The Problem: The Illusion of Control in Research Planning
In research, few things are as frustrating (or as persistent) as the feeling of falling behind.
For many doctoral students, postdocs, and early-stage supervisors, planning often defaults to managing ever-growing to-do lists. Tasks accumulate, deadlines approach, and the mental load expands. The result is a constant sense of chasing after unfinished work; no matter how much gets done, there always seems to be more waiting.
Some researchers (perhaps including you, since you’re reading this) have started to become interested in more structured approaches to managing their work, such as setting goals across multiple time horizons: quarterly targets, weekly planning, and daily priorities. (I’ve written elsewhere about multiscale planning as one such framework.) These approaches do help bring more clarity and direction. However, even for those who apply them, one persistent challenge remains: at the end of the day or week, there is still too much left undone.
This is not a failure of motivation or technique. It reflects a deeper issue in how we conceptualise our work.
The first problem lies in how projects are defined. A PhD student may refer to their entire PhD studies as a single project. But in reality, the PhD time is often a collection of smaller projects. Added to this are parallel projects: teaching duties, conference preparation, research papers, and administrative tasks. The same applies to postdocs juggling grant applications, collaborations, and lab leadership responsibilities. Each of these activities draws from the same limited pool of time and energy.
The second problem is a mismatch between perceived and actual capacity. A 12-week quarter nominally offers 60 working days. However, once teaching obligations, conferences, holidays, sick leave, administrative tasks, and unexpected disruptions are factored in, the actual number of available working days may shrink to 45 or 50. Planning based on theoretical capacity rather than real, available time almost guarantees overcommitment.
What follows is predictable: long hours, diminishing returns, creeping frustration, and an erosion of both productivity and well-being.
This is where the Glass Jar Theory, also known as the Jar of Life, provides a more practical mental model for planning academic work. Rather than trying to fit everything in simultaneously, it starts by recognising that not all tasks are equal and that some simply won’t fit.
Table Of Contents:
- The Problem: The Illusion of Control in Research Planning
- The Glass Jar Theory in Academia: A More Useful Mental Model for Planning
- Why Researchers Struggle With This And Why Portfolio Thinking Helps
- The Shift: Think in Terms of Portfolios
- From Control to Clarity: A Different Mindset for Planning Research Work
- Invitation to Explore Further
The Glass Jar Theory in Academia: A More Useful Mental Model for Planning
The Glass Jar Theory, popularised by Stephen Covey (the author of the productivity classic “The 7 Habits of Highly Effective People”), offers a simple but powerful metaphor for managing finite capacity. Picture an empty glass jar. Into it, you can place large rocks, smaller pebbles, fine sand, and water. If you start by filling the jar with sand and pebbles, there is no space left for the rocks. But if you start with the rocks, the smaller elements naturally settle into the remaining gaps.
In the context of academic research, this metaphor helps illuminate two critical shifts: how we define our work and how we allocate our limited time.
Step 1: Size the Jar
Before deciding what goes into your jar, you need to know how large it actually is.
Start by mapping your next quarter. On paper, that might look like 60 working days. But as we’ve discussed, that number is rarely accurate. Account for public holidays, conferences, supervision duties, teaching commitments, and known periods of leave. What remains is your actual capacity, i.e. your usable time. This is your real jar size.
Many researchers skip this step and build plans on an idealised version of the quarter. That’s where overcommitment starts. The goal is not to create a schedule that looks ambitious on paper; it’s to build one that reflects what is possible.
Step 2: List the Full Project Portfolio
Once you know your available capacity, list everything competing for that time. This is not just your formal research project. Include every ongoing piece of work: manuscript writing, literature reviews, grant applications, administrative duties, teaching preparation, conference presentations, collaborations, and student supervision.
Avoid the common mistake of collapsing multiple projects into a single umbrella label, such as “PhD work” or “postdoc responsibilities.” Each of these larger labels usually contains several distinct projects that need to be counted individually. You cannot prioritise what you have not clearly defined.
Step 3: Classify Workload by Size and Energy
With your full project list in place, you can now begin classifying them.
- Rocks: These are the high-impact projects that need meaningful progress this quarter. Most researchers can realistically take on one, perhaps two, true rocks in a given 12-week cycle.
- Pebbles: These are smaller projects or components that still require attention but carry less consequence if delayed.
- Sand: The ongoing stream of smaller tasks, such as emails, routine admin, minor revisions, and day-to-day maintenance.
Be deliberate in this step. Avoid treating too many tasks as rocks. If everything is a rock, you are not truly prioritising. It’s often necessary to break large projects into smaller sub-projects that can fit more realistically within the quarter. This allows steady progress without overloading your available capacity.
Step 4: Protect Space for the Unexpected
When researchers overfill their jar, they leave no room to manoeuvre when the unexpected happens. Every new demand forces reactive rescheduling, typically by sacrificing evenings, weekends, or sleep. Over time, this erodes both well-being and work quality.
The solution is to plan for uncertainty in advance. If your actual research capacity is 47 days, don’t allocate all 47. Protect a portion (often 10–30%) as an uncommitted buffer (I like to call this “time for the Unexpected”). This gives you a margin to absorb delays or unplanned tasks without destabilising your main priorities.
Importantly, this buffer is not “free time” waiting to be filled. It exists precisely to handle the unpredictable, which, in research, is a certainty.
Why Researchers Struggle With This And Why Portfolio Thinking Helps
Most researchers don’t struggle because they’re disorganised. They struggle because the way they conceptualise their workload leads them into planning traps.
The To-Do List Trap
For many, planning is essentially a list-building exercise. Tasks are written down in long linear to-do lists, often mixed together without clear distinctions: write an introduction, run an experiment, respond to reviewer comments, email collaborators, prepare for conferences, check equipment, and schedule supervision meetings.
In this format, everything sits side by side. The critical paper revision looks visually equivalent to updating a calendar. It invites the illusion that these items are somehow comparable in size, effort, and importance. They’re not.
To-do lists grow easily but rarely shrink at the same pace. The more items added, the more overwhelming the list becomes. Important work competes for attention with trivial tasks. This is one reason many researchers report feeling busy while simultaneously feeling they are not making meaningful progress.
The Linear Planning Fallacy
Another trap is linear capacity estimation. Researchers may look at a quarter, see 12 weeks ahead, and mentally calculate: “If I work full-time for 12 weeks, I should be able to complete these five projects.” The assumption is that capacity can be equally divided across projects and that all tasks move forward in parallel.
In practice, research doesn’t unfold this way. Some projects require long, concentrated blocks of uninterrupted work. Others generate waiting periods, e.g. for experiments to finish, collaborators to respond, or data to arrive. Some tasks create downstream dependencies that block others. And many consume cognitive energy in ways that are not captured by simple time estimates.
By treating capacity as evenly divisible, the plan becomes fragile. It leaves little room for disruption, fails to accurately reflect the true weight of different projects, and often results in a slow accumulation of unfinished work across multiple fronts.
The Shift: Think in Terms of Portfolios
Portfolio thinking offers a more accurate mental model. Your research workload is not a single project with multiple tasks. It is a portfolio of projects, each drawing differently on your finite cognitive and temporal resources.
Not all projects require equal attention every quarter. Some can advance incrementally, while others require focused sprints. Some can be deferred; others are time-sensitive. The Glass Jar Theory helps you prioritise this portfolio realistically by forcing explicit trade-offs: which rocks fit, which pebbles can progress, and which sand will simply have to wait.
Importantly, this approach is not about doing less for its own sake. It’s about focusing limited energy where it has the highest impact and accepting that not everything can, or should, move forward at once.
The result is a plan that aligns better with how research work actually unfolds: unevenly, unpredictably, and with varying cognitive demands across projects.
From Control to Clarity: A Different Mindset for Planning Research Work
Much of the frustration researchers experience with time management stems from chasing a kind of control that simply isn’t available. The desire to “fit everything in,” to stay fully on top of multiple projects simultaneously, and to hold every commitment on equal footing is understandable but not realistic.
The Glass Jar Theory offers something more practical: not control, but clarity.
Clarity starts with an honest view of capacity. How much time do you truly have? Not the theoretical number of working days, but the adjusted capacity after teaching, conferences, and administrative obligations are factored in. That is your real jar.
Clarity also requires a full view of your portfolio. Not just the headline projects but every active piece of work drawing from your time and cognitive energy. This allows you to see where the real load sits and forces you to make conscious trade-offs.
Clarity demands a more nuanced view of the work itself. Not all tasks are equal. Some will move the needle decisively, while others can progress incrementally; some may not require attention this quarter at all. The distinction between rocks, pebbles, and sand is not about labelling work as “important” or “unimportant”; it’s about sequencing limited capacity in a way that reflects both impact and feasibility.
Ultimately, clarity acknowledges that uncertainty is inherent to the system. The goal isn’t to eliminate surprises, but to maintain a sufficient buffer so that when the unexpected arrives (as it inevitably will), it doesn’t derail everything else.
In this sense, adopting a portfolio mindset anchored in the Glass Jar Theory is less about managing time and more about managing commitments with precision. It allows you to build plans that are not only more realistic but also more sustainable both for your work and for yourself.
Invitation to Explore Further
This model is one of several frameworks we actively teach in our Fast Forward training. In this seven-week structured, science-based training, over 1,500 researchers have applied these approaches directly to their complex workloads.
If you lead a graduate school, a postdoctoral programme, or a research institute and want to explore how your researchers can benefit from these methods — not with another Two-day workshop but through an applied system that builds lasting behavioural change — Let’s talk.
Book a call with Nadine Sinclair
Dr. Nadine Sinclair
Nadine is a trusted advisor to corporate and academic leaders and one of the Managing Directors of Mind Matters. Before embarking on her entrepreneurial journey, she was a project manager with McKinsey & Company. A scientist by training and at heart, she conducted her doctoral research at the Max Planck Institute for Biophysical Chemistry. Nadine brings close to 30,000 hours of experience in managing projects for research institutions, research foundations, pharmaceutical and biotech companies (including many Fortune 500) and governments. She continues to build her expertise with over 1,000 hours of project management each year. As a neuro leadership expert, she bridges the gap between science and business practices, leveraging the latest insights from neuroscience and behavioural economics to create breakthroughs for her clients.
