To identify and gain an understanding of these issues, this workstream will begin by mapping the researcher journey, and the Professional Service functions that support it, to identify pain points, bottlenecks and over-burdensome processes.

From here, the programme will work to develop skills and cohesion amongst research support communities and improve the support processes.

Providing signposting to these improved processes and clear documentation will be a key success indicator for this work. The team will work alongside the PS workforce planning group.

This workstream will lead on further RLP engagement, working with the newly recruited academic theme leads and colleagues on the Research Infrastructure Advisory Group.

This workstream sits alongside existing University approaches to research data management (RDM) and the work of the Office for Open Research and is further shaped by the University’s approach to delivering responsible research. The University Library already works to provide researchers with clear guidance to the management of research data and FAIR data principles.

The next phase of RLP will further develop RDM services, training, and processes as well as help support a community of data stewards across the University. This will include the review and development of open research platforms and ensuring they meet the changing needs of researchers across all disciplines. Solutions for archiving of research outputs will also feature in this workstream.

We will deliver projects to meet our aspiration to become a research institution that is recognised for our secure environment. New approaches will ensure that our funders, collaborators and regulators have confidence that we are working in a secure way, with Responsible Research as an underpinning principle. Within this theme, we will look at the changes needed to be made to policy, technology, process and behaviours.

Success here will see the environment in which we work enable researchers to thrive and produce work of the highest quality in its ambition, rigour, integrity and creativity. This will be underpinned by a joined-up service offering across libraries, professional services and cultural institutions that make it easy for researchers to ensure our data is ‘as open as possible, and as closed as necessary.’

The University of Manchester has a number of high-performance computing platforms (HPC), underpinned by a robust Research Data Storage platform. However, the pace of technological development, and the scale of investment by competitors, in the UK and overseas, mean the University is at risk of missing out on research income because data science and data analytics capability is not sufficient to match those of competitors.

Alongside investments in new hardware resources, this workstream will look to augment the University’s capability in this area by making it easier to access HPC resources. This will include single points of access and guidance to the most appropriate platforms and training and support for those whose work has not routinely required HPC access.

Additional capacity, including on-premise HPC, research virtual machines (VMs) and cloud platforms, larger numbers of users and reduced wait times for system access will all be indicators of success in this area. As will an increase in the size and scale of problems that can be tackled.

Competition between universities to recruit is more intense than ever. In Manchester this has led to significant skills gaps and high staff turnover in key areas such as research support, early-career academics and technical staff.

This workstream will develop an approach to recruiting and retaining staff in these key areas to create clear career and training pathways and support the development of a flow-to-work talent allocation model. This will feature research talent/expertise pools such as AI, spatial science, business and research consultancy to enable specific skillsets to be deployed efficiently and flexibly based on research priorities.

A computation training hub based, in Research IT, will act as a catalyst and central point of access for enhanced training materials for the High Performance Computing (HPC) Computational Shared Facility (CSF), spatial science and AI.

Success will see improved staff retention, improved training and development opportunities and clear career progression pathways within and between different faculties and schools for research support, early-career academics and technical staff. In addition, a workforce planning capability will be developed to ensure the University has the right skills available across academic, technical and research support teams.

The funding landscape for research is more complex than ever before with almost 200 grant-awarding bodies, each with their own processes and requirements. Post-Brexit, the competition for research funding is more intense than ever before.

We will ensure that our teams work with processes and technology that provide a journey for researchers which is efficient; effective; transparent; trackable; and able to grow with increased research income within the research funding lifecycle.

This will directly support the University’s strategic aim to increase research income by 8% per annum and support an increase in the number of successful grant applications. It will reduce the time between a grant being awarded; the start of procurement and recruitment activities; and minimise the current frustrations following the grant of an award.

Collaboration, internal and external, is central to the success of the University. Therefore, the processes that support marketing, the capture of enquiries, their triage and management to completion need to operate in a professional and timely manner. This is not limited to business engagement but can include support services such as finance, legal or any other department that is part of the collaboration process.

This workstream will address barriers to academic and commercial collaboration with a specific focus on the development of key long-term partnerships to unlock funding opportunities and enhance UoM’s reputation.

Success will be measured by feedback from our academic and professional support colleagues, increased income, partner and customer satisfaction and in the longer-term improvements in the University’s reputation as measured by comparative ranking.