{"id":80921,"date":"2026-08-03T00:44:53","date_gmt":"2026-08-03T04:44:53","guid":{"rendered":"https:\/\/world.edu\/?p=80921"},"modified":"2026-08-03T00:44:53","modified_gmt":"2026-08-03T04:44:53","slug":"the-special-nature-of-research-projects","status":"publish","type":"post","link":"https:\/\/world.edu\/the-special-nature-of-research-projects\/","title":{"rendered":"The special nature of research projects"},"content":{"rendered":"

<\/p>\n

Research projects come in many forms \u2013 applied, developmental, evaluative or data-driven inquiries \u2013 but regardless of type, they often operate in what might be called discovery mode. This mode is defined by open-ended exploration and inherently fuzzy deliverables. In discovery-oriented work, uncertainty isn\u2019t an obstacle to be eliminated but a condition to be navigated. Research projects tend to unfold iteratively, even when they start with a clear plan. Researchers often find themselves generating new questions alongside the answers they seek. Managing discovery research therefore requires a shift in stance. Researchers must act not just as project managers, but as advocates for their project \u2013 continually interpreting and re-interpreting the project\u2019s evolving shape for collaborators, funders and others. This kind of work demands communicative agility as well as intellectual resilience: the ability to explain, and re-explain (verbally and in writing), why the project looks different now from when it began and why it continues to have importance and value in its updated form.<\/p>\n

We hope what we have said so far makes one thing clear: there is no single project management theory, framework or approach that will work for all research projects. Therefore, \u2018importing\u2019 project management theories and approaches from the literature and applying them to any given research project, without critical awareness, is deeply problematic. Even if we could eliminate research project uncertainty in theory \u2013 say, with infinite time, data and control \u2013 in practice, we cannot. Time and resources are always limited, and projects unfold through the actions of people who make mistakes, revise decisions and bring diverse and sometimes conflicting interests. Budgets are finite, schedules slip and staffing can be inconsistent, especially with the \u2018neo-liberal\u2019 logics of university management. These constraints mean that uncertainty is not just an occasional disruption but a routine feature of the research environment. As B\u00f6hle and colleagues (2016<\/a>) argue, this inevitability can be understood in both ontological and practical terms: uncertainty is embedded in the very structure of research project work, and it persists because of persistent gaps between ideal conditions and real-world constraints. Whether we view this contradiction as a structural feature or a practical limitation, the implication is the same: research project management must start from the premise that uncertainty is not an exception, but the norm.<\/p>\n

In our view, all this uncertainty around how research should and could be managed means researchers should feel free to explore and adapt existing project management theories, approaches and tools to suit their needs and circumstances. However, the biggest difficulty researchers face in taking this kind of \u2018free-wheeling\u2019 approach is that most systems of research management and reporting are built around the assumption that conventional Project Management theories and approaches are applicable to research.<\/p>\n

Take, for example, the simplest \u2018staged\u2019 approach to managing projects which imagines a five-stage process, as outlined in the Project Management Body of Knowledge (PMBOK) (2025<\/a>). While this framework is problematic and has long been considered outdated by the Project Management discipline, the five steps are still the foundational assumption of many university management systems:<\/p>\n

Project Initiation:<\/strong>\u00a0where problems are defined, the project is scoped, a needs analysis might be done, resources are explored and deliverables (things you are going to make or write) are decided.<\/p>\n

Planning:<\/strong>\u00a0the actions needed to ensure your deliverables get done, preferably on time and on budget, are articulated and (usually) put on a timeline, often expressed as a Gantt chart.<\/p>\n

Execution:<\/strong>\u00a0where actions are done to get the deliverables out on time. This is what most people think of as the \u2018work\u2019 (which tends to make all the other work in the earlier stages \u2018invisible\u2019 (Star & Strauss, 1999<\/a>).<\/p>\n

Monitoring:<\/strong>\u00a0happens throughout the project, in formal and informal ways. Formal monitoring often includes milestone reports to a funding body. Informal monitoring might just be check-ins with team members in meetings or via email.<\/p>\n

Closure:<\/strong>\u00a0where a deliverable is declared done. Again, closure can be formal (such as a summary report) or informal, such as distributing a link to a publication to a mailing list or to your manager.<\/p>\n

Much of the grant administration infrastructure in universities, and the processes for managing PhD milestones for that matter, are built around these five stages. Thus, forms, templates and processes are often built on the assumption that research projects follow a predictable, linear sequence of stages. While this framework can be helpful for organising funding and accountability structures, it sits uneasily with the realities of research work. We question whether problems can always be clearly defined at the outset, deliverables firmly established and progress reliably tracked against predetermined milestones. As B\u00f6hle et al. (2016<\/a>) argue, uncertainty is not a deviation from project norms but an intrinsic feature of complex, knowledge-intensive projects. Researchers often encounter shifting problems, emergent insights and evolving methods \u2013 conditions that challenge the very premise of fixed scopes and timelines.<\/p>\n

The administrative insistence on linearity may therefore rub up against reality in uncomfortable ways. Sometimes projects adhere closely to the five-stage model, at other times they deviate spectacularly. For example, planning often starts before initiation and continues after it; monitoring runs alongside execution; closure happens all the way through as some deliverables are finished while others continue. Projects may also roll into each other, with the execution of some parts of an existing project triggering new projects, which can then leverage previous planning and monitoring work.<\/p>\n

Inger\u2019s PostAc project exemplifies the unpredictable, evolving nature of research. Even the name PostAc was assigned a couple of years in and is really an \u2018umbrella term\u2019 for six related research projects and two commercial ventures. All these efforts were united by a mission to help PhD students find employment. What began as an idea for a paper over corn chips and salsa with her friend Dr Rachael Pitt, morphed over a decade into a sprawling, interdisciplinary collaboration. Initially focused on academic job ads, the project expanded to all job ads, drawing in new collaborators, attracting funding, employing PhD students and ultimately spinning off into two commercial products. Inger wasn\u2019t so much a project leader as a \u2018crucial node\u2019 in a shifting research network \u2013 her stable employment allowed her to keep ideas alive across changing teams and multiple side-quests, chaotic administration and fluctuating funding. The project formally closed in 2024, but its research legacy lives on in ongoing collaborations, papers and shared mission-driven momentum.<\/p>\n

Not all projects are this messy! We can usefully contrast Inger\u2019s experience with Aimee\u2019s work in medicine. Aimee\u2019s projects follow much tighter trajectories, very closely aligned to the Gantt charts prepared during the planning stage of projects (see later in this chapter for an explanation of Gantt charts). This approach to research is strongly linked to the funding context within UK health research, where funders such as the National Institute for Health Research require regular monitoring throughout the project and a very detailed final report. Some of the studies Aimee has been part of have also had \u2018stop go criteria\u2019. This means that at certain points in these projects, performance against milestones is strictly assessed, and projects may have their funding removed early if the research doesn\u2019t appear to be feasible to deliver. (That said, Aimee says health researchers still often come up for ideas for research whilst hanging out with colleagues!)<\/p>\n

This post is drawn from pages 19-24 of Managing Your Research Project, 1st<\/sup>\u00a0edition, by Inger Mewburn, Pat Thomson, Helen Kara and Aimee Grant. Copyright 2026 by Routledge. Reproduced with permission from the Taylor & Francis Group.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Research projects come in many forms \u2013 applied, developmental, evaluative or data-driven inquiries \u2013 but regardless of type, they often operate in what might be called discovery mode. This mode is defined by open-ended exploration and inherently fuzzy deliverables. In discovery-oriented work, uncertainty isn\u2019t an obstacle to be eliminated but a condition to be navigated. […]\n… learn more→<\/a><\/p>","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[86115],"tags":[435730],"coauthors":[11733],"class_list":["post-80921","post","type-post","status-publish","format-standard","hentry","category-research","tag-discovery-mode"],"acf":[],"yoast_head":"\nThe special nature of research projects - World leading higher education information and services<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/world.edu\/the-special-nature-of-research-projects\/\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_US\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"The special nature of research projects - World leading higher education information and services\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"Research projects come in many forms \u2013 applied, developmental, evaluative or data-driven inquiries \u2013 but regardless of type, they often operate in what might be called discovery mode. 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