Maximilian Nicolae - Service Operations Management from System Engineering PDF

Maximilian Nicolae - Service Operations Management from System Engineering Perspective Chapter 1 - An Introduction to Operations and Operations Management 1.1 An Introductory Approach The primary objective of this chapter is to deﬁne “operations,” a term that, like many frequently used concepts, can be diFicult to pin down due to its broad usage and various interpretations. Typically, operations refer to the execution of a function, with “function” being another fundamental but elusive term to deﬁne precisely. As we will see later, operations are considered one of the three core functions within an organization, alongside marketing and product or service development, as noted in [sla07]. If we think of marketing as the outward-facing aspect of a business (often driving growth, though not necessarily proﬁtability), operations represent the organization’s commitment to delivering on marketing’s promises. In [bro01], the concept of operations is illustrated through the metaphor: “operations are where the rubber meets the road.” Essentially, operations encompass what the organization actually does, rather than what it should aspire to do. A useful example of the interaction between marketing and operations can be seen in the competition between Microsoft and Google, speciﬁcally in the context of their operating systems (OSs). We will revisit this example when discussing operations strategy, but it is relevant here to note the contrast. Microsoft, known for its aggressive marketing, has not always succeeded in fully delivering on its promises. On the other hand, Google tends to attract customers through strong operational performance, with fewer unmet customer expectations. Despite their diFering approaches, both companies continue to generate signiﬁcant proﬁts and consistently innovate, launching new products and services— some of which succeed, while others fail. To better grasp the complexity of operations, it may be helpful to draw analogies from two ﬁelds with which most people are somewhat familiar. First, the ﬁeld of computer science, particularly in how operating systems function; and second, military operations in theater. Both areas oFer valuable insights into the structured, dynamic, and multifaceted nature of operations within organizations. 1.2 Modeling Considerations This section is not meant to provide a rigorous, in-depth exploration of modeling but to highlight why modeling is a powerful tool for those who understand its advantages and know how to work eFectively with it. Even though childhood is evolving in today’s technological era, many of us can recall one of the ﬁrst models we ever engaged with— An Introduction to Operations and Operations Management the paper airplane. We learned how to design, modify, and optimize it for better performance without facing signiﬁcant risks or costs. This basic principle of modeling— trial, adjustment, and optimization—is also illustrated in Figure 1.1. Measure Abstract Conversions Structures Organization & Tools Real Life Virtual World Interpret / Act Figure 1.1. Modeling concept as a tool for operations The concept in Figure 1.1 oFers a perspective on the people involved in shaping an organization’s strategy. Although we will delve into operations strategy and the strategic role of operations in the next chapter, this visualization provides a glimpse of how critical it is for these individuals to have a thorough understanding of the organization’s day-to- day workings (i.e., real-life experience) while also recognizing which tools can oFer them a “competitive advantage,” a term popularized by Michael Porter. The basic model often used for both operations and organizations is the “Inputs- Transformation Process-Outputs” framework, depicted in Figure 1.2. Many books include feedback mechanisms in this model, and authors such as [bro01] and [sla07] propose more complex variations by highlighting speciﬁc aspects not immediately apparent in the basic model. However, none of these derived models have become standardized yet. Transformation Outputs Inputs Process Figure 1.2. “Inputs - Transformation Process – Outputs” Model Transformation Suppliers Inputs Outputs Customers Process Figure 1.3. Extension of “Inputs - Transformation Process – Outputs” Model Maximilian Nicolae - Service Operations Management from System Engineering Perspective From a systems engineering perspective, this model is particularly convenient as it reﬂects a simple input-output structure. If feedback loops are incorporated, they are typically internal to the system’s representation. However, if feedback is gathered through customer experience, the model should also account for the customers and, similarly, the suppliers. Figure 1.3 illustrates the distinction between internal feedback and external feedback. For instance, customer feedback (e.g., through surveys) could be seen as input from suppliers in certain contexts, especially in organizations that rely on external evaluations. Likewise, the quality of outputs might be assessed by specialized third-party organizations, feeding back into the system, not directly through customers but through suppliers. When considering inputs, it’s essential to account for all types of resources—raw materials, ﬁnancial assets, information, technologies, and people (including both customers and staF). The transformation process can aFect various properties of these inputs. While structural, physical, and chemical transformations are more common in manufacturing contexts, we should also acknowledge other properties relevant to services, such as location, ownership, health conditions, education, and other human characteristics. 1.3 Deﬁning Operations and Operations Management As discussed earlier, operations relate to how an organization produces and delivers its outputs. According to [sla07], operations management is the activity of managing the resources intended for the production and delivery of products and services. Every organization has multiple functions, some of which are critical to its core operations, while others serve to enhance and support these primary functions. Consider the common example of a sole proprietor or craftsperson. They must create a product or provide a service, which constitutes their core operational function. However, they also need to promote their services, which can be seen as a marketing and sales function. In [sla07], these functions are classiﬁed as “core functions.” In addition to marketing and operations, there is the product (or service) development function, which is responsible for creating or modifying products or services. Functions like ﬁnance, accounting, and human resources are considered “support functions.” To better understand this classiﬁcation, we can look at small family-owned businesses. Support functions tend to be more standardized across industries, meaning they operate similarly in many diFerent sectors. In contrast, core functions vary signiﬁcantly depending on the business sector. Table 1.1 provides examples of activities associated with core functions in various types of organizations. In practice, there are often no clear boundaries between an organization’s functions, and it is common for functions to overlap. This overlap can be seen as an opportunity, as many value-added decisions arise from these intersections. For example, in the context An Introduction to Operations and Operations Management of modeling, it is highly advantageous when individuals have competencies in both “real- world” operations and the “virtual” realm of models and simulations. Figure 1.4 uses Venn diagrams to illustrate the intersections between diFerent functions within an organization. Each function is typically the subject of specialized courses in economic or business education programs, with comprehensive materials dedicated to each. Although support functions are often presented as central within their respective domains, here we will not approach the operations function in isolation. Instead, we provide examples of the information ﬂow between the operations function and other functions in Table 1.2, with arrows indicating the direction of this ﬂow. Table 1.1. Examples of activities related to core functions Product/ Organizations Examples Operations Marketing service development Maintenance Repairing, Promotional For Car repair and repairing of Maintenance, services for Proﬁt workshop newer car Services Logistics, etc. loyal customers models based New study Not For Education Educating, Attract funds courses and Proﬁt organization Training, etc. programs Manufacturing Producing Advertising and New phone Phones Factory based phones Price policies models design Core Function B Core Function A Support Core Function D Function C Support Function E Figure 1.4. Intersections between organization’s functions Maximilian Nicolae - Service Operations Management from System Engineering Perspective Table 1.2. Information flow between organization’s functions Product/ Human Operation Marketing Finance Service dev. resources Customer requirements Designs of in terms of Financial Skilled Operation new products quality, indicators workforce and services deliverability, etc. Customer Product/ Process Skilled needs and Budget Service dev. features workforce requirements New Financial Process products and Skilled Marketing performance capabilities services workforce objectives outlines Required Estimated Estimated Skilled Finance data budget incomes workforce Skills and Skills and Skills and Skills and Human capacity capacity capacity capacity resources needed needed needed needed 1.4 Products vs. Services The distinction between products and services continues to spark debate, particularly in industries like software, where some applications are considered products (e.g., software sold on hardware) while others are classiﬁed as services (e.g., software delivered via the internet). According to the “inputs-transformation process-outputs” model, the features of the output determine whether it is a product or a service. Two commonly used criteria for classiﬁcation are tangibility and the level of customer contact. It’s easy to understand that products are tangible, whereas services are intangible. Additionally, customer contact tends to be present in services but often absent in product transactions. Other distinguishing factors include ownership, quality veriﬁcation, resale potential, demonstrability, storability, and whether production and consumption happen simultaneously. In [sla07], the merging of products and services is discussed, where all operations are increasingly viewed as service providers. Even when organizations manufacture products, their ultimate goal is to serve the customer. In practice, the outputs of most operations represent a blend of both products and services. Whether an organization leans more toward products or services depends heavily on its business strategy. An Introduction to Operations and Operations Management For instance, a company that begins by manufacturing products may eventually oFer after-sales services such as training or consulting to better serve its customers. On the ﬂip side, a service-based company might start producing its own products to improve the eFiciency or quality of its service delivery. This evolution is illustrated in Figure 1.5, where pure products and pure services are positioned at opposite ends of a spectrum, with most organizations falling somewhere in between. Products & Services Quasi- Mixed manufacturing services Only products Only services Figure 1.5. Tuning the product-service mixture A signiﬁcant observation is the evolution of human resource involvement in these two sectors—manufacturing and services. As noted in [bro01], in the 1880s, only 1 in 20 people worked in services, while today that ratio has shifted to 3 in 4. This shift highlights the growing importance of services in the modern economy. 1.5 Supply Network The transformation process described in the “inputs-transformation-process-outputs” model can be broken down into a series of smaller sub-processes, each following the same input-output structure. These interconnected sub-processes form a network or graph, as illustrated in Figure 1.6. This creates a similarity across three levels of analysis: the supply network (at the business level), operations (at the organizational level), and individual processes. There has been ongoing debate about whether issues at these diFerent levels should be approached uniformly. One argument against this uniform approach is that the business level operates in a free market, while at the process level, processes cannot easily choose between suppliers and clients. However, with the shift toward viewing processes as open systems (rather than closed), and the increasing use of concepts like “outsourcing” and “service externalization,” many modern businesses have adopted a more uniform approach to operations management. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Supplier Business A X1 Customer A Business A1 Supplier B Business Business Customer B A2 Xi Supplier C Business An Customer Y Supplier Business X Xm Transformation Inputs Process Outputs PC PA PB PD PE Figure 6. From Supply Network An Introduction to Operations and Operations Management Figure 1.6 oFers a way to view all business functions as a system of interconnected processes. Operations, in this context, can be understood both as a speciﬁc function within the organization and as the overarching activity of managing the organization’s various functions. As argued in [sla07], operations management is a responsibility that spans across all functions, meaning that all managers—regardless of their speciﬁc areas—can be considered operations managers. The key takeaway here is that every manager, regardless of their functional area, must have a solid understanding of the approaches, concepts, and tools used in operations management. This is essential for eFectively managing and optimizing the interconnected processes that drive the organization’s overall performance. 1.6 Characteristics of Operations Processes Although we aim to abstract and model business activities and processes for the virtual world, these processes have distinctive characteristics that require diFerent approaches. Among these characteristics, some are considered more critical. In [sla07], four key characteristics, known as the “Four Vs,” are identiﬁed: 1. Volume of outputs, 2. Variety of outputs, 3. Variation in demand for the outputs, 4. Visibility of the process from the customer’s perspective. The ﬁrst three—volume, variety, and variation—are directly related to the outputs, and their meanings are fairly intuitive. However, the fourth, visibility, requires further clariﬁcation. The term “visibility” refers to how the customer interacts with or perceives the business process. If customers only engage with the product after production or, in the case of services, during the service provision without actively inﬂuencing it, this is considered low visibility. Conversely, high visibility occurs when customers play a more active role in the production of services or products—through customization, detailed feedback, or requiring prompt and tailored services. In [bro01], additional characteristics are discussed that closely align with the “Four Vs.” These include the nature of tasks (manufacturing or service-related, which can be compared to visibility), the volume/variety ratio, the environment (e.g., hyper-competitive or niche markets, similar to demand variation), and the organization’s position in the supply network (supplying end customers or acting as an intermediary). Upon closer inspection, correlations between these characteristics become apparent. For instance, an operation producing a high volume of outputs will likely have less variety. These characteristics are often used to analyze business operations by plotting them within a characteristic space. Figure 1.7 illustrates how operations can be proﬁled based on these factors. By selecting relevant characteristics and using methods such as shading or marking, businesses can trace the unique proﬁle of their operations. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Tangibility of outputs Volume of outputs Variety of outputs Competition Distance to end users Contact with customers Figure 1.7. Operations profiling 1.7 Responsibilities of Operations Management and Operations Managers As discussed earlier, in real organizations, the boundaries between functions are often blurred. Consequently, all functions can be viewed through the lens of operations, and each manager can be seen as having operational responsibilities. However, if we focus speciﬁcally on what we have deﬁned as operations management, the key responsibilities are as follows: Aligning with the organization’s strategic objectives. Developing and reﬁning the operations strategy to achieve those objectives. Designing the processes for producing and delivering products and services. Planning and controlling day-to-day operations. Deﬁning performance criteria and continuously improving outcomes. Adapting operations to the evolving global context. These responsibilities will be explored in greater detail throughout this book. For now, they are intuitive without needing much elaboration, though the last responsibility merits a bit more attention. In [bro01], the “new world context” is examined through the lens of today’s pressures on operations management, which include: o Globalization, which makes it easier for international companies to compete. An Introduction to Operations and Operations Management o Employment, with an emphasis on actively integrating and developing human resources. o Ethics, particularly in terms of corporate social responsibility. o Environmental awareness and sustainability. o Information technology and communication, with artiﬁcial intelligence (AI) playing a pivotal role in transforming operations. In fact, AI has become a signiﬁcant force in operations management. It aids in predictive analytics, allowing operations managers to forecast demand more accurately, optimize supply chains, and make real-time adjustments. AI also enables the automation of repetitive tasks, improving eHiciency and freeing human resources for more strategic roles. Moreover, by analyzing vast amounts of data, AI helps operations managers respond to customer demands faster, ensuring better customization and enhancing the overall customer experience. The last pressure—information technology, with a strong emphasis on AI—can be a decisive factor for successful operations managers today. Referring back to Figure 1, which introduced the concept of modeling and the tools available in the “virtual world,” it becomes evident why an operations manager skilled in AI, Systems Engineering, and Computer Science could be a strong alternative to one with a purely economic background. In both engineering and economics, a common approach is to think in terms of performance objectives. History shows us how these objectives have evolved. Initially, minimizing cost was the primary goal. Then, quality was introduced, and the objective shifted to maximizing the quality-cost ratio. Over time, more sophisticated objectives emerged, such as continuous innovation, time-to-market, speed-to-market, mass customization, and agility. Today, it’s hard to imagine any business not leveraging the Internet, even in manufacturing. Competitive pressures and legal frameworks often require organizations to provide after-sales support, making operations management crucial for business success. Operations managers are tasked with balancing customer demands and organizational goals. We will conclude this chapter with a quote that captures the essence of customer expectations, to which operations must respond [nor02]: “Contrary to popular belief, getting to know customer requirements is not very diFicult… Any customer, in any industry, in any market wants stuF that is both cheap and better, and they want it yesterday. Organizations may spend millions of dollars every year getting [consultancy companies] to help them answer this question. But the simple truth is that the typical customer will always ask for improvements within the present frame.” Maximilian Nicolae - Service Operations Management from System Engineering Perspective References [bro01] Brown, S., Blackmon, K., Cousins, P., Maylor, H., 2001. Operation Management: Policy, Practice and Performance Improvement, Butterworth- Heinemann. [nor02] Nordstrom, K., Ridderstrale, J., 2002. Funky Business. Talent makes capital dance, BookHouse Publishing AB. [sla07] Slack, N., Chambers, S., Johnston, R., 2007. Operation Management, Fifth Edition, Prentice Hall. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Chapter 2 From Strategy to Operations and Vice Versa: Operations as a Driver and Implementation of Strategy 2.1 Strategy and Strategic Management “Strategy” is a frequently used term with roots in the military, often regarded as an art. It is deﬁned as the art or science of planning and conducting a war or a long-term plan for success, especially in business or politics [col03]. Given that strategy often covers broad areas with loosely deﬁned boundaries, deﬁning strategic management can be challenging. A noteworthy attempt at this is made in [nag07], which uses the analogy of a defendant unsure how to deﬁne pornography but claiming to know it when he sees it. Similarly, strategic management has often been debated, with each discipline claiming a central role in organizational success, much like the intersection of all organizational functions. In [nag07], a historical collection of strategic management deﬁnitions is presented, beginning with the concept of “business policy” from 1965. This early deﬁnition focused on analyzing the functions and responsibilities of general management and the factors that contribute to an organization’s overall success. By 1979, strategic management was deﬁned as a process that renews and develops the organization, formulating strategies to guide its operations. Later deﬁnitions added the consideration of internal and external environments to identify competitive advantages, emphasizing the alignment of operations with strategy to maximize resource utilization. After a thorough review of various deﬁnitions, [nag07] provides the following deﬁnition of strategic management: ”The ﬁeld of strategic management deals with a) the major intended and emergent initiatives b) taken by general managers on behalf of owners, c) involving utilization of resources d) to enhance the performance e) of ﬁrms f) in their external environments.” This deﬁnition is based on practitioners’ views rather than prescriptive concepts of what strategic management “should” be. From Strategy to Operations and Vice: Operations as a Driver and Implementation of Strategy Professor Michael Porter, a renowned authority on organizational strategy, distinguishes between operational eXectiveness and strategy in his article “What is Strategy?” [por96]. He argues that modern management tools and techniques have replaced true strategy, pushing organizations away from sustainable competitive positions. Porter emphasizes that the essence of strategy is performing diXerently from competitors, rather than merely adhering to “best practices.” He suggests that strategy deﬁnes an organization’s position, necessitates trade-oXs, and aligns activities accordingly. Porter also advises that organizations should position themselves where competitive forces are weakest [por08]. These forces include: Supplier power (force) – the inﬂuence suppliers exert through their trading power. Buyer power (customer’s force) – the motivation and bargaining strength of customers. Competitive rivalry – the pressure from existing competitors. Threat of new entrants – the potential for new competitors to enter the market and increase supply. Substitute products (surrogates’ force) – the availability of alternative products or services that reduce demand. While Porter’s focus is on positioning and competition, Mintzberg [moo11] introduced a more ﬂexible view, stating that strategy could emerge organically from operational decisions rather than being strictly planned in advance. In [bro01], strategy is distilled into three key objectives: Satisfying customers, Optimizing resource use (including external resources through alliances), Developing superior capabilities. 2.2 From Strategy to Operations In business, if our primary responsibility is operations, we derive our objectives from the strategy set by the organization. Our task is to implement these objectives through operational processes, eXectively translating strategy into action. Over time, many tools and techniques have been developed to assist and enhance operations. Originally rooted in manufacturing, these methods have since been adapted for the service industry as well. One of the seminal works on this evolution is The Machine That Changed the World [wom90], which draws on a study by MIT about the future of the automobile industry and outlines the development of lean principles. Historically, the ﬁrst form of production—whether in manufacturing or services—was craft production. It was characterized by highly skilled workers using multifunctional tools, which oXered ﬂexibility but resulted in expensive products or services. To address Maximilian Nicolae - Service Operations Management from System Engineering Perspective the high costs associated with craft production, mass production emerged. Mass production relied on narrowly skilled specialists who designed processes and tools that could be operated by less skilled workers. These workers, in turn, used highly expensive, single-purpose tools. The result was the production of cheaper goods and services, but with a high degree of standardization, leading to reduced variety. A collateral issue was the monotonous and unfulﬁlling nature of the work for employees. Mass production also introduced a challenge: the underutilization of costly equipment, as these machines needed to be running constantly to justify their expense. To maximize utilization, batch production was adopted, taking advantage of economies of scale. However, this approach proved problematic, as it led to increased inventory costs. To mitigate this, capacity management and the Just-In-Time (JIT) approach were developed, with the latter being closely aligned with the Theory of Constraints. This concept is eXectively explained in The Goal: A Process of Ongoing Improvement by Goldratt [gol04], which describes how optimizing the use of bottleneck resources improves the ﬂow of operations. To overcome the limitations of both craft and mass production, the Lean concept was developed. Lean production combines the strengths of both approaches—ﬂexibility from craft production and eXiciency from mass production—while mitigating their respective disadvantages. Henry Ford was a pivotal ﬁgure in this evolution. He was the ﬁrst to recognize the drawbacks of craft production and is credited with introducing mass production on a large scale, revolutionizing industry and setting the stage for modern operational methods. 2.3 From Operations to Strategy Thus far, we have seen how operations are typically viewed as the execution mechanism for strategy, turning strategic objectives into reality. This perspective treats operations as closed systems within the organization, playing no direct role in shaping the organization’s strategy. However, some authors argue that the relationship between strategy and operations goes deeper. For instance, in [hay84], a four-stage model is proposed (Figure 2.1), highlighting the dynamic relationship between operations and strategy. The stages are determined by two factors: 1. The organizational environment (internal or external knowledge). 2. The inﬂuence of operations on strategy (neutral or supportive). These four stages are represented as follows: From Strategy to Operations and Vice: Operations as a Driver and Implementation of Strategy Supportive Stage IV Stage III Stage I Neutral Stage II Figure 2.1. Four stages diagram Stage I (Internal Neutral): At this stage, competitiveness is derived from product/service design and marketing eXorts. The role of operations is simply to execute, producing the goods or services as designed and adhering to marketing’s volume demands. Operations only attract attention when there is a failure in execution. In this case, operations are neutral, meaning they do not negatively impact the strategy but do not actively contribute to it either. Stage II (External Neutral): Here, operations are tasked with seeking external “best practices” to align with industry standards. The goal is to achieve parity with competitors in performance and supplier relationships, thereby increasing the organization’s proﬁtability. Even though operations look outward, this stage is still considered neutral, as operations merely ensure they do not hinder strategic objectives. The focus is on eXiciency (doing things right) rather than eXectiveness (doing the right things). Stage III (Internal Supportive): In this stage, operations begin to play a more active role in shaping strategy. The relationship between operations and strategy becomes bidirectional: operations provide competitive advantages that inﬂuence strategic decisions. In this stage, operations are considered supportive, actively contributing to the organization’s competitive edge. Stage IV (External Supportive): At this ﬁnal stage, operations become the primary driver of strategy. The organization’s competitiveness stems directly from its operational capabilities. The focus is on excelling in its domain through world-class operations and continuous improvement. This approach embodies the concept of “world-class” organizations, where operational excellence shapes strategic direction. Maximilian Nicolae - Service Operations Management from System Engineering Perspective While Stage IV, in which operations dominate strategy, has its critics—particularly those who argue that marketing should remain the primary driver of competitiveness—there are modern frameworks that align with this view. For example, M. Porter’s earlier analysis [por96], [por08] presents an argument worth considering, where operational eXectiveness and strategy are distinct but complementary. Modern approaches, where operations play a pivotal role in competitiveness, include: Flexible Specialization (Flexibilism or Post-Fordism): This concept counters Henry Ford’s mass production model, focusing instead on ﬂexibility and customization. Small companies specialize in speciﬁc components and collaborate in clusters to produce better products and services, prioritizing adaptability over economies of scale. Mass Customization: This approach seeks to combine the advantages of mass production with product variety, allowing for customization while maintaining the cost beneﬁts of large-scale production. Lean Production: Popularized by [wom90], lean production focuses on waste elimination throughout the operations process. Agility: Agility emphasizes speed and responsiveness, allowing organizations to adapt quickly to changing market demands. Strategic Operations: A more formal description of Stage IV, where operations actively shape and drive strategic decisions. 2.4 Performance Objectives of Operations According to [sla07], there are ﬁve basic performance objectives of operations: Quality: Quality can be deﬁned in various ways, often from the customer’s perspective. Importantly, this customer may not always be external to the organization. Consider the supplier network model, which diXerentiates between the operations network and the processes network (as illustrated in Figure 1.6, Chapter 1). For example, Toyota’s commitment to quality is evident in its famous Toyota Production System, which emphasizes continuous improvement (Kaizen) and rigorous quality control measures. Speed: This objective refers to how quickly an organization can deliver the products or services requested by customers. For instance, Amazon’s investment in logistics and distribution centers enables rapid order fulﬁllment, allowing them to oXer same-day or next-day delivery in many locations, signiﬁcantly enhancing customer satisfaction. Dependability: Dependability is the ability to adhere to scheduled deliveries for both internal and external clients. While speed helps plan delivery times, dependability ensures that those commitments are met. For example, without using companies’ names, there are some renowned for their reliable delivery From Strategy to Operations and Vice: Operations as a Driver and Implementation of Strategy services, which have made them leaders in the logistics industry. The company’s commitment to meeting delivery deadlines is crucial for its customers, particularly in time-sensitive industries. Flexibility: This refers to the capability of operations to adapt their characteristics concerning outputs (such as type and volume) and processes (including duration and transformed inputs). A key factor in maximizing ﬂexibility is the eXective utilization of IT and communication infrastructure. The combination of high ﬂexibility with high speed is essential for achieving agility. For instance, some fashion wearing companies employ a ﬂexible supply chain that allows it to rapidly respond to fashion trends, adjusting production quantities and styles based on real-time customer feedback. Cost: Cost considerations are integral to nearly all operations. Companies like Walmart have built their business model around keeping operational costs low, allowing them to oXer competitive pricing while maintaining proﬁtability. Their extensive use of technology and eXicient supply chain management contributes to this objective. There are correlations among these basic performance objectives. For instance, while enhancing quality may increase costs, it can also lower them by eliminating expenses associated with faulty products and services provided to customers, including those internal to the processes network. Similarly, improving speed can reduce costs—such as inventory expenses—and, in critical cases like healthcare, can save lives. These correlations can be explored for all performance objectives. A commonly used measure of operational eXiciency is productivity, deﬁned as the ratio of certain output characteristics of a process to the corresponding input characteristics required for transformation. It quantiﬁes the output generated per unit of input. Common types of productivity include labor productivity and multifactor productivity (as shown in Figure 2.2). Labor productivity measures the amount of output produced by a worker over a speciﬁed period, using inputs such as the number of workers, job hours, etc. Multifactor productivity incorporates a combination of expenditures on materials, labor, capital, and more as inputs. Output Productivity = Input Output Labor productivity = Labor Inputs (workers, hours, etc.) Output Multifactor productivity = Operation’s expenditures (Labor, Capital, etc.) Figure 2.2. Productivity formulas Maximilian Nicolae - Service Operations Management from System Engineering Perspective Productivity is typically measured as an average. However, in practice, we often encounter alternative productivity forms by dividing the outputs of an operation by a single type of input (referred to in [sla07] as single-factor productivity). This approach facilitates comparisons between diXerent operations based on the same input. To enhance productivity, we can either minimize the number of inputs required to achieve the same outputs or improve the utilization of inputs to generate a greater output volume. However, it’s important to note that productivity ﬁgures can sometimes be artiﬁcially inﬂated, for example, through a lack of investment. To illustrate the signiﬁcance of performance objectives within operations, a polar representation can be employed ([sla07]). This intuitive tool (depicted in Figure 2.3) allows for the comparison of operations based on any relevant performance objective. Dependability Operation A Speed Flexibility Operation B Cost Quality Figure 2.3. Polar representation of relative importance of performance objectives In recent years, several trends have emerged in the ﬁeld of operations management that impact performance objectives: Sustainability: Increasingly, organizations are focusing on sustainable practices that minimize environmental impact while maintaining eXiciency. Digital Transformation: The rise of digital technologies has transformed how operations are managed. Advanced analytics, artiﬁcial intelligence (AI), and the Internet of Things (IoT) enable real-time decision-making and improve ﬂexibility From Strategy to Operations and Vice: Operations as a Driver and Implementation of Strategy and speed. For instance, Siemens uses IoT technology in its manufacturing processes to enhance productivity and reduce downtime through predictive maintenance. Customer-Centric Operations: There is a growing emphasis on aligning operations with customer needs. Organizations are leveraging data analytics to gain insights into customer preferences and behaviors, allowing for more tailored oXerings and improved quality. Starbucks, for example, uses customer feedback and data analytics to reﬁne its menu and service delivery. 2.5 Operations Strategy In the introduction of this chapter, we addressed the concept of strategy, highlighting the challenges of deﬁning it. These complexities also apply to operations strategy. Building on our earlier discussion, we can eXectively: 1. Understand the organization’s goals and objectives. 2. Design the operations accordingly. 3. Deﬁne and monitor the performance objectives of operations. Above all, we must plan for the long term—a strategy that oXers competitive advantages and enhances operations. In this context, operations strategy can be viewed as a roadmap for the future development of operations and the organization as a whole. There are four primary operations strategies commonly identiﬁed in literature: Top-down Strategy: Designed by senior decision-makers (often the owners), this strategy is inﬂuenced by various factors, including the owners’ perspectives and the political and social environment. Bottom-up Strategy: Based on operational experiences, this approach can be seen as resource-driven, as it utilizes the knowledge and skills acquired through hands-on experience in operations. Demand-driven (Market-led) Strategy: Rooted in marketing principles, this strategy begins with identifying market opportunities and then plans operations to meet customer needs. While some argue that this should be the sole strategy due to its customer-centric focus, there is considerable debate about the balance between demand and resources. Resource-driven Strategy: This strategy focuses on leveraging the organization’s operational capacity and supplier relationships. As noted by [sla07], these intangible resources can provide signiﬁcant competitive advantages and shape the corresponding operations strategy. In evaluating these strategies, it is crucial to recognize their advantages and disadvantages. The resource-driven strategy may lead to superior products or services that lack market demand, while the demand-driven strategy could result in ambitious plans that exceed operational capabilities. This gap between vision and operational capacity is frequently encountered in practice. An article titled “Why CEOs Fail: It’s Rarely Maximilian Nicolae - Service Operations Management from System Engineering Perspective for Lack of Smarts or Vision” [cha99] illustrates the strategic importance of operations and the role of operations managers. Many authors contend that a simplistic model for strategy is inadequate. As highlighted in [bro01], “strategy resonance” refers to how world-class organizations blend market- led and resource-driven strategies. A signiﬁcant aspect of operations strategy is managing trade-oXs between performance objectives. For instance, in a call center, speed (minimizing customer wait times) may conﬂict with cost (keeping the number of employees low). Operations strategy also involves balancing in-house capabilities against outsourcing options. Another strategic approach involves targeting market leaders at the peripheries of their business portfolios, where they may be vulnerable, before challenging their core business. A prime example of this is Google’s evolution from a search engine to an email service provider and eventually to competing in the operating system sector. With the shift toward smaller, integrated devices—often termed the “disappearing computer”— Google’s strategy appears increasingly viable. The rapidly evolving landscape of IT and communications has transformed the business environment, prompting potential changes to established economic principles. For example, e-commerce has redeﬁned competitive dynamics. It is intriguing to observe how many principles articulated by John Maynard Keynes in his landmark work from 1935, The General Theory of Employment, Interest, and Money [key36], remain relevant today. In contrast, the economic principles underpinning Google’s approach can also be analyzed [gir09]. Focusing on service organizations, as stated in [bro01], they can adopt one of the following strategies: Customer-oriented: This strategy prioritizes satisfying a niche segment by oXering a diverse range of services and developing new oXerings in response to existing customer needs. Service-oriented: This strategy aims to attract a broader client base by providing a limited selection of specialized, high-quality services. Hybrid Approach: This combines both customer and service-oriented strategies. Service organizations often struggle to meet performance objectives consistently. To compensate, they may oXer service guarantees and recovery options. A notable characteristic of service strategy is the incorporation of customers into production and delivery processes, known as co-production or the “consumerization” of production [bro01]. Examples include self-check-in kiosks, self-service banking, fast- food outlets, gas stations, supermarkets, and online shopping platforms. Three primary methods transform customers into labor resources for service operations: From Strategy to Operations and Vice: Operations as a Driver and Implementation of Strategy 1. Speciﬁcations: This approach minimizes the need for employees to provide customization advice, allowing customers to deﬁne their own service speciﬁcations using conﬁguration software (e.g., web hosting, transportation, accommodation). 2. Service Delivery: Customers actively participate in delivering services by performing tasks typically handled by staX (e.g., self-service options). 3. Quality Control: Customers are accountable for ensuring the quality of the services or products they receive. This practice is common in supply networks, particularly in implementing Total Quality Management (TQM). In summary, the strategic imperatives that organizations should consider, as outlined in [bro01], include: Process selection Innovation management Supply chain management Resource management Production management Workforce management Quality management (customer satisfaction) Among these, operations strategy should focus on: Capacity management Facility design and location Technology investments Supply chain and customer relationship management Development of new products and services References [bro01] Brown, S., Blackmon, K., Cousins, P., Maylor, H., 2001. Operation Management: Policy, Practice and Performance Improvement, Butterworth- Heinemann. [cha99] Charan, R., Colvin, G., 1999. Why CEOs Fail It's rarely for lack of smarts or vision. Most unsuccessful CEOs stumble because of one simple, fatal shortcoming. Fortune Magazine. [col03] Collins English Dictionary – Complete and Unabridged, 2003, HarperCollins Publishers. Maximilian Nicolae - Service Operations Management from System Engineering Perspective [geo03] George, M.L., 2003. Lean Six Sigma for Service: How to Use Lean Speed and Six Sigma Quality to Improve Service and Transactions, McGraw-Hill. [gir09] Girard, B., 2009. The Google Way, How One Company Is Revolutionizing Management As We Know It, No Starch Press. [gol04] Goldratt, E.M., Cox, J., 2004. The Goal. A Process of Ongoing Improvement. Third Revised Edition, North River Press. [hay84] Hayes, R.H., Wheelwright, S.C., 1984. Restoring Our Competitive Edge: Competing Through Manufacturing. John Wiley. [key36] Keynes, J.M., 1936. The General Theory of Employment, Interest and Money, Macmillan Cambridge University Press (available free on Interent) [moo11] Moore, L. 2011 - The Emergent Way: How to achieve meaningful growth in an era of ﬂat growth – Ivey Business Journal. Available online at link. [nag07] Nag, R., Hambrick, D.C., Chen, M.J., 2007. What is strategic management, really? Inductive derivation of a consensus definition of the field. Strategic Management Journal. Vol. 28, Issue 9, 935-955. [por96] Porter, M.E., 1996. What is Strategy? Harvard Business Review, November- December, 59-78. [por08] Porter, M.E., 2008. The Five Competitive Forces That Shape Strategy. Harvard Business Review, January. [sla07] Slack, N., Chambers, S., Johnston, R., 2007. Operation Management, Fifth Edition, Prentice Hall. [wom90] Womack, J.P., Jones, D.T., Roos, D., 1990. The Machine That Changed The World. Macmillan Publishing. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Chapter 3 Operations in the Process of Developing New Products and Services 3.1 Introduction Clients typically engage with organizations primarily because of the products and services they offer or are capable of delivering. This interaction often serves as the initial point of contact between the organization and the customer. However, the purpose of this chapter is not to explore the promotion of products and services—this responsibility lies within the marketing function. Instead, this chapter aims to examine a systemic, process-oriented approach to support the marketing “promises” and requirements in the development of new products and services (NPSD). This initial interaction can provide critical insights for designers of new products and services. The mechanisms for gathering and utilizing such insights are discussed in a separate volume dedicated to Customer Relationship Management. Here, the design activity is considered as a structured process (Figure 3.1) that must be carefully managed to achieve its goals. Resources: Transformation Specifications -information Process for -people (Subject to New products -equipment performance and services measurements) (including delivery) Figure 3.1. NPSD seen as process. Within this process, two types of resources play a pivotal role: Transformable Resources: These are resources subjected to the transformation process. In NPSD, they primarily consist of diverse information types, such as technical data, customer research, market studies, and competitive forecasts. Transforming Resources: These resources facilitate the transformation of the first category. They include personnel, equipment, and tools. Among these, computers and software, including Computer-Aided Design (CAD) and Computer Operations in the Process of Developing New Products and Services Integrated Manufacturing (CIM) applications, are crucial for competitive NPSD, supporting rapid design, testing, and simulation of new products and services. Like any goal-oriented process, NPSD is subject to performance evaluation. Key performance metrics—discussed in the previous chapter—include: Quality Speed Dependability Flexibility Cost Additionally, several long-term performance indicators reflect the organization’s primary objectives. Based on [gri93], these measures are recognized as effective for NPSD, including in the service domain. They fall into four main categories: Customer Acceptance Measures: o Customer acceptance o Customer satisfaction o Achievement of revenue goals o Revenue growth o Market share objectives Product/Service-Level Measures: o Development costs o Launched on time o Product/service performance level o Quality benchmarks o Speed to market Financial Performance Measures: o Break-even time o Margin targets o Internal Rate of Return (IRR) and Return on Investment (ROI) Firm-Level Measures: o Percentage of total sales from new products Maximilian Nicolae - Service Operations Management from System Engineering Perspective An essential measure here is “Launched on time,” which corresponds to the Time-to- Market (TTM) characteristic. TTM refers to the interval between the decision to develop a new product or service and its availability to customers. The “first mover’s advantage” underscores the significance of TTM, as a swift product release can increase revenues and market share. Conversely, delays can lead to substantial revenue loss. TTM can be broken down into three key aspects [bro01]: Continuous Stream of Offerings: In service-oriented sectors, particularly digital services, continuous improvements or added functionalities create a stream of “new” services. For products, success often depends on the support services and product enhancements provided post-launch, differentiating products in the market. Speed: This refers to the velocity of the iterative improvements above, which can define competitive advantage. Faster development cycles often enable organizations to capture market share earlier. Announcement Timeliness: Setting realistic release timelines is crucial, even if some features are still under development. For example, announcing, “Online payment options via credit card will be available by the end of June 2012,” provides customers with concrete expectations, helping maintain customer loyalty and attract new clients. In summary, the design phase cannot be isolated from the production or delivery processes of the final product or service. A cohesive process allows for systematic performance measurement and control. As highlighted in [bro01], operations and operations managers play a vital role in ensuring that new products and services deliver competitive advantages and that NPSD investments yield timely returns, rather than being delayed or underutilized. 3.2 Product/Service Components All products and services can be understood as comprising three primary components [sla07]: Concept: This is the foundational idea or objective that guides the entire design process. It captures the core purpose or goal of the product or service. Package: The package represents the tangible form in which the concept is realized. It typically consists of: o Core Components: Fundamental elements essential to the concept’s fulfillment. o Supporting Components: Additional features or services that enhance the appeal and functionality of the core components. Operations in the Process of Developing New Products and Services Process: This is the operational sequence through which the package is created and delivered to the end customer. To clarify these components, consider the example of a university. Beyond its research objectives, one central concept of a university is to deliver quality education at various academic levels. While the broader concept is the development of knowledge and competencies, students—who are the customers in this context—primarily engage with the university’s package. For instance, the university offers packages for bachelor’s, master’s, and doctoral programs, each culminating in a diploma as a core component. Supporting components might include certifications, hands-on research experience, access to internships, and involvement in high-level projects. The process here encompasses the methods by which these educational packages are delivered, from lectures and labs to internship placements and research opportunities. In developing new products or services, it is essential to address each of these components. Innovation may stem from introducing new concepts, creating novel packages around existing ideas, or developing new processes for producing or delivering existing packages. The extent of innovation can vary significantly: (A completely new) invention, introducing something novel to the market. A new addition to the organization’s existing portfolio. An improvement or reconfiguration of an existing product or service. An illustrative example is the banking sector. While the fundamental concepts of banking remain rooted in traditional ideas, the packages and processes have evolved significantly, as seen in the introduction of digital banking, mobile payments, and virtual customer service—all innovations built upon pre-existing concepts. As discussed in the previous chapter, operations can play a strategic role in developing new products and services. Effective operations often inspire service advancements, as seen in the example of universities, where high-performance research operations have led many top universities to elevate research to a core service alongside education. Similarly, operational improvements have driven new service developments in e-banking, enabling enhanced accessibility and convenience for customers through secure online platforms. 3.3 Operations in the New Product or Service Development (NPSD) Process In Figure 3.2, the role of operations within the New Product or Service Development (NPSD) process is illustrated. Typically, designers receive preliminary specifications from various sources, such as the marketing department—which analyzes customer needs— as well as research and development (R&D) units, competitor analysis, and supplier inputs. Using this information, designers craft new products or services with the ultimate objective of facilitating production and delivery. At this stage, designs take the form of Maximilian Nicolae - Service Operations Management from System Engineering Perspective detailed operational specifications, enabling the operations function to proceed with production or service delivery. Consequently, a strong understanding of operational requirements is essential for designers. Customer R&D Competitor s s Marketing Designers Suppliers Operations New Product/ Service Figure 3.2. Operations in context of NPSD Various generic approaches to product development can easily be adapted to service development as well [ulr00]: Market Pull: Development is driven by an organization’s response to identified customer needs. Technology Push: A new or specialized technology prompts the organization to find suitable market applications. For example, a company specializing in security technologies might launch secure payment solutions. Platform (Infrastructure): New services are developed using the same infrastructure that supports existing services, as seen with cloud-based offerings. Process Intensive: When service delivery requires a complex and costly process, the service design often evolves alongside the delivery method. Virtualization technology for cloud infrastructure, initially used for web hosting, now powers sophisticated processing services. Operations in the Process of Developing New Products and Services Customization: The organization tailors services to individual customers or helps them find the right service from a partner organization, as seen in consultancy services. As illustrated in Figure 3.2, the entire NPSD process should be treated as a streamlined operation, with a strong emphasis on process automation. Customer Relationship Management (CRM) forms a vital stage in this integrated approach, which will be discussed in detail in a later work. Here, we will delve into the design process from an operational perspective, as shown in the stages from initial concept ideas to final service specifications in Figure 3.3. Ideas Evaluating Pilot of Filtering Designing & Service Concepts Improving Delivery Figure 3.3. The stages of service design Stages in Service Design Idea Generation: Concepts may originate from diverse sources: o Customers: Through tools such as CRM and market analysis. o External R&D Organizations: Fundamental research, often government- funded, can contribute innovative ideas. o Internal R&D Departments: Tasked with creating and advancing new concepts. o Staff: Frontline employees interact directly with customers and often identify new opportunities. o Competitors: Techniques like reverse engineering reveal potential improvements. o Suppliers: New supplier technologies or infrastructure often inspire fresh service ideas. Idea Filtering: Evaluating ideas through criteria such as financial viability, strategic alignment, and operational feasibility is essential. Referred to as “concept screening” [sla07], this stage focuses on three main criteria: o Feasibility: Is the idea achievable? o Acceptability: Is the idea worthwhile? o Vulnerability: What are the risks involved? Maximilian Nicolae - Service Operations Management from System Engineering Perspective Figure 3.4 depicts a “design funnel” model commonly used to illustrate this filtering process. While the funnel’s simplicity is useful, it may not capture the creativity, negotiation, and complexity inherent in design activities [sla07]. Not all ideas progress to new products or services, yet even discarded ideas may hold potential for future licensing, patenting, or spin-off ventures. Ideas DESIGN FUNNE L New Keeping New product/ for the For sell business service future Figure 3.4. Concept screening Designing: This stage focuses on the product or service’s package and process. Design simplicity is often a goal, even though services can be inherently complex. Methods to reduce design complexity include: o Standardization: Limiting services to standardized options, such as in insurance. o Commonality: Using shared processes across multiple services, such as online payment systems for e-commerce and reservations. Operations in the Process of Developing New Products and Services o Modularity: Designing interconnected processes for flexibility, as seen in healthcare services. Evaluation and Improvement: Before launching, the design is assessed against objectives. If necessary, it returns to the design stage for adjustments. Evaluation techniques include: o Quality Function Deployment (QFD): Also known as the “house of quality” or “voice of the customers,” QFD aligns customer needs with technical solutions to balance satisfaction and cost. o Failure Mode and Effects Analysis (FMEA): This technique identifies potential failure points and classifies them based on severity, probability, and detection, using a Risk Priority Number (RPN) for prioritization. o Taguchi Methods: Statistical techniques for experimental measurement. o Value Engineering: This approach enhances product value by optimizing the ratio of customer-perceived utility to production cost. Pilot Service Delivery: Before full deployment, a service prototype is tested in a controlled setting with simulated customers. This mitigates the risks of direct market launch and allows for real-world testing. Simulation software is instrumental here, modeling scenarios such as queue length variability, customer arrival patterns, user profiles, and system load. This approach, resembling decision-making simulations in everyday scenarios, builds a comprehensive “film” of potential events, optimizing service readiness for real customers. 3.4 Other Designing Considerations Viewing the development of new products and services as a managed, operational process emphasizes the importance of efficiency and integration. In this approach, achieving increased automation and reducing the time it takes for a concept to reach the final service stage are primary goals. Equally important, however, is the need to clearly define what constitutes a well-designed service before launching operations to deliver it. In [bro01], several key elements are suggested for consideration in the design process: Customers’ needs and preferences Resource constraints Designers’ creativity Time constraints Technical constraints Marketability of the concept In the service sector, integrating customers directly into the design process has become a valuable trend, with three main approaches defined in [mag01]: Maximilian Nicolae - Service Operations Management from System Engineering Perspective Design for Customers – Shaped by the staff’s understanding of customer needs. Design with Customers – Developed with direct customer feedback. Design by Customers – Allowing customers to configure the service themselves. The entire NPSD (New Product and Service Development) process depends on strong integration, with recent trends in operations management, such as Lean methodology, extending into the NPSD process. Lean NPSD emphasizes reducing waste and establishing a pull system—creating services in response to demand without excess production, rather than a push system that prioritizes resource allocation. Among the Lean techniques recommended for NPSD is concurrent engineering, as discussed in [kar96]. Concurrent Engineering involves overlapping development stages, as seen in Figure 3.3, with the aim of accelerating time-to-market by minimizing back-and-forth between stages [bro01]. Also known as “simultaneous development” [sla07], this approach anticipates the effects of design decisions across various stages. Figure 3.5 illustrates an example from the electronics field using Altium Designer, an Electronic Design Automation (EDA) tool from Altium. A typical development scenario might unfold as follows: Figure 3.5. CAD tool for simultaneous development (top left - the schematic of the design, top right – the layout of the design - PCB, bottom down- the assembly simulation, bottom middle – the configuration commands for manufacturing machines, bottom right – the final product) Operations in the Process of Developing New Products and Services Concept Generation – Based on the desired functionality. Hardware Schematic Design – Initial planning of component interactions. Hardware Layout Design – Configuration and spatial arrangement of components. Fabrication Process – Checking the design against fabrication requirements. If issues arise (e.g., component positioning that impacts soldering), the design may need revision. Software Testing on Physical Device – Errors, such as unintended interference between closely spaced wires, may require revisiting and refining the schematic or layout. Ongoing Adjustments – Changes in supplier components or cost-saving opportunities may necessitate iterative updates, balancing redesign costs with potential profit gains. This figure shows how integrated tools today enable simultaneous design by supporting all stages of development. Known as “design for manufacture,” these tools create a realistic simulation environment, automatically validating key requirements. For example, in Figure 3.5, while designing the hardware schematic, code can simultaneously be developed and tested, and the layout adjusted to ensure signal integrity and fabrication readiness. These tools generate outputs for manufacturing equipment (Computer Integrated Manufacturing – CIM), allowing real-time updates across stages in case of design changes, drastically lowering redesign costs compared to traditional methods. For services, where the production and delivery processes occur simultaneously, such tools primarily focus on modeling and simulation rather than technical specifications, with platforms like Enterprise Dynamics serving as prominent examples. In modern product and service development, Virtual Commissioning (VC) has become a critical tool to optimize efficiency and reduce deployment risks. VC is a process that uses digital twins and simulation environments to validate and test systems virtually before deploying them in physical settings. By creating a high-fidelity virtual replica of the physical system, engineers can simulate various operating scenarios and identify potential issues in the design and operational flow without the need for physical equipment. VC integrates seamlessly with Lean NPSD principles by supporting iterative testing and refinement without production interruptions. This approach is particularly useful in identifying bottlenecks, optimizing layouts, and verifying control logic. The virtual environment facilitates safe and cost-effective testing of failure scenarios that could be difficult, costly, or dangerous to replicate in physical systems. For example, in simultaneous development environments, VC allows cross-functional teams to interact with a virtual model of the product early in the design phase, providing real-time feedback on factors like manufacturability, resource allocation, and customer requirements. Integrating VC into the development workflow ensures that by the time the Maximilian Nicolae - Service Operations Management from System Engineering Perspective physical commissioning phase is reached, most issues have been addressed, reducing both time-to-market and commissioning costs. Moreover, the digital outputs generated in VC can be directly applied to real-world control systems in many cases. This bidirectional capability of VC makes it a valuable asset in both the design and operational phases, ultimately enhancing the reliability and agility of NPSD processes. References [bro01] Brown, S., Blackmon, K., Cousins, P., Maylor, H., 2001. Operation Management: Policy, Practice and Performance Improvement, Butterworth- Heinemann. [gri93] Griffin, A., Page, L., 1993. An interim report on measuring product development success and failure, In Journal of Product Innovation Management, Volume 10, Issue 4, September 1993, Pages 291–308 [kar96] Karlsson, C., Ålhström, P., 1996, The Difficult Path to Lean Product Development, Journal of Product Innovation Management, 13, pp 283-295. [mag01] Magidson, J., Brandyberry, G., 2001. Putting Customers in the “Wish Mode”, Hardvard Business Review. [sla07] Slack, N., Chambers, S., Johnston, R., 2007. Operation Management, Fifth Edition, Prentice Hall. [ulr00] Ulrich, K.T., Eppinger, S.D., 2000. Product Design and Development, Second Edition, Irwin McGraw-Hill. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Chapter 4 Designing the Operation Process. Layout and Flow 4.1 Introduction In previous chapters, we examined the role of operations within an organization’s strategy and its crucial impact on designing products and services. We established that operations serve as the foundation for fulﬁlling promises made by marketing, making the design of the resource transformation process critical. Ideally, an operations specialist should oversee this design to align with organizational strategy and adapt to market dynamics and technological advancements. This evolving landscape positions every operations manager as a designer, adapting processes to continuously meet current demands. For service-based processes, the design phase often merges with service creation, as customers actively participate in the transformation process itself [sla07]. In B2B and M2M contexts, the term “client” may better capture this relationship than “customer.” EQective process design requires integrating client needs and feedback while aligning with clear process objectives. This chapter explores these objectives and the factors inﬂuencing them. 4.2 Considerations on Process Design Objectives Designing or redesigning an operational process involves making strategic choices that will shape the organization’s future performance. The eQectiveness of this process is often a competitive advantage, impacting metrics like quality, speed, dependability, ﬂexibility, and cost. Except for quality (discussed in a later chapter), these performance goals are directly inﬂuenced by the ﬂow within the process. A streamlined ﬂow minimizes customer wait times, reduces queues (supporting speed and dependability), optimizes capacity use (lowering costs), and enables a “pull” production model that reduces inventory levels (enhancing cost and ﬂexibility). Figure 4.1 illustrates the main factors in process design. When modifying an established process, overcoming inertia [bro01] (or resistance to change) is often a challenge, encapsulated by the saying, “If it isn’t broken, don’t ﬁx it.” Another vital design consideration is “green” or sustainable process design, especially for IT-heavy services. The energy costs of IT infrastructure now account for nearly half of total organizational power usage in some sectors [har09]. Consequently, sectors like ﬁnance are increasingly adopting cloud solutions, mobile technology, and green computing environments to manage their complex operations sustainably. Designing the Operation Process. Layout and Flow Top Level Strategy Marketing Operations Strategy Performance objectives: Quality Speed Dependability Flexibility Cost [Existing] Suppliers Process Characteristics Process Design Objectives Figure 4.1. Factors influencing the process design objectives. 4.3 Process Types Process types have evolved alongside advancements in manufacturing, progressing from craft production to mass production and, later, to more specialized approaches. The trend from individual craftsmanship to streamlined, high-volume manufacturing processes created a trade-oQ between product volume and variety. This dichotomy is visible in both manufacturing and service processes, where operations are categorized based on the balance between production volume and output variety. In manufacturing, ﬁve main process types have emerged: project, job, batch, line (mass), and continuous processes. As the service sector grew, methodologies from manufacturing were adapted to ﬁt service needs. While diQerences remain, the concepts of volume and variety are still central in service operations. Schmenner’s Service Process Matrix [sch95] (ﬁrst introduced in 1986) categorizes service processes by customer interaction and customization (analogous to product variety) and labor intensity. Labor intensity, once a measure of human involvement, now also considers computational demand in IT-driven processes. The matrix thus adapts with advances in automation and IT infrastructure. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Figure 4.2 (top) displays this matrix, while the bottom portion reﬂects the updated interpretation. Labor intensity level Mass Professional Service Service Service Service Factory Shops Customer interaction level Mass Service Service Professional Service Factory Shops Service Low Customer interaction level High Figure 4.2. Services process types Notably, the boundaries between process types are often ﬂuid. Higher complexity correlates with greater customization needs and a higher level of customer interaction, but not all processes ﬁt neatly within one category. Instead, volume-variety remains a more versatile framework for analyzing processes [sla07], discussed further in [hay84] and [sch95]. The key process types are proﬁled in ﬁgure 4.3 and include: Project Processes are deﬁned by high variety and low volume, with each output typically being unique and requiring tailored resources and skills. Due to the customized nature of these processes, they often involve complex, non-repetitive tasks that are diQicult to schedule precisely. Common examples include large- scale construction projects, complex research initiatives, and certain legal cases. These processes demand specialized management, signiﬁcant planning, and a high level of adaptability to ensure that resources align with evolving project requirements. Jobbing Processes closely resemble project processes in terms of customization and ﬂexibility but operate with a slightly lower variety and some repetitive elements. They are characterized by the presence of standardized steps that can be applied to diQerent outputs, though each ﬁnal product is still largely Designing the Operation Process. Layout and Flow customized. For instance, a web design ﬁrm might create highly customized websites but still rely on common templates or modules across diQerent projects. Jobbing allows for more eQicient use of resources compared to project processes, though still retains a degree of ﬂexibility. Volume of outputs Variety of outputs Complexity of tasks Throughput rate (Speed) Predictable Flow MANUFACTURING Project Jobbing Batch Mass (Line) Continuous Processes Processes Processes Processes Processes SERVICES Professional Service Service Mass Service Shop Factory Services Figure 4.3. Process types in relations with process characteristics Batch Processes are designed to produce a greater volume of outputs than jobbing while leveraging economies of scale to lower unit costs. Although batch processes accommodate a range of product variations, they require considerable setup time, particularly when switching between batches of diQerent products. For example, a CNC machine could produce small custom parts in batches, but the setup costs must be oQset by producing enough units within each batch. These processes occupy a middle ground on the volume-variety spectrum, requiring careful planning and management due to variability in demand and cost considerations. Batching is common in industries such as food production and printing. Maximilian Nicolae - Service Operations Management from System Engineering Perspective Mass (or Line) Processes represent a shift towards high volume and low variety, focusing on repetitive, standardized production methods that deliver consistent outputs at a low unit cost. The line production approach, often synonymous with mass production, involves a sequence of operations laid out to produce outputs at scale with minimal customization. Mass processes are widely used in automotive manufacturing, electronics assembly, and other industries that beneﬁt from high demand for uniform products. While eQicient and cost-eQective, these processes typically oQer limited ﬂexibility, as they rely on specialized equipment and layout designed for maximum throughput in producing a single or limited range of products. Continuous Processes diQer from mass processes in that they operate with a seamless, non-stop ﬂow, often producing outputs that cannot be easily divided into discrete units. This uninterrupted ﬂow is critical in industries where stopping and restarting production would be costly or impractical, such as in petroleum reﬁning, chemical processing, and utilities (e.g., power generation). These processes involve signiﬁcant upfront investments in infrastructure and equipment, and require rigorous control and maintenance to avoid operational disruptions. Continuous processes achieve low per-unit costs and extremely high volumes, but lack ﬂexibility for producing varied outputs or adjusting to ﬂuctuating demands. Professional Services are characterized by high variety and low volume, where each service provided is unique and labor-intensive, often requiring specialized skills and signiﬁcant customer interaction. These services rely on in-depth consultation with clients to deliver highly customized solutions, as seen in industries like legal consultation, architectural design, and specialized healthcare. Professional services tend to be expensive due to the high skill level required and the complexity of tailoring solutions to individual clients. They also beneﬁt from greater ﬂexibility and adaptability but often struggle with scalability. Service Shops combine high levels of customization with moderate volumes, oQering more standardized services than professional services but still requiring a tailored approach for each customer. Common examples include auto repair shops, hospitals, and certain types of restaurants. In a service shop, there are typically core service elements that are repeated for each client, with customization focused on the speciﬁc needs of the individual customer. Service shops strike a balance between personalization and eQiciency, making use of standardized processes where possible to improve speed and cost-eQectiveness while maintaining a relatively high degree of ﬂexibility. Service Factories deliver services in high volumes, using standardized processes to achieve eQiciencies similar to those seen in manufacturing. These operations are often structured to handle a large number of clients with minimal variation in service provision. Hotels, airlines, and large chain restaurants exemplify service factories, where customers experience similar services with limited customization options. Service factories beneﬁt from economies of scale, Designing the Operation Process. Layout and Flow allowing them to oQer services at lower costs, but they typically sacriﬁce ﬂexibility and personalization as a trade-oQ for eQiciency and speed. Mass Services operate at very high volumes with minimal customization, focusing on eQiciently serving a broad customer base through highly standardized processes. In mass services, customers experience a uniform level of service with few options for personalization. Examples include hypermarkets, educational institutions, and some transportation services. These processes maximize eQiciency and minimize per-client cost but oQer little to no ﬂexibility. Mass services are structured to handle high throughput, often by automating processes and limiting service variety to accommodate large numbers of customers with minimal variation in service requirements. While these categories provide a useful framework, many real-world processes do not ﬁt neatly into a single type. Hybrid processes, which combine elements from multiple categories, are increasingly common. For instance, an automotive repair shop may operate as a service shop, but specialized work on custom or high-performance vehicles might elevate some tasks to a professional service level. Additionally, the traditional volume-variety matrix does not always capture the complexity and nuances of modern processes, particularly in sectors where digital transformation or IT infrastructure aQects labor intensity and customization. From analyzing these process types, we see a historical trend toward increasing output volume, often to gain price advantages and improve delivery speed. This drive for higher output has sometimes led to issues of overproduction (what is often called the “overproduction crisis”). As the focus shifted towards eQiciency, the concept of ﬂow through the process became a central concern. In this context, understanding ﬂow measurements is crucial for operations managers aiming to optimize throughput and eQiciency. Key ﬂow-related metrics include: Work Content: This is the total time required to produce a single unit of output. It reﬂects all individual transformation steps and associated time costs that contribute to the ﬁnal product or service. Throughput Time (Lead Time): Throughput time refers to the total time an output unit spends within the transformation process from start to ﬁnish. This measure is distinct from work content, as an output unit may undergo multiple transformations in parallel or sequentially, which can sometimes result in a shorter throughput time than the cumulative work content. Cycle Time: Deﬁned as the average time interval between successive output units, cycle time provides insight into the pace of production and is useful for identifying potential bottlenecks or delays in the process. Work-in-Process (WIP): Also referred to as TIP (things-in-process), this metric represents the total number of output units currently within the transformation process. These units have entered the process but are not yet complete. In services, WIP could include pending customer requests, reports, calls, or items waiting for approval. Little’s Law simpliﬁes this relationship by expressing it as: Maximilian Nicolae - Service Operations Management from System Engineering Perspective Throughput time = Work-in-process x Cycle time This law aids managers in linking throughput time with cycle time and WIP, enabling more precise management of resources. Throughput Rate (Average Completion Rate): The throughput rate, which is the inverse of cycle time, indicates how many units are completed per unit of time. It provides a measure of the speed at which output is generated by the process. Throughput EAiciency: This metric represents the ratio between work content and throughput time, often expressed as a percentage. High throughput eQiciency indicates that the process is eQectively converting input time into productive output without excessive delay. Value-Added Throughput EAiciency (Process Cycle EAiciency, PCE): In many cases, not all of the work content time adds direct value to the output. By identifying and reducing or eliminating non-value-adding steps (e.g., wait times, redundant checks), the process cycle eQiciency can be improved. This eQiciency measure compares the time spent on value-adding activities with the total throughput time, oQering insight into potential areas for streamlining. These metrics, though idealized, form the foundation for modeling and simulation in process optimization, as depicted in Figure 1.1 from Chapter 1. Managers use these models to simulate real-life scenarios and predict potential outcomes, facilitating better decision-making and resource allocation. In practical applications, however, processes are rarely ideal. Fluctuations and variability are common due to factors such as equipment malfunctions, input shortages, or ﬂuctuating demand. These challenges introduce a trade-oQ between fast throughput and eQicient resource utilization. For instance, a service ﬁrm may face the dilemma of whether to invest in additional resources to minimize client wait times or to prioritize resource eQiciency, accepting that some clients may experience delays. Statistical methods and simulation tools are often necessary to account for these variances and to model diQerent scenarios eQectively. More detailed applications of these principles, including examples of real-life scenarios, can be explored in the application companion book [nic15]. A well-designed layout is also essential for optimizing ﬂow, as it facilitates smooth transitions between stages in the process and minimizes unnecessary movement or delays. This is brieﬂy explored in the following section. Designing the Operation Process. Layout and Flow 4.4 Layout of the Process The layout of a transformation process is fundamental to its operation, involving the design of physical positions for both transforming and transformed resources. This spatial organization, alongside task allocation at each transforming resource, is collectively known as layout [sla07]. In services, layout plays an even more immediate role, as it often directly inﬂuences the customer experience. For instance, in web-based services, the arrangement of pages and navigation ﬂow serve as the layout, and any changes to this familiar setup can disrupt customer engagement. Similarly, in physical settings such as banks, layouts directly impact customer ﬂow, leading to outcomes like long queues, unpredictable service ﬂows, and extended wait times, which can aQect satisfaction and operational eQiciency. Layouts are generally classiﬁed into four basic types, each closely associated with diQerent process types. These classiﬁcations are foundational, though hybrid layouts are often developed by combining these types based on the operational requirements: Fixed Position Layout - the output (e.g., a customer or a product) remains stationary while resources and staQ move to perform tasks around it. This layout is common in sectors where the output is too large or complex to move, such as in construction or specialized medical treatments. It’s well-suited for professional services, where clients generally stay in one place for the service duration, and is also seen in service shops and factories, depending on their positioning in the volume-variety spectrum. Functional (Process) Layout - this layout groups tasks based on function, serving varied customer needs through specialized task clusters. Unlike a ﬁxed-position layout, there isn’t a single, common ﬂow. Instead, customers move through diQerent paths depending on their service requirements, as seen in hospitals, auto repair shops, and hypermarkets. Functional layouts enhance throughput time and serve higher volumes but present challenges in managing complex ﬂows and resource u

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