I couldn’t tell you WHY, but learning about scams has become one of my top COVID hobbies. From multilevel marketing to embezzlement to fixing the lottery, plain old bribery, Ponzi schemes, and all manner of fraud, I’m riveted. This week, the journey led me to listening to a fascinating, albeit heartbreaking, podcast about romantic scams.
The journalists from said podcast conducted some deep research about trust. Where does trust come from? How is it earned? Why are some people more trusting – or more trustworthy – than other people? It turns out that gullibility or susceptibility to being scammed cannot be explained by intelligence, education, or other social advantages. Here’s another fact that was particularly shocking to me. Trustworthy people are more likely to be taken advantage of. Why? Well, we (yes I am including myself in the trustworthy bucket) are reliable and honest in our dealings, and we can barely imagine that anyone would act otherwise. Plus, trustworthy people may be more likely to volunteer sensitive information, which makes scamming us even easier. So, we have two counts against us. We are more vulnerable to scamming in the first place, and worse at spotting it when it does happen. YIKES!
Focusing on the scam-ee borders a little to heavily on victim-blaming in my opinion. Certainly, scamming wouldn’t be a problem if there weren’t scammers going around and making trouble. Some scammers go broad – given the law of averages, the more people you spam via email, the more likely someone will take the bait. But the really scary situations, in my opinion, anyway, are the scammers who are looking for people in vulnerable or tenuous situations. Exploiting someone’s sense of despair or loneliness for personal gain seems like the absolute worst of the worst. And I think it’s a lot more common than I realized.
On a social Zoom meetup this afternoon, my friends Emily, Justin, and Bill made an analogy from discussing romantic scams to nonprofit data and tech. While that might seem like a quantum leap / non-sequitor, I couldn’t stop thinking about the analogy. It stayed with me while I chopped onions, roasted feta cheese, and even cleaned the dastardly Cuisinart. Last but not least, it distracted me while I was reading (RUDE!!!). So… I shut the book and opened the laptop. Clearly, I had something to say.
In my career as a nonprofiteer, I’ve seen organizations fighting the good fight be taken advantage of by tech companies and snake oil salesmen. I’ve wracked my brain to try and understand why. I used to think it was a combination of underdoggism (master’s tools, etc), impostor syndrome, lack of adequate resources, and facing uniquely complex problems. It never occurred to me that mission-driven organizations face a similar dynamic as survivors of romantic scams. We expect our vendors to negotiate in good faith because we have an overall optimistic posture to the world and we are perhaps more likely to be altruistic (or at least, non competitive) people. Many of us are less likely to ask for discounts. We are trusting and convincible, even if tech solutions seem too good to be true, or more brawn than we really need. It’s really refreshing for me to reframe this as an asset about impact-first organizations. It’s reasonable to expect honesty and good results from our tech!
I am thinking about a time a software vendor dramatically oversold a product, including dishonestly adding items to the quote before we signed the invoice. When I complained about the nefarious practice, already thinking about all of the other people who were likely impacted, I was offered the advice “caveat emptor” which roughly translates to “buyer beware.” It’s our responsibility to research and verify these claims, not the responsibility of the vendor to be honest and transparent. This one is a tough pill to swallow for someone who is generally trusting, especially when faced with relentless marketing about the socially progressive values of technology companies. (No need to guess which company here – I’ve been disappointed by quite a few!)
I’m writing a lot about vendors because of my own experiences and the fact that I am politicized/concerned about increasing consolidation of technology companies, and their objectionable investments in racist artificial intelligence, exploiting our privacy, and generally bankrupting society at large. However, I think we should also turn the microscope inward and look at trustworthy data (or not so much?) inside of our own orgs.
For example, I am working on a project to streamline some reports that culminate in inviting donors to a big annual event. The problem is that everyone who runs the report got different results. This, my friends, is a recipe for disaster. So, which contacts should be included in the results? Anyone who contributed this year? Anyone who pledged to contribute? What about people who are part way through their Monthly Recurring Donation, but have not yet fulfilled their pledge? What about people who last gave on 12/31 of last year? Should they count in the next “scoop” of donors to recognize, even though they were technically last year? Questions abound, let alone coming up with reasonable automation to make the calculations go faster, and make the results reproducible – day to day and year over year.
Failing to provide reliable results, well, resulted in (a) disgruntled donors (b) disgruntled colleagues (c) lack of trust in the system to answer what should be routine data questions. We gotta earn that trust back! I could think of dozens of similar scenarios (and I’m sure you can too!) – where either because of lack of clean data, bad tech products, or inconsistent criteria, trust and commitment to the data system begin to erode. It’s a totally natural human process, and sometimes it’s barely even noticeable at first. However, once the distrust gears start to turn, a/b/c get a lot worse very quickly! Even trusting people will eventually give up, especially if we have reason to doubt the validity of a data system, which is pretty easy to do in our culture. It’s generally easier and less destructive to ghost a Match.com profile than to abandon your data system.
I’m genuinely worried about bad data in nonprofits and the impact of bad data on our trust, relationships, and outcomes. So, here are my top 5 tips about how to move forward with increased trust in our data and our vendors.
- Set realistic expectations
As my dad says, “if it seems to good to be true, it probably is!” He also says, “there’s no such thing as a free lunch.” I think you probably get the point by now – if it was easy, it would be done! When salespeople try to market the sun/moon/stars, take a step back and consider what’s at stake. Take smaller, more predictable bites of big problems, and communicate, communicate, communicate every step of the way.
Same is true with internal projects! I try to be very specific about deadlines, send updates early and often, and promise only what I am reasonably certain that I can actually deliver. When we “underpromise and overdeliver” (good rule of thumb on the way to radical transparency, which is my North Star), we are setting up circumstances that promote trust.
- Ask for help before you get desperate
I learned on my romance scam podcast that desperate lovers are more likely to overlook red flags and get into dangerous situations. When it comes to data and tech, I’m a huge proponent of asking for help early and often. (If you follow me on twitter, you can see that I take my own advice!). In one project that really went sour, I wish I had admitted how much I was struggling early on. By trying to be a hero, I got deeper and deeper into trouble and I eroded trust with my team.
Buying data systems is a lot like buying a used car. The sticker price is almost always negotiable – so don’t be afraid to ask!
From the internal perspective, I generally go through a negotiation and prioritization exercise before I make changes to any data systems because I want to get as many colleagues on board as possible.
Whether aiming for compromise, discounts, or improved clarity, a healthy negotiation practice should be part of daily life with you and your data systems.
- Don’t be afraid to phone a friend
In the podcast, I learned that one of the best ways to prevent romance scams was to confide in other close relationships, so that someone knew who you were cavorting with and/or when/where you were meeting up with them.
The same is 100% true with nonprofit data and tech! Never used XYZ Platform? Find someone in your network who has used it and ask for a demo. Same with a new spreadsheet formula, email blaster, website hosting platform, ticketing vendor, etc etc etc. If your friends are anything like mine, they’ll be delighted to show you what the platform is capable of, or introduce me to someone else who can.
- Proceed with empathy
Sometimes we try tech ideas and they JUST DON’T WORK as expected. Sometimes we are deliberately bamboozled (ugh) and other times, there’s just a mismatch in needs/features/skills. Either way, try try try (and I know how hard this is) not to blame yourself. I would *never* blame the survivor of a romance scam, or my own friend who had a terrible data situation on their hands, and I should extend the same compassion for myself. We can’t let impostor syndrome and self doubt win!
I’ve tried tech products that are so farcically bad that I wonder if they are a scam. I have to hope that other people who use them fare better than I did!
I’ve used tech systems that truly make my imagination pop and sizzle with what is possible – but at the same time, I worry that if the ambitious vision is basically not attainable, we are being sold a lie.
It can be really stressful to perform on this tightrope of balancing system abilities with teammate requests, building buy-in while communicating about inevitable disappointments, admitting mistakes and moving the needle all the while toward data systems that are truly worthy of our trust. I think it requires some pragmatism and vulnerability from all of us, which is why I’m so glad that we have this corner of the internet. Thanks for being here.