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The Internet of Things (IoT) real-time data collection can help to more efficiently optimize and control companies' internal processes. Prior research analyzed IoT benefits and potential applications. Nevertheless, there is little empirical evidence and theoretical understanding of how IoT impacts new product development (NPD). This article aims at narrowing this gap.

In total, 54 case studies were selected from an IoT database – IoT ONE. IoT ONE has a section on NPD. NPD was divided into three phases: discovery, development and commercialization. The adopted IoT technology maturity level was also analyzed. A content analysis was carried out to identify the impacts of IoT in NPD.

This study’s findings capture the emerging patterns of IoT adoption and its impact on NPD. Of the total, 33 IoT adoption cases in the sample were in the machinery and equipment sector. Adopted technologies were at least two years old in 85% of the sample. Only 15% adopted cutting edge technologies (less than 2 years old). Key actors (e.g. vendors) facilitate IoT adoption. By a small margin, the larger impacts of IoT were in the commercialization phase, where it was primarily applied to improve and optimize production processes, to better execute and synchronize new products launching, and to increase the factories' productive capacity. In the discovery phase, IoT was mainly used to identify new opportunities in the market and to collect customer data, to generate a better customer experience. In the development phase, IoT allows greater integration across departments, increasing internal collaboration and allowing more flexible NPD.

Many articles studied the impact of information technologies in NPD. Few address the impact of IoT in NPD. IT tells about the impact of better communications with relevant people. IoT tells about machine acquired information and knowledge. This is new, much broader and deals with quite different impacts on NPD.

Public sector data analytics concerns the process of retrieving data, data analysis, publication of the results as well as re-using the data by government organizations to improve their operations and enhance public policy. This paper aims to explore the use of public sector data analytics in the Netherlands and the opportunities and challenges of this use.

This paper finds 74 applications of public sector data analytics, identified by a Web search and consultation with policymakers. The applications are categorized by application type, organization(s) involved and application domain, and illustrative examples are used to elaborate opportunities and challenges.

Public sector data analytics is most frequently used for inspection and enforcement of social services and for criminal investigation. Even though its usage is often experimental, it raises concerns for scope creep, repeated targeting of the same (group of) individuals, personal data use by third parties and the transparency of governmental processes.

Drawing on desk research, it was not always possible to identify which type of data or which technology was used in the applications that were found. Furthermore, the case studies are illustrative rather than providing an in-depth overview of opportunities and challenges of the use of data analytics in government.

Most studies either perform a literature overview or present a single case study; this paper presents a more comprehensive overview of how a public sector uses data analytics.