Got an analysis or experiment to run? I bet you follow a protocol for that. Protocols represent a key part of processes or step-by-step plans of action. Standard operating procedures, protocols, and other forms of process provide critical infrastructure for research to ensure reproducibility, fidelity, consistency, and efficiency, with respect to experimental or analytic endpoints. These are tangible products of research and many PIs have optimized their research workflows. Yet, few take the same deliberate approach to their “knowledge work”, the less tangible side of running a research program. But what if I told you that these activities also can also benefit from processes that streamline how you—and your team—think, decide, and create?
As researchers, and particularly as a leader of a research program, a significant part of your role involves knowledge work—high-level tasks such as planning research strategy, writing grants, designing new experiments, and mentoring your team. Knowledge work is more cognitive, creative, and often harder to structure because it may not seem that the result is a tangible product. It might be harder to check off of your “to-do” list than, say, the myriad administrative tasks you tackle day to day (for more insight on handling the administrative overload, read my recent article here). Yet, without the right processes in place, this type of work can also suffer from inefficiency and disorganization, leading to missed opportunities or unnecessary stress.
What is Knowledge Work?
Knowledge work encompasses activities that require you to generate visions, hone ideas, and make strategic decisions. For PIs, this could mean coming up with new research directions, drafting a manuscript, or mentoring a PhD student on their thesis. It’s the work that requires deep focus, critical thinking, and creativity.
The challenge is that knowledge work is invisible—you can’t easily see progress like you can with physical or lab-based tasks. It’s easy for knowledge work to feel overwhelming because it typically requires a heavier cognitive input. However, by introducing structure and processes into your knowledge work, you can turn it into a repeatable, efficient, and impactful part of your job.
Create a Knowledge Management System
One of the most overlooked aspects of knowledge work is managing the knowledge itself. Information in a research environment tends to accumulate: notes from meetings, manuscripts-in-progress, feedback from collaborators, preliminary data, and more. If this information is scattered across emails, random folders, and sticky notes, it’s easy to lose track of key insights.
Create a centralized knowledge management system to capture, organize, and retrieve the information you need when you need it. Tools like Notion, Evernote, or even OneNote allow you to build digital notebooks where you can collect meeting notes, ideas, papers, and to-do lists all in one place.
Key tips:
- Tag your notes with relevant categories (e.g., “manuscript,” “grant ideas,” or “collaboration”) so they’re easily searchable.
- Develop a routine to organize and review your notes on a regular basis to keep your ideas fresh and actionable.
- For lab-based work, consider integrating tools like Benchling to connect your experimental data with your strategic notes, so you always have the full picture at hand.
Make Decision-Making Processes Repeatable
As a PI, you’re responsible for making numerous decisions, from research priorities to personnel matters. Decision-making can be stressful when there’s no clear framework in place. One way to reduce this burden is by standardizing your decision-making process.
Consider using the following approach:
- Create decision matrices: For large, strategic decisions (e.g., which grant to apply for next, or which direction to pursue in a collaboration), create a simple decision matrix that allows you to weigh different factors such as time, potential impact, and resources needed.
- Delegate routine decisions: Not every decision should fall to you. Train your senior lab members or team leaders to handle day-to-day decisions (e.g., equipment purchases or meeting schedules) so you can focus on higher-level strategies.
By creating a structured approach to decision-making, you free up mental energy for more creative tasks and reduce the chance of decision fatigue.
Block Time for Deep Knowledge Work
Similar to my previous post on time-blocking for administrative tasks, it’s helpful to block off time for deep, focused knowledge work. Cognitive tasks like writing or designing experiments require uninterrupted blocks of time, free from meetings or other distractions. Without this protected time, knowledge work tends to get squeezed into the margins of the day—often with suboptimal results.
To maximize the quality of your deep work:
- Identify your most productive hours and schedule your knowledge work during those times.
- Protect this time fiercely: Let your team know that you’re unavailable for meetings, phone calls, or interruptions during these blocks.
- Use tools like Focusmate or Pomodoro timers to create accountability and structure during your deep work periods.
Refine Your Writing Process
Writing is one of the most cognitively demanding forms of knowledge work for STEM leaders—whether you’re crafting a grant proposal or writing a manuscript. Many PIs face the dreaded blank page and struggle with how to organize their thoughts effectively.
Rather than leaving the writing to the last minute, build a repeatable process for writing tasks:
- Create a process and routine around identifying and compiling funding opportunities, and pair this with your decision matrix to help you decide how and when to go for one.
- Sketch out a workflow, and use templates for common sections of grant apps and papers (like the methodology or specific aims). Over time, develop a personal library of these templates that can be quickly adapted for new projects. Share your workflow with those you mentor so they can also develop a process for writing.
- Set mini-deadlines: Writing an entire paper or grant proposal can feel daunting. Break it down into smaller sections, set deadlines for each, and hold yourself accountable for finishing a section before moving on to the next. Skipping around between sections often triggers a loss of true focus that leads to slowed progress on everything.
For collaborative writing, platforms like Google Docs or Overleaf can facilitate smoother coordination, allowing real-time feedback and reducing the back-and-forth of email exchanges.
Automate Project Tracking and Feedback Loops
When managing multiple projects, it’s easy for details to slip through the cracks—especially if you’re juggling feedback from collaborators, overseeing student projects, or managing lab experiments.
Instead of relying on memory or scattered to-do lists, automate your project tracking and feedback loops:
- Use project management software like Trello or Asana to track project timelines and tasks. Assign tasks to collaborators or students, and set up automated reminders to check in on progress.
- Establish regular feedback loops with your team. Schedule weekly or biweekly check-ins where group members provide updates, and use structured reporting templates to make sure key metrics (such as research progress or manuscript drafts) are captured consistently.
These systems reduce your cognitive load and ensure you’re consistently aware of the progress being made without needing to micromanage.
Conclusion: Streamlining Knowledge Work Empowers Your Research
By implementing repeatable systems for writing, decision-making, project tracking, and more, you’ll find that you have more mental energy for creative problem-solving and strategic thinking—the very things that drew you to academia in the first place.