Disruptive Technology, Data, and the Future of Philanthropy | PEAK Insight Journal
Disruptive Technology, Data, and the Future of Philanthropy

Disruptive Technology, Data, and the Future of Philanthropy

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For most grants managers, new technologies have been a constant across their working lives—so much so that managing disruptive technologies has become part of the routine background noise of their work. We have seen grantmaking processes transformed by innovative software and technology platforms: communication with grantees and foundation staff are fundamentally altered and analytical approaches are applied to our work in new ways. These changes suggest a future for philanthropy that is smarter, faster, and more effective than ever before, with grants managers serving as critical catalysts.

We tend to think of disruptive technology as being, well, disruptive. But such technology usually serves in its first application as a replacement for a legacy system, leaving underlying processes unchanged. Consider the application of the electrical motor to manufacturing. Before the advent of electricity, manufacturing depended on water or steam power. A central steam engine or water wheel drove lineshafts that distributed power throughout the factory using a series of belts, thereby delivering power to individual workstations. The first factories to adopt electrical engines simply swapped water power or a steam engine for an electrical motor, leaving the rest of the system more or less in place. Only when electrical motors were miniaturized and applied to individual manufacturing processes—the lathe, the press, the drill—was manufacturing truly transform and, subsequently, the productivity of manufacturing began to grow dramatically.(1)

endowmentvsstaffgrowth

Improvement Gives Way to Innovation

In philanthropy, the key technologies that have been so disruptive to our daily work lives are the personal computer and the Internet. Even for the simplest processes, like grant modification, these technologies have propelled change. In most foundations, grant modification involves a series of emails, first from the grantee to the grantmaking team, then up through the organization for necessary approvals, with periodic data entry and information logging in grants management systems and online document repositories. The process includes a lot of back and forth at each stage, as information is requested and clarified. A grants manager from 1975 would find the process largely unchanged, with the use of email being the primary difference—no more postal stamps and inter-office envelopes.

Now consider what can happen when new technologies are called on to help redesign the process itself. Instead of starting a grant modification request with an email, a grantee might begin by framing a request for a modification using an automated form on the foundation’s website. Conditional requirements built into the form would ensure that all necessary information is present, eliminating at least some of the back-and-forth between foundation staff and the grantee. The system might also be able to recognize some of the more straightforward modification requests, automatically approve them without human intervention, and update data systems accordingly. For more complicated requests, a workflow process would route the modification through the organization, securing necessary approvals, and updating data systems and document repositories as necessary.

While this is not the typical process in most foundations at this time, it is hardly the stuff of science fiction. As foundations update their data systems and staff gain experience with automation, systems like these will begin to emerge and expand.

Relating Data to Staffing

To get a picture of how well grantmakers have capitalized on technology innovations, consider how staffing has changed at some of the largest foundations. The white line will be familiar to anyone who has studied foundation endowments over the last 25 years. Foundation staffing patterns have gotten less attention, so the black line might be less familiar. Putting them together, though, it’s clear that foundations are doing more with less.

Looking at the issue from a broader perspective, compare foundation productivity with the productivity of the U.S. economy as a whole. Leaving aside the regrettable endowment declines of the last few years, changes in the efficiency of the foundation sector pretty well mirror those of the economy overall.

foundations productivity

Forward Thinking Change

For grants managers, knowing that we’re only beginning to see the truly disruptive side of disruptive technology, trends like these suggest that we have a lot of work to do to transform our roles and avoid falling into irrelevancy. But how?

In the February 12, 2012, issue of The New York Times Magazine, reporter Charles Duhigg revealed how Target Corporation is mining information from their frequent shopper program database:
Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought cocoa-butter lotion, a purse large enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August. What’s more, because of the data attached to her Guest ID number, Target knows how to trigger Jenny’s habits.

Because Target is able to study thousands of shoppers like Jenny and combine its data with information gleaned from demographic databases all over the country, the company can learn things about its shoppers that even close friends and family might not know. What’s more, because Target knows that the birth of a child is a key moment in a consumer’s development of new shopping habits and brand loyalty, they can exploit this information along with the triggers that work for Jenny direct mail, email blasts, a coupon for a free latte to get her to come back to the store and buy new items needed by an expectant mother and, ultimately, a family with a newborn child.

This is the power of big data.

Applying the principles of big data to our grant modification example, we know that industry collaboration is critical, since individual foundations typically don’t have enough transactions to develop independent data models. However, the Ford Foundation processes many grant modifications, more than 1,000 each year. Looking at a few years of data, grants managers can predict which grants are most likely to require modifications. In addition to learning that modifications tend to cluster in particular programs and offices, we also see from the data that grant term and grantee type are highly correlated with the need for grant modifications. One of the best indicators is the length of time it takes a grantee to return its signed grant notification letter.

This was a simple bit of analysis and, while actionable, it is limited in terms of how it might alter our approach to the social change objectives of our grantmaking. But the example suggests that a close look at our data might help us answer more meaningful questions related to the missions of grantmakers and grant recipients:

  • What level of general support grant is sufficient to stabilize a grantee and enable it to achieve significant programmatic effectiveness?
  • What attributes of an organization make it most likely to achieve local or state advocacy success using grassroots mobilizing strategies?
  • What direct services grants in family nutrition are more likely to fall short of expectation?
  • What environmental factors need to be present for a scaling-up grant strategy to be successful?

While we could undoubtedly find any number of consultants who could reason out a hypothesis for any of these questions, almost no one would think to go to the data to review the experience of funders—data is locked away in grantee reports and grants databases not generally open to the public and not calibrated for comparability across funders. As a sector, philanthropy has not yet built the systems or acquired the habits to conduct such an analysis.

Building data systems to answer complex questions will be a challenge. No foundation has enough data points on its own; we will need to combine our observations, a prospect fraught with obstacles of comparability, coding and taxonomy, and cost. Fortunately, nascent efforts to address these problems are already underway. Funders using the Foundation Center’s eGrant and hGrantreporting systems are supporting the critical aggregation of data for sector-wide analysis. Affinity groups are collecting and organizing meticulous data to understand the grant-making landscape of particular fields. At the Center for Effective Philanthropy, a new Strategy Landscape Tool allows funders to work together to understand the relationships between grantmaking strategies in particular places and fields. These are important beginnings.

Today, philanthropy is at an inflection point, as we embrace the disruptive technologies that are transforming our field into a data-driven enterprise. Grants managers have a crucial role to play in fostering the advances ahead: they know more about foundation data sets than anyone else in their organizations and can do more to build robust information sources and promote sharing with other funders.

Leading from Within

Here are six ways grants managers can stimulate a data-driven approach to philanthropy.

  • Look up from transaction processing. Recognize that transaction processing ultimately, if not already, will be greatly simplified by technology.
  • Nurture your curiosity. From time to time, delve into your institutional database and ask it questions about the nature of the organization’s work, grant performance and grantee behavior, and outcomes.
  • Give yourself a new title, Director of Institutional Research. Master the tools and processes that enable your organization to learn from its data and the data of others.
  • Become a coding maven. Use your organization’s coding and taxonomies to categorize grants for comparison and analysis.
  • Start one conversation each month by saying “Let me show you something…” Share what you find with grantmaking teams and foundation managers. Try to make the appreciation of data and inquiry infectious.
  • Connect to data efforts in other foundations. Where possible, connect with colleagues and champion the value of sharing information with affinity groups, the Foundation Center, and funder collaboratives with the goal of building larger and better data sets for inquiry.

By taking these basic but essential steps, grants managers can help their foundations—and the field as a whole—build knowledge that advances social change.

 

(1) 1   I am indebted to David Wessel’s Prosperity: The Coming 20 Year Boom and What it Means to You for this anecdote.

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