Questions for Nonprofit Teams

Ground Truth is a better book read with the people you’d actually have to fix this with. The questions below are built for a team to argue over — a Development Director, an Executive Director, and whoever manages your CRM or bookkeeping — not for one reader to answer alone. They follow the three acts, which are the three rungs of the ladder. None of them have a clean answer in the book; they have an answer in your shop.

If you only do one thing with this guide: get the question how many donors do we have? asked out loud, by three people, in the same room. What happens next is the whole book.

Act I — Clean (can you trust the number?)

These are the wound. Read them before anyone reaches for a fix.

  1. Three answers. In Chapter 2, Maya finds that the dashboard, the annual report, and the household report all give different donor counts. If your Executive Director, your Bookkeeper, and your Grant Writer each ran “how many active donors did we have last year,” would the numbers match? If they don’t, who does the board believe?
  2. The lapsed list. Eleanor Brandt is categorized as “lapsed” because her husband always wrote the checks, and the system couldn’t see their marriage. How many “lapsed” records in your database are actually active donors giving through a spouse, a family foundation, a Donor-Advised Fund (DAF), or a corporate match?
  3. Which date. In Chapter 3, Gene the Controller reports $19.6M in recognized revenue, while Maya reports $31.4M in campaign commitments. How do you explain the gap between “grants/pledges promised” and “cash in the bank” to your board? Do you have a clear, mathematical “bridge” to reconcile the two, or do you just argue about it?
  4. The tool you already bought. Is there a “smart” feature switched on in your shop right now — automated outreach, scoring, segmentation — running on data you wouldn’t defend in a board meeting? What is it doing faithfully with numbers you don’t trust?

Act II — Connected (does it mean the same thing twice?)

These are the build. The shift from patching reports to fixing the shape.

  1. Commitment vs. transaction. A donor signs a multi-year pledge to fund a new programmatic initiative. Where does the date of that gift live in your CRM? Does it show up as a single promise made years ago (meaning the donor looks “lapsed” now, like Dorothy Ames in Chapter 5), or does each payment count as active giving?
  2. One person, every query. Is a married couple one donor to your system or two or three? A major donor giving through a fund — does the gift officer ever see them? Name the relationship your database can’t currently see.
  3. Could you leave? If you decided to change systems tomorrow, what would you lose that lives only in the vendor’s shape and not in yours? How much of “we could never leave” is true, and how much is just gravity?
  4. The definition that drifts. Pick one word your shop reports on — donor, active, raised. Who owns its definition? Is it written down? Could the next person who inherits the database reproduce your number?

Act III — Predictive (can you act before the outcome?)

These are the proof — what the foundation makes possible.

  1. Sort, don’t decide. Reggie trusts the new list because every name comes with a reason a person could say out loud. What would your shop need before a gift officer trusted a ranked call list instead of working the A’s again and pretending?
  2. Fooled before trusted. Priya tested the list on invented donors, where being wrong cost no one. Before you point any model at real people, how would you know it can see — on data where a mistake is free?
  3. The forty-three. If you could hand each gift officer the few names actually worth their hour this week, instead of the eight hundred, what becomes possible that isn’t now? What’s the cost of not knowing which forty-three?
  4. Privacy and suppressions. When a supporter tells you “do not contact me,” where does that decision live? Does it suppress them across all channels (direct mail, email newsletters, event invites, personal text messages), or does it live in a single staff member’s email inbox? Can you guarantee you won’t accidentally mail them next month?

The Coda — and then, your shop

  1. Day One, Again. Maya’s win was never the $2M; it was a shop where the drift gets caught on an ordinary Tuesday, by the team, without her and without her mentor. If the one person who truly understands your data left tomorrow, who would notice the next mistake — and is that a name, or just a hope?
  2. Where does it hurt most? Of everything in this book, which scene was the one that felt like your shop? That’s not a coincidence and it’s not the place to feel bad — it’s the place to start.