Team Science Best Practice #2 - Facilitate cross-disciplinary conversations on approaches, methods, and results
Post 4 in the Six Team Science Best Practices series
Ways to talk about cross-disciplinary differences before they become problems
What is Cross-Disciplinarity?
You may recall that my definition of Team Science includes an element of cross-disciplinarity. Cross-disciplinary research generally serves as the umbrella term for a number of research orientations and exists across a spectrum of interaction and integration. We often use this fruit smoothie analogy to represent cross-disciplinary research to help research teams understand the distinctions among the most commonly used terms. It’s important to remember that cross-disciplinarity is a spectrum, as opposed to discrete categories. (Please see the image at the end of this post for a visual representation!)
Uni-disciplinary research is the conventional definition of a discipline and is represented in the figure as an apple - one single, distinct piece of fruit. Multi-disciplinary research involves multiple disciplines, but the interaction and integration among them may be low. Multi-disciplinary research is represented here by the fruit basket, which contains multiple kinds of fruit but they aren’t integrated in any way. Interdisciplinary research is the next level of interaction and integration, where researchers from various disciplines are working in a more intertwined way, with perhaps more discussion of methods and approaches and more joint interpretation of data and results. This kind of research is represented by the fruit salad, where the pieces of fruit are tossed together and the flavors are melding a bit. Finally, transdisciplinary research is characterized by high levels of integration and emergence. In this type of research, it may be difficult to characterize the work being done as belonging to one discipline or another, and may in fact even begin to look like an entirely new field of research. Transdisciplinary research is represented by the fruit smoothie, in which multiple times of fruit have been combined so thoroughly that you may not even be sure what was thrown into that particular blender!
Why are cross-disciplinary conversations necessary in Team Science?
A key benefit of TS is stepping outside our comfort zones and thinking about our own research differently. It’s so easy to keep using the methods and approaches we learned in our training - if it works, why change it? But if you want to shift from business-as-usual, incremental research to leading high-impact, breakthrough science teams that effect real change in the world, doing things the same way you’ve always done them isn’t enough. We know that innovation often flows from taking interesting ideas in one field and applying them in new ways in another and that requires having cross-disciplinary conversations. Having deliberate conversations about how we do our science and why we do it this way has three important benefits.
First, done well, these conversations start to build trust and a sense of community when people are learning together in a psychologically safe environment. As such, it’s really important that the discussions are fun and playful, not scary and mean-spirited. Second, these conversations force us to take something that can become rote and automatic and take a step back and ask ourselves, why exactly are we doing it this way? Is this the best way or is there a better way out there? Is my way the right way or does someone else on this team have an idea that can make our work even more innovative and exciting? Methods can become so entrenched in a discipline that they can lose their impact. Third, in listening to our collaborators describe their methods, we may discover new ways of thinking about our own work. We may discover tools or methods that, once adapted to our context, change our approach or even our field.
How do I start and lead cross-disciplinary conversations?
Cross-disciplinary conversations don’t have to be a huge, complex undertaking! All you need is curiosity, some ground rules, and a little structure. It helps to remember that cross-disciplinary understanding isn’t a “one-and-done” conversation. It needs to be an ongoing discussion throughout the life of the project. Equally important is for the project leadership to model this behavior for the team, asking questions, giving team members time to share, and emphasizing the value of all team members’ contributions. Also, please remember that there’s no shame in bringing in someone from outside the team to facilitate these conversations, like an external facilitator or a research development person with this expertise. In fact, if the team leader isn’t comfortable leading such conversations, it’s probably going to be more productive to bring in an external person.
Here are a few ideas and activities to get you started!
Early in the discussions about the project, take time to discuss why each discipline is required for addressing this problem space. Post 3 in this series addresses this kind of discussion.
Ask key personnel or sub-teams, whether scientists or PIs on the project, to deliver a short overview of what they plan to do, how they’ll do it, and why they’ve chosen this approach, with the majority of their time focused on that final point. What makes this the right way to approach the problem? What are the alternatives and why are they not right for this project? For more complex problem spaces, this may require additional time but there is also value in forcing succinctness! It can be uncomfortable to require busy and successful researchers to justify their approach, but, as noted in previous posts, team discussions may lead to discovering discrepancies in understanding of what is happening on the project or discover new ways to approach the problem. And if you’re doing this exercise before writing your funding proposal - which you should! - your team will probably be asking the hard questions that reviewers will be asking, so it’s worth having those conversations in advance to preemptively address them.
Discuss the overlap of methods, approaches, resulting data, and analyses methods. Where are different sub-teams or researchers similar and different? Does everyone get what they need from this plan? Again, we often gloss over the details, then find ourselves with mismatched expectations, conflict, and lost opportunities down the road.
Dedicate a meeting or a chunk of time to ask the question, Are there other ways to do this work that may be better in some way (e.g., more effective, faster, with less overhead, with less burden on participants, etc.)? This is a great place to leverage graduate students or post-docs who may have exposure to new methods they’ve read or heard about. Let everyone bring their wildest, most creative ideas and see what happens! As a side benefit, this kind of conversation also can lead to new insights about what the outcomes of the project truly are, when we are forced to think more carefully about how we get there.
At team meetings, reserve some time each month to review what each sub-team or lab has done so all team members understand the broad strokes of the project and start to see where the intersections of work streams are and how they are coming together. It’s a great way to identify disconnects and to model a systems-thinking approach to research for trainees. Even if we are a small part of the project, our work contributes to the greater whole in some way, and it is our job to understand, with a big assist from leadership, our contribution, the dependencies, and to try to catch small problems before they become big ones.
When data analyses are ready to be interpreted, bring that conversation to the larger team. Again, this is a way to challenge our own assumptions and biases, our default approaches, by explaining them to others. It may feel really uncomfortable at first, but if your team discovers something new and exciting in the data, or even a mistake in the interpretation, it’s absolutely worth the extra effort.
If your team wants to move beyond “throw-it-over-the-wall” transactional collaboration, it is essential to have these conversations early and often. Leading with curiosity and epistemically humility - both core skills of successful team scientists - has the power to take your research to depths of integration that will magnify your scientific impact.
Slide credit: Dr. Holly Falk-Krzesinski
