Five Reasons to Learn R for Project Monitoring

Monitoring is an important part of project success. It includes looking at quality of data being collected, identifying gaps in data collection, and creating monthly reports to show the program standing. For anyone who oversees the data management component, there is always the question of what software to use. The dilemma lies in choosing a tool that is affordable for the agency, is multifunctional (statistical analysis vs visualization), and requires less technical knowledge/coding to operate.

Monitoring is an important part of project success. It includes looking at quality of data being collected, identifying gaps in data collection, and creating monthly reports to show the program standing. For anyone who oversees the data management component, there is always the question of what software to use. The dilemma lies in choosing a tool that is affordable for the agency, is multifunctional (statistical analysis vs visualization), and requires less technical knowledge/coding to operate. As a matter of fact it is not easy to find one software that meets all these requirements.

In my practice, I have looked at various tools, and I have discovered that R appears extremely helpful for project monitoring. It deals perfectly with routine tasks in data management fields such as combining datasets, controlling data quality, updating missing data, slicing/subsetting data to project needs, and creating monthly reports. A specific dashboard example is provided later in this article.

Of course, you can do other advanced things with R including interactive dashboards, comprehensive statistical analysis, and developing your own functions or programs. Yet, the truth is that you don’t need to use that type of skill daily. Simple things that you know how to do in R can make you more efficient at your workplace — eventually, simple things make our lives easy and joyful.

Combine Dataset

R works with various types of data formats like spss, sas, txt, excel, and csv. Many agencies are using google sheets for data storage and collections. The data from google sheets can be loaded to the R environment in seconds.

Here is a specific example:

A program has four different projects: Education, Health, Job training, and Family Advocacy. Each project collects details on the beneficiary’s case, the date, and the service provided. The beneficiaries can be enrolled in several projects at the same time. Each beneficiary receives his or her own unique ID. Before being enrolled into a specific program, a separate unit completes intake (demographics) and decides on the project to enroll the applicant. Since data comes from various places, your task is to combine it into one dataset. Data is being stored using google sheets.

Here’s is how you can do it using R.

r ggplot2 monthly-report project-management nonprofit

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