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Maintaining Data Reliability for Your Associaton
Daily changes such as role transitions, membership cancellations, relocations, or other modifications can quickly render your data unreliable. This inefficiency affects your organization's member administration, communication, and tasks like collecting membership fees. In this article, you'll learn how to clean up your data effectively.
Understanding the Importance of Data Maintenance
We keep our homes tidy because living in mess and dirt isn't pleasant. We maintain our cars because flat tires and broken brakes make driving unsafe. However, when it comes to data, it's not so obvious that we should devote time, attention, and care to cleanup and maintenance.
With tangible things, we intuitively understand that care and maintenance are necessary to keep them usable and extend their lifespan. This applies to your home, car, clothing, and many other possessions. But when it comes to intangible assets, such as information or data, we tend to let things slide. This happens because we haven't learned that we need to take care of them—and consequently, we don't know how to do so.
Why can this be a problem? If you don't regularly maintain your data, its quality deteriorates. You can imagine that in a library—where time and energy are invested in maintaining a system to organize books properly so they're easily findable—you'll find what you're looking for faster and where you expect it compared to a book market. Data quality is therefore defined as the extent to which information is suitable for the purpose you intend to use it for.
In the case of your organization, that purpose is to deliver value, such as working to expand your membership base. For instance, you want to know where your members' interests lie, provide them with relevant content, and thus work on member retention.
This is why you need to continuously pay attention to your data quality. It helps to automate this process as much as possible. If a member moves or gets a new email address, it's convenient if that change is implemented simultaneously for both your billing and email communication (and other relevant processes).
Ensuring Data Quality and Accessibility
You want your data to be high-quality and easily accessible to those who need access, and for it to stay that way. I've written previously about the key principles of good data management, but I'll repeat them here for completeness:
🔄 Actual (up-to-date) data, collected in a central system, where it is;
👥 Accessible to everyone who needs access, and where information is only;
🔐 Amended centrally in one place, so you always have just one version of your membership database.
This "AAA" approach sounds more complicated than it is. Below, we've concretely outlined the conditions your data should meet so you can easily implement these principles.
Accurate and Up-to-date
To begin with, your information must be accurate and current. Are address details outdated, is a name misspelled, do roles still match what someone actually does?
Complete
Additionally, it's important that data is complete. There's no use in having only names without email addresses if you want to send a newsletter.
Consistent
Next, you want the data to be consistent. This involves seemingly unimportant things: for example, you want addresses to always be recorded the same way. That means no house numbers in the street name field and no abbreviations (like "Rev." or "Dr.") when the agreement is that these are always written out in full.
Correct
Then you check if the data is correct. Do bank account numbers, for instance, meet the required format?
Unique
Information must also be unique. Duplications cause confusion and can lead to using incorrect data.
Comprehensible
Finally, the data must be interpretable, or in other words: is it clear what is written? If it says 18, is it immediately clear that this is an age, or is it an amount of money?
Determining Which Data to Maintain
We now know what quality data should meet. But we don't yet know which data are worth preserving and therefore maintaining. It's important that you make sharp choices here, because just as you waste time by not properly maintaining your data, you also waste time maintaining data that isn't actually very valuable.
Therefore, always ask yourself and establish in processes with stakeholders:
- What purpose collecting certain data serves
- Whether that aligns with why your organization exists; does it contribute to your mission and the value you deliver?
- Whether it's feasible to maintain this data, do you have the people and resources for it?
If you can't answer these questions well, then it's not worth the effort to collect the data. Also keep the principles of good privacy policy in mind when it comes to personal data. Don't collect more than necessary for the purposes for which you use the data and ensure you have clarity about the legal basis on which you collect and process the data. This way, you can already make a selection in the data you collect. You don't need to interpret "as little as possible" as "almost nothing," because for many types of personal data (beyond basic contact information), your organization can perfectly well explain why you collect it, for what purpose, and that you're therefore simply complying with GDPR.
The Key to Sustained Data Quality
Finally, maintaining data quality is a matter of dedication. Work processes, coordination within the team about who does what and when, and of course software that supports this way of working, are all very important. But always in this combination: dedication and good work processes that are consistently followed are just as important as the right software. If any of these three elements is lacking, you will see it reflected in the quality of your data. And consequently, in your organization's ability to deliver value to members and stakeholders.
Connections Between Systems and Data Quality
Perhaps you're already using them, or maybe you're not: system connections or APIs (Application Programming Interfaces). These are pieces of software that allow one system to "talk" to another and thus exchange data. This can be data that is important for your member administration, which means you need to ensure that this data also remains in good order. After all, you don't want these connections to cause pollution in your system, making your data unreliable.
A disadvantage of building (or having built) these kinds of connections between separate systems is that they're quite expensive, both as a one-time cost and ongoing. Moreover, it means that when something changes somewhere in your system, you risk that the rest no longer connects properly. Here too, maintenance is important.
Connecting separate systems via APIs is not an ideal solution, but is often seen as necessary. This is because few suppliers are able to deliver a comprehensive software package that fits your membership organization perfectly. Having all your functionality in one unified platform is significantly more efficient and reliable for maintaining data quality than managing multiple API connections between different systems.
Keep in mind, however, that establishing these connections between separate systems is not simple and that you'll therefore likely need to make an investment. Alternatively, choosing an all-in-one platform specifically designed for membership organizations can eliminate many of these challenges.
Everything in One Place
There are specialized software packages for membership organizations on the market that can deliver many functionalities without requiring multiple connections. As the founder of Procurios, I am (naturally) a huge advocate for such an integrated system. By integrated, we mean that the system offers multiple functionalities and automatically ensures good data quality, because there is only one place where all that data is stored and processed (think back to the AAA principles).
In my opinion (and that of many of our customers), such a system works much more easily than manually moving data back and forth. Consider, for example, registration for an event via the website. In an integrated system, the data generated by that registration ends up in the CRM. Subsequently, that data can be used to send mailings about the event. You don't need to export and import data: all modules in the system have access to the same data that is always easily accessible.
When you combine this with the right processes, the discipline to follow the established procedures, and give employees responsibility for this, data quality suddenly becomes attainable. A major advantage of integrated data is that the system can automatically perform several checks on that data: for example, does the information already exist in the system, and if so, should the data be merged or should a new contact be created? The system thus supports the working methods, dedication, and processes of employees.
Getting Started
If you want to work on your data quality, it's good to do things in the right order.
Involve your colleagues and any third parties who work with your data from the beginning. Ensure that together you develop processes and agreements that ensure everyone is on the same page, creating support to make data quality a priority.
Afterward, ask yourself if you're storing the right data, as I've described in this article. Then investigate whether the data you store meets the requirements for data quality. As a reminder, you can use this list:
DATA QUALITY REQUIREMENTS
- Accurate - does the data match reality?
- Complete - do you have everything you need?
- Consistent - is all data recorded in the same way?
- Correct - does the data meet requirements that are important for your organization (e.g., bank account numbers)?
- Unique - are there no duplications?
- Interpretable - is the data understandable?
This is also where the question of connections and integration may arise. Although I personally am a strong advocate for integration, because it's a less error-prone and failure-sensitive solution, the reality is that connections between separate systems may sometimes be necessary.
If that's the case, make sure you thoroughly plan with the person who builds or supplies the connection how this connection should look. And whether you can reliably meet the principles discussed in this article.
Ultimately, it all comes down to one thing: a streamlined experience for your members and target groups when they (need to) come into contact with your organization. If your data quality is in order and you properly maintain your data, you'll find that you're much better able to provide that experience, both online and offline.
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30 January 2025
