Datenbasierte Produktionsoptimierung*/Data-driven production optimization: Areas of development for manufacturing companies

2018 ◽  
Vol 108 (03) ◽  
pp. 108-112
Author(s):  
D. Bauer ◽  
T. Maurer ◽  
T. Bauernhansl
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Applied Research ◽  
Business Models ◽  
Big Data Analytics ◽  
Production Optimization ◽  
Data Driven ◽  
Manufacturing Companies ◽  
New Business ◽  
New Business Models

Unternehmen sehen in Big-Data-Analysen ein großes Potenzial zur Optimierung der klassischen Produktionsziele sowie zur Entwicklung neuer Geschäftsmodelle. Eine Studie des Fraunhofer IPA analysiert, welche Herausforderungen bei der Umsetzung dieser Potenziale auftreten. Darauf aufbauend werden Entwicklungsfelder für die angewandte Forschung und produzierende Unternehmen erarbeitet.   Companies expect huge benefits from big data analytics both to improve traditional production targets and to develop new business models. A study conducted by Fraunhofer IPA analyzes the upcoming challenges in exploiting these opportunities. It provides the basis for identifying areas of development for applied research and for manufacturing companies.

Understanding Data Analytics Is Good but Knowing How to Use It Is Better!

2019 ◽  
pp. 125-160
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Business Models ◽  
Big Data Analytics ◽  
Success Factor ◽  
New Business ◽  
Technical Architecture ◽  
The Veil ◽  
Key Success Factor ◽  
New Business Models

Collecting the data and being able to generate value from it: this is certainly the key success factor of tomorrow's champions, one that will allow you to innovate and create new business models. Faced with the 3Vs of big data, many companies are embarking on big data projects with the main objective: generating value. The goal is to succeed, by the detailed analysis of large amounts of data, to lift the veil and discover hitherto hidden models and barely perceptible correlations, as many new business opportunities that companies must grasp. The key to the success of any big data analytics initiative is to define your goals, identify specific business questions that a suitable technical architecture will need to answer, and use the data experts to generate value from data by using specific algorithms.

Big Data and Data Analytics Research

Web Services ◽  
2019 ◽  
pp. 2161-2171
Author(s):  
Miltiadis D. Lytras ◽  
Vijay Raghavan ◽  
Ernesto Damiani
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Business Models ◽  
Internet Technology ◽  
Cognitive Computing ◽  
New Paradigm ◽  
Web Science ◽  
New Business ◽  
Value Propositions

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.

scholarly journals Digital transformation: harnessing digital technologies for the next generation of services

2019 ◽  
Vol 33 (4) ◽  
pp. 429-435 ◽  
Author(s):  
Mohamed Zaki
Keyword(s):  
Business Models ◽  
Digital Technologies ◽  
Customer Experience ◽  
Digital Transformation ◽  
Data Driven ◽  
Next Generation ◽  
Content Type ◽  
New Business ◽  
Market Opportunities ◽  
New Business Models

Purpose The purpose of this paper is to discuss digital transformation and its four trajectories – digital technology, digital strategy, customer experience and data-driven business models – that could shape the next generation of services. This includes a discussion on whether both the market and organizations are all ready for the digital change and what are the opportunities that will enable firms to create and capture value though new business models. Design/methodology/approach Providing services is a proven and effective way to secure a competitive position, deliver long-term stable revenues and open up new market opportunities. However, it is also clear that some organisations are struggling to digitally transform. Therefore, the commentary provides a brief insight into how firms explore the possibilities of digital transformation and navigate these uncharted waters. Findings Today’s digital technologies affect the organisation outside and in, enabling the creation of new business models and transforming the customer experience. The incumbents are acutely aware that they need to transform strategically – to build new networks and value chains. Originality/value This commentary extends earlier work exploring the digital disruption within services to highlight a number of connected areas: the challenges and opportunities of digital transformation at a strategic level, as well as understanding and enhancing the customer experience and seeing how new data-driven business models can underpin service transformation.

scholarly journals Integrating Product-Service Systems with New Business Models Definition for Manufacturing Industries

2014 ◽  
Vol 5 (3) ◽  
pp. 16-33 ◽  
Author(s):  
Pedro C. Marques ◽  
Pedro F. Cunha
Keyword(s):  
Business Models ◽  
Service Systems ◽  
Service Development ◽  
Clear Understanding ◽  
Manufacturing Companies ◽  
Specific Product ◽  
Product Service ◽  
New Business ◽  
Product Service Systems ◽  
New Business Models

Nowadays, manufacturing companies are pressured to be competitive and innovative. Particularly this concerns the delivery of value to their customers. The assessment of the overall value chain, designed and implemented for a specific product and/or service, should be sustained by new business models (NBM), thus contributing to higher levels of customer satisfaction. Integrated product-services are assuming importance, allowing manufacturing companies to achieve longer and stable relationships with their customers. This requires, among other, organizational changes and novel methodologies for product-service development. In fact, an effective integration allows product-service innovation, which being exploited, contributes significantly to businesses' competitiveness and sustainability. In this paper, a “roadmap” for NBM definition and implementation is presented, along with a new methodology for Product-Service Systems (PSS) development. Two case studies are used to test both the roadmap and the PSS methodology. As such, this work is expected to contribute to a clear understanding of NBM and their integration in a methodology for PSS.

Cognitive computing, Big Data Analytics and data driven industrial marketing

2020 ◽  
Vol 90 ◽  
pp. 663-666
Author(s):  
Miltiadis Lytras ◽  
Anna Visvizi ◽  
Xi Zhang ◽  
Naif Radi Aljohani
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Driven ◽  
Cognitive Computing ◽  
Industrial Marketing
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