Taking services seriously: how policy can stimulate the 'hidden innovation' in the UK’s services economy

Policy could have an important role in stimulating innovation in services. However, policymakers have lacked robust evidence showing how these sectors innovate. Drawing on a survey of more than 16,000 firms, this research reveals the high levels of ‘hidden innovation’ in some services sectors, especially in how they develop new business models and exploit technology. But the research also reveals that innovation is confined to a minority of service firms, and that many lack the skilled personnel or intelligence on markets and technology that would enable them to become more innovative. Because of their dominance in the economy, improved performance by the UK’s services sectors is necessary if we are to significantly close the productivity gap between the UK and other leading nations. However, if we are to take innovation in services seriously, we must recognise that they innovate differently from advanced manufacturing. We need policies to support increased training and development, and the effective dissemination and exploitation of technology

Experimenting with Realism in Software Engineering Team Projects: An Experience Report

Over Several years, we observed that our students were sceptical of Software Engineering practices, because we did not convey the experience and demands of production quality software development. Assessment focused on features delivered, rather than imposing responsibility for longer term `technical debt'. Academics acting as 'uncertain' customers were rejected as malevolent and implausible. Student teams composed of novices lacked the benefits of leadership provided by more experienced engineers. To address these shortcomings, real customers were introduced, exposing students to real requirements uncertainty. Flipped classroom teaching was adopted, giving teams one day each week to work on their project in a redesigned laboratory. Software process and quality were emphasised in the course assessment, imposing technical debt. Finally, we introduced a leadership course for senior students, who acted as mentors to the project team students. This paper reports on the experience of these changes, from the perspective of different stakeholders

Missing the Starting Gun? Entry Timing Decisions into New Market Niches

This study analyzes incumbent entry timing decisions in new markets in the case of Encryption Software (ES). In ES first technological movers were slow to enter the downstream market, losing their initial advantages to the benefit of newcomers. This work tests the hypothesis that this wait-and-see strategy was an optimal choice compared to the assumption of inertia embedded in the decision process of potential entrants. We find that entry decision is not the outcome of firm rational balancing among different strategic variables, but it is more similar to a heuristic process that fails to accommodate the full logic of decision.Entry, Entrepreneurship, Innovation, Software.

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

AHAA- Agile, Hybrid Assessment Method for Automotive, Safety Critical SMEs

The need for software is increasingly growing in the automotive industry. Software development projects are, however, often troubled by time and budget overruns, resulting in systems that do not fulfill customer requirements. Both research and industry lack strategies to combine reducing the long software development lifecycles (as required by time-to-market demands) with increasing the quality of the software developed. Software process improvement (SPI) provides the first step in the move towards software quality, and assessments are a vital part of this process. Unfortunately, software process assessments are often expensive and time consuming. Additionally, they often provide companies with a long list of issues without providing realistic suggestions. The goal of this paper is to describe a new low-overhead assessment method that has been designed specifically for small-to-medium-sized (SMEs) organisations wishing to be automotive software suppliers. This assessment method integrates the structured-ness of the plan-driven SPI models of Capability Maturity Model Integration (CMMI) and Automotive SPICETM with the flexibleness of agile practices

Short interval control for the cost estimate baseline of novel high value manufacturing products – a complexity based approach

Novel high value manufacturing products by default lack the minimum a priori data needed for forecasting cost variance over of time using regression based techniques. Forecasts which attempt to achieve this therefore suffer from significant variance which in turn places significant strain on budgetary assumptions and financial planning. The authors argue that for novel high value manufacturing products short interval control through continuous revision is necessary until the context of the baseline estimate stabilises sufficiently for extending the time intervals for revision. Case study data from the United States Department of Defence Scheduled Annual Summary Reports (1986-2013) is used to exemplify the approach. In this respect it must be remembered that the context of a baseline cost estimate is subject to a large number of assumptions regarding future plausible scenarios, the probability of such scenarios, and various requirements related to such. These assumptions change over time and the degree of their change is indicated by the extent that cost variance follows a forecast propagation curve that has been defined in advance. The presented approach determines the stability of this context by calculating the effort required to identify a propagation pattern for cost variance using the principles of Kolmogorov complexity. Only when that effort remains stable over a sufficient period of time can the revision periods for the cost estimate baseline be changed from continuous to discrete time intervals. The practical implication of the presented approach for novel high value manufacturing products is that attention is shifted from the bottom up or parametric estimation activity to the continuous management of the context for that cost estimate itself. This in turn enables a faster and more sustainable stabilisation of the estimating context which then creates the conditions for reducing cost estimate uncertainty in an actionable and timely manner