What’s Your Research Blind Spot?

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If you want to be a “good researcher,” in the hard sciences there are some things you are expected to do across the board: read journal papers, get better at analyzing data, keep an organized lab book (keep an organized everything…), learn to make visually attractive PowerPoint slides, learn to write…

Anjali Gopal is a PhD Student in the joint UC Berkeley-UCSF Bioengineering program. You can follow her on Twitter at @anjali_gopal.


If you want to be a “good researcher,” in the hard sciences there are some things you are expected to do across the board: read journal papers, get better at analyzing data, keep an organized lab book (keep an organized everything…), learn to make visually attractive PowerPoint slides, learn to write…

These are not the types of blind spots I want to discuss in this post. In fact, these are problems that are relatively straightforward to solve. Sure, you may not have a good system for keeping track of journal papers, and you might need to improve your PowerPoints, but there are many posts about it already. Getting a good system might just be a case of buckling down and implementing the suggestions.

What I want to talk about here are the research skills that are more tenuous to describe, but also more instrumental for success. I want to talk about the research skills that answer the question, “How do you pick a project, decide to work on it, and be productive at it even when you get stuck?”


Ben is a member of a microfluidics lab at a prominent graduate institution. He’s had a very successful research career: four first-author publications, and several more second-author papers. His main goal is to look at really interesting biological questions. He describes his research style as “methodical” and “persistent.”

“I’m pretty patient when something doesn’t work out,” says Ben. However, Ben also feels some degree of stress when things aren’t working out--and subsequently, is much more calm when he’s at the stage of a project where the basic concept is working, and his main goal is to collect data to bolster his verified hypotheses.

Mary is also a member of the same lab, and has also had a very successful research career. She’s had three first-author publications, and a couple more in submission. She describes most of her projects as having “worked out,” despite running very few experiments.

She describes her research style as “intuitive.” She tries a whole bunch of different things, and picks the project that seems to be making the greatest traction. One of Mary’s coworkers joked that she has the “greatest amount of preliminary data” out of anyone else in the lab. Mary delights in getting proof-of-concept demonstrations in her projects. She finds the subsequent data collection rather boring.

Both Ben and Mary’s styles have their own strengths and weaknesses. Persistence is often touted as a key virtue of research, though young scientists like Ben might have a hard time figuring out when to abandon a project when it’s not working. By contrast, Mary’s style of research might seem favourable to those of us who want to get things done quickly, though Mary might struggle with working on projects that do, indeed, just take time, patience, and grit.


One of the most well-formed hypotheses of research productivity that I’ve come across is Willliam Shockey’s paper, “On the statistics of individual variations of productivity in research laboratorie” (originally summarized in Brian McGill’s blog). In 1957, Shockley was an engineer at Bell Labs, where he was working with dozens of researchers, and also had access to their publication records. I’ll issue a disclaimer and say that Shockley used the number of papers published as a proxy for ‘productivity’--something which many students and professors alike will vehemently argue against. (Another disclaimer: Shockley was quite a controversial figure, known for his support of things like eugenics.) Nevertheless, his analysis of researcher productivity is still quite interesting.

In his paper, Shockley hypothesized that the following key trends would be correlated with with high scientific productivity:

1. ability to think of a good problem

2. ability to work on it

3. ability to recognize a worthwhile result

4. ability to make a decision as to when to stop and write up the results

5. ability to write adequately

6. ability to profit constructively from criticism

7. determination to submit the paper to a journal

8. persistence in making changes (if necessary as a result of journal action).

Shockley claimed that each of these factors was as important as the other in increasing productivity. He models the productivity of each of these components as multiplicative; that is to say, if you’re 10% better than the average researcher at each of these components, you’ll be 1140% more productive than each researcher.

As mentioned with Mary and Ben, it’s the areas of 2, 3, and 4 that lead to difficulty. When is it optimal to be tenacious and keep hammering away at problems, as opposed to calling it quits and focusing on your other projects? I want to avoid the cliched response and claim that “to be a successful researcher, you need to have a balance of Ben and Mary’s styles.” Rather, I hypothesize that these are both orthogonal skill sets, both of which we can get better at. You want to be the type of researcher who can be intuitive and weed out intractable project ideas quickly, and be the researcher who can be methodical and tenacious when necessary.

I think we should be able to build more systematic heuristics to help us do this--to help us to figure out which skills are more useful in which cases. I don’t necessarily have good answers or suggestions for this; this isn’t one of the posts that end with a list of recommendations of things you can do. Nevertheless, I think it’s useful to be aware of what sorts of skills we lack, and try to figure out ways to achieve them, even if we don’t necessarily know how.

What are some research areas that you think you could strengthen?

[Photo by Flickr user conchu, used under a Creative Commons License.]

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