Completed Economics & Business Education & Skills

Business Model Innovation for Intelligent Automation: Unpacking the Productivity Paradox

In plain English

AI plain-English summary

British companies are adopting digital tools but failing to turn them into faster growth—a puzzle known as the productivity paradox. Dr. Velu’s research tackles this gap by examining why automation investments so often fail to boost output, focusing on the neglected redesign of business models and processes after new technology arrives. The work matters because the UK’s productivity slowdown is worse than in other major economies, and the most tech-intensive industries have contributed most to the drag. If the problem is not understood, firms waste money on automation that does not deliver, and policymakers cannot measure the digital economy accurately. If successful, the project will produce a digital tool that helps managers spot where to reshape their business models after adopting intelligent automation—not just install software and hope. It will also propose a new framework for national productivity statistics, giving policymakers better data on how digital investments actually affect the economy. The research draws on historical data and close collaboration with firms in manufacturing, distribution, and the sharing economy to build something practical, not just theoretical.

View original technical description
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.

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Researchers

Chander Velu (Principal Investigator)Duncan McFarlane (Co-Investigator)

Related Research

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relationship between business model innovation and productivity following the adoption of digital technologies
Building Better Business Models: Capturing the Transformative Potential of the Digital Economy
Addressing productivity paradox with big data: implications to policy making
Improving management practices, work engagement and workplace innovation for productivity and wellbeing
Productivity from Below: Addressing the Productivity Challenges of Microbusinesses

Original classification

Fellowship

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