Johannes Piipponen

With over 95% of my PhD journey behind me, I’ve pondered the question: “What did I learn while doing research that I wouldn’t have learned otherwise?” Before moving on to new challenges, I want to reflect on my experiences and share insights that might resonate with others navigating similar paths.

Many of the themes I’ve introduced in this blog involve expanding one’s comfort zone. I think that’s extremely important—not just as a general rule but also because pursuing a PhD is essentially about problem-solving while continuously stepping outside your comfort zone (Figure 1). Additionally, another background assumption guiding this blog is that I’ve always tried to consider my work from the perspective of what I want to learn and what I believe will be useful in the future. While perhaps everyone does this, I think it’s important to remind oneself occasionally why you’re doing what you’re doing, rather than mechanically following routines without much thought. Of course, it’s a bit sad at times to have to consider the utility aspect of different things so much, but for me, many things start to feel enjoyable once I perceive them as beneficial.

Efficiency: The Double-Edged Sword

There are multiple ways to approach work, and due to family circumstances, I chose to maximize efficiency and keep my working hours to a minimum (max 8 hours/day). Being efficient all the time doesn’t always work, of course, but as a general guideline, it has been beneficial and has allowed me to have more time at home where I’m most needed. As Gandalf wisely said in The Lord of the Rings:

“All we have to decide is what to do with the time that is given us.”

and for me, that meant adopting practices that enhanced efficiency and working offline without interruptions whenever possible. One key approach I believe in is “grabbing the bull by the horns”— tackling the most challenging tasks during my peak productivity hours (early morning). While doing this every day can be truly unpleasant and sometimes nearly impossible, it remains effective. When I manage to do so, the day is unlikely to be wasted.

Efficiency and AI: Purposefully exploring relevant AI tools for work (reading; comprehending; coding; writing) further enhanced my efficiency. Even to my own surprise, I adopted the notion: “AI won’t replace you, but a person using AI will.”

I learned to use tools like GitHub Copilot, Consensus, SciSpace, Elicit, and of course GPT, Claude, Gemini, Llama and a few others from the large language models (LLM) family to speed up my research processes. Funnily enough, contrary to what I initially expected, these tools didn’t reduce my working hours but just allowed me to accomplish more within the same time frame.

Commuting between home and the office became an opportunity to utilize these tools: listening to research articles and podcasts, or even engaging in discussions with AI assistants via voice mode while cycling or sitting on a bus (however, as I discuss later, I sometimes question whether it’s wise to fill every spare moment this way). One important realization occurred when I listened to one of Lex Fridman’s podcasts, where Meta’s CEO Mark Zuckerberg suggested that the future likely holds multiple specialized language models rather than a single general one. This insight inspired me to customize LLMs for different aspects of my work and later utilize other state-of-the-art tools for specific tasks instead of relying solely on GPT, which many people seem to use for every task.

However, it’s important not to overlook traditional tools. While AI can enhance productivity, foundational resources like Google Scholar (at least for now) remain invaluable for literature searches, even as newer AI-powered services emerge. This aligns with the idea that we shouldn’t trust LLMs blindly without verifying their outputs; often, combining AI tools with traditional methods and common sense yields the best results.

The Downsides of Striving for Maximum Efficiency

Is striving for maximum efficiency sometimes hindering our ability to think deeply and be creative?

That’s something I’ve been considering lately. When you constantly try to work at full capacity and efficiency, there may not be time for leisurely reading or in-depth exploration of topics, which is essential, particularly in research work. Instead, the focus tends to be on understanding the main message and nothing more. While this has its advantages, it also has drawbacks; I may not know the background of many aspects related to my research as deeply as others do (or so I believe). It often feels like there’s no time to thoroughly examine an issue, which is somewhat paradoxical since one would think that a PhD offers time to ponder something in depth. On the other hand, perhaps it’s good not to examine every detail too thoroughly; it’s easy to lose focus on what’s essential.

Prioritizing and Time Management

People often say that you learn something from everything, but I don’t fully agree—or let’s say that not everything learned is equally beneficial. With only eight hours in a workday (due to my efficiency ideology), I must consider what is sensible to learn and what the opportunity cost is of deciding to learn something new. (Opportunity cost refers to the benefits we miss out on when choosing one alternative over another.)

There’s so much interesting stuff in the world that it’s not practical to try to learn everything. Therefore, understanding where to focus and when to say no is crucial. For example, sitting in meetings where you’re not engaged, truly present or even needed isn’t the best use of time, nor is diving into the newest twists of university bureaucracy if you’re planning to leave academia. It not only consumes that hour, but it can also drain your energy beyond that, affecting your productivity and well-being.

Instead, it might be better to focus on activities that bring you closer to your goals. Personally, I’ve become quite precise regarding time management, where I participate or engage at work and beyond. Often, this approach is not only more enjoyable but also more beneficial from various perspectives. I understand that sometimes we’re obligated to participate in activities we don’t find valuable, but there are occasions when we have the chance to choose and say “no”.

However, it’s important to remember that saying “no” doesn’t mean declining every opportunity. If we always say no—perhaps due to fear of risk—we might miss out on some unique opportunities. Striking the right balance is essential. While it’s vital to protect our time and focus, being open to new experiences can lead to something good. I’m still learning this, but concentrating on activities that bring joy or benefits without consuming too much energy is perhaps a good general guideline.

I hope this approach doesn’t come across as bitter; rather, I’m emphasizing that we often have the ability to choose what to focus on to make the most of our limited time.

The Importance of Taking Breaks

Working at full capacity all the time can be counterproductive and even lead to burnout. I’ve learned that it’s not always beneficial to “advance something” or fill even short periods of free time with audiobooks or other activities aimed at increasing efficiency. Empty space doesn’t always need to be filled. Firstly, without moments of rest, we might not get the downtime we need. Secondly, constantly consuming others’ ideas through podcasts or reading might prevent us from thinking for ourselves. Sometimes, allowing ourselves to simply be—without any agenda—can lead to our most creative and insightful thoughts.

This ties into the idea that not thinking about work during free time has its pros and cons. Sometimes, it’s nice that work matters don’t occupy your mind during leisure by default, allowing you to focus on other things (I find I’m pretty good at switching off when needed).  On the other hand, good ideas might fail to materialize if we refuse to think about work-related issues and let our minds wander during activities like an evening walk or a shower. So, these spontaneous thoughts can be beneficial, but it’s also okay to put them aside when they start to take up too much mental space. Easier said than done, perhaps, but I believe finding this balance is possible. Recognizing that it’s often ourselves, not external actors or our bosses, who demand that we carry unnecessary burdens or lose sleep over work matters is a good starting point. Many professionals manage to maintain a healthy work-life balance without letting work become overly burdensome. So why should it be different here?

General Reflections

Data analysis, coding and visualizing data

My PhD work has been extremely data-intensive; I’ve been coding in R daily, or at least weekly, for the past five years (BTW, try to work closely with more experienced programmers, it really accelerates learning). Although my recent research focuses on global-scale studies and involves making maps (a rather narrow field), the methods and tools I’ve learned are applicable elsewhere, as I highlighted earlier in this blog.

I have to admit, anyone who knows me will agree that I’m not naturally skilled at creating beautiful figures. Thankfully, some others in our group are and through years of trial and error, along with resources like the book Storytelling with Data, I’ve learned the importance of presenting crucial insights from the data in a way that others can understand.

Writing: I had always thought of myself as an underdog when it came to the English language. However, as discussed in a previous blog post from our group, in this line of work, you end up writing so much and receiving so much feedback that we become professional academic writers for sure.

Failures happen, but their significance and sting often diminish over time. Initially, even small failures can feel significant, but you soon realize they have no long-term negative impact—at least not always! On the contrary, they can even be beneficial as stated in this article, provide the possibility to learn and, as I really like to emphasize, force you out of your comfort zone.

Challenges and Misconceptions

Independence vs. Collaboration

Despite extensive collaboration in environmental sciences—with numerous co-authors on articles—the work is highly independent. Meetings, apart from those with the closest colleagues, mostly take place remotely via video calls or email, and collective brainstorming isn’t always the most efficient way to work. As a result, you get used to solving things yourself, sometimes without asking for help, to avoid burdening others (I discussed this in The Art and Science of Asking Questions blog post). This independence can lead to PhDs being perceived as overly independent individuals who may struggle with group dynamics outside academia.

I’ve noticed this in myself; more than before, I sometimes prefer tackling challenges solo rather than reaching out. Recognizing this habit, I’ve been making an effort to collaborate even more and ask for help when needed, seeking input from others. Of course, hard solo work is still essential—I’m not suggesting otherwise—but it’s worth considering the best way to learn or progress.

The Precision Trap

Precision is everything in this job. This has been particularly challenging for me because I’ve felt that time and resources are wasted when a small numerical value or coefficient is examined and refined for months before moving forward. I’ve finally understood that if anywhere, this meticulousness is sensible in academic research.

However, in many other organizations, decisions need to be made more quickly, even before we’re 95% sure about everything. Changing the mindset of a meticulous researcher can be difficult because we’re used to making decisions only when very well-informed but companies often operate on a 50-50 uncertainty principle: it’s more important to make a decision than no decision at all (following that same principle, I decided to publish this blog post without a final round of fine-tuning, because otherwise it might never have seen the light of day).

I’ve noticed a habit—which might be a side effect of careful research work or perhaps just come with age—to spend too much time weighing small everyday decisions. For example, choosing completely accurate and fact-checked wording for a casual conversation or otherwise overanalyzing every option can be counterproductive. Sometimes, academics avoid making sharp statements or giving opinions to the extent that we don’t say anything concrete but instead discuss at a superficial level. This is something I’ve been working on improving—expressing my thoughts when I feel sufficiently knowledgeable (even if not 100% certain), rather than staying silent (which I often do simply because I don’t care enough, which isn’t ideal).

The Illusion of Incompetence in Other Jobs

Because I’ve been doing research for a long time now, it’s easy to think that I can certainly do very good research, but can I manage in other jobs? Talking with colleagues, I’ve noticed that this thought lurks in the minds of many highly skilled workers. But such worries are unnecessary! Without taking a stand on how narrow or broad your research field is, if you know what you’re capable of and can apply it to other jobs, it’s unlikely that a talented and skilled individual wouldn’t perform well in any task.

At least that’s how I see it: sometimes you have to believe in yourself a little too much to succeed outside your comfort zone. This is something also emphasized by the world number one chess player, Magnus Carlsen, who once said that it’s better to overestimate your prospects than to underestimate them.

Final Thoughts

The key isn’t choosing between efficiency and depth—it’s knowing when to prioritize each. In both academia and business, we strive for progress and excellence. The real skill is understanding when to fill ourselves in details and when to move forward.

It’s clear to me now that many things can be learned with a curious mind and the willingness to explore. A degree isn’t required to master a specific set of skills; often, genuine interest is a more powerful driving force. While my PhD has been pivotal in various ways, it’s the approach to learning and focusing, and the mindset I’ve cultivated, that hold the most value.

I hope this reflection sheds some light on the realities of pursuing a PhD—the good, the bad, and everything in between. While the efficiency principles discussed in this blog (including AI tools) have significantly enhanced my productivity, they also come with their own set of challenges. Ultimately, it’s about finding the right balance and remembering that efficiency is a tool to help us achieve our objectives without overshadowing the importance of depth, breaks and well-being.

 

This text was crafted largely with the help of AI technologies but was, of course, reviewed many times to ensure it’s accurate and reflective of my experiences. I think AI did a decent job in editing the text and ideating the structure, thanks to my excellent ideas 😉 though I acknowledge that the structure ended up somewhat unusual due to the influence of these AI tools and that I could have devoted more effort to refining it.

 

Johannes Piipponen is a doctoral researcher at Aalto University’s Water and Development Group. He holds an MSc (Agr. For) in Agricultural Economics and his research focuses on the sustainability and productivity of global livestock grazing, including its challenges and potential future pathways.