As consumers, we’re inundated by information all day long, through any number of devices as we go about our day, scrolling through news feeds, driving down the road, or working on computers. According to Pew Research Center, approximately one-third of American adults report going online “somewhat constantly.”[1] We’ve come to expect easy access to information and it’s no different when we show up to work.

In recent years, nonprofit leaders have experienced a digital transformation with a big push towards cloud solutions, software integrations, and data-driven decision-making. Everything from grant proposals to budget forecasting ties back to internally-tracked data. Although the promise of data looms large, stewards of nonprofit data need to make sure it's orderly and current in order for it to remain useful! Implementing some simple data hygiene practices--starting with the ones mentioned below--can go a long way toward protecting data integrity and investing in its long-term relevance.

1. Incorporate data quality into your organizational culture

Working in a collaborative environment requires trust and a commitment to excellence so that everyone has access to information that represents the most current version of the truth. One way to weave this sentiment into the culture is to reflect on the organization’s value statements or strategic goals. Can you articulate how data quality speaks to one or more of the values or goals? Bringing greater intentionality to data quality will automatically raise its level of importance; communicating its importance directly through shared values will bring even greater emphasis to it. Note that resource allocation equates to intentionality, so be sure to account for the time necessary to conduct data hygiene activities. This is particularly important for grant proposals and budgets, though equally relevant for internal budgeting purposes as well.

2. Conduct an audit of existing data and data entry processes

Take a look at the data that your organization tracks—donor behavior, program participation, volunteer hours, moves management touchpoints, and perhaps other data. What data is most important to your operations and various stakeholders? Evaluate its completeness (is there any data missing?), quality (is the data accurate or out of date?) and formatting (does the data follow any standards?). What data is unnecessary and no longer useful? Document your findings in preparation to bring order to the chaos!

3. Clean up identified areas of concern

Clean data is both accurate and adheres to defined formatting standards. Consistency is key! Based on the data audit (tip #2), define a plan to make bulk changes to existing data deemed critical and remove or otherwise segment unnecessary information. Weigh the data’s importance against how much time it will take to clean it up. In some cases, it may make sense to define data integrity standards for all new data entered after a certain point in time and ignore the historical data. For example, with limited resources, we recommend prioritizing cleaning up current and LYBUNT[2] donor records over SYBUNT[3] donor records. We know that clean-up activities such as these lead to better donor engagement. The more you trust your own data, the more you can customize development activities for each donor segment.

4. Define data hygiene practices to ensure data integrity going forward

Data hygiene includes two types of parts: data entry standards to establish consistency and periodic sweeps of the data to catch and correct errors. Each important data field needs data entry guide rails to follow. When followed, data entry standards make information easier to aggregate, manipulate, and otherwise analyze. What does this look like in practice? For each relevant field, make explicit decisions about how data ought to be entered. A few suggested examples to get you started:

• What date is used for a donation? Is it the date received? The date of the check? The date entered? There isn’t a right answer here–but selecting one definition and sticking with it will make for more accurate and clear communication.

• How do you define an 'inactive' donor record…? Your organization may want to consider a donor record ‘inactive’ in a variety of situations including, but not limited to when a person is deceased or experiencing long-term health challenges. Decide how to segregate these records when working with donor records for active stewardship and solicitation activities.

• What is the process for removing duplicate records? It’s very common for a donor database to have duplicate records at any given time. If donors can make donations from the organization's website, chances are, the system likely creates a new record for them each time they do that. How will you review the records and merge duplicates? And at what frequency? Each software system has a different method and flagging system. Some of them may run a sweep automatically, but typically they need a user to approve an action regarding found duplicates.

How does your organization approach data hygiene? What’s the smallest change towards better data hygiene your organization could make that would have the biggest impact? Tell us in the comments below!

[1] https://www.pewresearch.org/fact-tank/2021/03/26/about-three-in-ten-u-s-adults-say-they-are-almost-constantly-online/ [2] Last Year But Unfortunately Not This [Year] [3] Some Year But Unfortunately Not This [Year]

Photo by Alex Padurariu on Unsplash