Selling Data-Based Value in Business-to-Business Markets

Rantala, Tuija; Apilo, Tiina; Palomäki, Katariina; Valkokari, Katri

doi:10.22215/timreview/1313

Cited by 6 publications

(5 citation statements)

References 13 publications

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“…The former also means that new value propositions, such as smart services, start out with a credence goods character (Grubic and Peppard, 2016; Klein et al , 2018; Rantala et al , 2020). Hence, to ensure value uptake and delivery, Grubic and Peppard (2016) point at the need for skilled communicators among the staff to market these services as their benefits are often not clear to users.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In addition, Paiola and Gebauer (2020) argue that when services are digital or smart, there tends to be a need to incorporate personnel with data analytical skills. Accordingly, Raddats et al (2019) and Rantala et al (2020) state that selling smart services may require a different and/or diverse set of professionals on the vendor’s side.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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How can machine tool builders capture value from smart services? Avoiding the service and digitalization paradox

Kamp

Zabala

Goena

2022

JBIM

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Purpose This paper aims to assess the existence of, or the risk of running into, a smart service paradox for industrial firms and how to overcome it. Design/methodology/approach A qualitative multiple case study is conducted involving four machine tool builders. The main source of data is formed by semi-structured interviews with service business managers. NVivo software was used to structure the interview harvest. Findings The findings reveal that a smart service paradox is a realistic threat for industrial firms, that smart service business development is a supply push affair rather than a matter of demand pull, that two types of permissions need to be granted by prospective users (license to operate and license to charge) and that three intermediate steps need to be undertaken and validated to overcome a smart service paradox: value testing or proofing; value recognition; and value sharing. Research limitations/implications This study was vendor-centric and did not involve the industrial customers to whom the smart services were directed. It was based on a small sample, which limits the generalizability of findings to a broader or different (sectoral) context. Practical implications Lessons are identified for service managers on how to circumvent a smart service paradox. Originality/value This study departs from a value creation-delivery-capture (“business model”) perspective to assess smart service paradox dynamics. By adopting a relational perspective to it, the present paper succeeds in presenting a more granular version of the base business model.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

How can machine tool builders capture value from smart services? Avoiding the service and digitalization paradox

Kamp

Zabala

Goena

2022

JBIM

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“…There appear to be some specific reasons for firms’ lack of engagement with Big Data. Projects based on Big Data are seen as complex and challenging (Rantala et al , 2020). There is also a lack of direction as to how to link Big Data to firm strategy (Ram and Zhang, 2021; Khan et al , 2022) and a lack of suitable talent to exploit data (Qaffas et al , 2022).…”

Section: Importance Of Understanding the Strategic Benefits Of Big Datamentioning

confidence: 99%

The outcomes of B2B data-driven customer focused value creation

Holmes

Zolkiewski

Burton

2023

JBIM

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Purpose Despite data being a hot topic, little is known about how data can be successfully used in interactions in business-to-business relationships, specifically in the boundary spanning contexts of firms working together to use data and create value. Hence, this study aims to investigate the boundary spanning context of data-driven customer value projects to understand the outcomes of such activities, including the types of value created, how resulting value is shared between the interacting firms, the types of capabilities required for firms to deliver value from data and in what contexts different outcomes are created and different capabilities required. Design/methodology/approach Three abductive case studies were undertaken with firms from different business-to-business domains. Data were coded in NVivo and interpreted using template analysis and cross-case comparison. Findings were sense checked with the case study companies and other practitioners for accuracy, relevance and resonance. Findings The findings expand our understanding of firm interactions when extracting value from data, and this study presents 15 outcomes of value created by the firms in the study. This study illustrates the complexity and intertwined nature of the process of value creation, which emphasises the need to understand distinct types of outcomes of value creation and how they benefit the firms involved. This study goes beyond this by categorising these outcomes as unilateral (one actor benefits), developmental (one actor benefits from the other) or bilateral (both actors benefit). Research limitations/implications This research is exploratory in nature. This study provides a basis for further exploration of how firm interactions surrounding the implementation of data-driven customer value projects can benefit the firms involved and offers some transferable knowledge which is of particular relevance to practitioners. Practical implications This research contributes to the understanding of data-driven customer-focused projects and offers some practical management tools. The identification of outcomes helps define project goals and helps connect these goals to strategy. The organisation of outcomes into themes and contexts helps managers allocate appropriate human resources to oversee projects, mitigating the impacts of a current lack of talent in this area. Additionally, using the findings of this research, firms can develop specific capabilities to exploit the project outcomes and the opportunities such projects provide. The findings can also be used to enhance relationships between firms and their customers, providing customer value. Originality/value This work builds on research that explores the creation of value from data and how value is created in boundary spanning contexts. This study expands existing work by providing greater insight into the mechanics and outcomes of value creation and by providing specific examples of value created. This study also offers some recommendations of capability requirements for firms undertaking such work.

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“…[28], [68], [69], [70] y [71]. El diagrama estratégico tiene como objetivo estudiar las diversas posiciones relativas dentro de la red de los actores, así como también sus traslaciones de tendencias a lo largo del tiempo del tema estudiado.…”

Section: Deep Learning (Machine Learning)unclassified

Tendencias del uso de la Inteligencia Artificial en Empresas Globales en el periodo 2018-2023. Una revisión sistemática de la literatura científica

Calvanapón Alva,

Llaque Fernández,

Mendoza-Castillo

et al. 2023

Proceedings of the 3rd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development (LEIRD 202

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In recent years there has been an accelerated interest in artificial intelligence on the part of global companies due to the high benefits it provides, therefore, the objective of the research is to carry out a systematic review of the literature to collect the information most relevant and available on the trends in the use of artificial intelligence, to observe in detail the evolution and application of this new technology in internal and external processes, transparently using relevant quality sources (articles by large and renowned researchers of the economic area, whose research is indexed in Scopus and ScienceDirect) for the period 2018-2023. The definition of artificial intelligence covers the empowerment of new software with cognitive capabilities. The review lands on 4 main trends where this new technology points; 1) Artificial neural networks. 2) Digital twins. 3) Industry 4.0. 4) Deep Learning. Among them, various approaches and appreciations of researchers can be seen, where they focus mainly on trust, security and attention. In the search, the main limitation found is that artificial intelligence applied to business and economy is still beginning to gain focus, so it is expected that the advancement of technology will foster global competition, within the managerial and financial framework. .

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Selling Data-Based Value in Business-to-Business Markets

Cited by 6 publications

References 13 publications

How can machine tool builders capture value from smart services? Avoiding the service and digitalization paradox

How can machine tool builders capture value from smart services? Avoiding the service and digitalization paradox

The outcomes of B2B data-driven customer focused value creation

Tendencias del uso de la Inteligencia Artificial en Empresas Globales en el periodo 2018-2023. Una revisión sistemática de la literatura científica

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