Technology Scouting – a case study on the Deutsche Telekom Laboratories

Technology Intelligence has become an important field of study in which a variety of different methods are discussed, all aiming at identifying opportunities and threats arising from advances in technology. In this respect, Technology Scouting is a method which can lower the time lag between the advances in technology and their detection by methods such as patent or publication analysis. Furthermore, in an environment of increasing technological complexity and the globalization of R&D, the successful identification and usage of external sources of knowledge is becoming increasingly important. In the sourcing of technology the scouts can also play an important role in identifying valuable sources and facilitate the sourcing. Based on two case studies of the Deutsche Telekom and British Telecom, as well as a literature review, the paper proposes a definition of Technology Scouting, a generic process, and identifies the motivations of the actors in the process.technology intelligence, technological forecasting, technology foresight; technology scouting; technology exploration; strategic foresight; technology monitoring; technology scanning

Making university-industry collaboration work - a case study on the Deutsche Telekom Laboratories contrasted with findings in literature

The growing competition in consumer as well as business customer markets is forcing industry to explore new ways to foster product and service innovations. To increase the clock speed of incremental innovations and raise the number of radical innovations, university-industry collaborations (UIC) are a powerful means discussed by practitioners as well as by scholars. This paper discusses the approach of the Deutsche Telekom Group (DTAG) of building a UIC by creating a separate organization. This organization consists of R&D personnel both from industry and academia and proves to be effective in channelling innovation potential. Being an organization with its own identity and situated on university premises, the Deutsche Telekom Laboratories (DT Laboratories) offer different ways to overcome the cultural, institutional and operational barriers associated with UIC. The case study validates and challenges findings on UIC in literature. The paper closes with practical advices for the establishment and management of UIC and suggestions for further research in this field.university–industry collaboration; technology transfer; technological innovation; basic research; applied research; innovation development; radical innovations; incremental innovations; technology intelligence; explorative capabilities; university-industry research center (UIRC)

Strategic Foresight in multinational enterprises – a case study on the Deutsche Telekom Laboratories

Strategic Foresight activities enable companies to use weak signals to identify opportunities and threats. Research on Strategic Foresight proposes different methods, discusses their implementation and gives recommendations on how to link Strategic Foresight with other functions in an organization. Based on a literature review, we define a generic framework for the management of Strategic Foresight activities on the strategic, tactical and operational level and identify and discuss actors, methods and systems of Strategic Foresight. Building on an in-depth case study of the Deutsche Telekom Laboratories we shed light on the implementation of Strategic Foresight activities. In the discussion we focus on the interaction of methods from Consumer Foresight and Technology Intelligence. Taking an example project, we explore how Strategic Foresight is used on the operational level of innovation management. We conclude that Strategic Foresight can successfully contribute to coping with uncertainty and complexity and can feed the front-end of innovation from the market (customer needs) and technology (realization opportunities) perspective.strategic foresight; consumer foresight; technology foresight; technology intelligence; market foresight; trend analysis; future studies; future analysis; telecommunication industry

Concurrent Biological, Electromagnetic Pulse, And Cyber Attacks - A Challenge To The Interagency Response

The U.S. including its military depends on an electrical grid and electricity-based critical infrastructure. An electromagnetic pulse (EMP) and cyber attack can disable not just a significant portion of the electrical grid and critical infrastructure, but also the networkcentric military response to such an attack. There is a large range of actors that might attempt EMP attacks against the U.S.. Health surveillance systems are network-centric, and if mass destruction is the goal of an adversary, launching a biological attack concurrently with EMP and cyber attacks may achieve this goal. Current agency response plans focus on one WMD attack at a time but combined attacks without emergency management plans may compromise a timely response. An EMP and cyber attack could amplify the effects of a biological attack because the loss of the electrical grid and electricity-based critical infrastructure could disable detection and response efforts as well as disrupt interagency efforts to coordinate a medical response. EMP is often perceived as science fiction because the immediate effect does not result in loss of life, but the cascading failures of critical infrastructure will affect civilian and military capabilities to support survival and recovery. Key steps to mitigate the catastrophic effects of an EMP attack should be taken and include: prevent an attack in the first place, prepare so personnel can respond after an attack, protect the critical infrastructure to limit the impact, and recover after an attack to restore power and critical infrastructure

Combining spin-out and spin-in activities – the spin-along approach

After a long period of restructuring and outsourcing, companies are increasingly looking for new growth opportunities. Growth with existing prod-ucts or by expansion in new markets is limited. Therefore, companies are searching for ways to expand their activities in new businesses. A frequently used tool of multinational enterprises is corporate venturing. Within cor-porate venturing a further differentiation can be made in internal venturing and external venturing. Internal venturing promotes business ideas generated within the organization whereas external venturing promotes business ideas developed outside the company. Research has been able to show that venturing activi-ties both internal and external can create value. In this paper we explore a special case of venturing which we call the ‘spin-along approach’. It can be seen as a combination of internal and external ven-turing. In the spin-along approach, a company encourages its employees to take their business idea external and to found a company. Successful companies might later be bought back and integrated into the parent company or the paren-tal will exit the company by selling its equity share. Through literature re-view we have identified different motivations, best practices, and barriers to the successful implementation of a spin-along approach. Furthermore, two case studies will be discussed and compared. We conclude that the approach can successfully complement internal innovation management.Corporate venturing; spin-along; venture leader; spin-out; spin-in; Deutsche Telekom Laboratories; Cisco Systems

Self-Managed Groups: Fitting Self-Management Approaches Into Classroom Systems

Examines the factors limiting the use of classroom self-management interventions. Self-management approaches that contribute to its inappropriateness and impracticality; Review peer tutoring as a strategy with self-management features in classroom use; Combination of student choice and student management with interdependent group reward contingencies; Reciprocal peer teaching

A joint estimation approach for monotonic regression functions in general dimensions

Regression analysis under the assumption of monotonicity is a well-studied statistical problem and has been used in a wide range of applications. However, there remains a lack of a broadly applicable methodology that permits information borrowing, for efficiency gains, when jointly estimating multiple monotonic regression functions. We introduce such a methodology by extending the isotonic regression problem presented in the article "The isotonic regression problem and its dual" (Barlow and Brunk, 1972). The presented approach can be applied to both fixed and random designs and any number of explanatory variables (regressors). Our framework penalizes pairwise differences in the values (levels) of the monotonic function estimates, with the weight of penalty being determined based on a statistical test, which results in information being shared across data sets if similarities in the regression functions exist. Function estimates are subsequently derived using an iterative optimization routine that uses existing solution algorithms for the isotonic regression problem. Simulation studies for normally and binomially distributed response data illustrate that function estimates are consistently improved if similarities between functions exist, and are not oversmoothed otherwise. We further apply our methodology to analyse two public health data sets: neonatal mortality data for Porto Alegre, Brazil, and stroke patient data for North West England

Bayesian spatial clustering of extremal behaviour for hydrological variables

To address the need for efficient inference for a range of hydrological extreme value problems, spatial pooling of information is the standard approach for marginal tail estimation. We propose the first extreme value spatial clustering methods which account for both the similarity of the marginal tails and the spatial dependence structure of the data to determine the appropriate level of pooling. Spatial dependence is incorporated in two ways: to determine the cluster selection and to account for dependence of the data over sites within a cluster when making the marginal inference. We introduce a statistical model for the pairwise extremal dependence which incorporates distance between sites, and accommodates our belief that sites within the same cluster tend to exhibit a higher degree of dependence than sites in different clusters. By combining the models for the marginal tails and the dependence structure, we obtain a composite likelihood for the joint spatial distribution. We use a Bayesian framework which learns about both the number of clusters and their spatial structure, and that enables the inference of site-specific marginal distributions of extremes to incorporate uncertainty in the clustering allocation. The approach is illustrated using simulations, the analysis of daily precipitation levels in Norway and daily river flow levels in the UK

A spatio-temporal model for Red Sea surface temperature anomalies

This paper details the approach of team Lancaster to the 2019 EVA data challenge, dealing with spatio-temporal modelling of Red Sea surface temperature anomalies. We model the marginal distributions and dependence features separately; for the former, we use a combination of Gaussian and generalised Pareto distributions, while the dependence is captured using a localised Gaussian process approach. We also propose a space-time moving estimate of the cumulative distribution function that takes into account spatial variation and temporal trend in the anomalies, to be used in those regions with limited available data. The team's predictions are compared to results obtained via an empirical benchmark. Our approach performs well in terms of the threshold-weighted continuous ranked probability score criterion, chosen by the challenge organiser