Helping Personal Service Firms to Cope with Digital Transformation: Evaluation of a Digitalization Maturity Model

Background: Maturity models are strategic and systematic instruments that help firms in the process of digital transformation. They are widely used as tools to display trajectories to guide the progression from an analog to a digital stage. To date, maturity models for industries such as manufacturing, software development, public services, telecommunication, and startup companies have been developed, and also being applicable in real-life practice. However, for the sector of personal services (e.g., education, retail, hospitality, healthcare, arts and entertainment, and craftmanship), maturity models are missing. To address this gap, this research aims to present a digitalization maturity model for the specific needs of personal service firms, and evaluate its applicability, usefulness, and impact in practice. Method: The research is embedded in a comprehensive Design Science Research cycle. Based on descriptive and prescriptive knowledge, a maturity model has been developed. This paper evaluates the applicability, usefulness, and impact of the maturity model by conducting a mixed-method approach, including a survey with 30 experts from personal service firms and eight semi-structured in-depth expert interviews. Results: Our results indicate that the maturity model serves as a strategic and systematic tool for short-, mid-, or long-term digital transformation projects by guiding personal service firms through consecutive development maturity stages until reaching a so-called stage of “digital maturity”. The model has been determined to be applicable, useful, and to potentially impact personal service firms towards the development of a digital business ecosystem. Conclusion: The presented maturity model offers guidance for personal service firms to achieve the transition from analog to digital and serves as a basis for future research in developing effective instruments and strategic tools to cope with challenges from digital transformation

Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review

The digital transformation of manufacturing (a phenomenon also known as "Industry 4.0" or "Smart Manufacturing") is finding a growing interest both at practitioner and academic levels, but is still in its infancy and needs deeper investigation. Even though current and potential advantages of digital manufacturing are remarkable, in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies has already developed ad hoc strategies necessary to achieve a superior performance. Through a systematic review, this study aims at assessing the current state of the art of the academic literature regarding the paradigm shift occurring in the manufacturing settings, in order to provide definitions as well as point out recurring patterns and gaps to be addressed by future research. For the literature search, the most representative keywords, strict criteria, and classification schemes based on authoritative reference studies were used. The final sample of 156 primary publications was analyzed through a systematic coding process to identify theoretical and methodological approaches, together with other significant elements. This analysis allowed a mapping of the literature based on clusters of critical themes to synthesize the developments of different research streams and provide the most representative picture of its current state. Research areas, insights, and gaps resulting from this analysis contributed to create a schematic research agenda, which clearly indicates the space for future evolutions of the state of knowledge in this field

Toward the Development of a Maturity Model for Digitalization within the Manufacturing Industry’s Supply Chain

The aim of this paper is the scientific development of a maturity model concerning the digital transformation of companies within the manufacturing industry’s supply chain. The rather “broad” and dispersed “mega-trend” of digitalization is expected to play an increasingly important role for companies as well as for the (digital) supply chain of the future. Such a model comprises the objective of addressing fundamental components, complementary innovations and relevant terminologies, like smart products, Cyber-Physical Systems (CPS) and Big Data Analytics. Scientific rigor is achieved through conducting grounded theory research and in-depth interviews as methods of data collection and evaluation. Furthermore, relevant aspects concerning the development and construction of maturity models are discussed, before a suitable and scientifically elaborated maturity model concerning digitalization emerges from the course of investigation and its value for economic practice as well as for the scientific community is specified

Rakennusprosessin Digitalisointi ja Teollistaminen - Tapaustutkimu

This thesis presents an overall description of industrialization and digitalization in construction industry and pipe repair sector and a framework to assess organization's industrial maturity. Industrialization in construction industry strives to make production effective by repeating work processes in factories, design offices and at building sites by the coordination of different activities. In the core of industrialization is the relocation of activities from on-site to specialized off-site factories (e.g. pre-assembly) and to remote digital units (e.g. designing). The two theoretical contributions of this study are i) the new framework for industrial maturity measurement in construction industry and pipe repair sector and ii) the detailed description of case company's current industrial maturity. The industrial maturity framework defines organization's current industrial maturity in six different process categories related to production. These contributions also have managerial relevance as they can be utilized to evaluate and plan a transformative process towards higher industrialization with digitalization as an enabler. The empirical evidence of this study proposes that the existing literature on industrialization might focus too strongly on industrialization as a concept and has not considered the potential of a framework to assess the level of industrialization. By having a framework to assess the current status, organizations can approach industrialization in a more strategic manner, focusing to enhance the weakest areas in the organization.Tämä tutkimus esittelee yleisen kuvauksen teollistumisesta ja digitalisoinnista rakennusalalla ja putkiremonttisektorilla, sekä viitekehyksen organisaation teollisen maturiteetin mittaamiseen. Teollistuminen rakennusalalla pyrkii tekemään tuotannosta tehokkaampaa luomalla toistettavia työsuoritteita tuotantolaitoksissa, suunnittelutoimistoissa ja rakennustyömaalla aktiviteetteja koordinoimalla. Teollistumisen ytimessä on työmaan aktiviteettien uudelleensijoittaminen erikoistuneisiin tuotantolaitoksiin (esivalmistus) ja digitaalisiin yksikköihin (suunnittelu). Tämän tutkmuksen kaksi pääasiallista teoreettista kontribuutiota ovat i) uusi viitekehys teollisen maturiteetin mittaamiseen rakennusalalla ja putkiremonttisektorilla, sekä ii) yksityiskohtainen kuvaus tapaustutkimuksen yrityksen nykyisestä teollisen maturiteetin tasosta. Teollisen maturiteetin viitekehys määrittelee organisaation teollisen maturiteetin nykytilan kuudella eri tuotannon osaalueella. Näillä kontribuutioilla on myös johtoryhmän relevanssia, sillä niiden hyödyntäminen mahdollistaa digitalisaation avulla korkeampaan teollistumiseen tähtäävän muutosprosessin arvioimisen ja suunnittelemisen. Tutkimuksen empiirinen näyttö osoittaa, että nykyinen teollistumista koskeva kirjallisuus on saattanut painottaa liiaksi teollistumista yleisen tason konseptina ja ei ole huomioinut teollisen maturiteetin mittaamiseen käytettävän viitekehyksen arvoa organisaation teollistumisen mittaamiseen. Tutkimuksessa rakennetun viitekehyksen avulla organisaatiot rakennusalalla pystyvät lähestymään teollistumista strategisemmin ja osoittamaan kehityskohteita saavuttaakseen korkeamman teollistumisen taso

Framework for Quantitative Digitalization Measurement in Supply Chain Planning

Measurement is a central element for any effective management. The megatrend of digitalization enables new possibilities, but also requires research on its appropriate monitoring considering digital transformation. In supply chain planning, todays methods are mostly qualitative. Thus, this study analyzes how the impact of digitalization can be quantified scoped to this field of application.Based on the literature streams supply chain planning performance measurement, digitalization assessment and digital technologies the authors develop a holistic framework for quantitative digitalization measurement (QDMF). The framework comprises three dimensions: ‘Man’, ‘Technology’, and ‘Organization’. These itemize to 22 measurands specific to the context. The logic allows the comprehensive assessment of the effectiveness of digitalization projects and provides reliable, informative value for decision-making by the quantitative scaling. The framework is applied by conducting expert interviews for customization and data collection, whereon analytics calculates the measurands. In the end, experts interpret the results.For verification and validation, the framework is deployed to the empirical use case of Infineon Technologies AG, Europe’s largest semiconductor manufacturer. The study concludes that quantitative digitalization monitoring is promising and can deliver new insights for effective managerial decision-making. Obstacles as limited data availability and constrained explanatory power are investigated and provide options for further studies.Measurement is a central element for any effective management. The megatrend of digitalization enables new possibilities, but also requires research on its appropriate monitoring considering digital transformation. In supply chain planning, todays methods are mostly qualitative. Thus, this study analyzes how the impact of digitalization can be quantified scoped to this field of application.Based on the literature streams supply chain planning performance measurement, digitalization assessment and digital technologies the authors develop a holistic framework for quantitative digitalization measurement (QDMF). The framework comprises three dimensions: ‘Man’, ‘Technology’, and ‘Organization’. These itemize to 22 measurands specific to the context. The logic allows the comprehensive assessment of the effectiveness of digitalization projects and provides reliable, informative value for decision-making by the quantitative scaling. The framework is applied by conducting expert interviews for customization and data collection, whereon analytics calculates the measurands. In the end, experts interpret the results.For verification and validation, the framework is deployed to the empirical use case of Infineon Technologies AG, Europe’s largest semiconductor manufacturer. The study concludes that quantitative digitalization monitoring is promising and can deliver new insights for effective managerial decision-making. Obstacles as limited data availability and constrained explanatory power are investigated and provide options for further studies

A multi-dimensional model to the digital maturity life-cycle for SMEs

As companies try to maintain and strengthen their competitive advantage, they should be aware of the level of their digital maturity. The study aims to present a methodology that helps to determine the position of a small and medium-sized enterprise in the digital maturity life-cycle. This is performed on the basis of maturity and digital maturity models, and company growth theories. A number of studies and models have been prepared to determine digital maturity on the basis of various sectoral criteria, but these are all one-dimensional. The study therefore proposes a multi-dimensional model for determining the digital maturity life-cycle of small and medium-sized enterprises that takes into account companies’ digital maturity, the IT intensity of various sectors and their organizational characteristics. The model defines five maturity levels together with their relevant characteristics, classified into three levels in terms of data- information. It can help small and medium-sized enterprises adopt more accurate decisions regarding areas in need of development