skip to primary navigationskip to content

Cambridge Service Alliance

developing new understanding and approaches to complex service systems

Studying at Cambridge

 

White Paper: Succeeding through Service Innovation

last modified Nov 24, 2015 10:39 AM
This White Paper is based on a discussion paper and a feedback process that arose from the Cambridge Service Science, Management and Engineering Symposium, held in July 2007. Overall, more than 150 people contributed to the symposium and the two documents.

[Report]

'Succeeding through Service Innovation: a service perspective for education, research, business and government'

Service systems are dynamic configurations of people,  technologies, organisations and shared information that create and deliver value to customers, providers and other stakeholders. They form a growing proportion of the world economy and are becoming central to the way businesses, governments, families and individuals work. Innovation, a term applied almost exclusively to technologies in the past, is increasingly used in relation to service systems.

Ideas of service are, of course, not new. However, the scale, complexity and interdependence of today’s service systems have been driven to an unprecedented level, due to globalisation, demographic changes and technology developments. The rising significance of service and the accelerated rate of change mean that service innovation is now a major challenge to practitioners in business and government as well as to academics in education and research. A better understanding of service systems is required.

Many individual strands of knowledge and expertise relating to service systems already exist, but they often lie in unconnected silos. This no longer reflects the reality of interconnected economic activities which, for example, sees manufacturers of engineering products adopting service-oriented business models and health care providers learning lessons from modern manufacturing operations. Indeed, there are wide gaps in our knowledge and skills across silos.

In response, Service Science, Management and Engineering (SSME), or in short Service Science, is emerging as a distinct field. Its vision is to discover the underlying logic of complex service systems and to establish a common language and shared frameworks for service innovation. To this end, an interdisciplinary approach should be adopted for research and education on service systems.

Developing Service Science is no easy task; it not only requires intensive collaboration across academic disciplines but also a doubling of R&D investment in service education and research by governments and businesses. All stakeholders must start to engage each other and make plans for service innovation.

For those responsible for creating a service innovation roadmap, this white paper provides a starting point to raise awareness. For those who have already developed such roadmaps, it serves as a benchmark for improvement. More specifically, drawing upon the expertise and experience of leading academics and senior practitioners, this document makes the following interrelated recommendations:

For education

Enable graduates from various disciplines to become T-shaped professionals or adaptive innovators; promote SSME education programmes and qualifications; develop a modular template-based SSME curriculum in higher education and extend to other levels of education; explore new teaching methods for SSME education.

For research

Develop an interdisciplinary and intercultural approach to service research; build bridges between disciplines through grand research challenges; establish service system and value proposition as foundational concepts; work with practitioners to create data sets to understand the nature and behaviour of service systems; create modelling and simulation tools for service systems.

For business

Establish employment policies and career paths for T-shaped professionals; review existing approaches to service innovation and provide grand challenges for service systems research; provide funding for service systems research; develop appropriate organisational arrangements to enhance industryacademic collaboration; work with stakeholders to include sustainability measures.

For government

Promote service innovation and provide funding for SSME education and research; demonstrate the value of Service Science to government agencies; develop relevant measurements and reliable data on knowledge intensive service activities; make public service systems more comprehensive and citizen-responsive; encourage public hearings, workshops and briefings with other stakeholders to develop service innovation roadmaps.

Service Science is still in its infancy; but we are confident that, by adopting these recommendations, we can accelerate its development and place ourselves in a better position to create and benefit from service innovation in the future.

ISBN 978-1-902546-65-0

RSS Feed Latest news

Webinar - High-Quality Prediction Intervals for Deep Learning

Jun 11, 2018

11 June 2018 - High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach - by Tim Pearce, Mohamed Zaki, Alexandra Brintrup, Andy Neely

Theme Update - Blockchains in Smart Services

Jun 06, 2018

In May, Veronica and her team worked very hard on the first practical phase of the project – the Codification of the Blockchain Prototype for the CAT/Perkins’ Supply Chain.

Project Update - OMMS: the Wireless Micro-Factory that will Treat People with Cancer

Jun 06, 2018

The OMMS micro-factory project lead by Dr Veronica Martinez made a great progress this month.

June 2018 Newsletter

Jun 04, 2018

Find out what the Cambridge Service Alliance have been doing and how you can get involved.

Rare-events classification: An approach based on Genetic Algorithm and Voronoi Tessellation

May 31, 2018

by Abdul Rauf Khan, Mohamed Zaki, Henrik Schiøler, and Murat Kulahci. The paper was accepted at 'The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)', a leading international conference in the areas of knowledge discovery and data mining (KDD). In this paper, Mohamed and co-authors propose a novel strategy for data mining based on partitioning of the feature space through Voronoi tessellation and Genetic Algorithm, where the latter is applied to solve a combinatorial optimization problem.

View all news

Upcoming events

Shift to Services Executive Education Programme

Nov 07, 2018

IfM, Cambridge, UK

Ecosystems Strategy One Day Course

Nov 15, 2018

IfM, Cambridge

Upcoming events