CRM is Dead. Long Live Data!

There’s a new technology solution for nonprofits, one that promises to help deliver and accelerate your mission, understand and reach your constituents in new ways, and help you make the best decisions for your organization’s current and strategic goals based on real data. It will absolutely empower your employees, deliver near-real-time results towards understanding your impact, and help you determine the most efficient allocation of your fiscal, staff, and time resources.

Sounds amazing, doesn’t it?

Just one problem: this is the same talk track that’s been repeated for as long as I’ve been in nonprofit tech, about every new technology, almost like clockwork. That custom database that replaced your Rolodex? Revolutionary! Email? Groundbreaking! Cloud tools and CRM? World changing! The list goes on, nowadays landing on Artificial Intelligence (AI) – Monumental!

For as long as there have been microchips, nonprofits have been subjected to a continuous litany of “go here, do this,” with technology tools, systems, platforms, and strategies. Couple this with the ever-present, “If you just operated more like *real* businesses...” that gets recycled every few years for public discussion, the incredibly damaging “Overhead Myth,” and the perennial efforts by philanthropy to “share power” with grantees, and well, I find myself rolling my eyes a lot these days.

But, it’s equally important to call out that the progression of technology systems and tools is agnostic to many social and political trends, and this is one opportunity to be proactive and set a foundation for the future.

Here's the industry trend that I’m beginning to track in my conversations with a number of nonprofits and their leadership teams:

• Divest data delivery structures (such as CRM) from the literal data that organizations are collecting; 

• Stop dealing with constant promises that by centralizing data into specific CRM solutions organizations will open a new world of understanding of themselves and their constituents; and,

• Start thinking about how the data itself can be better positioned to do the heavy lifting that organizations have been promised by myriads of databases, cloud applications, and CRMs.

The vehicle by which this is delivered is data lakes and warehouses (I’ll shorten this to “data hubs” from here out for the sake of brevity) – themselves rapidly emergent technologies that store unstructured and structured data, respectively. Just like every new technology, it has its own learning curve and adoption cycle, though one key difference is that organizational staff should be experiencing the outputs of these, with the expectation that they participate in identifying and clarifying the inputs.

Data hubs aren’t exactly adopting a brand-new system – in fact, the organizational technology entity diagrams I’ve seen frequently place data lakes/warehouses at the receiving end of data from multiple existing systems and applications. Hence, my observation that data is the hub of modern operations, slowly and steadily inching out CRM, which has not lived up to the promise of data centralization for action.

There’s a lot to geek out on here. From the perspective of technology administration inside an organization, this means that the constant drive to ensure all of an organization’s systems are fully integrated with each other to produce reporting results and outcome measurement is alleviated. My volunteer system doesn’t need to integrate to my CRM so long as both integrate to a data hub. My CRM doesn’t need to do every single centralized function of transaction processing, programmatic support, and donation tracking in so long as it receives the right contextual outcomes from a data hub that does this work first or gets this information from other sources.

It substantially revises a question I’ve asked organizations for years as a consultant:

“Do you actually need to report on or do something with this information, or just see it inside your CRM?”

The answer to both for a very long time was “yes,” largely because many of the other systems that were being deprecated by CRM were some version of terrible at even making data seen in the first place, let alone actionable.

We’re now entering an era when the new question we should be asking is

“How do you need to act on this data?”

for every single tool and system an organization adopts. The idea that there would ever be one application or platform to proverbially “rule them all,” was perhaps always a myth, because at some point two things were true: either the systems themselves were extensible to a fault, and therefore data got put into them that started to become square pegs in round holes; or, the owners of these systems promised they could “do it all” in the sales cycle, and once they were handed off to an impact organization, a series of add-ons were needed to make this promise come true: more licenses, more analytics tools, more storage, whatever. I’ll also add that for a long time, there were no alternatives.

Let’s acknowledge that impact organizations themselves are generally pretty adept at knowing where they want to go for their constituents, and doing so in ways that balance everything from major donor relationships, grant applications and reporting to multiple levels of Byzantine systems, and everyday fundraising, operations, and programmatic activities. What breaks down, every single time, is the literal disconnect between a corporate sales cycle and our commerce-driven economy, and the timelines necessary for mission-driven work to achieve lasting results. So, when nonprofits are presented with a new technology solution, they make an investment in dollars, but what’s behind this is a calculation of time: How much more time will be necessary to learn a new solution, adopt it across a staff that lasts, on average, 18 months to two years, and keep it maintained when whatever consultants that presented it to them depart? Time and again, diving into nonprofits adopting CRM solutions, folks who are already time and resource constrained choose the Devil They Know (generally spreadsheets) over the New-New.

Change for anyone is hard, and for nonprofits it can be even more so. Technology alone won’t save anything. It’s how a culture of practice is created around technology that matters, and the values that this culture places at its center. When we’re implementing technology for nonprofits, we’re changing culture. Or at least I hope we are, because the alternative is a promise of a Panacea of solutions that merely extracts consulting and licensing dollars and leaves the door open to do the same at an indeterminate period of time later.

The promise of data hubs is a rethinking of both organizational culture and data administration.

If data administration becomes a technically focused role designed to distill the properly matched datasets from multiple inputs into a data hub, and from there produce what are called golden tables (deduplicated and source verified matched data), that drive analytics, then the person serving in the role of “CRM Admin” is alleviated these challenges inside the CRM itself. If organizational culture demands the use of specific tools and systems, frequently redundant with each other across large organizations, then we can better meet staff where they’re at by keeping them rooted in systems that serve their needs while rethinking the ones that don’t. We don’t need to change everything, all at once, to adopt a new CRM’s ecosystem of integrated applications, we just need to let go of what isn’t serving us. Data hubs change the conversation about how organizations can adopt cloud technology.

Add in the hyper-accelerated evolution of AI tools and systems, which can help organizations both make sense of large volumes of their own data on the front end, meaning deduplication and hygiene, while spotting trends in it for predictive outcomes, and it opens up a new modality for how impact organizations can consider their technology tools and systems. A colleague and friend, Derek Drockelman from ROI Solutions, picked up on my (re)post of an old LinkedIn article and added his own assessment of this new world.

This is the beginning of a new signal over all the noise. Derek is correct, we are very much at an inflection point, and we will be talking about it more at the upcoming NTEN NTC. The strange and wonderful thing about working in technology is that the advent of these inflection points are sometimes correlated with, and sometimes the product of, massive amounts of social and cultural change, writ large. Sometimes, they even create them, as is the case with AI.

What are impact organizations to do with yet another discussion of a new, revolutionary technology? It’s important to call out that this is taking place in a larger context of extreme pressures on the Impact Economy: nonprofits, the businesses that serve them, and many staff and stakeholders are directly affected by the erratic, and occasionally vindictive, targeting by the Trump Administration of funding sources, operational parameters, and their efforts at inclusive service. We are a country in crisis, and nonprofits are now on the vanguard of experiencing this crisis. I’m making note of this because my perennial enthusiasm for adopting new systems and strategies to the Impact Economy is substantially dampened by my fears of the severe democratic backsliding that we’re now experiencing. The current crisis that many American nonprofits feel is one that I suspect will last for the duration of the Trump Administration, and yes, it does create its own urgency, need to act, and rethinking of organizational data – this is my own hypothesis from December.

So, when I make a post on LinkedIn, or in this case, a post that resurrects and further enumerates on something I wrote four-and-a-half years ago, that proposes a major structural change to how organizations should consider their data and technology, it’s because I’m seeing an opportunistic throughline through a lot of noise that could become its own signal.

While you’re acting with your data and technology, consider this: do you want to act in a way that replicates the journey of your past, or puts a stake in the ground to the future? This is the promise of data hubs for your organization, and one that necessitates its own development of best practices, thought leadership, roles, systems, and structures for impact organizations. In the meantime: Nolite te Bastardes Corborundorum.