August 26, 2014
Your data is vital to your association. You use data to analyse the decisions you’ve made and to make sound decisions for the future. Data such as the number of members in good standing your association has can transform initiatives from wishy-washy campaigns to effective programs. Ensuring that your data is as accurate as possible is key towards using it to the greatest effect. And a big part of having accurate data is making sure your data is clean.
What does it mean for data to be clean? There are a few components to clean data. The first is data consistency. Is the data in your system in the same format? Take addresses for example. If a member is based in the United States, does it say “US” in the system, or “U.S.”, or “United States”, or “America”? Is this consistent across all records?
The second component to clean data is its completeness. Is everything you need to know populated in the system? If you need to know what industry a member is in, do you have that on a third of your contacts, half of them or all of them? Is some of that data is junk data, like “space mining” or “other”?
The third component to clean data is the content of the data. Is the content accurate? Are there extra fields in your data? Many associations think they need to store and track many different fields of data, but in many cases, less is more. After all, data is useless unless you can do something with it.Many associations think they need to store and track many different fields of data, but in many cases, less is more.”
Having unclean data is a detriment to your association when you’re trying to run searches or report on certain information. Throughout the years your data may have gone through multiple AMS implementations, getting dirtier with each transformation. You may also have duplicate records in your database or even information that you no longer track. If your association is to succeed, you’ll want to ensure that the data that you need to view and report on is useful to your organization. Keeping your data clean is paramount to the success of your organization.
The most common time data is cleaned is prior to implementing a new AMS. At the beginning of the data migration process, it’s important to think about your data, what’s absolutely necessary for migration and what can be left behind. Being really honest about your data needs is key here. So many associations think “more is better” and end up migrating data they don’t need or will never use. This is a mistake. Having useless data clogs up your system and makes it less usable for your staff, de-incentivizing them from using the database. Then when the database is neglected, the data quality gets worse and worse, further reinforcing this cycle. Wes Trochlil wrote a great synopsis of this cycle of doom on his blog, if you want to dive into that concept further. So keeping your data clean at the outset of an AMS implementation is of vital importance.
Now you should know what data cleansing is, why your organization should do it and when. If you have any further questions or concerns, feel free to connect with us in the comment section below or to contact us!