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The additive manufacturing technique of "Selective Laser Melting" (SLM) provides the basis for a fundamental paradigm shift in industrial spare part manufacturing, affecting both technological and organizational company prac-tices. To harness the full potential of SLM-technology, considering agility and customizability, decentralized additive production networks need to be estab-lished. According to the principles just in time, just in place and just enough, a global online platform, which efficiently distributes construction orders to local manufacturing hubs could empower the market participants to utilize production capacities at optimal costs and minimal efforts. This work evaluates and selects key factors and creates scenarios for the development of platform-based networks for additive, SLM-based, spare part production. For this purpose, the selected key factors (e. g. material expenses, quality and process management and platform-based business models) are projected into the future, forming the three major scenarios "New distribution of roles in the SLM value chain", "SLM-technology for high wage countries" and "Individualization instead of mass production". These scenarios not only allow estimating the potential of an online network for additive spare part production, but also enable market participants to react pur-posively and agilely to unexpected market developments, and to foster the suc-cess of a platform-based additive spare part production.
Pricing is one of the most important, but underestimated tools, to enhance a company's profitability. Especially value-based pricing has a high potential to reach higher levels of satisfaction because it equates the needs of providers and customers. Even though, it is a well-known price model and promises higher satisfaction, many companies struggle to implement it. Especially the manufacturing industry is characterized by cost-plus pricing and competition-based pricing. However, especially for digital products these pricing strategies are insufficient. Therefore, this paper aims at exploring the design fields for value-based pricing of digital products in the manufacturing industry. To achieve this, the basics of digital products and value-based pricing are explored. Furthermore, an expert workshop is conducted that follows a framework for value-based pricing consisting of four consecutive steps analysis, price strategy, pricing, and market launch to capture the design fields. This paper concludes with limitations, and practical and research implications.
The mechanical and plant engineering industry faces a stagnation in the new machinery market and is relying on innovative business models such as subscription to overcome these. In this business model, individually customized solution packages are offered. The success of these models depends directly on the future success of the customer, making the selection of the right customers crucial. The aim of this paper is to identify the criteria that indicate the suitability of customers for subscription models. While there are individual descriptions of suitability criteria in the existing literature, there is a lack of comprehensive consideration of customer relationship, customer company, and customer market, as the extensive consideration was not necessary in the transactional sale of machines until now. Therefore, in this study, expert interviews are conducted with companies in mechanical and plant engineering that offer subscription models. The results show criteria that are used to evaluate customers in the six main categories of creditworthiness, market potential, benefit potential, feasibility, relationship, and sales effort. In total, 24 criteria can provide insight into the suitability of the customer for a successful subscription relationship. These criteria are intended to develop target systems that meet the requirements of different stakeholders in the customer and thus support the economic viability of these business models.
More and more companies in the mechanical and plant engineering industry are transforming their business model and evolving from product to solution providers. Subscription business models play a key role in this development. They enable companies to enter long-term collaborative relationships with customers and thus monetize the potential of Industry 4.0. However, this development is not easy for many companies and is associated with numerous hurdles. One of these hurdles is the development of a suitable range of services tailored to customer needs. In this context, the bundling of individual services to service modules plays a key role in realizing new value propositions. In practice, however, companies often lack an understanding of which services need to be combined in what way to be able to realize new value propositions. Accordingly, the goal of this work is to identify relevant services for subscription business models, to cluster them into meaningful value-adding bundles, and to derive new value propositions accordingly. The new value propositions in turn enable mechanical and plant engineering companies to strengthen customer loyalty and thus achieve long-term economic success.
In Germany’s transition to a more sustainable industrial landscape, electricity generated by wind turbines (WT) remains a mainstay of the energy mix. Operating and maintenance costs, which account for roughly 25% of electricity generation costs in onshore WTs make improvements of maintenance activities a key lever in the economic operation of WTs. Prescriptive maintenance is a possible approach for improved maintenance activities. It is a concept where asset condition data is used to recommend specific actions and has great potential for the operation of wind parks. However, especially small, but also large wind park operators, and maintenance service providers often struggle with the implementation of such a new maintenance approach. As a part of the research project ReStroK, a learning game has been developed to support the training and familiarization of maintenance technicians with the concepts and underlying principles of this maintenance approach. In this paper, the concept for the development of a learning game will be presented. Multiple scenarios for its usage and their corresponding requirements will be discussed and an overview over the game will be given.
Towards a Methodology to Determine Intersubjective Data Values in Industrial Business Activities
(2021)
This paper contributes to a valuation framework for valuing data as an intangible asset. Especially those industrial manufacturers developing and delivering holistic digital solutions are limited in calculating the true business value of data initiatives. Since the value of data is strongly dependent on the respective use case, a completely objective valuation is not possible. This complicates decision-making on the internal side regarding investments in digital transformation, and on the external side to communicate existing benefits to third parties via financial reporting. Therefore, the target is to design a valuation framework that allows industrial manufacturers to determine an intersubjective, i.e., traceable and transparent, data value. In order to develop a framework that can be applied in practice, the approach is based on industrial case study research.
The industrial food production is currently caught between the increas-ing demands of numerous stakeholders, economic profitability and the challenges of digitization. A solution to face these various challenges can be seen in the aggregation of data into higher-value, independent data products that can be of-fered and sold on a buyer's market. Large amounts of heterogeneous data are already available in the value chain of the industrial food production, e.g. throughout the data-driven harvesting of primary products, further processing by interconnected production facilities and the information-intensive product distri-bution to end consumers. However, the data is usually only evaluated and used locally for the optimization of internal processes or, at the most, within compre-hensive partnerships. The purpose of this paper is to identify new revenue oppor-tunities for current and future players in the industrial food production by using data as an independent economic good (data products). For this purpose, scenar-ios for the development and use of data products via Industrial Internet of Things platforms are developed for a food technical reference process, the industrial chocolate production and its value chain. On this basis, examples for different types of data products and their value propositions are derived. The results can not only serve food producers and relevant stakeholders but all industrial produc-ers as an input for the future, yield-increasing orientation of their business models.
More and more manufacturing companies are starting to transform the transaction-based business model into a customer value-based subscription business to monetize the potential of digitization in times of saturated markets. However, historically evolved, linear acquisition processes, focusing the transactionoriented product sales, prevent this development substantially. Elemental features of the subscription business such as recurring payments, short-term release cycles, data-driven learning, and a focus on customer success are not considered in this approach. Since existing transactional-driven acquisition approaches are not successfully applicable to the subscription business, a systematic approach to an acquisition cycle of the subscription business in the manufacturing industry is presented, aiming at a long-term participative business. Applying a grounded theory approach, a task-oriented model for themanufacturing industry was developed.
The model consisting of five main tasks and 14 basis tasks serves as best practice to support manufacturing companies in adapting or redesigning acquisition activities for their subscription business models.
Competitive differentiation in the manufacturing sector is no longer based on product and service innovations alone but on the ability to monetize the usage phase of products and services. To this end, manufacturers are increasingly looking at so-called subscription business models as a way of supplementing the traditional sale of products and services. Since supplier success in the subscription business is directly dependent on customer success, the setup and expansion of a so-called Customer Success Management (CSM) is required. While CSM has already been established in the software industry for several years, companies in the manufacturing sector are often still in the conceptual phase of a CSM, parallel to the setup and expansion of their subscription business. Therefore, this paper aims to support the set-up of a CSM by providing a reference data model, based on case study research, that can be used to support the organizational or daily CSM tasks and to serve as a blueprint for conceptualizing CSM-specific IT systems.
Industrial companies are moving to a solution driven business by offering smart product service systems (Smart PSS). In addition to an existing portfolio of physical goods and technical services, companies develop new digital services and combine all three offerings to an integrated digital solution business. While the development of new digital services does not pose any major challenges for companies, the successful sale of Smart PSS does. Due to changing customer requirements and value propositions of a solution, the sale of Smart PSS requires new design principles for the sales organization compared to the simple sale of physical goods or technical services. While there are already many publications on the topic of industrial sales in research, the description of Smart PSS in particular represents a new field of research. The combination of both topics is therefore not only interesting from a theoretical point of view, but also has a particularly high practical relevance and impact for industrial companies. This paper therefore describes on the one hand, which characteristics can be used to derive customer requirements for Smart PSS and on the other hand, which effects these requirements have on the sales organization of the industrial company. The design principles give recommendations for the organizational structure, the resources, the information systems and the culture of the company depending on the targeted customer type. In order to identify and describe both the customer requirements and the design principles, two morphological boxes were developed based on a literature research and semi-structured interviews with industrial companies. The paper gives an outlook on the different characteristics of the design recommendations and describes first best practices for the successful transformation of the sales organization.