In 2021, US companies generated $2.77 trillion in profits—the largest ever recorded in history. This is a significant increase since 2000 when corporate profits totaled $786 billion. Social progress, on the other hand, shows a very different picture. From 2000 to 2021, progress on the United Nations Sustainable Development Goals has been anemic, registering less than 10 percent growth over 20 years.

What explains this massive split between the corporate and the social sectors? One explanation could be the role of data. In other words, companies are benefiting from a culture of using data to make decisions. Some refer to this as the “data divide”—the increasing gap between the use of data to maximize profit and the use of data to solve social problems.

According to a survey commissioned by IBM in 2022, 77 percent of companies reported they were already using artificial intelligence or were exploring how to use artificial intelligence in their business. In contrast, a 2017 report found that only 5 percent of nonprofits were using artificial intelligence, and only 28 percent of nonprofits were using data for predictive or prescriptive purposes. The public sector isn’t much different. While government agencies worldwide face enormous challenges in leveraging their data to deliver services effectively and efficiently, 89 percent of public sector respondents in 2020 said they were unprepared for rapid data growth.

The fact is, we are in a transformative era where the speed of technological advances and exponential data growth has already changed how we work and live. Thus, it is highly plausible that this data divide between the corporate and social sectors could be a key differentiator in overall progress. The same 2017 survey of nonprofits conducted by IBM found that 78 percent of nonprofits with advanced analytics capabilities reported higher effectiveness in performing their missions.

So, if there is such an obvious correlation between data and progress, why aren’t more nonprofits and social sector organizations using data?

Early research to understand the lack of data adoption has primarily focused on the organizational level. This important work has uncovered real barriers: lack of investment capital, lack of internal capacity, cultural barriers, lack of technology innovation, limited access to data scientists, and more. According to IBM’s research, “While these [budget, technology, and talent] barriers are common across sectors, nuances of the nonprofit industry intensify the effects. In the private sector, market forces drive investment in data to stay competitive. Conversely, nonprofits struggle with raising funds for what is considered internal overhead investments, as funding is often restricted to programmatic activities.

Read the full article about the social sector's lack of data by Jason Saul and Kriss Deiglmeier at Stanford Social Innovation Review.