Sounds like chaos theory, doesn’t it? Well, unfortunately, it’s true.
As with every other industry today, nonprofits are dependent on good data to be successful. And donor data is at the top of the critical care list. The problem that every nonprofit faces, however, is that data degrades, and donor data degrades faster than most.
So what’s going on?
The term “data degradation” refers to the worsening of data quality over time. Degradation is unavoidable because of the many negative influences acting on your data. For example:
- Technologies and tools used to capture and manage data change, get upgraded, get replaced. With change comes the potential for error.
- Within a nonprofit organization, many data inputs are often manual. Manual data entry is always prone to errors, and non-staff resources will create more errors than staff.
- Then there’s the obvious problem of the donors themselves. Lives change, people move, workers find new jobs, new interests emerge, families form, kids go to college … all sorts of life events that nonprofits (hopefully) record as part of our donor profiles require that we manage our donor data aggressively.
What about cleaning?
Yes, we need to practice the art of data cleaning … or cleansing … or hygiene … pick a term. It is important to remember, however, that cleaning cannot be a one-time or occasional event. The typical nonprofit that we talk with cleans data reactively, once problems are discovered or direct mail pieces are returned to the office.
We need to practice good data management, and that means that we clean and enrich (more on that in a minute) data regularly and proactively.
Your CRM system should have data quality tools built into it, and some of these tools help you manage data quality via tasks like checking for duplicate records. But nearly all of these tools work one record at a time, at the point of data entry. And that doesn’t help us with over all degradation across the database.
Managing data quality will require you to get the data out of the confines of the CRM database and into an environment where it can be analyzed, problems identified, and repairs or clean-up scripts applied.
What about data enrichment – isn’t that helping my data quality improve?
Yes it is. Data enrichment is the practice of refining or enhancing the quality of your information assets, especially your donor database. Think of enrichment processes as including not just cleaning, but also adding to existing records with better information about your donors.
Do you ask donors how they want to be communicated with? Do you track their event participation at your organization? Do you ask them about interests or in what ways your mission inspires them? Do you sync up survey responses to their profiles in your database?
The best way to enrich your donor data is to reach out to your donors and engage them. Establish a better relationship. Communicate and learn.
That said, even with good data enrichment practices in place, your data quality is still getting worse. Frustrated? Don’t be. Instead, be proactive.
What you can do now
Taking action will generate benefits quickly. For starters, you need to know the extent of the problem, and you need to develop a data management plan that is consistent with your fundraising strategy.
In other words, you need a map and a plan. Map first.
- Get a data quality assessment of your donor data. This will determine the extent of your immediate data quality problems.
- Document your data needs. What data is required to execute your fundraising strategy? This becomes particularly important when you start addressing market segmentation and targeted messaging of your donors and prospects.
- Determine your data gaps. What data do you need, but are not collecting?
Now you need a plan.
- What is your schedule for communications and fundraising appeals? Now, stop trying to update or clean your donor data in response to that schedule. It’s important to know it, but your data management plan must be proactive, not reactive.
- Create a new schedule for data management. Does your organization need monthly data refreshes? Quarterly? This is the skeleton for your data management plan. You are going to follow this plan independent of fundraising or event schedules.
- Identify your data quality problems and build them into your plan. Identify a solution or process to address each point of vulnerability. Do your data input resources need training? Are your contact addresses stale? Not enough emails? Duplicates? Data normalization problems?
- Prioritize the data gaps that you want to close and identify a solution or process to obtain the necessary data. Do you need a survey tool on your website? Do you want to add Facebook as a registration option? Will you start a new outreach program to engage donors on topics of interest? Does your CRM database need new fields!!
- Determine your data quality standards. How old is too old for a lapsed donor? How many old addresses will you store? What determines the ‘completeness’ of a record? Some experts will tell you to start with your data standards first … and that’s solid advice, too. I usually prefer to address standards late in the process of planning, because wrestling with the other questions and priorities will help us develop a better, more practical set of standards for each nonprofit.
- Assign responsibilities for data management and data quality, and budget for it. If no one is held accountable, it won’t get done.
With a map and plan you are ready. Data quality won’t improve because we want it to. It takes some hard work, but the work gets easier with time. Managing to plan is always the best way to ensure success.
And remember, when it comes to data, if it isn’t getting better, it really is getting worse.