Research

1. Technology Testbeds
(Led by Prof Parr, supported by Milner, and Ren)

We recognise that technology testbeds exist at three levels:

• (L0) research,
• (L1) state-of-the-art
• (L2) state-of-the-practice

2. Digital Business Models Tool
(Led by Profs Maull and Vorley supported by Dr Godsiff)

In this work package, we consider key questions such as:

• What business models are appropriate for what technologies and specific sectors?

Our aim is to move beyond a simple checklist process for considering business models (seen, for example, in the business model canvas) to identifying what works in different contexts, how different value models influence organizational styles, impact on employee wellbeing, etc. We are particularly interested in how moving to revenue models based (on ‘use and outcome’) influences the adoption of digital technologies. This will be translated into a framework informed by the research outcomes.

3. Develop Organisational Systems Tool (OST)
(Led by Prof White)

In this work package, we will consider how digital technologies transform:

• Business Process Design
  Adopting digital technology often calls for fundamental process re-design and this work package will produce a methodology for how that should be structured.
• Organisational Structures and reporting
  We will develop the work of Birkenshaw to build a proforma and question set around alternative organisational systems and match them to the business processes and test them on our user sites.
• Organisational Working Practices
  Evidence is increasing that traditional command and control practices are often too rigid for working in a digital world and that ways of interacting between organisational members, suppliers, customers and even competitors need to quickly adapt. These changes challenge existing values, attitudes and behaviours, requiring careful analysis. We will develop use cases on best practices for adoption.
• Organisational Trust
  We want to understand how digital technologies affect trust, and test mechanisms to retain or build trust during digital transformation.

4. Develop Employee Wellbeing Tool
(Led by Dr Plans, Prof Hartley and supported by Dr Aung)

Our approach to employee wellbeing involves a quantitative analytic approach and a qualitative employee engagement part led by David. The quantitative study considers the impact of job strain (characterised by a combination of high demands and low levels of control regarding one’s job) and an individual’s resilience to that strain. Stress can be measured through changes to an individual’s Heart Rate Variability over time (HRVt). Our team will collect data from individuals to identify disruptions to HRVt and monitor how resilient a person is to these disruptions over a six-month period. From the HRVt data we will use machine intelligence techniques to build predictive models that can detect when employees are in danger of experiencing burnout. The qualitative study explores wellbeing from the bottom-up. Through psychometric/biometric real-time data capture methods, we will investigate employee experiences with, wearables, mobile apps, and BYO devices and compare this subjective and objective data collected from the wearable device to explore the relationship between stress and wellbeing.

The responsible innovation component of this work package, led by Prof Hartley and Dr Hugh Williamson, will draw on qualitative methods to examine digital transformation and wellbeing in the animal agricultural sector.

5. Data-driven innovation
(Led by Prof Ahmed-Kristensen)