Speaker 1: Dirty data is the worst. If you're living in a dirty database, you can't pull lists, can't find good prospects, can't see the journey that donors have been on over the years with your organization, and can't generate reports or make data-driven decisions. And one of the worst parts is that nobody trusts the database. There's this organizational lore that the database is wrong or the database can't be trusted. Those are really hard mindsets to break. So let's talk about a tool that will help you either confirm that the database is a hot mess, or at least tell you the extent of the mess, or help you rebut that negative perception of the database. This is what you do. You diagnose your database. You access every field and module in the database and assess it to find everything that's right and everything that's wrong. If this sounds unmanageable, we do have a course called the Database Diagnostics Process that will help you with a scorecard and best practices for every field and module within your database, and then also video lessons on how to present your diagnostics reports to leadership. Now the benefits of doing this diagnostic exercise is that you can now articulate the state of the database, what efforts it will take to completely clean it up, and then any resources that you'll need throughout the process. Now if you go to your supervisor and you say, the database is a mess, they'll say, OK, clean it up. If you go to your supervisor with a filled-out diagnostic scorecard that benchmarks your database against best practice, that's a totally different conversation because you're bringing the problem and the solution to your boss, which they will love. The other benefit to diagnostics is that you can build a streamlined, efficient, doable cleanup plan instead of cleaning things up as they're discovered. It's just not efficient. Now if you're building your own scorecard, you're going to want to open Excel and list every field and module in your database down one column. The next column should be what is the current state of that field and module, and the final column should be what needs to happen exactly to clean up this field or module. As you build your scorecard, you're going to want to really group your fields and modules into four categories. The first is overall database health. And here we're looking at duplicate records, all the code tables that are in your dropdowns, empty records with no GIFs. The second is constituent management and tracking, which is all of the fields tied to a donor or a prospect. So you want to review your donor types, addressees, salutations, relationships, titles, and suffixes, and all of the other fields. The third is gift entry and pledge management. So you want to examine campaigns, funds, and appeals, and how consistently those are applied to GIFs. Like you might ask yourself, do all of my pledges have corresponding payment schedules? Are my soft credits in good shape? Are all of the GIF codes consistent? And the database utilization is our fourth and final category, and this is really looking at all of the modules you're paying for and if you're using them. But it's really not if you're using them, it's are you using them properly? So that is how you build your scorecard. Now the document that you produce is going to help you articulate the state of the database, build a manageable cleanup plan, and be able to see everything that's right and wrong in your environment. If you're interested in the Database Diagnostics Project that comes with a database e-membership, I'll put a link below. Happy diagnosing.