Fall Cleaning: Is it Time to Tidy Up Your Data?
Are you investing enough in data hygiene? In the final installment of our three-part data series, learn how regular data housekeeping can strengthen one of your organization’s most important resources.
It’s not often that the term “fall cleaning” gets thrown around, but this year isn’t like most others—and if the pandemic has forced you to put big projects on hold, you might have time to focus on more day-to-day things. One example: data hygiene.
Wes Trochlil, founder of the association consultancy Effective Database Management, says diving into data cleanup has plenty of benefits. “Better data will give us better insight into our members and customers, allowing us to create more appropriate products and services and to provide much more effective customer service,” he says.
Trochlil offers a few tips to keep in mind as you decide whether a round of data hygiene is right for you.
Identify the data you want to tackle. Trochlil warns against trying to do too much all at once when you’re doing data cleanup and says starting small is the way to go. “Understand what data you’re trying to improve and that the best way to eat an elephant is one bite at a time,” he says. “Identify which pieces of data are most critical.”
This would usually include contact data (such as addresses and email accounts), membership status data, and demographics. “Focus on what will bring the most bang for your buck and acknowledge that it will take time and effort to do this,” he adds.
Understand the resources needed. While data hygiene may cost money if you invest in an outside resource, Trochlil says staff time is a key factor. “Most data cleanup efforts will take significant amounts of time, which is why I typically recommend breaking the project into the smallest piece possible and working on it over a period of days or weeks,” he says. “For example, if we’re cleaning individual records, work on them in chunks by alpha: As today, Bs tomorrow, Cs the next day, and so on.”
Consider outside tools. Data management can be automated in many ways, Trochlil notes, and it may be preferable, at least at first, to use a service. “If the data is really a mess, this can be a good place to start,” he says. But it’s important to have a plan of attack afterward: “Once beyond this, go back and focus on the key data elements that bring the most ROI [or] are the most critically important.”
Take the opportunity to reset bad practices. Of course, all this work will be for naught if you maintain the same poor habits that required data hygiene in the first place. Trochlil notes that data cleanup “is not an event, it’s a process.” He recommends taking the time to shift your organization’s mindset and processes around good data management to reap its benefits over time.
“Data cleanup and management is much like gardening,” he says. “If you don’t weed consistently, over time, the garden gets overrun, and pretty soon, it stops producing.”
In part 1 of our series on data today, we invited people who typically make gut decisions to consider the value of data-based decision-making. And in part 2, we looked at balancing the data privacy needs of attendees and sponsors of virtual events.
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