The Importance of Data Science in Project Management
Data usage is growing at a steady pace, permeating every aspect of our lives—especially in the corporate environment. Some enterprise practices are growingly relying on data science (or some form of data analytics) to guide the decision-making process. This integration includes the professional activities of project management.
The PM field greatly benefits from data-driven decision-making frameworks—which in turn ask the project manager to be flexible and proactive, to react and take advantage of what data products bring to PM practices.
In this article, I'd like to focus on projects outside those of the data science field, but that still somehow relate to both corporate environment requirements and the use of data science products, services or inputs to maximize the value of the project outcomes.
Value of Data-Driven Activities in Project Phases
Let's briefly consider phases of a waterfall project and how they can make use of data science inputs in their overall landscape:
- The initiation phase can significantly benefit from data science through the application of statistical inference on project selection, including several criteria like business relevancy, social impact or return on investment, which dramatically influence the final sponsorship of the project.
- A great deal of planning activities involve gathering current-state
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