality of the data entered in the first place, thus improving the accuracy of the entire estimate. The pedigree matrix (see table 6.4) used here will be taken from Erkoyuncu et al. (2011). Although the authors intended for it to be used within the 43

55 Uncertainties in Producer Value evaluation in PSS scope of cost-assessment, it may also be applied here, where the value-assessment is also in focus. Future research in this field may lead to a more tailor-made matrix for the proposed purpose, since this is not the main focus of this thesis Results of the NUSAP-Based uncertainty-calculation The task of fully exploring NUSAP and all related issues is too large to fully resolve within this thesis. In order to provide the engineer performing the assessment with comprehensible and usable results, a color-scheme has been chosen for use as an indicator of the quality of the data utilized for the evaluation with respect to uncertainty. Since this quality might range from just a gut-feeling and no past experience with an entirely new component or offering that has no example in the market to a wellestablished offering with a lot of statistical data regarding sales, pricing etc., a three level indicator was determined to be appropriate, not only because of its familiarity with the user but also because a more elaborate structure would require substantially more and in-depth research in this specific field. Since again, as with other items of assessment, a weighting between the different pedigree-assessment categories is not feasible at this point, the following simplified approach is taken: The scores from all three categories are added up. The error made through not-weighting is assumed to be annihilated by guessing errors in the scoring itself. In accordance with table 6.5, the sum of the pedigree-scores will lead to a different color-code of the associated uncertainty-value. Table 6.5: Color-codes for Pedigree scores Sum of scores Respective Color 6 Green Yellow 13 Red The indicators were determined as shown in table 6.5 for the following reasons: When a six or better is scored, a maximum of one three-score is permitted, leading to a strong assessment and reduced uncertainty. The mid-range values up to twelve allow for medium scores across the board or one rogue result, indicating that the results of the assessment should be addressed with care. Scores from 13 and above can, save for some extreme diversion which is unlikely, be only attained with bad scores across the board. This approach is in need of improvement by a more conclusive procedure as the development of this method progresses in the future. The prior aim of this procedure within the scope of this thesis is so sensitize the user for possible errors in the assessment of the producer values that is due to a lack of sufficient data or past experience. 44

56 Chapter 7 Properties to determine producer value 7.1 Introduction Producer value is the essential unit of measurement for the method proposed in this thesis. The determination of this value within the area of PSS is a complicated task. In order to simplify the process of choosing components that provide an optimized benefit to the producer, certain characteristics must be assigned to these components and eventually evaluated. In this section, methods and characteristics to determine the producer values of components will be explained in their use and background. Existing research on producer value assessment in PSS design has been introduced and discussed in chapter 4.4. Further, the presence of producer value in literature in general was discussed, and it was found, that the main focus for the determination of producer values lies with profits or variables directly linked to it (see chapter 4.2). While these indicators are very important and also a major part of the assessment as introduced in this thesis, they are insufficient in today s multidimensional environment. They focus, referring to the categorization shown in figure 7.1 of the following subchapter, mainly to the immediate effect on the operational scale. From the starting point provided by Schäppi et al. (2005), determinants for producer value were derived. They are discussed in the following sub-chapters as to their relevance to PSS and how their impact on producer value can be assessed. 7.2 Categorization of value parameters The decision, what a PSS offered by a company is supposed to be comprised of, mostly does not lay with the management, but with the engineering level, especially when small to medium size companies are considered. When comparing a PSS to a regular physical-product-only offer, though, it is clear that the components of a PSS system play a decisive role in the strategy in the coming years, sometimes even decades. The 45

57 Properties to determine producer value following example might illustrate this issue more comprehensibly: Company X used to sell floor-cleaning machinery as a standalone product for decades, shipping worldwide and becoming an important player in the market. Since the size of the company and the sales achieved did not allow setting up service representatives worldwide to contract and control maintenance and repair of their goods, X decided not to offer any services. Hence, the design of their offerings was completed without services in mind, as explained for example by Aurich et al. (2004). As the company evolves, it seeks new fields of business and decides to offer its machinery with long-term maintenance-contracts or even as a result-oriented PSS (Meier et al., 2010), selling square meters of floor cleaned to malls, universities etc. It is assumed, that the additional revenue allows the setup of an international service network and design changes that are supposed to simplify service and maintenance are planned. All these decisions are made by the management of the company, but it is the engineers and designers, who have to decide on the new product, what it comprises, how it is supposed to look and how it will work. Strategic Tactical Operational Strategic Tactical Operational Producer Customer Figure 7.1: Categorization-Pyramid for producer value parameters This method helps engineers make these decisions in an efficient and traceable manner. The categorization of value parameters helps assess different components the way managers do, by sorting them into short-term (operational), medium-term (tactical) and long-term (strategic) decisions (Figure 7.1). This increases the understanding of the challenges and necessary decisions within the engineering department and places the decisions made on firm ground. The categorization of the respective characteristics will be noted as they are introduced in chapter 7.3. It must also be noted, that the categorization of characteristics in a scheme such as shown in Figure 7.1 helps put the values found into perspective. For example, if a product receives high evaluations mainly in the short-term operational space and low values in the strategic category, it might be useful for a company seeking to pass a current low-point in company revenue, but it is not well-equipped to foster long-time growth or stability. 46

58 Properties to determine producer value 7.3 Characteristics of Producer Value in PSS Introduction In order to eventually create a ranking of all the components available, common criteria need to be found. Within this section, the criteria found and the possible ways of implementing them into a tool will be discussed Knowledge as a criterion for PSS evaluation Scope As a first and essential criterion for the producer-focused value of a PS System, the term knowledge comes to mind. Knowledge is defined as facts, information, and skills acquired through experience or education (Oxford Dictionaries, 2010). It is self-evident, that in a competitive environment, acquiring knowledge is essential in order to increase the competitiveness of a company and, eventually, make higher profits. Further, in a world faced with climate change and scarce resources, knowledge can also lead to a cutting edge in the respective technologies, thus ensuring fast advancement and an advantage over competitors and for those who use the product - and even those who do not. To illustrate this, the following example is given: Rolls-Royce offers with their civil aircraft engines a program called Total Care (Rolls-Royce, 2012). The scenario detailed here was similarly laid out in Baines et al. (2007): In short, Rolls-Royce monitors the performance of the aircraft and is thus able to schedule maintenance or repair ahead of the surfacing of any errors, reducing downtime and saving their customers money. It is obvious, though, that Rolls-Royce gains a lot from this relationship, other than monetary value through maintenance contracts: They remain in close contact to their offering throughout its lifetime. This enables the company to exactly locate areas, where errors frequently occur, as well as possibilities for optimization, be it individual parts or the entire engine. Remote monitoring, being a component of the Total Care package, makes it very easy to monitor for example fuel consumption and through that, to offer an improved product in the future. The service component remote monitoring within the PSS-offering aircraft engine bears an enormous producer value and is very likely to be vital to the company s success. There are many scenarios, where this might be the case for an offering. The purpose of the PSS evaluation tool is to help identify these scenarios and the components necessary. Quantifying Knowledge in a PSS evaluation Whether the engineer is using an automated tool or following the procedure by hand, he has the chance to choose if Knowledge is an applicable criterion to quantify the producer value of a certain component. In order to achieve a relevant input on this parameter, it must be clear to the engineer, what the context of knowledge within the scope of this thesis is: 47

59 Properties to determine producer value 1. Customer feedback, directly or indirectly provided by the component 2. Knowledge gained through design and production of the component (physical) 3. Knowledge gained through servicing and maintenance of the component (service) 4. Information about the state of the market conveyed through the use of the component 5. Information about the use of the component and the offering as a whole Additional parameters fitting into this list may be added to it. In part, even passive knowledge restrictions may end up being a tremendous producer value: When deciding to sell a result-oriented PSS, the customer comes in virtually no contact with the product. When maintenance and operation are all done in-house, the chance for theft of intellectual property (designs from manuals etc.) is minimized. Some PSS-components, such as Maintenance by company representatives may score higher on knowledge than Maintenance by external personnel, even though according to the points mentioned above, both may not differ much. As indicated before, this evaluation characteristic serves as an initiator for a thinkingprocess within the engineering personnel. In contrast to traditional component design as laid out for example by Pahl et al. (2007), which focuses mainly on the function to cost-ratio (compare to Value Engineering in chapter 4.3.1), the process laid out in this thesis takes a more life-cycle-inclined approach. Within the scope of figure 7.1, this means, that the engineer may rate his assessment of the knowledge-based producer value of a component as long-term or strategic. This may justify higher spending or even monetary losses when including a particular component, if the outlook shows that this initial investment may pay off. This is true not only for the knowledgecharacteristic, but for all characteristics mentioned here. Consequently, the knowledge-characteristic must be located in the tactical to strategic portion of the pyramid in Figure Relation to customers Scope Product-Service Systems are an ideal offering if close ties between producer and customer are desired. According to Meier et al. (2010), the benefits of offering PSS for the producer-side are getting more revenue out of the additional service business with the customer and the longer business relationship. These advantages can only be established by taking the whole life cycle into consideration. This also reinforces the statements made in section The value of close ties to customers As with knowledge, assessing customerrelations is a difficult task. Therefore, it must be again left to the user of the methods 48

60 Properties to determine producer value provided whether or not to enter a value estimate on the benefits to the customerrelation offered by this component. The same scale as stated above applies here. Factors that may influence scoring are 1. Service contracts in the areas of maintenance, repair etc. 2. Service-contracts that provide functional and performance-updates for a defined period of time 3. Physical components that no competitor can provide (patent-protected etc.) 4. Component aids or is even essential to the integrated design of the product-service system Especially the last statement may need some clarification, which should be provided through the following example: A regular laptop computer of one of the large manufacturers (such as Acer, HP, Asus etc.) is a set of parts that are assembled within a casing and shipped to consumers. Crucial elements, such as RAM and the hard drive, are standardized. Once the ownership of the laptop has passed to the consumer, the relation the manufacturer is, for the most part, over. Warranties are offered with most laptop computers, but again there the manufacturer serves only as a channel connecting the consumer and the manufacturer of the defective part. Possible earnings from this are minimal. If the user wants to upgrade his system, for example from a HDD to a SSD, all he needs to do is loosen a few screws on the base of the laptop, replace the unit and reinstall the operating system. Casual users might contact their nearest computer-shop to do this work for them. Apple, the most profitable computer manufacturer at this time (Goldman, 2012), takes an entirely different path: They offer a completely customized system containing almost no straight-from-the-market components. They were also one of the first companies offering laptops with non-removable batteries. Hence, no matter how long after the sale of the product and the possible end of the warranty, the direct contact to the customer remains intact: The only way to replace the battery is either to directly send the laptop to Apple or have it changed in one of their certified locations. The same goes for upgrades and so forth. It must be suspected, that before long Apple will even deepen this relationship, offering a true PSS with guaranteed repair- and uptime for a certain period of time. The Apple Care Plans are one step into that direction (Apple, 2012). This design paradigm might not be transferable to all offerings, but even small steps into that direction may offer the opportunity to strengthen ties to the customer and increase revenue. Locating the value of a close customer relationship in the pyramid-view (Figure 7.1), it is clear, that this plays a major role especially in the tactical and strategic area, thus mid- to long-term thinking. This may be explained, using the example above: Some manufacturers focus on high sales volumes instead of quality, which may lead to a large short-term revenue, but likely not to recruiting a large number of recurring customers. 49

61 Properties to determine producer value On the other hand, others focus on top-notch quality, design and development. This approach has very high up-front costs, but in the long run, returning customers and in some cases even brand loyalty may make up for this Time-to-market and its producer value Scope In some cases, a very small part of an offering can lead to tremendous delay in the time it takes to bring a product to the market. This is true for massmarket and even highly customized goods. Cohen et al. (1996) have, although not recently, indicated, how the speed of new product development, performance and timeto-market can be balanced in order to achieve good results on all fronts. Partly, this can be transferred to designing PS-Systems. More recently, Alfonso et al. (2008) have examined the relation between the use of established product development practice (see Chapter 3), target costing and time-to-market. Further, Lay et al. (2009) have said that offerings possessing an operational focus (Availability-oriented in chapter 2.5) can lead to economies of scale and a reduction of lead times. In a PSS, with a large number of components of various types forming the offering, some may greatly contribute to in- or decreases in the time it takes to bring a product to market. This section intends to address this issue and point out means of assessing the time-to-market value of PSS-components. Assessing time-to-market value At this point, the assessment should be very straight-forward. For some of the components, there will be quite reliable knowledge on the time to market from previous experience. In this case, they may serve as the measure for other components competing with it. Also, the reliability of the estimations will be expressed in the uncertainty-assessment using the NUSAP-scheme. Within this area, naturally, products that have been used before will have an advantage over new developments, which require additional time for testing, certification etc. The same is valid for services: It is essential to assess, whether additional staff-training is necessary, if all service facilities are present, or if there is even a need to hire extra staff in order to perform according to plan. For these reasons, it would be helpful to focus on the following issues when assessing time-to-market and its producer value: 1. Development stage of the component or relations to a possible supplier of the component 2. Prior experience with the component 3. Presence of required staff 4. Presence of required skill 5. Need to set up additional facilities 50

62 Properties to determine producer value At this point it becomes clear, that the various characteristics are not without interaction. Knowledge gained from a previous offering might drastically affect the producer value of the components of a present PSS. Within one single PSS, it is essential, though, to assess all value-affecting characteristics as independently as possible. With reference to the pyramid-view shown in Figure 7.1, it is assumed that timeto-market refers to the short-term, tactical thinking. Decisions initiated with this characteristic in mind will likely be motivated by expectations and assumptions directed at the very near future, e.g. beating a competitor to a market launch Infrastructure Scope This category is chosen to be broad, so the engineer performing the evaluation has the opportunity to refine it with subcategories if he deems this to be appropriate. The category is intended to encompass anything from manufacturing infrastructure, sales infrastructure to service infrastructure. These subcategories and how they may be evaluated will be discussed in the following sections. Depending on the subcategory, these producer values cover nearly all of the categories shown in the pyramid (figure 7.1). Manufacturing belongs with respect to possible investments into the operational, with respect to use into the tactical and strategic category, while sales and service infrastructure can both be located in the medium- to long-term section. Manufacturing Infrastructure This category may be the most obvious and easy-to-evaluate of the three categories given above. Using the categories given by Schäppi et al. (2005), this subcategory would be assigned to strategic conformity. Since Schäppi focuses on product (or in this environment: component) development and does not take the offering-perspective an integrated solution such as PSS requires, this categorization is not applicable to components, since the functionality of the offering must be taken into account in its entirety. Further, this category applies to components (when re-cycling through the method, also clusters or offerings) that are, at least in part, produced in-house. Evaluation with respect to this is straightforward and mainly consists of an assessment of present facilities and the cost of building/extending facilities. This includes checking for crosscompatibilities with other components or products. In short, the following points are important to assess when evaluating components within this category: 1. Presence of required facilities 2. Cost of setting up additional facilities 3. Shared use with other components 51

63 Properties to determine producer value Sales Infrastructure This category applies mostly to the offering-perspective and will likely come into use as the evaluation is repeated after clustering (see chapter 8) or after putting together a rough draft-offering, but may, in cases of high-value components, be also used in the component-perspective. Schäppi et al. (2005) assign this to the cost-category of product development, which obviously applies to almost all factors of product development. A more detail-oriented approach is deemed necessary here. The focus in this category is on offerings that may, if marketed accordingly, and if they are of high quality, find a large market on a global perspective. In short, the following questions are a starting point to evaluate and offering or component with respect to the sales infrastructure: 1. Are sales divisions set up in vital markets? 2. Can they be set up at acceptable cost? 3. Is there a chance of cooperation with local partners? Service Infrastructure This category is essential for service-components, but also for components, that are themselves essential in supplying functionality for services to be performed. Essentially, the factors determining the producer value are very close to what was said with respect to sales. An additional factor to consider is the possible exposure of intellectual property to third parties, especially in regions of the world where intellectual property theft is likely to occur: 1. Are service stations set up in the relevant markets? 2. Can they be set up at acceptable cost? 3. Are appropriately skilled technicians present? 4. Can third parties perform service activities where setting up dependencies is not feasible? 5. Is there a danger of exposing intellectual properties to third parties? State of the Market and its development Again, this category applies in a very large part to the offering perspective. Both Schäppi (2005) and Eppinger/Ulrich (2008) name market size and market growth rate as factors in this category. As they focus on product development and decisions whether or not to go forward with the development a certain product, the focus here is slightly different: The decision, to go to the market with a PSS has been made, the decision what this PSS is made up of, has not. This will determine the alignment of the offering 52

64 Properties to determine producer value (e.g. service-heavy, oriented towards a certain niche) and requires an additional assessment: This is true for certain vital components (such as a service that is intended to create substantial revenue over the life-cycle) and various offerings comprised of different components. In order to determine the producer value with respect to this category, the engineer performing the evaluation may refer to previous evaluations made going into design for the PSS, adjusting them to the requirements of the component/offering. 1. Is there a sufficient market for the respective offering/component? 2. Is the market growing/matching expectations to provide sufficient revenue? Further work on the evaluation-method has shown that assessment with regard to the market state is inconclusive and in most cases does not provide information going beyond the other producer values. It was therefore decided to omit this category in chapter Life-Cycle and Environment General environment-related considerations with focus on policy Environmental considerations are an integral part of PSS. The producer value of the factor Eco-efficiency is not immediately apparent, but becomes clear once it is given some deeper thought. As said above, Yoon et al. (2012) mention environmental factors as a category to assess producer value. This is logical once the factors of policy and governmental regulations are taken into account. This mainly applies to large machinery that produces a lot of carbon dioxide or similarly relevant byproducts, but in the future this might be relevant on a smaller scale, too. In this light, energy-consumption of components and offerings is an essential factor. Wasteful management of energy-resources might lead to taxation by government authorities or disadvantageous positioning in the market. Also, materials and recyclability play a very large role: Concerning e.g. electronics, producers are obligated to take them back and recycle them according to regulations in place within the EU (EU Directive 2002/96/EC). The choice of materials can therefore, over the lifetime of the product, lead to significant costs or savings and also impacts the environment greatly. Since PSS in their property of being an integrated offering of products and services, are intended to be used over long periods of time, possible advances in environmental regulations on all fields should be considered beforehand. Failing to do so might lead to great losses in revenue that have been assigned to services over the lifetime of the product. In general, the following points might be helpful when assessing a component or offering with respect to environmental issues, especially focusing on policy: 1. Consider energy consumption, carbon output and associated costs 53

65 Properties to determine producer value 2. Assess materials used, recyclability and associated regulations 3. Consider future implications of policy on the life-span of the PSS Life-Cycle-focused considerations The idea of the life-cycle perspective on PSS design was introduced in chapter 3.4, including a review of literature connecting lifecycle-focused considerations and PSS. After reviewing this literature, making the lifecycle perspective a part of the assessment of the environmental impact of PSS components and its reflections on producer value was a logical step. This indicator is especially useful when assessing offerings, since some components might yield beneficial effects to a part of the life-cycle, while others might be adversarial to that particular effect, together eliminating all benefits to the producer. For that reason it is important to again stress, that the focus of the engineer during PSS design should be on all aspects of the life-cycle (Sundin, 2009). The following individual steps within the life cycle may serve as a guideline to aid these considerations (taken from Sundin, 2009): 1. Manufacturing; 2. Delivery 3. Usage 4. Maintenance 5. Recycling 6. Remanufacturing 7.4 Scale of Scoring When the connection between components and different producer values has been established, the relation between the two must be quantified, for the following reason: While two components might both have an impact on the value of the producer within the scope of the knowledge-category, it is very likely that this impact is not going to be identical. Using a Boolean variable (applies/does not apply) for this step was therefore not sufficient. It is essential for this method to function properly and be utilized correctly to provide an immediate understanding for the use of the tools provided. Alignment to present tools in engineering that include evaluation performed by assigning numeral values to items is therefore logical. After contemplating a number of different scales or leaving the decision to determine a proper scale of evaluation to the user, the following was decided: Firstly, the scale introduced by Zangemeister (1976) and as laid out in Pahl et al. (2007) in Cost Utility 54

66 Properties to determine producer value Table 7.1: Scoring Scale for Producer Value Assessment (based on Zangemeister, 1976) Score Label Explanation 0 None This category of PV may be omitted for the evaluation of this component 1 Inadequate Component benefits regarding the PV in question are negligible 2 Weak Benefits regarding the PV yielded by the component are almost negligible 3 Acceptable Very slight benefits regarding the PV can be expected from the component 4 Sufficient Below-average, component benefits producer value less than expected Benefit to PV is on-par with expectations for this 5 Satisfactory component/function 6 Fair Slightly above expectations for possible PV-benefit for the component in question 7 Good Benefits regarding the PV notably exceeding expectations on this component 8 Very Good Benefits regarding the PV substantially exceeding expectations on this component 9 Excellent Benefits exceeding expectations by large margin regarding PV for the component 10 Optimal Best performance in terms of PV for the respective component Analysis was adopted, adjusting the definitions for every level to the issues at hand and providing additional explanations. This is illustrated in table 7.1. This scale was chosen since it offers large number of options to properly discriminate the scores on different producer values, but still limits the possible options compared to a continuous scale, e.g. from zero to 100. Such a scale might lead to unrealistic discrimination between the different producer values: The user might score one component with 53 on a certain producer value, and, just for the sake of using a different number, score another component 54 this PV. This may lead to a difference in the sorting even though there actually is no difference between the two components in this particular area. By using a stepwise scale, this can be avoided. 7.5 Derivation of an aggregate Producer Value At this point of the development of a producer value assessment method, it seems worthwhile to establish an aggregated producer value. This is due to the following reasons: A number of producer values that characterize a component or an offering have been established above. In order to provide a comprehensive overview and a basis of comparison, an aggregate value for every component is needed. Additionally, at this point this must be done by the user himself. When viewing all producer values asso- 55

67 Properties to determine producer value Table 7.2: Example of the derivation of aggregate Producer Values Component Producer Value Score Weighting Average (Component) Physical Component A Knowledge Time-to-Market Service Component B Knowledge Time-to-Market ciated with a particular component or offering, an aggregate value is to be estimated. This must be done taking into account the differences in importance that the various producer values have on different components. The following example will illustrate this dilemma and the importance of an arbitrary aggregate producer value: While the value of knowledge might be of paramount importance to a certain component, it may be virtually negligible for another. Simply calculating a mean value of all scores is hence not a feasible option. Table 7.2 shows a possible scoring for two different components, that both impact on the same producer values, though with different importance. The column labeled Weighting is not present in the tool-description in chapter 9. Also, the problem of a weighted average requires great consideration. Even though in Cost Utility Analysis, a weighting with factors that in total sum up to one is included, it was decided not to enforce a common weighting-mechanism into the method at this stage. Rather, it was decided to let the engineer decide for a more or less arbitrary average derived after scoring the component on the applicable producer values. The consensus was that including the weighting mechanism utilized by CUA without further researching its implications and issues arising from that, is not feasible. 56

68 Chapter 8 Interdependencies in PSS evaluation and how to address them 8.1 Introduction When evaluating and choosing components that will eventually constitute an offering such as a Product/Service System, evaluating the characteristic features of the individual components and, in the case of the method proposed here, their impact on the producer value, is essential. Nevertheless, it is no less important to focus on the interactions between these components and possible means of optimization of these interactions. 8.2 Design Structure Matrix and PSS components Introduction In this section, the properties of the design structure matrix should be briefly introduced, together with an explanation on how it applies to the selection of components for a PSS offering. This section is based on the comprehensive tutorial by Lindemann et al. (2012). The recent book Design Structure Matrix Methods and Applications by Eppinger and Browning (2012) is suggested if additional information for a profound understanding is required Definition and Scope The DSM has been first introduced in the early 1980s and has been developed continuously since then. It is always a square matrix that shows relationships between elements in a system (Lindemann et al., 2012). Although DSM is mainly used for system modeling and to describe and optimize process interactions, it is also applicable to the component-perspective taken here, although not all means of optimization may apply. 57

69 8.2.3 Possible relations conveyed by a DSM Interdependencies in PSS assessment The first and most obvious form of interaction between different components is no interaction. Within the systems theory as applied to DSM, this is a parallel relationship, where two components have no (or in the case here, very little) interaction and the omission of one of the components has no direct or indirect effect upon the other (see figure 8.1). Figure 8.1: Parallel DSM relationship (compare Lindemann, 2012) The second possible relationship between two PSS-components that a DSM may show is unidirectional, or sequential, as it is called in DSM-research (see figure 8.2). To explain this, an example from the world of automobiles seems fitting: Component A is an engine running on combustibles; Component B is the exhaust pipe. Whereas a motor can function without the presence of an exhaust, the exhaust serves no purpose without the motor. This relationship may occur regularly in physical to servicecomponent relations, since many services depend greatly on the presence of physical components, where components may serve their purpose without the sale of a certain service alongside. Figure 8.2: Sequential DSM relationship (compare Lindemann, 2012) The third option, as now obvious, is that both components depend on one another, thus forming a true interdependency- they are coupled. When referring to systems, DSM-theory often speaks of requiring information or input from one component, which may, in case such information is lacking, eventually delays and rework within the project is needed. In the case of components, information regarding their function and also transfer of information is conveyed through the DSM. 58

70 Interdependencies in PSS assessment Figure 8.3: Coupled DSM relationship (compare Lindemann, 2012) What comes to mind now are different intensities of relations between two components. This idea seems very logical and in the field of DSM, it is applied within Numerical DSMs. These have been introduced very early in the development of DSM, for example by Steward (1981). Within the area of systems engineering, applying weights to different processes as they interact seems worthwhile. When dealing with components, as is the case here, this process becomes difficult to manage. A lot of research and experience is necessary to be able to accurately assess the relation between several components and to go as far as comparing the intensity of these relations. For that reason, a traditional-style DSM was chosen for this method and the practicability and efficiency of having just the options interaction/no interaction will become clear in the following How to read a DSM The reading and understanding of Design Structure Matrices will be explained using figure 8.4. The way the components are interconnected was taken from the tutorial mentioned above. Examining this matrix begins with looking at the components in the vertical column and checking for interactions with components in the horizontal column. Component A has an interaction with component B, which may be sequential- meaning, that component A has an impact on how component B works. In this case of the DSM as stated above, the weight of this impact is not evaluated, all interactions are Boolean in nature. Now, cross-checking A in the horizontal column reveals, that the opposite, namely component B having an impact on A, is also true. This pair of components is fully interdependent or, as said above, coupled. When continuing with component B in the vertical column, it is obvious that B has an impact on E. In return, B does not have influence on E, making their relation sequential. Since most relations between components go either in both directions or are not present at all, this shows in the figure displayed. The B/E-relation is the only exception in this case. This becomes obvious, when using the diagonal as a virtual axis of symmetry. 59

71 Interdependencies in PSS assessment Figure 8.4: Example of a DSM with unaltered data in CAM 8.3 Optimization of a component-dsm Introduction, Cambridge Advanced Modeller After the introduction to DSM in general, what the matrix conveys and how data is entered, this constitutes the most important step of this part of the evaluation process. When designing a PSS, a large number of components must be evaluated. To do this in an efficient manner, the aid of software is essential. David C. Wynn (2007) and his colleagues have developed and continue to develop the Cambridge Advanced Modeller (CAM), a software, that makes optimizing DSM a much easier task than handling large Excel-spreadsheets. 60

72 Interdependencies in PSS assessment DSM clustering When working with a component-based DSM, clustering the components is the optimal use of the abilities of this method. The goal of clustering is to find groups of components that have a lot of interaction amongst a fairly well-defined group but little interaction with other components. Should this be the case, decision-making with respect to what to include into a PSS-offering is significantly simplified, since a DSM-cluster suggests using one of two options: Either use all of the components included within a cluster and making maximum use of its capabilities. Or, rather than omitting one of the components and reducing the usability of many others alongside and losing money, omit the entire cluster of components. Figure 8.5: Clustered component-based DSM The clustering is done by arranging as many components as possible near the diagonal line. This happens through rearranging components within their column or row, but not interchanging components between the two. Doing this by hand is a long pro- 61

73 Interdependencies in PSS assessment cess of trial and error; with the CAM-process, the optimization is carried out almost instantly. It becomes clear when examining figure 8.5, that three clusters have been identified from the DSM given above in figure 8.4. They consist of two, three and four components. The couple P/O did not fit into one of the optimization-clusters, as well as the sequence B/E. 8.4 Interpretation and results of DSM-based optimization The main benefit of optimizing relations between PSS-components through clustering of a Design Structure Matrix is that now, rather than a large number of seemingly independent pairs of components, the dependencies among groups (clusters) of components become clearly visible. Without a second thought, the engineer will be able to determine the effects of omitting one particular component, or, when examining the issue from the ground up, it will be immediately clear what components might provide a large producer value through a low added cost, when a certain component is mandatory and others, belonging to the same cluster, are added to it. What is also clear now, is that components, which do not belong to a certain cluster, may be chosen to be part of the offering without any notable effect on the rest of the PSS. This fact seems self-evident, but when dealing with a large number of components, factors like this might otherwise go unnoticed. When directly comparing the figures 8.4 and 8.5, this becomes particularly obvious. This optimization is a first and important step towards moving from individual components towards the offering perspective. This is laid out in more detail as the entire method is explained in chapter 9. 62

74 Chapter 9 Structure and operation of the method proposed 9.1 Introduction Within this section, the use and operation of the proposed method is laid out in detail. It serves as a guideline and provides a clearer understanding as to how the steps and methods introduced before should be used in order to evaluate PSS components and offerings from the provider-perspective. The process depicted in figure 9.1 acts as a guide through the evaluation-process. It must be stressed at this point, that going through this process, is a very extensive and time-consuming task. It may be necessary to go back to the theoretical chapters for reference, since this chapter is designated to aid the user of the software or introduce the method to anyone researching in the field in a compact manner. 9.2 Structure of the process As shown in figure 9.1, the evaluation-process proposed is mainly linear, meaning that step 4 should not be performed before completing step 3. Only the final step 7 (A and B) may be performed in any order, or only partly. Additionally, the tool as such is intended to be used in an iterative manner: After completing the entire process once, the user should reflect on the results, make changes and experiment with possible effects. This will be discussed in more detail in chapters and 9.5. Additionally, the process was split into two major sections: Steps 1-4 focus on the collection of data and the component-focused evaluation, whereas steps 5-7 take a broader perspective, when evaluating several combinations of components and the effects that arise due to influences among them. The intention of this division is to make it clear to the user that the first steps focus on the assessment of individual components without addressing their interactions, whereas the last steps focus on selecting components to form offerings and the related issues of interdependency as well as cost 63

75 Structure and operation of the Method Component-Focused Assessment Component Catalogue Producer Value List Engineering Assessment Prior Experience, Data, ext. Input 1. Enter/Load Components 2. Enter/Load and select applicable Producer Values 3. Assign numeral values to Producer Values 4. Assign probabilities to values, assess uncertainty A compilation of all components, whether physical or service. Pairs of components and applicable producer values Database of components, applicable producer values with evaluation Uncertainty Values, NUSAP Assessments and indication of data strength Component Catalogue 5. Select interdependent components Grouped Components Offering-Focused Assessment Lists, Data, Experience 6. Enter data regarding cost and revenue 7. A Find optimal combinations of components by one or more of the following ways: sort by desired Producer Value Determinant show only components posessing a certain value regarding a Producer Value show interdepending components show only components scoring more/less than a certain value regarding a Producer Value Adapted cost, anticipated revenue 7. B Assess components within the context of other components, reflect on how they influence each other: reassess costs and revenue reassess values of individual components in an offering introduce new Producer Values through review from the offering-perspective evaluate clusters formed in step 5 Figure 9.1: Description of the evaluation process 64

76 Structure and operation of the Method and revenue. 9.3 Component Focused Assessment Step 1 - Enter/Load Components This step is rather self-explanatory. All components, whether physical or service, should be collected within this step. Even obvious elements critical to the PSS as a whole must be included into this catalogue in order to ensure a complete evaluation, especially when considering interdependency (Step 5) and value-changes due to different combinations of components (Step 7.B). The collection and sorting of components is not part of this thesis and the electronic processing of the data as introduced in chapter 10. A good option for collecting components may be Design Catalogues, as described by Diekhöner (1980) and in many volumes by Roth ( Konstruktionskataloge ). Although these are focused on physical components of design project, the method can likely be expanded to services. Verifying this might be a question for further research. Further, sorting different solutions (components) for similar tasks might call for the use of a morphological box (Zwicky and Wilson, 1967) Step 2 - Enter/Load and select applicable types of Producer Values This part of the evaluation actually contains two sub-steps: The first step is exactly along the lines of step 1, although it is assumed that the Producer Values (PV) are present in advance. The determinants investigated within this thesis are found in chapter 7: Knowledge Customer Relations Time-to-Market Infrastructure Environment When the required PVs have been collected, they must be assigned to the components. Since not all producer values apply to all components, this must be done for every component individually. 65

77 Structure and operation of the Method Step 3 - Assign Values to Producer Value Determinants In order to convey the different degrees of influence a certain component has on a producer value, it is necessary to assign scores to each of the producer values. As explained in chapter 7.4, a scale modelled after the one used in Cost Utility Analysis was derived, it may be found in table 7.1. The scale reaches from zero to ten, zero meaning that there is no influence whatsoever by this component on the respective producer value, while ten means that the benefits gained for the respective producer value exceed expectations by far. Table 9.1 shows a possible outcome of the scoring of a number of components (captions had to be shortened, see above for details). Table 9.1: Matrix of Components and PV-Scores Producer Value Know. CR T2M Infrst. Env. Component Physical Component A Service Component B Service Component C 7 9 Physical Component D Physical Component E 4 8 After assigning values to all of the individual producer values, a common producer value must be derived. As explained in chapter 7.5, this is done on an arbitrary scale, meaning that the engineer performing the evaluation assigns an aggregate producer value based on his assumptions and, of course, on the values assigned to the individual producer values. This means, that the aggregate value does not necessarily have to be an average of all scores on producer values. At this point, is was decided not to include a full weighting mechanism, as explained in more detail in the theoretical chapter above (7.5) Step 4 - Uncertainty Assessment The purpose, goal and structure of the uncertainty assessment is covered in detail in chapter 6. In short: When assessing the producer value of a certain component or offering, a large number of uncertainties are involved in this process. A strategy on how this uncertainty can be assessed and reduced is presented above. For this purpose, the NUSAP-system is utilized. In order to aggregate all of the information given above and to provide a simple procedure to perform the steps required, this short list of steps is provided: 66

78 Structure and operation of the Method 1. Numeral The aggregated numeral value as explained above serves as the base of the assessment. 2. Spread An uncertainty is assigned to the producer value assessment of all components. 3. Pedigree Reasons for the decisions made on the previous steps are assessed using a pedigree-matrix. Figure 9.2: Shortened NUSAP process to reduce uncertainty Step 1 - Numeral The aggregated value introduced in corresponds to the numeral value in the scope of the NUSAP system. This can be skipped here, since this step has already been completed. Step 2 - Spread As explained in detail in chapter 6.3.4, an uncertainty will be assigned to every aggregated assessment attached to a component. The engineer may use the uncertainty-categories introduced in chapter to provide for a more detailed display of the uncertainties involved. An arbitrary average of these categories will be chosen by the user. At this point, as stated in chapter 6.3.4, the uncertainty-values will serve as an additional indicator alongside the producer values and pedigree assessment. Step 3 - Pedigree Using the pedigree-matrix provided above (Table 6.4), each uncertainty and value assessment must be scored. This refers mainly to the way the information leading to the above assessments was acquired and gives the assessment a certain weighting. Since this method is not fully explored at this point, color-indicators next to the respective values will show, whether or not the evaluation is backed by highquality data. The color-coding is intended to work as introduced in chapter The scores from all three categories are added up. In accordance with table 6.5, the sum of the pedigree-scores will lead to a different color-code of the associated 67

79 Structure and operation of the Method uncertainty-value. The aim of this is so sensitize the user for possible errors in assessment. 9.4 Offering-Focused assessment Step 5 - Interdependencies When selecting components that are meant to form an offering at the end of the product development process, interdependencies are very important to keep in mind. More information on the theoretical background and the methods used to assess interdependency through the Design Structure Matrix in the context of producer value assessment may be found in chapter 8. In order to make dependency-related information computer processable, this information must be entered into a database. As described above, the Cambridge Advanced Modeller by Wyatt and colleagues is recommended for this, since it enables input, optimization, output and exporting in a very easy and straightforward procedure. Of course, using spreadsheet-based software such as Excel or OpenOffice Calc is possible, making the process much more laborious and time-consuming. Although weighted interactions between components are also possible in numerical DSM, it has been decided use the traditional DSM in this method. Process of DSM optimization As explained in detail in chapter 8, the DSMoptimization process involves the following steps: Step 1 - Enter Components All components, regardless if physical or intangible in nature, need to be entered into a database. In this example, this is shown on the left side of figure 9.3. The order or nature of the components is of no interest at this point, although sorting by hand is possible within CAM. Step 2 - Assign relationships As explained in chapter 8.2, there are three possible relations between two components: Parallel relationship: There is no interaction between the two components. Sequential relationship: The interaction is unidirectional, meaning that although component A influences component B, the opposite is not true. Coupled relationship: Both components influence one another. In figure 9.3, the grey squares each represent such an interaction. When reading the Design Structure Matrix, the direction of reading is always Y-Axis-component influences X-Axis-component. 68

80 Structure and operation of the Method Figure 9.3: Example of DSM optimization by clustering Step 3 - Apply clustering algorithm The following happens when applying this algorithm: All relationships are scanned for components that interact heavily amongst a defined group, but little or not at all with other components. Through this, functional units can be isolated. The transition shown in figure 9.3 is exemplary of this. This is a very important step from the perspective of independent components toward an offering. Within CAM, this step may be applied several times, especially with large databases. The results are sub-clusters, so that the engineer evaluating possible PSS components can work his way from the macro- towards the micro-structure of a possible offering. Additionally, when entering a large number of components that contain partly similar function, choosing components that integrate well and work hand in hand is supported by this method. Example Figure 9.3 shows the effectiveness of clustering in DSM. The components shown all refer to an automobile, but are chosen completely at random. As said above, relationships were put into place and the clustering-algorithm applied. The result: Instead of a large database of seemingly unrelated components, four clusters that could be titled drivetrain, wheels, waste gas, and interior have been isolated. In this case, the relations are easy to spot. In more complex and realistic cases, this method is likely to provide vital insights for the evaluation process Step 6 - Cost and Revenue Besides the producer value, cost and revenue are important focus-points when deciding upon the components of a PSS. In order to have these in mind when assessing components and offerings, it is important to assess and display this information within the tool. 69

81 Structure and operation of the Method Entering cost data is at this stage done by entering cost per unit, which includes all cost in- or out of house, as well as the number of units. If desired, and applicable, scale effects can be defined and will be taken into account when displaying the data at the end of the evaluation (for more detail on this see chapter 5.3). When considering revenue-related data, the process is very similar: A number of units is combined with a price. The main difference is, that the revenue-assessment is virtually impossible on the component-level. Therefore, this part of the process is largely part of step 7. In particular with respect to service-components, the effects of the experience curve must be considered (explained in detail in chapter 5.2). Therefore, the engineer may, based on previous data and experience in the field, choose a slope of the curve, which then will be taken into account Step 7A - (Re-)Evaluation of Components This part of the final review- and evaluation- process is focused on the individual components and how they compare to one another. There are many possible scenarios for how this task might be executed, these will be illustrated within this section: Table 9.2: Possible grouped components view Component/Category Cost Revenue PV A PV B PV C Category A...Component A.A Component A.B N/A 9...Component A.C Category B...Component B.A N/A 3...Component B.B N/A 5...Component B.C The evaluation of components must also take into account interdependencies. They may be dealt with in the form of categories: Closely dependent components often refer to a common task that defines their purpose. Using this as a category that serves as a placeholder for all it contains, a reduced overview may be achieved and it is ensured, that no functionality is omitted due to disregarded interdependencies. For these categories, a common cost may be shown and reassessed as explained in 7B. Additionally, common producer values for categories may be given, although this is not examined in this thesis. In addition to the information show in table 9.2, an additional column may show the aggregated values as well as the respective uncertaintycalculation, in particular the quality-of-data assessment as described in In the context of other components, the re-assessment of the values put in earlier in the process is already applicable. This may also lead to a step back and a change in the uncertainty assessment as illustrated in step 4. 70

82 Structure and operation of the Method Although there is no particular order in completing these two final steps and jumping back and forth is even strongly encouraged, components may be sorted and displayed independent of any interdependencies in order to ensure a proper re-assessment in due process. This may help detect new connections between components that were not as apparent before Step 7B - (Re-) Evaluation of Offerings This particular step is vital in order to ensure a successful evaluation of the producer value of components and offerings with respect to Product/Service-Systems. It is only one side of the coin to evaluate components independent of their surrounding environment. It is therefore vital to re-assess the data gathered in the previous steps from the offering-perspective. One area that may be tackled during this reassessment is cost and revenue. When assembling several components into an offering, they interact and it is very likely their cost as well as revenue may change. Therefore the engineer may make changes to these evaluations, whether they are made directly within step 7B or through going back a few steps and altering the assessment there. Also, a different scale effect or experiencecurve slope may be chosen in the light of the offering created. An implication of this could be the following: A certain component may be needed to be sold below cost, meaning the initial revenue is lower than the cost of the component, so that in most cases, including this component is not feasible. In the light of other components within the offering, it might seem more than logical to include this particular component, thus changing it s producer value. The following practical example describes this: Google recently announced its 7-inch tablet computer Nexus 7. It is being sold for US$199,- and at cost. [...] There s no margin, it just basically gets (sold) through. (Souppouris, 2012). While a product like this would not make it to the market in most cases, this did. The reason is, that the component tablet computer is eventually just a media-consumption device. The tablet, running the Android OS developed by Google, offers Software, Games, Books, Magazine subscriptions, Movies and more through Google s own Play Store. Google receives a portion of all revenue created through this store and also through its vast advertisement-network. This service-component and the immense revenue created through it, therefore may justify the use of a component that has to be sold without profit or even at loss in the long run (illustrated in figure 9.4). The close relation of product and service in the case of this media-consumption device, both designed from the ground up and made to work hand in hand, is an ideal incarnation of Product/Service Systems as it is understood today. In addition to adjustments made with respect to previous assessments, in the light of the offering perspective, completely new producer values might come to mind. It is then advisable to go back within the process to enter the new producer value and 71

83 Structure and operation of the Method Figure 9.4: PSS illustrated by Tablet and Sales-Platform offering assess all components with respect to that. Additionally, the lessons learned regarding interdependencies in step 5 are in many cases very helpful when deriving offerings from a large pool of components: Once clusters of components have been formed, the number of clusters that need to be evaluated should be a lot smaller. If deemed appropriate, the process of evaluation in its entirety might be repeated with clusters instead of components. Obviously, alignments in cost and revenue also apply in these cases. Even without this additional repetition of the evaluation process, clustered components prove to be helpful in the evaluation and selection process. Budget A useful way of choosing components on a set budget is illustrated as follows: Within a set budget, only components fitting into the boundaries of that budget are displayed in the software. It is worthwhile to attempt budgeting after completing the steps above, including reassessments and alignments. When a component is chosen, it s cost is deducted from the budget, hiding all other components that exceed the new budget level. Using this technique, needs for cost cutting or additional revenuecreating might be more easily identified than by leaving budgeting to a completely different development-step altogether. 9.5 Iterative nature of the method What has been said throughout this chapter needs stated explicitly once again: The use of this tool is not over once the process has been completed one time. Reassessing and rethinking what lead to prior assessments is a major task of this method. For that reason, a computer-software that aims at simplifying the processes laid out above must be designed in a way that supports and encourages the change of data entered. At this stage of the development of a set of tools that assists the evaluation of Product/Service 72

84 Structure and operation of the Method Systems, raising awareness for the particular features of these types of offerings, is the key to future success. 73

85 Chapter 10 Software automating the evaluation process 10.1 Introduction For a method to be used in a modern-day engineering-environment, proper implementation in the form of an automated tool is crucial. This ensures the usability of the method, proper documentation as well as consistent and repeatable results. Since the design and programming of this software would go way beyond the scope of this thesis, only the databank-related operations of the programming have been realized. The rest of the process is illustrated in this section by mockup-graphics. All figures, whether mockups or actual screenshots, should be understood as suggestions for the future development for this portion of an integrated development of a PSS design software. The database-handling software was written as a Visual Basic Application (VBA) in Excel The software is in the development stage and only capable of data handling; no PSS-related functionality has been implemented at this point. It is open source and will be available through for the community to use, expand and alter. Should the development of the software continue in the future, coming versions will be made available through this channel General Structure The structure of the software should follow along the lines of the method described in chapter 9. Of course, there are many ways to guide a user through a software. There are a few issues that are essential to the method and therefore must be taken into account in the software design. A visualization of this is given and detailed in Figure

86 Software automating the evaluation process Tabbed View: The tabbed view has the task of structuring the use of the software and entry of the data. Having just a forward and a back-button to go from step to step is not a feasible solution. The user lacks overview and a lot of pointless clicking occurs when going back from step seven to one. Even worse is the option of one large scrollable view. A tabbed view enables the engineer to go back and change his data at any time. What must be prevented is skipping steps and completing e.g. five before three. This would in many cases even defeat the purpose of the software, since values might be assigned to data that is not present yet. After completing the process once in its entirety, jumping back and forth is possible and even encouraged (see 9.5). Continue-Button: The continue-button is a easy way of preventing the skipping of tabs in the first walk through the software. Additionally, it encourages the user to ponder upon the data he just entered. After completing the process once, the button may disappear or, in cases of scarce processing capabilities, serve as a recalculate-button for the Current Results -Box. Interaction field: The interaction field is the area of the screen the engineer will be using the most. It should be kept simple, with few fields of entry and as little scrolling as possible. Moving components and editing etc. should be realized in the easiest possible manner: For example utilizing Drag-and-Drop instead of multiple button-clicks. Current Results Box: This is one of the most powerful possibilities offered by using software for the purpose of evaluating PSS from a providers viewpoint. After completing the entire process of the software one time, changes to the data entered may take immediate effect that can be viewed in the Results Box. Since some of the assessments made may be vague and not stand on the firmest ground, small changes in assumptions made might lead to substantial differences in the results obtained. This can be examined either systematically or even through trial and error, as changes to items of interest are made. A downside of this option is, that it may push the user towards a bias, e.g. giving components high scores that he prefers over others without being fully aware of it. In order to prevent this, the box must be collapsible to hide it from the view of the user Suggested design of the software Entry of Components The first step to evaluating components and offerings in any design environment is the gathering of all the data. This means, that every component must be entered into a database, whether it is a physical or service component. How this was realized in the software introduced above is visible in Figure

87 Software automating the evaluation process Current Results Component A Component D Component K Component F More Info... More Info... More Info... More Info... Current Entr Data entered Data entered Data entered Button Button Button Button Continue Figure 10.1: Mockup of the general structure of the software 76

88 Software automating the evaluation process Figure 10.2: Dialog for entry of components (Screenshot) As stated above in chapter 9.3.1, the collection of a database of components is not part of this thesis. It is assumed, that all components required are listed in one or more Excel-spreadsheets. More sophisticated software might include other forms of databases, obviously. Functionality to open external spreadsheets without leaving the software has been included. If only a very limited number of components is present, entering these by hand is also possible. The compiled database can be saved for further reference. Functionality to delete and move items has also been included Selection of Producer Values The selection of applicable producer values for each of the components and the adding of numeral values to the connections established is realized as a single step within the software. How this was done in the form of an Excel-connected VBA software is shown in Figure The software presented automatically tries to load a database of producer values from a predefined location and alerts the user in case this fails. The user has the chance to add to this database through the dialog shown. In order to connect a component to a producer value, the component is chosen from a dropdown list, a producer value is selected in a box, and when a value is entered, the combination gets saved and displayed. Once a different component is selected, the display changes. This is not fully intuitive and must be executed differently in a future development of the software. There must be a overview available of all entries of values made, in order to enable the engineer to view them at a glance without clicking through every component. Another option to realize the selection of producer values is ticking boxes at each applicable value and including a next sub-step or showing input-fields right next to each of the values. In this case, no value entered on any producer value-component 77

89 Software automating the evaluation process combination implies there is no connection between the two. Figure 10.3: Selection and connection of producer values (Screenshot) Uncertainty Assessment In order to enter the data related to the assessment of the uncertainty of the producer value assessment, again pairs of components and producer values must be chosen. The logic here is, that once a component is chosen, only the producer values with a value attached for that particular component will loaded into a dropdown. A larger box displaying more than one item at a time as seen in figure 10.3 may also be feasible, although more space on the screen is used. Current Results Uncertainty Value Component A Component D Component K Component F More Info... More Info... More Info... More Info... Save Continue Figure 10.4: Mockup of the Uncertainty-Assessment-Tab 78

90 Software automating the evaluation process In figure 10.4, the individual categories of service uncertainty as discussed in chapter are not shown. The uncertainty value is understood to be the average uncertainty as stated above. Since a procedure to directly include this figure into the producer value evaluation, for example through an optimized producer value-figure, is not present at this point, further elaborating this in the software is not worthwhile. The criteria of the pedigree-table should be chosen by just clicking on them. Additional information through tooltips or dialog-boxes might be required, since this table is likely to be not immediately intuitive Incorporation of interdependency into the software In chapter 8, the Design Structure Matrix and the software Cambridge Advanced Modeller has been discussed at length. Since this very sophisticated software already exists, there is no necessity to redo work that has already been done. An importing function is present in Cambridge Advanced Modeller. It is capable of importing CSV-type files. After exploring the exact syntax these files are required to possess, an exporting function should be included into the PSS evaluation software. If the software would be programmed in Java, a direct handover of data without further hassle for the user might be a feature to consider. Since this also requires action from researchers at Cambridge, it would likely be one of the last optimizations after all other features have been realized Integration of Cost and Revenue Since there is a lot of software already present in this market, reaching from smallscale business-applications to large-scale corporate software, the following approach seams feasible here: Limited functionality regarding cost, revenue, experience curve and economies of scale should be included directly into the application, for more extensive purposes, interfaces for other software would be an option to assess. The illustration in figure 10.5 is a suggestion for the implementation of basic functionality regarding cost and data with respect to economies of scale. Experience curve and economies of scale can in the case shown here be selected using a toggle-button, although other solutions to this issue might be practicable. The term step visible in figure 10.5 requires some additional explanation. In most cases, a notable improvement due to scale and experience curve effects may only be seen after a number of services have been performed or a number of physical products included. The term step has been conceived to cope with this issue and make the evaluation in this part more accurate. Since the issue of revenue is more relevant in the offering-perspective, it should be included at a later stage when components are combined into offerings. 79

91 Software automating the evaluation process Current Results Component A Component D Component K Component F More Info... More Info... More Info... More Info... Economies of Scale Continue Figure 10.5: Integration of cost-related data in the software Creation of Offerings Creating an actual offering is a crucial step of the evaluation process. The following implementation into software is suggested: The offerings that have been agglomerated in DSM are shown in clusters. Should the user have linked components with similar functionality and close relation, scrolling through the list of clusters may help the selection of components for a possible offering. Current Results Component A Component D Component K Component F More Info... More Info... More Info... More Info... Continue Figure 10.6: Creation of offerings in a software Also, a sorting-mechanism for components by value or cost should be implemented. When appropriate components for inclusion into an offering have been found, they 80

92 Software automating the evaluation process should be added to the offering by a drag-and-drop mechanism. More offering-boxes can be added at any time. A simplified interface visualizing these paradigms is shown in figure Revenue Including revenue-related input seams feasible after offerings have been created. As cost has been assessed and the effects of economies of scale and the experience curve have been taken into account, a more realistic view on cost-related data is now possible. The expertise of managers and business-related personnel is very likely required in case very detailed information is necessary to complete this step of the evaluation. Afterwards, an unbiased comparison of offerings is possible and the engineer is ready to reassess and detail his evaluations. Current Results Component A Component D Component K Component F More Info... More Info... More Info... More Info... Continue Figure 10.7: Interface for inserting revenue-related data What could also be stressed through the software and is indicated in the mockup figure 10.7, is a more long term view with regard to revenue and product lifetime. While Offering II in the figure is obviously a sell and forget-type product, immediately delivering a profit of 40, offering two burdens the company with an initial loss of 80. Because of continuous revenue over the product lifetime (sale of add-ons, servicecontracts etc.), the break-even point with offering II is reached after approximately 1.5 years and over the product lifetime, the profits will rise up to Overview The overview-tab needs to provide all information about the data entered at a glance. For the mockup (figure 10.8), a simple view with one box was chosen, displaying all 81

93 Software automating the evaluation process offerings and providing the option to drop down the components of each of the offerings to enable the engineer to perform a detailed comparison. This provides the starting point for the re-assessment of the evaluation. In situations where more information than what the small pop-out-window provides is required, the engineer can go to the Overview-tab at any time to get all information at a glance. When the focus lies on producer value and cost, sorting components by a defined producer value is helpful. With the values found and uncertainty assessment completed, such a sorting option may greatly aid the decision-making process with respect to the components forming an offering. Additionally, it is feasible to hide all components with an insufficient value for a certain producer value. The same procedure may be applied with respect to cost and/or revenue. Figure 10.8: Overview of the data entered 82