Data hoarding: Does the term apply to your donor data?

Data hoarding: Does the term apply to your donor data?

Have you watched the A&E television show Hoarders? The clutter and garbage in some of the homes on that show are unmanageable. It makes you want to shout at the tv: “Throw that trash away!”

Now, let’s talk about your donor database.

When was the last time you cleaned it up? Got rid of dupes? Threw the trash out?

Perhaps this story is familiar. Year after year you gather information about donors. Donors lapse. Some move away. Others pass away. You keep mailing out newsletters and fundraising appeals. Your response rate falls from 60% to 40% to under 30% over time. You keep adding new donors, new prospects and your mailing lists get larger. That feels right! You are raising more money. That feels even more right! Your success, however, is masking a serious problem.

Is your organization is a donor data hoarder?

Donor Response Rate

Data hoarding extends far beyond just your donor data and CRM software. It applies to outcome measurements, web traffic, social media data, emails, image files, document versioning, backups, backups of backups, etc. All data needs to be managed. Email data is overwhelming corporate America. But for our purposes, let’s narrow the focus to donor data.

Nobody gets rid of anything in your donor database. Why? Because it is so easy to keep it all. And on the surface, data storage keeps getting cheaper. Storing and managing, however, are horses of a different color.

The costs of managing too much bad data

Hoarding data is wasting time and costing money. Consider the following examples.

The cost of discovery. Filling up your database with bad data means you will spend that much more time and effort finding the data you need. Do development directors have to sift through duplicate records … or worse yet, conflicting records? Are you keeping records on people who haven’t made a donation in five years, ten years? Measuring lost productivity is difficult, but rest assured, if your data quality is falling, then your lost productivity is rising.

The cost of using bad data. Have you done the math on returned mail? Have you been blocked for sending out spam because too many of your emails go to bad addresses? Consider a nonprofit with 100,000 names in its donor database. If 5% of the addresses are bad, that’s 5,000 pieces of returned or wasted mail each mailing. Can your organization afford to waste that kind of money?

The (potential) legal costs. Not trying to scare anyone here, but a quick Google of “data hoarding” will produce articles talking about the potential legal issues of too much data, bad data, and data theft. Remember that donor data is filled with PII – personally identifiable information. If you don’t need a record, don’t store it. If you need it, keep it current.

The cost of eventual cleanup. One customer we worked with would not purge records, and in fact, created multiple versions of the same records over time. At some point, the number of duplicates and conflicting records was overwhelming … to the point that they did not have the time or resources to manually do the clean up work that was needed. So we studied the problem, then created custom scripts to clean and de-dupe based on reasonable best practices. The result was a much cleaner, higher quality donor database. The cost was easily a factor of 3X greater than had the customer cleaned their data just once a year. Even after the cleanup, the customer agonized over “what might have been lost” by not keeping multiple versions of the same record. That’s a data hoarder!

How to stop (or avoid) data hoarding

Step one is always acknowledging that you have problem!

Step two, determine the extent of the problem. Get your donor data assessed. What’s the average age of your records? Frequency of record update? Number/percentage of duplicates? Number/percentage of incomplete records? Etc. A good assessment will tell you a lot. Many service providers will perform an assessment for free – we do! Some CRMs contain tools that analyze the data. A word of caution, though – CRM tools may not point out data deficiencies that expose the limitations of their database.

Step three, fix the problem. You will need to establish standards for data management. This is referred to as data governance. How long do you maintain a non-giver? How complete must a record be to be useful? A good data cleaning starts with automated services that remove duplicates, consolidate, separate out records that fail to meet your standards, and more. Automated services won’t do it all. You will have some tough choices to make. How much manual work are you willing to invest in reviewing bad records or record anomalies discovered in the cleaning process? At the end of the day, don’t keep it if you don’t have a good reason to use it.

Step four, don’t let the problem recur. Develop a plan to improve data quality, starting with the point of entry into your database(s). Then, keep your data clean, current and manageable. Some organizations should clean their data quarterly, others annually. The determining factors in the schedule are: size of the database, number of new records added every month/quarter/year, and the variety of input sources (manual vs. automated, professional vs. volunteer).

Don’t be intimidated by the problem

Years ago, a friend of mine worked at a United Way organization that kept five years worth of giving records in their system. That’s it. Purged giving campaign data every year. They did not have a storage problem. Few duplicate or conflicting records. This United Way was definitely not hoarding data. Unfortunately, they were intimidated by data and data management, and as a result, established policies that limited their ability to benefit from the data they stored.

You don’t need to be intimidated by your data. Just recognize that it needs to be kept clean, consolidated, and current. And like most other things, if you don’t have a use for it, get rid of it.

Don’t be a donor data hoarder.

About Gary Carr

Gary is the founder and president of Third Sector Labs. With more than 20 years of experience delivering software and data solutions to a wide variety of clients, Gary turned his attention to the overwhelming problem of data. Third Sector Labs is committed to making sense of data for the nonprofit industry.

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