Every team needs great reports. Successful and effective reporting is essential to advancement efforts. Your team’s report framework may be different than others, but you should have some set principles. I’ve written about the critical importance of great reporting for operations efforts.
A simple way to determine if your team’s reporting environment works is to determine if it is FACTual. In this approach, reports should be:
- Formatted. Users trust data (and experiences overall) that are consistently delivered. Just as a brand promise helps ensure that, say, every Coca-Cola will taste the same as the next (and apparently make the consumer happy), the report consumer should trust the facts and understand the familiar formatting.
- Accurate. Users must receive accurate reports. In addition to reports relying on tested programming to yield consistent results, “accurate” reporting also requires that all users share common definitions and understanding.
- Complete. Reports (and the reporting environment) must contain all records and details expected by the user and defined in the parameters of the report. This principle requires that data be reported from a central, comprehensive source.
- Timely. The ideal reporting environment requires that information be readily available. In the absence of timely reporting, many offices will resort to highly inefficient, hybrid reporting solutions that increase room for error and inconsistent formatting.
Want to see how your reporting environment stacks up? Check out my “confidence calculator” to test whether your reporting environment is FACTual.
The trend toward online, and more specifically, mobile direct response fundraising continues. My colleague and mobile strategist, Molly Kelly, blogged about this very point recently (click here for Molly Kelly’s Mobile Donation Form Blog). Of course, big campaigns are still won with the biggest of gifts. However, if you’re strategies aren’t engaging 20- and 30-somethings who are immersed in mobile access and apps, your current participation rates and future campaigns will suffer.
If you’re having a challenge getting investment into mobile technology, take a look at Molly’s piece. Mobile donations: no longer a fad; they’re a fact!
An interesting visual depiction of spurious correlation (check it out here) reminded me of my grad school days and the rigor with which I would build hypotheses. Rather than let R, SPSS, or Excel correlate away and then proclaim some amazing finding, I started from the reasons and results I expected to validate with data. The difference is, all too often, that the former approach tells you very little due to endogeneity, spurious results, and the lack of context.
Some organizations–Google is known for this–will say “don’t worry about the why”. Some have referred to this approach as “theory-free“, a nice euphemism to indicate how little long-term value we might find in these correlations. Now, for consumer behavior where Big Data is truly present perhaps this works. But, data points are rarely available for nonprofit analytics in the same way as, say, Target and Wal-Mart have data…although there are new options underway, like David Lawson’s newsci.co.
And, if you talk with a gift officer who’s been disappointed with predictive modeling results, you see a different picture. From that vantage point, the analytics results are frequently devoid of context. The result confirm what we already knew (“these prospects look rich! they live in a nice neighborhood!”) or reflect a pattern we already see (“they gave last year! let’s ask them again!”). Yet, modeling doesn’t typically improve relationships with prospects.
A big culprit: Context. Donor context is critical in building relationships. And, context is quite challenging to incorporate into modeling. The following are real examples of discussions about potential prospects surfaced by a context-free model:
- “Sure, Jane looks promising, but we don’t have a phone number to reach her and no volunteer connection, so how likely is it she’s approachable?”
- “Absolutely, Ed looks great, but did you know he just filed for divorce?”
The solution to this issue isn’t to cast off analytics. It’s to improve it. Start with and add in theory. Guard against spurious results. Don’t elevate an endogenous variable as meaningful. And, most of all, our industry needs resources that can actually add context to results. As a student of philanthropy, I am anxiously awaiting the time when our new science of analytics better delivers on the hype and improves our understanding of donor behaviors, while avoiding endogeneity and spurious results.
In the last few weeks, I’ve been interviewed regarding trends in our industry’s technology sector and how this will affect the future of fundraising. We have a challenge: we don’t have the funding for the technology we want to use for fundraising. It’s a market issue. At the same time, we are faced with changing trends among 20- and 30-something donors, new, innovative, and possibly disruptive technologies, and a concentration and transfer of wealth that’s nearly unique in human history.
Have a look at this article in TechTarget to get a sense of how our industry is shaping up. And, be on the lookout for additional posts on these vitally important topics.
$1 Billion Reasons You Can’t Always Get What You Want.
$1 billion–it sounds like a lot, doesn’t it? But, we have a problem: fundraising technology demand (in the form of fundraisers’ expectations) is much greater than fundraising technology supply (in the form of vendor offerings). Put another way, our industry’s annual $1 billion fundraising technology budget doesn’t get us what we want.
This demand derives from consumer experience. On our way to work, we all have computers in our pockets and access to billions of dollars of free technology, software and online experiences from the likes of Facebook, Amazon, and Google. Then, we clock in, boot up, and, voila…1997 is delivered by our 6-year old computers. We suffer from what I call the iPhone problem: we want work resources based on our consumer experiences, but these are far too expensive to replicate given our fundraising technology market and budgets. It’s relative deprivation at a high, costly level. It results in wasteful workarounds, decentralized data and systems, and dissatisfied end users. And, in the end, these things keep us from raising more money.
Why are we in this predicament? The short answer is there is not enough incentive to supply great fundraising technology that matches consumers’ expectations. Why don’t we have enough incentive? That part is a little more complicated. One might charge (as I did in February) that our industry is hamstrung by narrow thinking around investment. Another might suggest that, while the industry appears quite large, it is unsophisticated and relatively immature. A third might notice that our industry isn’t really large enough as a market sector to warrant the kinds of innovation our colleague-consumers would like.
All of these observations inform the infographic above, which depicts the problem: we are a $300 billion industry per annum that can only spend about $1 billion on technology each year. When we consider how much fundraising is done without the benefit of technology (referred to here as “plate and gate” efforts that reflect more grassroots, manual efforts prevalent in certain religious organizations and new and smaller nonprofits), then calculate what we get to spend, then determine where we get to spend it, the market just isn’t that big because our budgets are so small.
Of course, there are some exceptions. Leading software providers do their best and it is, frankly, often good enough. I’ve helped organizations leverage nearly every fundraising system and they are all passable. These systems collect addresses, store gifts, provide institutional memory, and support programs. Are they efficient and user friendly? Not particularly. Are their add-ons, such as reporting tools and online functionality, what we’d like? Not usually. But, behavior and poor user adoption are often bigger problems than the technology itself.
The issue is not with the core functionality supplied by the market; these tools do what is “necessary”. However, they tend not to deliver on what we define as “neat”. What’s “neat” is shaped by what Apple, Google, and a bunch of other billion dollar corporations bring to the market. It feels like we are destined to have a large gap between demand and supply.
While it’s unlikely you will be able to re-direct the market’s “Invisible Hand”, there are three steps that can help:
- Manage expectations. You need to persuade your users that you don’t get to invest like a Silicon Valley start-up, so the tools are a little less nifty. But, they still (should!) work. Convince team members that what you have supports their programs or make commitments to better align what you have with current needs.
- Illustrate value. Where you see a gap in programs or productivity because of a lack of functionality, quantify the real and opportunity costs. Are donors failing to complete online transactions because of poorly designed forms? Are reports re-worked in Excel at the cost of hundreds of hours a year that could be focused on new donations? Show how the gap deserves to be filled with better technology.
- Do-It-Yourself. Out-of-the-box solutions will solve some needs, but not all. You may need to partner with specialists and experts to address an opportunity that vanilla systems can’t handle. The market for innovative solutions in between and beyond core systems functions may be in reach, but the same vendor that delivered the vanilla solution may not be able to deliver the customizations you need.
Our industry is trapped in a Catch-22: to get funds, we need appropriate technology, but we can’t get the technology we need without these funds. Or, more simply: $1 billion isn’t enough. The fact remains that many of us will have to make the most of what the market has to offer. Those of you with means and vision to implement more custom solutions will likely need to create your own solution when expectations are high and ROI is clear.