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Details of Grant 

EPSRC Reference: EP/R024367/1
Title: Business Model Innovation for Intelligent Automation: Unpacking the Productivity Paradox
Principal Investigator: Velu, Professor C
Other Investigators:
McFarlane, Professor D
Researcher Co-Investigators:
Project Partners:
Dept for Bus, Energy & Ind Strat (BEIS) Digital Catapult High Value Manufacturing (HVM) Catapult
IBM UK Ltd Office for National Statistics Scottish Enterprise
The Conference Board
Department: Engineering
Organisation: University of Cambridge
Scheme: EPSRC Fellowship
Starts: 01 October 2018 Ends: 30 September 2024 Value (£): 1,268,022
EPSRC Research Topic Classifications:
Artificial Intelligence Human-Computer Interactions
EPSRC Industrial Sector Classifications:
Manufacturing Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
28 Feb 2018 EPSRC DE and ICT Fellowship Interviews 28 February and 1 March 2018 Announced
11 Jan 2018 EPSRC ICT Prioritisation Panel Jan 2018 Announced
Summary on Grant Application Form
Productivity growth has been slowing down in the last decade in major economies as well as in emerging markets despite the prevalence of digital technologies. This phenomenon is widely known as the productivity paradox. The productivity growth slowdown is particularly acute in the UK compared to other major economies. Moreover, industries that are the most intensive users of Information and Communication Technologies (ICT) appear to have contributed most to the slowdown in productivity. One of the main reasons for this productivity slowdown could be due to the limited redesign of business processes and business models following the adoption of new digital technologies by firms. Through the research programme Dr. Velu will provide a better understanding the relationship between business model innovation and productivity improvements following the adoption of intelligent automation technologies. Dr. Velu will build a digital tool for management information and decision support systems for assessment of productivity of business models in order to enable rapid and sustained improvements in productivity within firms following the adoption of digital technologies. In doing so, the Dr Velu aims to propose a new framework for productivity reporting for national income accounting.

Dr. Velu will conduct historical analysis of firms that have implemented intelligent automation technologies in order to learn and develop the criteria for productivity measurement of business models. This will include analysis from historical publically available data as well as within firm analysis of a number of selected sectors such as manufacturing, distribution and the sharing economy. In addition, the research will conduct longitudinal in depth analysis of firms in similar sectors as the historical analysis in order to build a digital tool that will identify business model innovation opportunities following the adoption of intelligent automation technologies. This will involve working with the senior management team of a selected number of firms in these sectors in order to define the data requirements, draw-up the technology specification, develop the software programme, populate and test the digital tool with data and propose ways to embed the digital productivity tool within existing management reporting systems. The research will benefit firms as it will provide the basis for a systematic evaluation of the need for business model innovation opportunities following the implementation of intelligent automation technologies. The research will also benefit policymakers by defining good quality and appropriate data in addressing the challenges of measuring productivity in the digital economy.

Key Findings
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