Corporate skills in the PhD: Project pipeline

Corporate skills in the PhD: Project pipeline

I spent 3  years working in a corporate office before I started my PhD.  The corporate world is a different breed of work than the PhD, but many of the skills learned are transferable to a successful PhD.  I will to do a short series on what I learned in my experience in corporate work and how I use these skills every day in my PhD.

When you work in a corporate office, common phrases about productivity can be foreign to others outside of the corporate world or even outside of your company.  One concept I learned at my former company that has helped me in my PhD research the project pipeline.

The project pipeline is a way to describe your work in a set a defined stages.  These stages will aid in describing the maturity of the project and allow you to clearly spot a project that is hung up at a certain step or taking more time than typical to get completed.  The project pipeline method enables you to track multiple projects with ease and ensure you have project coming through the pipeline even if it is still in its infancy.

In my PhD work, my project pipeline includes 4 specific stages: literature review/idea clarification, experiments, data analysis, and writing.  At any one point in time, it is good practice to have a project in each one of these four stages.  Experiments take time to run and anyone who has written an extensive manuscript knows you cannot just sit down and write day in and day out until it’s done.  If you have other projects in the pipeline, you can move on to another project while your experiment is running or you can start cultivating ideas for your next project.  Best practices include tracking the time to completion of each stage and project.  In the beginning, these dates won’t be mean much, but after you have several completed projects, you will be able to identify projects which are stuck in the pipeline.  For example, if it has taken you 6 months to do the data analysis for a project when previous projects have taken on average 3 months, you may wish to evaluate why this is occurring.  It might be that the data analysis is more complex and takes longer but it also may be that you are not working efficiently towards completing the current project and may need to spend more time on it.

At any point in time, you should have projects at most stages in the project pipeline.  Using this method, you can easily see where future publications are coming from and the direction of your work as a whole.

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