Wednesday, March 21, 2018

Project Management for Academia 101: learn the basics

Project Management (PM) is a full-fledged discipline which focuses on the planning, execution, and completion of projects. In large corporations, projects like the launch of a new product can take a year and involve dozens or hundreds of people with different expertise in different departments (R&D, marketing, sales, production, distribution). The Project Manager's role is to plan and coordinate the project so that it is successfully completed by a defined date.

I started looking at these practices just through conversations with friends in other industries and quickly realized that many academics are already expert project managers and other academics would really benefit by learning some of the PM rules. I have always thought that your PhD is supposed to teach you how to conduct and complete a project, your postdoc is to identify and plan a project that will get you a job while you learn how to write grants and manage a few people, and your faculty position steps everything up to next level where you manage projects, people, budgets, and several other responsibilities. PM is a critical skill to develop early as it will sustain you throughout your career, and is readily translatable to any other industry.

A good place to start is the Harvard Business School Project Management Manual. It's 20 years old, but it's short and simple and a good introduction to basic practices. The major steps for managing a project are: Initiating, Planning, Monitoring, Executing and Close Out.

Initiating involves defining and organizing the project and it’s one of the most critical aspects of PM. If you don't know what the project is about, what is needed, and who is doing what, you are setting yourself up for chaos from the very beginning. You need to define objectives and the expertise needed to achieve them, including bringing people on board and giving them clear instructions on what their responsibilities are.

Then you Plan: set intermediate objectives, deadlines, and deliverables, assign specific tasks to people and define how the different parts of the process fit together, for example, whether assignments are sequential or parallel and which steps depend on completion of previous assignments. My guest blogger Duc Phan will expand on this in the next post.

Only after you define objectives and set out a plan, you start Monitoring how the different moving parts proceed and get into the Execution/Management portion. Depending on the size of the project this is where things can get hairy due to planning errors, unforeseen obstacles, or personnel issues. This is where the manager may step in to troubleshoot or find someone else with the expertise to do it, reallocate resources, adjust deadlines, etc, until "Tada!" the project is complete and the final deliverable is produced. As part of the Close-Out process, it will be important to go through the flow of the project and see where things went wrong and whether a different design is needed for the future.

I'm sure you can see how these principles could be applied in the lab, but I will give you a concrete example. You can think of projects in terms of published articles, and this type of project management is a good primer for both trainees and faculty. Managing a large project like the one outlined in an R01 application will include multiple publications.

GOAL: I want to publish a paper!
Great! How?

* What is the paper about? Define the title of your project/paper, the main hypothesis that you want to prove.
* What was known about this before? Read the literature to decide what are important questions left to answer and where the knowledge gaps lie.
* What do you need to do? What are the necessary steps to prove your hypothesis and what are the techniques/approaches involved? Are there techniques/reagents you need to acquire?
* How many people do you have and how many do you need? Do you need collaborators to bring different expertise? Do you need to recruit a few junior trainees to take on data collection/analysis?
* Do all the steps need to progress in an IF/THEN fashion (each step dependent on the previous) or are there parallel steps where multiple techniques can be used at the same time (e.g. biochemistry and histology on the same tissue to answer parallel questions)?
* What if my hypothesis is wrong? Develop a risk management plan: alternative approaches and when to abandon the project.

* Lay out the steps you have identified and outline experiments.
* Assign experiments (to yourself or different people) and determine how long it would take to complete them.
* Factor experimental failure, broken equipment, illness, and other factors that could delay the process.
* Prioritize experiments and organize them based on time available, personnel, reagent generation and troubleshooting, animal breeding, equipment scheduling and other factors intrinsic to your research design.
* Define clearly who is responsible for what, who reports to whom, and how participants are supposed to communicate.
* Set deadlines for each component of the project and make everyone aware of them. This is critical when hand-offs are needed, e.g. animals to be shipped to a collaborator, summer student leaving, etc...
* Remember that most likely the manuscript will go to several rounds of review and that you also need to factor time for revisions. If you plan to graduate or leave the lab, who is going to finish it?

Note: Some people like to lay out figure plans when starting to develop a paper: they organize the outline of each figure and which data is needed to complete it. I sometimes find this difficult as the story can change a bit as you go along. I use a hybrid system where I write out the questions we are asking (e.g. Does loss of gene X alter protein levels of Y and Z?) followed by bulleted experimental outline (e.g. 1. Generate 5 animals per genotype/sex, 2. Prepare protein lysates, 3. Run Western blot for Y and Z). Then when we have enough data, we print things out and start organizing figures at the white board, then find the holes and plug them. Which brings me to...

* If the plan is laid out well, the tracking becomes easier during regular staff meetings, as you can just go through the experimental outline and see what is done and what is not done.
* There are ways to monitor without meeting such as Asana which I have discussed in a previous post or the team messaging app Slack and its ToDo option. I will further discuss these strategies in a post dedicated to getting lab members on invested into projects.
* The simpler and more annoying part of managing the project will be dealing with troubleshooting and unforeseen delays leading to changes in deadlines.
* The hardest part of managing a scientific project will be reframing and readjusting your goals as you go along. Scientific discovery is not like launching a new iPhone. As your results come in, you may find your hypothesis is not true or you may find your beloved biological mechanism does something amazing you had not anticipated. The thing is that once you have this PM loop ingrained in your day to day planning, you can shift very quickly and use the same framework I outlined to redesign your workflow and continue based on new goals. Instead of single loop, doing research is more like going through these steps over and over again in a spiral.
* Overall the hardest part of managing in general is managing people, which is particularly challenging with smart and strong-willed scientists, but as I said above, this merits an entire post.

Close out:
* Once you have a collected all the data, you set up a mini-project to write the manuscript and submit, while you plan for revisions do to on the holes that you willingly left for the reviewers to find. 
* The reviewers find a few other holes and you plan for revisions. The manuscript goes back in and is accepted!! 
* Remember to celebrate and thank all the contributors for their valuable contribution. 
* The proofs of course come back while you're on vacation without internet access (I don't know how journals know that, but they do), so remember to plan for a back-up proofreader as your final Close-Out item. 
* Review your process, adjust, and repeat roughly 100-200 times throughout your career.

Now, think of how else you could apply these strategies!

Tuesday, March 20, 2018

Why should you care about project management in academia?

I promised I would start this year on a more positive note going back to the original goal of my blog, learning how to manage a research laboratory. I was inspired by a discussion about Project Management on Twitter a few weeks ago. I've been obsessed with learning more about Proect Management for over a year now and I thought I'd share what I found out.

Design flowchart (Wikimedia Commons)
What is Project Management? I will do what we tell students not to do, cite Wikipedia. "Project Management is the practice of initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at a specified time."

This should sound familiar to anyone who has ever published a research paper or written a doctoral thesis...possibly with the exclusion of "at a specified time". What many students and postdocs don't realize is that, in general, Project Management is one of the most important skills acquired during a PhD that is directly translatable to industry or to any other job.

Project Management has evolved into a discipline with certifications and Master's programs, and Project Managers (PMs) are a now critical part of most projects in various industries. In conversations with friends in PM roles in banking or IT, I have been amazed by how similar our issues are, and how easily we can share tips and concerns about managing people and tasks in our respective fields. While scientists usually develop Project Management skills on the fly, having some idea of the type of approaches that have been tried and tested in different industries may help streamline project development and performance. It's also a very useful skill to mention early in your resume when you are looking for a nonacademic job, and it's absolutely critical when running a lab.

To take the time to go through different aspects of adapting PM rules to research, I thought I'd run a series of posts providing info and useful links to additional materials:

1) General Project Management rules and how they apply to scientific research
2) Different types of Project Management approaches to chose from depending on your personnel and project (guest post by Duc Phan, UCI grad student and PM aficionado)
3) Managing your own project vs. managing several projects in a lab
4) Managing different people to make sure they perform as necessary and are invested in the project

Stay tuned! Links will be added here as the posts are published. Also, if there is something specific you are interested in, write a comment. We would be happy to elaborate and add more posts.

Saturday, March 3, 2018

You are not alone and the scientific community is strong and caring

Some days on Twitter it sounds like the academic scientific community is cold and competitive with a few evil overlords sitting on piles of money and feasting on the remains of trainees killed by overwork. While I will not deny that such characters exist, I sometimes worry that the image portrayed online is bleaker and scarier than the reality, and that it may contribute to deterring trainees from staying in academia. Social climbers are the same in academia as they are in corporations or banking, you will always find power hungry people with no scruples.

My experience both in real life and online has always been that many remain in academia because they enjoy teaching and mentoring, creating a strong caring network that has cheered for me and supported me every step of the way. I have seen my friends from grad school rise through the ranks, postdocs are now associate/full professors and grad students are my peers. Students that I knew as a postdoc are now starting faculty positions and becoming colleagues and collaborators. Mentors and senior faculty have been staunch advocates, often when least expected. Everyone knows how hard this is! It became really clear to me when I was checking references for my first postdocs and I would mention I was starting my own lab. Every single senior faculty I talked to was eager to help and discussed my needs and whether their trainees would fit in a new lab or not.

In this job you constantly meet new people, but once you've been around for a while in a particular field, you constantly find how you are connected with everyone by fewer degrees of separation than you think. You can often sit at dinner at a conference and find that the person next to you is a good friend of a friend, and every year your circle becomes larger and larger. As a trainee I really did not appreciate the benefit of networking with your peers, since for me it was just hanging out with other students and postdocs. But because of academic mobility, every time I moved and my friends moved, we accumulated more friends, who are tied in a mesh of other close colleagues around the world. Online academic communities, be Twitter, ResearchGate or The New PI Slack, only expand these horizons. This supports job opportunities and collaborations, talks and conference invitations, requests to review manuscripts and grants. It will make your career.

Young scientists are often intimidated by approaching older/"famous" faculty, especially if they are hanging out in a group, but often what they are doing is exactly what the juniors are doing: complaining about stuff and catching up with friends. If you want to meet them at a conference for a job opportunity or a collaboration, shoot them an email before the meeting and set up a time to chat. Many people will be happy to comply and to help. Some won't because they have no time or they do not care, which brings me to what motivated me to write this post. Do your due diligence when choosing a mentor and surrounding yourself with a mentoring team. Do not accept abusive behavior as the norm. In rising through the ranks I have begun to be involved in broader conversations about scientific training and career development and I have been inspired by so many senior scientists who care very deeply about helping trainees and affecting change. They are dismayed at their colleagues who use trainees as cheap labor to produce high-profile papers without providing proper training, and there is constant discussion on how to change that culture. One solution is just not to go work for the jerks and find those who will support you. If you consciously choose to work for a jerk at your own risk (sometimes science and money may drive the decision), find others who will support you. But also ask for what you need from your university's trainee office and student/postdoc association or your scientific society. There are a lot of people out there who really care. You are not alone!

So to open the discussion, students and postdocs, what do you need? Let's say I'm in the position to generate some of these resources in the future, what resources are you missing?