Hi, my name is Anatol Kreitzer
and today I'm going to be telling you
about how concepts from business
that you've learned about in this course
are actually applied to your academic lab.
So you've learned about the value proposition,
in other words, why is the work important?
And what is unique about the technology
or the product? But this also
applies to the academic lab.
For example, is your lab primarily
need-based, is it addressing a question?
Or is it technology-based, are you developing
new tools? So for my laboratory,
we care a lot about systems neuroscience
questions, such as how is movement
organized and planned, and how is that
disrupted in Parkinson's disease?
In other words, my laboratory
is primarily a need-based
laboratory, but we of course rely on
technology to address our questions.
So we rely on both the why's and the what's.
So for us, the what's of my research
program are essentially the techniques and tools
that we bring to bear on the questions.
Now the questions, of course, are
primary. But the techniques are absolutely
critical. So for example, we use
imaging technologies, we use electrical
accordings from the brain, we do sophisticated
behavioral measurements. And these are all the what's
of my research program. But we didn't develop
these tools myself.
Instead we used them to focus on
critical questions related to adaptive
motor control and its disruption
in movement disorders and diseases
such as Parkinson's Disease.
So, who are the stakeholders
that I think about and care about most?
Well, primary would be my peer scientists.
So, as you saw when you thought about
stakeholders in industry, there are also a set of stakeholders
for academia. And research peers is
solidly in the middle, and the reason
that research peers are so fundamental
is because they evaluate your work
for almost all of your other stakeholders.
So for example, when you want to publish
a paper in a journal, that paper is going to be
reviewed by your academic peers.
When you want to get funded
by the National Institutes of Health,
for example, your peers are going to be reviewing
your grants. Similarly, if you want to get promoted,
you want your department chair to recognize
your value, your department chair will
actually get evaluations from your peers.
Furthermore, if you want to get a good postdoctoral
fellow applicants, those are going to be coming
from the laboratories from your peers.
So for me, my number one academic stakeholder
is my academic research peers.
However, individual stakeholders,
such as my employees, are obviously
treated quite differently. And I think my
second most important stakeholder
are the people in my laboratory itself.
Because fundamentally, in order to run
a successful laboratory -- similarly to run
a successful business, one needs to have
quality employees, and of course that
is really the heart and soul of the laboratory.
So next, we're going to talk about how
the organizational context influences
academic lab. Now you learned about how
organizational context is important
in the developmental cycle of a business
and how it helps structure a particular
enterprise. But in a laboratory,
many of the same concepts apply.
So for example, whereas in industry
one might have a developmental cycle
for various projects or drugs, or what have you,
in the lab, one has academic projects
that ultimately will become publishable units.
And so, I have a number of people
in my lab, probably about ten people.
And each of those people is responsible
for driving a particular project forward.
Now I have projects really at all stages
in my laboratory, I have
projects in their very infancy,
where it's really brainstorming ideas
and coming up with interesting and exciting
hypotheses. Often these are driven by
people new to the lab. Now there are also projects
that are sort of midway, where we've really
explored questions and developed some fascinating
pilot data, we may have even written some grants.
But these projects have not come to fruition.
And lastly, we have projects that are
actually almost finished and we're in
the final stages of preparing manuscripts,
putting together figures, trying to get this work published.
So in my laboratory, there's always
various projects at different developmental stages
and that is absolutely critical for
continued productivity in the lab.
And this is quite similar to business
strategy, in which you want to have multiple
products in the pipeline at all times.
So I would say that I like to have
roughly a regular turnover of people in the lab,
so new students coming in every couple years,
and therefore, new projects being
developed every couple years.
And that really ensures a continuous productivity.
Now in terms of organizational
capability, I've actually chosen to have
my lab split about 50/50 between
graduate students and postdocs.
And we have two research support staff.
And so this was actually a very intentional
allocation of resources on my part.
Graduate students, I think, are really
the creative force in a laboratory.
They bring new ideas, they're willing to take risks,
and when they leave the lab, they don't take
those projects with them.
So they really help build your laboratory.
In contrast, postdoctoral fellows come to the lab,
they're already trained, they get projects up and running
quickly. Usually they're a little more risk averse,
so they tend to go after more solid projects,
and when they leave the lab they actually
take those projects with them.
And that actually reduces really
the sorts of topics you can work on
in your laboratory. On the other hand,
they tend to be a little more productive.
So, I think it's really important to have
a balance between these two
types of people in the lab.
Finally, the support staff is really an important
and strategic decision, how many resources
do you allocate towards supporting
the either the graduate students or the postdocs
in the lab? And because this really is a zero sum game,
you have to figure out for any individual laboratory,
how much resources should be devoted to
supporting people in the lab.
So, for me, in terms of strategy, I really am
thinking about both near and long term
strategies. In the near term, I'm
mainly a project manager,
I'm meeting with people regularly, trying to bring
projects to completion, to publication.
But at the same time, I have to be thinking
five to ten years out. So this is really the long
term vision of the laboratory, what
new areas are we going to go into?
What new techniques are coming online
that we can bring to bear to really address
really exciting questions?
So, this is really a more long term vision,
and I think you need to think about both of these
things in parallel. And this really
applies to both the business setting
as well as the academic setting.
Now finally, I think running an academic
laboratory really does involve a number
of tradeoff decisions regarding resource allocations.
I alluded to one of those earlier,
when I mentioned how much money should we
devote to support staff versus primary
researchers. But these sort of decisions come up
all the time, for example, do you want to devote more
resources to imaging, for example, do I
want to buy a new microscope? Or do I
want to devote more resources to electrophysiology,
in recording from the brain?
So this is just from my particular case,
these are really fundamental decisions
that impact the kind of data that you can acquire,
and ultimately, the kinds of questions
you can address. So really,
you need to take into account
your longterm strategic plan
when you develop these sort of tradeoff decisions.
So with that, thank you for listening
and I hope I've illuminated some of the
parallels between academia and industry strategy.
Thank you.