How Are Social & Environmental Organizations Growing with Data?

by Rhia June

As data analysis has become a more mainstream practice over the years, it has spawned an industry unto itself. University programs and online learning institutions alike have prioritized this field of study to meet the growing demand for data professionals, and a Maryville University's data analytics careers page makes it clear that this has resulted in data making its way into businesses of all kinds.

Organizations driving social and environmental initiatives are no exception, having opened their doors to data analytics experts to improve internal efficiency and external practices alike. While the applications for data analytics in this space are limitless, the fundamental idea is quite simple, as described in an article in The Conversation on data science: extract insight from data — that is, gather measurable information and determine what it says about performance and potential.

To fully understand the benefits, it's helpful to break data analytics down into simple steps to see how the idea is transforming businesses and organizations.

1. Gather Data:

The first step in any data analytics operation is to gather the data itself, which can be done in a number of ways, depending on the type of organization, including combing through transaction histories, assessing finances, monitoring customer feedback and social media conversation, and/or maintaining numbers related to website performance. These are just a few examples of the means by which company and organization leaders can begin to gather the data that will serve as the foundation for an analytics operation.

Keep in mind also that this shouldn’t sound overwhelming. While it’s true that gathering data requires some effort, and the more data the better, a lot of this process is typically automated. With the right tools and software, even a small organization can collect a great deal of valuable information.

2. Draw Insights:

People tend to imagine data analytics as a thoroughly advanced process involving complex computation. The not-so-secret truth though is that once an organization gathers its data, it can begin discovering insight with relative ease, often by simply turning raw information and numbers into something that can be interpreted clearly and at a glance.

This process is referred to as data visualization, which means turning data into charts and graphs. Creating simple visual representations out of unclear sets of information helps in analyzing the data and strategizing plans.

3. Apply Learnings:

Once an organization has its data in an easy-to-digest format, leaders can begin making key improvements.

• Identify where operations are breaking down and falling short. Last summer’s blog post on ‘Using Data Analytics for Good’ touched on this very idea, noting that surveys in test communities had helped an analytics team to “understand what isn’t working and what is needed.” It really is about as simple as that. Whether in startups, civic engagement, or even big business, one of the key purposes of data analytics is figuring out what’s going wrong and why.

• Identify growth opportunities. Spotting opportunities is in fact leading many organization leaders today to hire analysts or enlist volunteers from what has become a robust talent pool of data experts. As an example, a trained analyst might observe data that indicates the success of a particular outreach effort at generating engagement, and from there develop ways to repeat or imitate that effort on a continual basis. Someone in this role drives data-driven decision-making efforts, taking advantage of insights to revamp strategy and seize opportunity.

• Improve targeting and outreach strategies. Data analytics is also used to target customers (or partners, donors, voters, and so on). This article by Towards Data Science delved into how targeting and outreach works, essentially pointing out that organizations can use data to glean demographic information about consumers. Whether this information relates to socio-economic status, purchasing history, location, interests, or any other factors, it can help organizations of all kinds sharpen their outreach efforts towards targeted audiences in specific ways that are more likely to work than a more general approach.

Any organization leader — of a non-profit, a volunteer group, an app-based company combating climate change, or anything similar — can appreciate the potential benefit of this sort of data collection. In the simplest of terms, more insight into operations (both internally and with regard to customers or communities served) lays the foundation for improved performance. All of these efforts are transforming organizations of all kinds, and will continue to do so for the foreseeable future.