SSIR Winter 2023 Supplement

Smart Nonprofits

BY BETH KANTER & ALLISON FINE

The digital revolution that began two decades ago enabled organizations to share information and communicate with large numbers of people over vast spaces quickly and inex pensively. However, this digital connection and the imme diacy it afforded came with a huge cost: the erosion of boundaries between work and home life, resulting in the demand for the always-on and always-connected worker. We are encumbered by the endless, daily battle of email whack-a-mole. Statistically, American workers check their email on average 74 times a day.

A new chapter in digital technology is emerging that operates very differently from the previous generation of digital tech like email and social media that made life faster—but not necessarily better—for workers. It will free workers from the time-consuming, rote tasks that take up 30 percent of staff time. This newly freed time provides nonprofit workers the opportunity to pivot to building relationships, sharing stories, and solving big problems. In other words, workers will be able to spend much more time on meaningful work and less time on busywork.

In our new book, The Smart Nonprofit, we define this next genera tion of “smart tech” as the universe of technologies that includes artificial intelligence (AI) and its subsets and cousins, such as machine learning and natural language processes, that all rely on cloud computing. These technologies—rather than individuals—use Library of Congress-size data sets to find patterns and make deci sions for people. Current commercial applications are being used by organizations to screen resumes, answer frequently asked and fact-based questions (e.g., “What time do you open?” and “Is my donation tax deductible?”), automatically update budgets, organize meetings, and research donor prospects.

The purpose of using the technology in organizations isn’t to do more, faster, but to free people from time-consuming tasks and create what we call a “dividend of time”—the surplus of time that is produced from having smart tech replacing basic, repetitive tasks. This new time can be allocated for tasks and activities that only people can do, such as building stronger relationships and solving problems. Or, this dividend of time could afford us the ability to pace ourselves and our labor for our personal benefit and for the benefit of the work we produce.

The articles in this series exemplify how next-generation nonprofits are employing cloud-powered smart tech to improve the quality of their work and their staff’s lives. For example, Share Our Strength,

Beth Kanter is a thought leader in digital transformation and well-being in the nonprofit workplace, as well as a trainer, facilitator, and author. She has more than three decades of experience in designing and delivering training programs for nonprofits and foundations.

Allison Fine has written four books on using technology for social good, including The Networked Nonprofit and The Smart Nonprofit with Beth Kanter.

an organization dedicated to finding solutions to poverty, uses this tech to gain insights for fundraising. The nonprofit and renowned art museum the Barnes Foundation relies on it to make art educa tion more accessible to all. And charity: water, a nonprofit dedicated to providing clean water to developing nations, uses smart tech to facilitate their processes in order to make clean drinking water more reliably available. A common factor uniting the nonprofit efforts enumerated in this supplement is that each has an organizational leadership that understands why, where, and when to use smart tech.

COBOTTING

In addition to program delivery, smart tech applications are avail able for every department, from communications to accounting to service delivery. Efficacious use of this technology requires a deep understanding of what it is and does, in addition to careful, strategic thought on how to incorporate it into an organization in a way that generates the best out of the technology and people. This comple mentary dynamic is called cobotting. There are aspects of labor that are suitable for automation, such as cutting and pasting data from one spreadsheet to another and analyzing huge data sets. But few, if any, can or should be com pletely replaced by smart tech. What automation can improve is the experience of work. Rather than doing the same work faster and with fewer people, smart tech creates an opportunity to redesign jobs and reengineer workflows to enable people to focus on the distinctly human parts of work that are especially critical to the missions of nonprofits.

Cobotting takes time and care ful implementation. And when it is done well, the benefits to staff are enormous. A 2021 MIT research study found the benefits of implementing AI extend beyond efficiency and decision-making: More than 75 percent of staff see improvements in team morale, collaboration, and collective learning. These profound cultural changes indicate what can be gained from the strategic and deliberate implementation of smart tech. As chief global officer of charity: water Christoph Gorder explains in his article, a culture that embraces the use of smart tech requires an understanding of both the opportunities and risks of using it.

Making the transition to smart tech requires leaders to dig into the implications of automation and make ethical choices about using smart tech to bring out the best in workers—not to replace them. This is why we believe so strongly that using smart tech well is primarily a leadership—not a technical—challenge. Success of smart tech integration requires that nonprofit leaders ensure that their organizations are:

■ Human-centered | Always ensure that people come first. This means that workers are trained to understand and use smart tech

Cloud-powered smart technology liberates resources so that organizations can focus on the work that matters most.

Smart tech creates an opportunity to reengineer workflows to enable people to focus on the distinctly human parts of work that are critical to nonprofits.

well, and outside constituents know when and how they are interacting with smart tech and not directly with people.

■ Knowledgeable | The impact smart tech is too far-reaching to sequester to the domain of the IT department alone. Leaders in the boardroom, the C-suite, and on staff need to understand what smart tech is and does. Once automated systems are in place, leaders need to be vigilant about whether the technology is performing as intended or whether unintended consequences have arisen, and how clients and end users ultimately feel about those systems.

■ Reflective | Leaders must understand when and how bias is embedded in the data or the algorithms used to analyze that data. They don’t need to be engineers; rather, they must be criti cal minded and question the assumptions that lie beneath the code and the origins of the data set. A thoughtful, participatory process is required to select values-aligned systems, vendors, and consultants. In particular, smart tech systems—because they are created by humans—can have racial and gender biases built into them. It is incumbent on organizational leaders to investigate how biased these products are and to take the lead in mitigating their potential harms.

GETTING STARTED

The adoption of smart tech by companies is skyrocketing. This trend is a result of the lowering cost of the technology in conjunction with the increase of commercial applications. The technology that only NASA had available a few years ago is the very same that museums,

NGOs, and nonprofits of all sizes can use today. This means that smart tech is becoming a core component of not only what organizations do but who they are

Here is a brief overview of how your organization can begin to use smart tech:

Identify pain points to determine the right use cases. | These should focus on areas where smart tech can take over rote tasks that can streamline unmanageable workloads and reduce worker labor and stress. Outline exactly which tasks and decision-making will be retained by staff and which tasks will be automated when the system is implemented. This includes identifying how automation will be supervised by someone with subject matter expertise.

Choose the right smart tech for the job. | Make sure the product or system you choose will create the right cobotting balance. Work to guarantee that the assumptions built into the smart tech align with your values. Additionally, ensure that the tasks that require empathy and intuition will be assigned to people while tasks such as data entry or multi data-set analysis will be assigned to smart tech—and not the other way around.

Create a virtuous cycle of testing, learning, and improving. | Step carefully and slowly, because it can be difficult to undo the harms of automation once smart tech is operational within an organization. Pilot the new system and workflow to test assumptions and objectives.

Cloud computing and smart tech have the power and potential to enable us to turn the page on an era of frantic busyness and scarcity mindsets. We are entering a new era in which nonprofits will have the time to think and plan—and even dream. ◆

Cloud Transformation

A road map for your nonprofit’s sustainable, digital future.

BY ALLYSON FRYHOFF

It was impossible to imagine a nonprofit using the same advanced technology as the world’s largest corporations twenty years ago.

But cloud computing—the on-demand delivery of IT resources over the internet with pay-as-you-go pricing—has made the impossible possible. With the cloud, nonprofits have access to the same innovative technologies available to for-profit companies, and they can leverage those technologies to increase their impact.

Getting started with cloud technology can be daunting for nonprofits with limited resources and staff. A 2020 Salesforce report found that the vast majority—85 percent—of 725 nonprofits surveyed said that tech nology is critical to their success. However, fewer than one-quarter—23 percent—had a vision and long-term strategy for how technology would be incorporated into their organization and programming.

Nonprofits looking for an entry point into their cloud journey can turn to AWS to over come barriers to technology adoption and enhance their mission outcomes. AWS has more than 15 years of experience partnering with nonprofits. While each cloud journey is unique, AWS has found that organizations are most successful when they approach this process in four steps:

Envision | In this phase, your organization defines its goals for the future by determining what problems need to be solved to advance your mission, and why. Some possible answers might include better efficiency, cost savings, or more access to innovative technology, tools, and services.

A lack of funding results in a nonprofit’s inability to deliver on its mission. So, if your objective is to enhance fundraising, some potential goals might be to build better donor management, generate personalized email campaigns, or create dashboards that track the impact of donations. AWS recommends that you assign each goal to a senior leader who is capable of driving change when road blocks are encountered.

One successful example of the envisioning process is EB Research Partnership (EBRP),

a nonprofit dedicated to funding research aimed at discovering treat ments and ultimately a cure for epidermolysis bullosa (EB)—a family of life-threatening, rare genetic disorders that affect the skin. A pervasive issue for EB patients and their families is data management. Patient information and medical research are siloed, meaning researchers and individuals have a hard time accessing current information on the disorder. EBRP’s leadership determined that one of their objectives was to use cloud tools to combine this data together on one platform, making it easier for patients and their families to access educational resources and connect with other patients, doctors, and clinical trials. This led EBRP to build a cloud-based platform that guides patients to the nearest doctors, research studies, treatment clinics, trials of new drugs, and patient support groups—similar to the way that GPS navigates you to your destination.

Align | Once your organization has identified the purpose of its cloud journey, you can direct your efforts to encouraging your stakeholders to align on this vision. Alignment is often the most challenging part of any cloud journey because it requires people to change how they work. Identifying gaps across the organization can help build alignment. For instance, do you have the right skill sets in house? Do you have existing contracts and licenses to consider? All stakeholders, no mat ter their role or contribution in the cloud journey, should be included in this phase. By involving your full team and identifying their concerns from the start, you’ll help stakeholders understand that their input is

valued and that they have a stake in the success of the cloud journey. This process also helps to build trust among all involved stakeholders.

The Urban Institute, a nonprofit research organization that provides data to advance upward mobility and equity, wanted to make data-driven decision-making easier for people. In 2016, they began transferring their data from an on-site data center to the AWS cloud, which has enabled them to run sophisticated data analytics and microsimulation models with flexibility, speed, and accuracy. By leveraging the AWS IMAGINE Grant—AWS’s public grant that offers nonprofits money, computing credits, and tech support—the institute built a demo of a cloud-based data hub that helps policy makers and researchers use local data sets for policymaking. To ensure a successful rollout, the Urban Institute knew they would need to identify areas of skill building on their team. They utilized free AWS training opportunities, such as the Developing Serverless Solutions and Architecting on AWS courses, to train their staff. By increasing their cloud knowledge, the institute was able to launch their cloud efforts with confidence.

Launch | Experimentation defines this phase: identifying a specific challenge, working with your cloud partner to design a solution, and building a pilot. The pilot should have clear goals and metrics to help you determine when you are ready to scale, or if any improvements are needed. All experimentation should tie back to specific goals—and focusing on your original goals will remind you to not lose sight of the bigger picture.

For example, PATH is a nonprofit on a mission to end homelessness in California. Before using cloud infrastructure, their case managers had to manually sift through market-rate listings in newspapers and online, which increased the time it took to find high-quality, affordable housing for clients. Beginning their work with AWS in 2019, PATH built a mobile application that automatically pulls in real-time information on properties in the area and filters for clients’ housing preferences and special needs—drastically reducing the time it takes to get clients into their rental units. Before launching the app, PATH created a pilot program to test the app’s functionality before scaling it to address the needs of the larger homeless population in California. PATH tested the app in Los Angeles, used their learning, and later launched the app in additional cities.

Scale | In this final step, your organization is ready to expand your pilot and run your cloud applications at full scale. To ensure you’re see ing returns from your investments, you’ll want to continuously measure your progress against your original goals. The first project is always the most difficult as your team begins building the organizational muscle to do new things. But once you begin, you’ll find other opportunities to automate tasks that were previously time-consuming and manual.

About five years ago, the Los Angeles LGBT Center established a cloud contact center to provide community health services at a lower cost. Compared with a traditional contact center, a cloud-based contact center can be staffed by employees working remotely and allows for easy scaling up to support an increase of customers. When COVID-19 hit the United States in 2020, the nonprofit orchestrated a live telethon to raise funds to help some of the most vulnerable people in Los Angeles. To support the atypical increases in calls received, they scaled their existing cloud-based contact center to support the greater call volume and, as a result, were able to raise nearly $1.3 million for their cause.

As all the examples demonstrate, moving to the cloud is not a one-and-done transformation but an iterative approach of building momentum and learning from experience. Think of these four phases not as rigid steps but as a future-oriented, gradual progression. ◆

Data-Driven Crisis Analytics

BY CAROLYN FLOREY

In the humanitarian aid community, research methods have tra ditionally skewed toward the qualitative: Participant interviews, focus groups, and field surveys have been the predominant tools determining context-specific interventions. With advances in data science, however, aid organizations have been able to supplement these evidence-driven methods with quantitative ones.

For global humanitarian NGO Mercy Corps, supporting com munities affected by crises is just the first step. Finding the means to sustain livelihoods and become more resilient to future upheaval requires longer-term, more complex and dynamic solutions. What a humanitarian organization like Mercy Corps needs, then, is the ability to gather information and data as well as the ability to synthesize and analyze the data in a continuously evolving environment.

Mercy Corps is committed to investing in and improving our capac ity to apply quantitative data to drive program processes, impact, and scale. This approach extends beyond our work in crisis analytics and immediate humanitarian response to medium- and longer-term pro grammatic design and implementation. Through our 10-year global strategy, Pathway to Possibility, Mercy Corps has committed to be an evidence- and data-driven organization that will first focus on the foundational components of people, culture, structure, and systems as the groundwork for an overall strategy. We now know that proper collection, processing, and analysis of large amounts of data have the potential to improve our programs around the world.

When it came to finding the right technologies to accomplish such complex tasks, it was essential to our success that we had the dedi cated resources and strong partnerships. Internally, our technology for development team helps our program teams leverage technology to improve their performance and quality. We also have a global crisis analytics team dedicated to in-depth analysis to support our humani tarian operations in the world’s most complex operating environments.

Externally, partnering with AWS has allowed us to leverage cloud architecture and products to facilitate advanced data storage, shar ing, and analytics, as well as to have a thought partner with a vision for transforming the humanitarian and disaster-response sector. Designating ownership, leadership, and staff across both organizations, furthermore, allows us to take more risks in data-driven transformation.

A BLENDED APPROACH

“Crisis analytics” is the umbrella term used in the humanitarian sec tor to describe how an organization generates, aggregates, and ana

Mercy Corps has paved a new era of innovation with cloud-driven programming that fully grasps the complexities of humanitarian emergencies.

Carolyn Florey is the senior director of technology for development at Mercy Corps. She has previously worked at the World Bank, United Nations Foundation, and the United States Agency for International Development.

lyzes data to improve time-sensitive decision-making. It can aid us in understanding complex contexts where crisis occurs at the nexus of political conflict, climate, and economic turmoil. While it is typical of our sector to explain these crises qualitatively, the dynamic inter actions between sectors in the communities we serve require more focused, quantitative analyses. Through our work with AWS, Mercy Corps has sought to embed and build data science as a core practice, focusing on designing cloud architecture for agency-wide crisis and climate analytics. Specifically, Mercy Corps expanded our use of crisis analytics to strengthen and deepen our capacity to use quantitative data curation, collection, and analysis.

The strategy has already shown tremendous promise, particularly in our work in Syria, where we employed this new blended approach. Using qualitative methods, we performed informant interviews with those who had critical insights into what was happening in the nation. Teachers, business owners, and doctors created a picture of how the financial crisis affected their daily lives. Because of the high volatil ity of currency exchange rates, we added economic forecasts to model the affordability of essential goods and inform our country team about potential price fluctuations. The country team then used this information to plan for inflation. It was through quantitative methods that price affordability could be forecast to improve programming, as households dealt with shocks to their financial and food security.

To assist in this work, Mercy Corps has crisis analytics teams in 11 countries. These analysts aggre gate and analyze data to improve decision-making in crisis situations. At a global level, the teams identify similarities across operations and apply both quantitative and qualita tive data collection and analysis to understand situational challenges. For example, currency fluctuations can have harmful effects on household consumption and food security, threatening livelihoods and economic growth. Using Syria as a first test case in leveraging cloud technology, Mercy Corps developed a platform for price forecasting, a model that provides lessons that can be replicated in other geographies with similar challenges. Because of similarities in process and in situational challenges, our experience leveraging cloud technology for price forecasting in Syria provides lessons others can apply to increase their impact.

Based on our early success with this process, we have learned that a precise data collection strategy—especially the introduction of auto mated solutions for collecting, cleaning, processing, and integrating data from several sources—is a crucial first step. Ideally, this process includes a component that incorporates a country-specific under standing of data trends, patterns, and anomalies. This data strategy should also include processes and principles for secure data storage. An organization employing this strategy will also benefit from thinking about the data analysis that needs to take place through visualizing, analyzing, and interacting with data.

In working to support our crisis analysts, we discovered that we needed to tackle the challenges of data management across a large, global organization. To do so, we needed to build a cloud-based, datascience practice to bring together fragmented data from around the world into a shared space.

This transformation from a largely qualitative approach based in literature and field interviews to one that incorporates data and fore casts has opened a world of possibilities for our humanitarian work. It has accelerated our ability to scale solutions for entire communities and regions based on analysis of real-time data, including the afford ability of commodities such as bread, meat, fruit, and vegetables in different zones in Syria.

FORECASTING AFFORDABILITY

To test this new approach, we embarked on an experiment to model people’s ability to afford their most basic needs amid erratic price swings and cur rency instability in Syria. Since late 2019, the price of a food basket—the monetary threshold required for a family to meet its nutritional needs—has increased 250 percent. The concept of a food basket allows organizations to gauge how much they need to spend to provide support to families. The affordability of the basket is determined by wages and costs. When costs rise faster than wages, people must work more hours to afford the basic necessities. The basket becomes unaffordable when families are unable to work enough hours in a day to afford their minimum needs.

The ability to forecast wages and the price of a food basket over a three-to-six-month period is critical information for humanitar ians, who must allocate limited resources efficiently. In this case, this information was lacking. Relevant data available to our team was fragmented, varied across formats, sources, and quality, and the col lection was often inconsistent.

Mercy Corps worked with AWS to design a cloud-based approach to aggregate contextual data into a shared space, making it possible to access normalized data (i.e., data that has been standardized across all records) about the economies, populations, conflicts, climate dynamics, and food security in Syria.

For our Syrian test case, we were able to pull data into the cloud from two different sources: the World Food Programme’s Global Food Price data-set website, which is hosted by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) Humanitarian Data Exchange; and a second set of internal data on individual mar kets compiled by a Syrian analyst. With AWS, we built a model that analyzed historic patterns of commodity prices and forecasted their affordability in just four months. This work leveraged cloud-based predictive analysis tools to better understand future cash flows for food security at the household level.

This model predicted the price of food basket items with an aver age accuracy of 88 percent. This ability has helped our Syria team to better target emerging crises and use data-driven information to advocate, plan for, and implement programs and interventions such as increasing supply-side production methods to encourage domestic production to protection programming around coping mechanisms (like skipping meals) taken up by households.

Our Syria experience shows that when looking to apply cloud technology to crisis analytics, narrowing the scope to a clear use case leads to the best results. We are currently expanding this approach to more than 40 countries. We did not attempt to build a top-down, organization-wide data model to address every challenge. Instead, we

The promise of data-driven crisis analytics allows us to reinforce what our experts see and experience with large-scale, realworld supporting evidence.

took the approach of working backward from a single challenge and asked how we might predict the number of people who would need humanitarian food aid in Syria.

From the insights gleaned from this case study, we pursued data projects with other teams encountering challenges or data-analysis needs that could benefit from cloud technologies and predictive analytics. Over time, we have developed a broad understanding of the common data needs of our teams.

LESSONS LEARNED

Data science and cloud technology are providing Mercy Corps with powerful new tools to balance qualitative and quantitative evidence. As we have developed our understanding of our organizational data needs, we have learned three important lessons:

■ Identify narrow test cases and build a foundational, small core team to develop the data pipelines that service those cases.

■ Staff the analysts as geographically proximate to the problem as possible. Data have country-specific patterns. Keeping analysts as close to complex problems as possible enables faster learning and greater adoption of new models.

■ Leverage existing cloud tools before building new ones. Experimenting with standard services that minimize development costs helps proto type the systems that follow in later stages of the maturation curve.

Since our Syria study, Mercy Corps has sketched the data-science infrastructure necessary to scale our analytics efforts. This work has focused on two milestone projects: a data catalog standardizing our data pipelines, which has enabled us to build a shared data catalog where analysts can access data sets from more than 40 countries, and modeling infrastructure that uses cloud-based machine-learning tools to analyze historical trends and forecast probable futures.

We expect this work will make Mercy Corps programs more effec tive at the junctures that often matter the most: anticipatory action and adaptive program management. The promise of data-driven crisis analytics allows us to reinforce what our experts see and experience with large-scale, real-world supporting evidence. It means that we can determine if what we perceive about a crisis situation is in fact cor roborated by data-based evidence. The data also allows for broader, more effective applications of humanitarian assistance. Because of the power of the data and analytics tools, we can do our work with more confidence and efficiency. We are now able to uncover and gather facts in an organized way to illuminate crises and trends. With this data-driven approach, Mercy Corps is effectively using information to advocate for resources and programming.

We have recently implemented cloud-based solutions gathering, analyzing, and modeling data about the economic crises in Yemen and Lebanon, as well as the ongoing political and military conflicts in Lebanon, Ukraine, and the Democratic Republic of the Congo. We also continue to explore modeling strategies. For example, we are currently developing a system-dynamics model that illustrates the complex nature of environmental, economic, and social factors in livestock systems in Somalia, where one out of three cattle have died since mid-2021 due to severe drought.

Mercy Corps will continue to approach crisis analytics in ways that create faster, more precise, and more powerful effects with the help of cloud services. We are committed to data sharing within the broader humanitarian community to better coordinate our efforts, as well as sharing our best practices and lessons learned so that we can contribute to the strengthening of data-driven transformation across the sector. For organizations thinking about developing a data or analytics strategy, it’s important to see the potential value of data for your mission, and then take the leap to commit. ◆

Data Lakes

BY RICHARD KOSTRO

Technology has afforded nonprofits access to a tremendous amount of data to raise revenue, run their operations, and pursue their mis sion. But access is not the equivalent of understanding the full story that data can tell.

It is easy for organizations to make sense of their data when they only have to deal with a few data sets. However, the process becomes more difficult when additional data sets are added, particularly when those addi tional data sets come from tools purchased from different vendors and that have their own unique data structure. When this hap pens, traditional spreadsheets and databases are insufficient. Simple databases can crash under the weight of too many users, and large, complex spreadsheets with thousands of lines of embedded calculations can freeze or run maddeningly slow.

Fortunately, data lakes allow users to store, manage, clean, transform, and analyze different data sets in one place. To be clear, a data lake is not a data warehouse—the main difference being the order in which data is loaded and transformed. Traditional data warehouses require data to be transformed first, and only data that adheres to a specific format and schema are accepted. This generally means that not all data can be stored, especially newly acquired or unstructured data sets, leading organizations to lose access to that data. Data warehouses are also typically just storage facilities. They don’t contain the tools that allow for data cataloging, reporting, governance, advanced analysis, and machine learning.

Data lakes, on the other hand, allow data to be stored immediately and create or change schema over time. They also come with a com plete complement of modular tools for access control, cataloging, and analytics, which together enable organizations to easily customize their data lake for their specific needs.

At Share Our Strength, a US nonprofit committed to ending child hood hunger, we addressed the challenges of managing our many dis crete fundraising data streams by initiating the process to implement a data lake in 2021. This has put us on a path to replace the organization’s

numerous independently managed spreadsheets with a single, acces sible, shared system of record. It has reduced the burden on our data base administrators by providing automated, real-time reporting. It has further prepared us to use advanced concepts in AI and machine learning to create better predictive models of donor behavior to improve our fundraising. Also, the data lake has made us more cyber-secure by giving us the capability to grant or restrict access to sensitive data sets on a granular level.

The technical journey from identifying the need for a data lake to implementing one was relatively simple. The cloud-based tools for storing, transforming, cataloging, and analyzing our data as well as controlling access to it were readily available from AWS. Far more difficult than the data engineering, however, was the cultural engineering required to bring new teams together, build trust in a new way of doing business, and agree on a new set of standards for managing our data.

CULTURAL REENGINEERING

During the process we learned that the real work in building a data lake is in reengineering the way that the organization thinks about its data. Our team estimates that we spent 80 percent of our time building

Richard Kostro is the senior vice president and CIO at Share Our Strength and serves on the board of directors of The Nonprofit Alliance Foundation.

A powerful tool for collecting and analyzing data requires nonprofits to rethink not just their technology, but their culture.

consensus across teams, and only 20 percent of the time designing and implementing the actual infrastructure.

One of the first areas of cultural reengineering was to make the IT department a better partner to the fundraising department. Prior to when I joined Share Our Strength as its CIO in 2017, the IT department focused almost exclusively on server maintenance and desktop support, and—although we had technical skills to offer—we were never part of the conversation of how to better manage data. Therefore, my first step was to expand the services the IT department offered to include building and maintaining the organization’s data lake. In doing so, my department offered a new source of creativity, capability, and perspec tive to our business units’ efforts to use data and technology wisely.

A second aspect of our cultural reengineering was building trust between the IT and fundraising departments. This effort took time and patience for people coming from different disciplines to learn each other’s language and to trust each other’s expertise. For example, when the IT department demonstrated the data lake’s capabilities, we were met with some skepticism because the analyses looked different from the Excel spreadsheets the fundraisers were familiar with. At the same time, we in the IT department also needed to guarantee that we were demonstrating capabilities germane to the fundraisers’ current priorities, such as automating data-cleaning tasks that occupied an outsize part of their day, instead of demonstrating capabilities that would only be potentially useful in the future, such as finding unique trends in donor behavior. It took several iterations and rounds of clarifying questions before we began to understand each other’s perspectives and were then able to establish a priori tized list of problems to solve.

Finally, our organization embarked on a third area of cultural reen gineering: developing a shared understanding of how our data was captured and structured. Often, the rules for storing and structuring data made sense for one fundraising team, but those same rules did not easily translate and apply to the work of other teams. This led to irrelevant data being stored in some structured fields, a lot of important data being stored in comment fields that did not easily lend themselves to analysis, and a realization that sometimes our analyses were incom plete because they did not fully take into consideration the nuances of how or where our data were stored. Data cataloging, which is a central feature of data lakes, gave us the tools and opportunity to identify and resolve these irregularities and ultimately improve our analyses.

Share Our Strength is only a year into using a data lake to improve our fundraising, but we are already seeing tremendous gains. We are beginning to measure returns on various investments with greater specificity because we are including more and better data streams, which in turn allows us to make smarter decisions. We are also work ing to automate complicated yet repetitive data transformations and data pulls—saving our donor operations team time as they support major- and mid-tier fundraising officers in multiple markets. Finally, our more consistent data standards are helping us to better under stand donor behaviors, which has allowed us to have more meaningful communications with them.

The data lake contributed to each of these successes, yet the lake itself was only possible thanks to our nonprofit’s cultural transforma tion. For organizations looking to take a similar journey to improve their fundraising capabilities, our advice is to build trust within the organization and then iterate, iterate, iterate, as there are likely several unknown opportunities for innovation within your own data sets. ◆

Accelerating Mission Impact

Cloud technology has fueled Moneythink’s ability to better serve students in real time.

BY JOSHUA LACHS

Afew years ago, my nonprofit organization, Moneythink, went through a digital metamorphosis. Since 2008, we have worked to increase the number of historically mar ginalized students graduating with college degrees while carrying little to no financial burden. Early on, we identified college matriculation and affordability as critical inflection points that were prime for innovation. In 2016, we committed to finding the most strategic intervention for the largest number of students who could benefit from our services.

In partnership with the behavioral science firms Ideo.org and Ideas42, we embedded a human-centered design approach into our product development. Meeting with students, their families, and student-advisors helped us to understand and think through what successful digital experiences could look like for our primary beneficia ries—current and future genera tions of education consumers.

Between 2016 and 2019, we ran a virtual college financial-coaching program with one-on-one college and financial guidance for Pell Grant-eligible high school seniors in Chicago and the San Francisco Bay Area. Our students were supported throughout the college applica tion and matriculation processes, including FAFSA completion, col lege fit and matching, financial aid award letter comparison, and personal financial planning. Our coaches used an in-house proto type to have more effective advis ing conversations, which led our students to make more informed decision about which college to attend. We tested several tools within our program that expedited previously laborious tasks such as collect ing financial award letters and translating their information by hand. And we discovered that our technology enabled students to quickly understand the affordability of college options, so that our advisors could then focus on the conversations that really matter.

Despite our successful virtual coaching program, we still faced barriers to large-scale growth and impact. Our in-person student

Joshua Lachs is the CEO of Moneythink. For more than 20 years, he has served in leadership positions within the college success and career-readiness fields.

Cloud technology proved to be the right solution for translating confusing financial aid letters, thus allowing users to compare their college affordability options.

recruitment and acquisition strategy was personal but time consum ing and resource intensive. Our service model was hamstrung by the reality that our students truly benefited from our services when they were able to access a Moneythink coach in real time—but we weren’t available 24/7. In addition, our then-current model required significant finances to expand.

In 2019, we wondered how we might reduce obstacles to access ing our virtual coaching model to develop an automated, yet personal, experience that would enable students to receive real-time support without individual coaches. We knew we needed to become even more innovative, agile, and, frankly, more digitally centric to bring our vision to life. After considering our options, cloud technology proved to be the right solution for translating and demystifying confusing financial aid letters, thus allowing users to compare their college affordability options.

Once we identified AWS, we started building DecidED in the fall of 2019, which has become our core prod uct strategy. DecidED is a web app that uses cloud technology to provide students and their families with guidance and sup port to understand financial aid options and budgeting for college costs. Not only is DecidED designed to engage and guide more students, but it is also used by student counselors so that they can have access to straightforward, effective, and precise data to more meaningfully support their students’ college decision-making process.

BECOMING PRODUCT-CENTRIC

The decision to pursue an open-access col lege affordability tool built on a cloud server presented us with a series of “risk and reward” questions and conversations about our business model, staffing structure, funding opportunities, as well as possible long-term strategic directions.

The results of those considerations led us down a clear path of next steps. First, we recruited experienced product-centric individuals to serve on our board of direc tors who could guide our strategic activi ties. Next, we purposefully included our long-time funding partners more closely in our impending organizational shift by explaining our intentions, asking for honest feedback, and inviting them to support our direction. We then added the necessary engineering capacity and technical expertise to our product team to facilitate long-term growth. Our final step was to assess the kind of organization we needed to be in order to deliver on our vision.

This work resulted in a big culture shift to becoming a “product-centric” organiza tion. In practical terms, this enabled us to reimagine the kinds of structure, systems,

and talent needed to propel our work forward. As the leader of our organization, it was important that I consistently communicated our refined “what” and “why” to our team, stakeholders, and community partners to continue creating buy-in and goodwill.

From a product standpoint, serverless technology helped us launch DecidED quickly and prepared us to scale with no wasted computing capacity. DecidED relies on a machine-learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. When a student uploads a digital version of their col lege financial award letter into the DecidED app, the file uses ML to extract text, tables, and other data points. Moneythink categorizes these outputs and then inputs them into a standardized award-letter feedback dashboard the user can access to make visual comparisons between college costs.

DecidED was also designed for student counselors to maximize the assistance they give high school students to make financially informed

college decisions. Before utilizing cloud technology, a college advisor would need to either manually interpret each financial aid document or ask their students to do so. DecidED’s award-letter processing gives practitioners cloud-based, verified college affordability information. Besides controlling for human error, it saves organizations hundreds of hours of administrative time.

Building DecidED on cloud technology has accelerated our overall growth. Already, we have thousands of students and advisors across 41 states. To stay ahead, we’ve increased our product team by 50 percent. We also doubled our organizational budget from $1.5 mil lion to $3 million, while securing new philanthropic support to fuel DecidED’s expansion and potential influence on systems change, including major grants from The Bill & Melinda Gates Foundation, the Michael & Susan Dell Foundation, Capital One Foundation, and other major supporters.

In 2021, Moneythink launched the DecidED API, which expands our database of college financial-aid data and provides public access in a bid for greater transparency around college costs. Because DecidED solves for an acute need in the marketplace, we’ve been able to serve our beneficiaries in ways that we never before could have imagined.

THREE TAKEAWAYS

From our experience, we offer three takeaways for nonprofits consid ering building a digital programmatic component, developing an app, or pursuing a digital strategy:

Digital is not the endgame. | Rather, it is a powerful vehicle that can fuel your mission. Human relationships matter the most. Leading with empathy and compassion are what will give you a competitive advantage.

Determine the right intervention. | Allocate time to figuring out the parts of your program or organization that could be auto mated—without compromising your programmatic aims and your equity-centric mission.

Conduct lean, rapid testing. | Iterating helps mitigate early, unnecessary spending on what could be costly endeavors designing in-house technology. For Moneythink, this meant operationalizing a human-centered design approach so that we could find ways to build lightweight prototypes and use design sprints to test new tools and features. We also routinely tested our ideas with and for our end users. This has resulted in an accelerated and oftentimes cheaper development process.

Data-driven transformation can lead to and sustain greater mis sion impact. For Moneythink, this means systematically empowering students by giving them clear and correct information and ownership of their choices. It means holistically transforming the college suc cess ecosystem by shifting the role that college advisors play using our automated solutions that allow practitioners more freedom to provide the support students really need. And it means informing college affordability practices and policies by leveraging our auto mated tools and predictive data sets that could influence efforts toward greater student financial and academic equity, research, and advocacy.

Digital shifts to cloud technology demand enormous energy, vul nerability, and high-risk tolerance. However, this effort was essential to better serve our beneficiaries and our team members. ◆

Beyond the Gallery Walls

The Barnes Foundation is using digital tools

BY MARTHA LUCY

The Barnes Foundation is a world-class art collection with a progressive educational mission. Our founder, the Philadelphia scientist-turned-collector Albert C. Barnes, believed that art had the capacity to transform lives, and that everyone—not just the elite—should have the opportunity to learn about it.

He chartered the Barnes Foundation as a place where such learning could happen, filling the galleries with his own collection and admitting his first cohort of students, many of them factory workers, in 1925. Art education classes were conducted in the galleries, with students seated in wooden folding chairs. On the walls hung a mixture of objects from all over the world arranged by Barnes himself into densely packed, ahis torical groupings, including modern French paintings, African sculpture, medieval triptychs, and ordinary household objects like spatulas and door hinges. Lessons focused on rigorous visual analysis that required no background in art or world history. Before his death in 1951, Barnes created the foundation’s bylaws to ensure that his method of installa tion could never be changed: The groupings must be kept exactly as he designed them, and no explanatory text could ever be added to the walls.

A hundred years later, we have vastly expanded our founder’s mis sion of accessible art education. The Barnes still offers classes in the galleries, but we have grown the number and diversity of offerings. We’ve introduced free programs for underserved communities and for K-12 students from Philadelphia public schools, and we’ve established a research department that produces new knowledge about the collec tion. Yet, we often find ourselves stymied by the limitations of physical space. The Barnes galleries are small compared to other city museums, making it a challenge to welcome school groups during public hours and to meet the growing demand for seats in our adult classes. Many of the rooms can fit only a handful of people, which means that parts of the collection, like African sculpture, cannot easily be incorporated into lessons. And given Barnes’s no-wall-label policy, how were we supposed to share new research about items in our collection with our visitors?

EMBRACING TECHNOLOGY

Cloud technology helped us maneuver around some of these challenges, first on-site and then in virtual spaces. In 2017, we launched Barnes Focus, a cloud-based mobile app built using AWS that lets us share historical information about the collection while keeping the gallery walls free of labels and text. The visitor simply positions their phone in front of a painting or object and the app immediately pulls up the name of the artist, title and date of the work, and a brief contextual description. The

to grow its educational mission and reach new audiences.

Martha Lucy is an art historian and the deputy director for research, interpretation, and education at the Barnes Foundation.

app is elegant, simple to use, and popular with our visitors—the use rate is over 80 percent—and, for our research team, it’s easy to add and edit content. Currently, there are 800 interpretive texts accessible via the app.

But we still had the problem of how to grow audiences given the Barnes’s limited physical space. In 2019, we began exploring the idea of online classes for adults. Not only would a virtual classroom allow us to enroll more students, but it would help us to circumvent the immovability of Barnes’s ensembles: Teaching with digital images would open a whole world of new juxtapositions for our instructors.

And yet we grappled with a philosophical dilemma: The idea of teaching in virtual spaces that took people away from the actual art felt counterproductive. After all, there was a uniqueness to the work of art that had to be experienced in person—a certain quality, or “aura,” as the philosopher Walter Benjamin termed it, that no reproduction can capture. Museums offer visitors the pleasure of the aura, of know ing that the object before them was touched by the hand of the artist. What would it mean, then, for a museum to embrace virtual learn ing? Were we somehow suggesting that the actual physical object no longer mattered? How could we square an online format, with all its amazing democratizing potential, against our historical role as an institution dedicated to direct study of the work of art?

A year later, in 2020, these theoretical questions seemed less important. That March, the COVID-19 pandemic forced the Barnes, like so many other institutions, to close its doors and suspend all on-site programs. Eager to keep our students engaged, we decided to migrate a handful of adult classes, already in progress, to a digital platform—a huge logistical lift. For the first time in the Barnes’s history, students were learning in spaces other than the gallery collection and, based on a survey

issued three months into the migration, they were having a good experience: More than 94 percent said they would continue taking online classes after the pandemic ended, and our enrollment numbers had tripled.

Part of our students’ enthusiasm for online learning is owed to what the technology let them experience. Our instructors, teaching from home, used deep-zoom images stored on the cloud to bring students closer than they had ever been, visually, to artworks in the Barnes collection. The deep-zoom technology allows the user to pan over the image, inch by inch, so that you can see the nubby texture of a canvas, even the way a paint stroke gets hooked on the surface’s minuscule bumps. In an impressionist painting, you can see brush strokes moving over and across one another, their different colors dragged together. Maybe people didn’t need to be in the physical pres ence of the art for meaningful learning to take place. Maybe there was more to the work of art than its physical aura.

Our students were seeing the artworks in new and revelatory ways. But if we were going to continue with online classes, we also wanted to capture the singular experience of being in the Barnes galleries. Our IT and audiovisual teams developed mobile carts mounted with cameras that allow us to toggle between the deep-zoom images of individual paintings and live shots of the instructor standing in the gal leries. Students can get a sense of the space, and of the unconventional groupings, but they also get to see details of the works of art that can’t be seen in person. Crucially, this technology also allowed us to solve the problem of teaching from the restrictively small rooms. With just the instructor and the audiovisual technicians present, we can now “fit” hundreds of students into the galleries housing our African collection.

A VIRTUAL EDUCATION

The pandemic also interrupted our K-12 school program—a large, grant-funded operation that includes visits to the collection for more than 11,000 students and teachers annually. When those visits were suspended, our team responded by developing Barnes Art Adventures, a live, interactive program hosted on the cloud that lets students explore and create while learning about art from around the world. As with the adult classes, instructors make use of deep-zoom technology to expose learners to the art on a granular level. Barnes Art Adventures became our primary offering for schools during the 2020-2021 academic year, and we continue to deliver it alongside our on-site programs.

With the ambition of scaling our virtual K-12 offerings, our IT depart ment built a custom livestream site with AWS that allows us to deliver the program to multiple partner schools simultaneously, in real time. This efficiency has been crucial for our small organization. Flipping the “camera on, mic off” model typically used for virtual field trips in Zoom rooms, we instead encourage students to express themselves through chat, where they can type or use our custom designed art emojis. We also enabled polls that update in the video feed in real time.

Early data from Barnes Art Adventures suggest that the rate of active student participation is consistently high—much higher than for a comparable on-site lesson. This is due to students being able to offer ideas simultaneously, unlike the traditional “sequenced partici pation” in a physical classroom. Moreover, students who are reluctant to participate in person are often more likely to speak up in the chat. In one episode of Barnes Art Adventures, with 240 participants in grades 2–4, students collectively logged more than 800 responses to questions and prompts given by the instructor.

EXPANDING OUR REACH

The single most important statistic affected by cloud technology is the number of students we can reach. During the 2020-2021 academic year, we delivered Barnes Art Adventures to 16,600 pre-K through grade-8 students in six states—a 40 percent increase from pre-pandemic years. Enrollment in our adult education classes more than tripled, from 1,195 students in 2019 to more than 3,000 enrollments in both 2020 and 2021. Earnings from adult classes also tripled from $200,000 in 2019 to more than $600,000 in 2020.

One of our major goals for the adult programs is diversifying our student body, and cloud technology helps us to do this in several ways. First, new revenue generated by online classes allows us to offer more scholarships at multiple price points to students who may not have the resources to pay for them. We offered 253 scholarships in 2020 and 378 in 2021, up from 100 in 2019. Second and more immediate is the way this technology eradicates physical barriers to access. A student in New Zealand told us she had always wanted to visit the Barnes but it was simply too far away. Yet she was able to beam into the gallery and participate in a lively discussion about the French artist Henri Matisse. Since launching our online classes, our geographic reach has grown exponentially, with students tuning in from 48 states and 8 countries.

Cloud technology has given us the opportunity to grow the Barnes’s educational mission in ways that our founder never could have imagined. Virtual spaces allow us to serve new and diverse audiences. People with disabilities or who lack the economic means to travel to Philadelphia can access our gallery classes online. Underserved communities and individuals with psychological and social barriers to entering an art museum—the most common being the perception that art museums are not “for them”—might feel more welcome in a virtual format.

Looking to the future, the Barnes will continue to build on the dem onstrated early successes we have experienced using the cloud. Thanks to an AWS IMAGINE grant and support from the Pew Center for Arts and Heritage, we’re hard at work on a major new project—a digital arts education platform—that is essentially built on top of this technology. The platform, which we plan to debut in early 2023, breaks from the screenshare model to create a much more immersive, interactive expe rience for both pre-K through grade-12 students and adult learners. By offering 360-degree panoramic views of the gallery space, synchronous and asynchronous delivery modes, as well as a searchable library of completed classes, the platform will afford students more control over and flexibility within their learning experience. The project is grounded in ongoing research into the digital-arts education landscape and responsive to the needs and motivations of learners of all ages. We are optimistic that this new platform will be a major innovation in the field of digital arts education and that, with adaptions by peer institutions, it will not only help to shape the future of financial sustainability in the arts and culture sector but will truly democratize access to the study of art. ◆

From the Cloud to Clean Water

BY CHRISTOPH GORDER

Nearly 800 million people worldwide lack access to clean drinking water. They are forced to rely on contaminated water sources such as streams and ponds that can cause illness and death. According to the United Nations, diseases from dirty water kill more people every year than all forms of violence, including war. Women and girls, who are most often tasked with col lecting water, spend hours walking to find water instead of earning income, caring for themselves and their families, or attending school. charity: water is a nonprofit on a mission to bring clean, safe drinking water to people in developing countries. When a clean-water project is built in a community, it brings health, economic development, educa tion, and dignity. With the generous support of more than one million donors, in 15 years charity: water has funded 111,709 water projects in 29 countries and brought clean water to more than 15 million people. Since our founding in 2006, we have pursued tech innovations to tackle the global water crisis and provide accountability and transpar ency to our work. For example, we have used Google Earth mapping technology to provide the GPS coordinates for every water project so that donors can see where their money is deployed. We were one of the first charities on Instagram, where we engaged with our support ers by sharing project photos and stories of impact, and we were the first charity to reach one million followers on Twitter. We were also an early adopter of virtual reality; we created a film that captured the 360-degree experience of gaining access to clean water for the first time.

As we’ve grown, we continue to face new challenges. One of the hardest lessons we’ve learned is about the sustainability challenges experienced by rural communities in the developing world. The reality is that some of the water systems in the remote communities we serve will break down over time due to heavy usage. When that happens, families are forced to return to contaminated water sources. Local governments have scant resources, and many villages are so remote that water systems are only checked periodically. Historically, there has been no real-time data regarding remote water systems. As a result, governments, nonprofits, and businesses have been severely limited in their efforts to keep clean water flowing.

As charity: water sought solutions to the problem of long-term sus tainability of water projects, we were surprised to discover how little technological innovation had been adopted worldwide to address this massive problem. In 2012 we began looking into water management in developed economies for inspiration on how vital public services are managed. We learned that in cities like New York, Singapore, and

charity: water’s sensor technology guarantees that potable water flows continuously to communities in need.

Christoph Gorder is the chief global water officer of charity: water. Previously, he spent 15 years leading disaster-response operations and managing large-scale health-care delivery programs around the world.

Copenhagen

Internet

Things (IoT),

We became convinced that this technology also held the potential to help those living on less than $1 per day.

safeguard

charity: water set out that year to develop a first-of-its-kind sensor technology to provide real-time data on the performance of remote water systems. We believed these sensors could enable local non profits and governments to monitor rural water systems that serve millions of beneficiaries without needing on-site visits—saving time, money, and human resources. We also hoped the sensor data would give local governments valuable knowledge about water usage in their communities, helping them to better manage water services and plan future investments.

The first phase of the project involved a comprehensive evaluation of all commercially available options for remote-flow sensing in various industries, such as petrol or irrigation. Unfortunately, we found that no viable alternatives existed to measure the flow of water in hand pumps, so we determined that we needed to design and produce an original device. With grants from funders, including the AWS IMAGINE Grant, charity: water was able to invest in the research and development of water-sensor technology.

To start, we knew the device had to be durable and able to withstand harsh conditions and potential vandals. It needed to be something that a local technician could easily install without complicated instructions or difficult-to-find, costly tools. It needed to have a long battery life so that villagers would not have to worry about battery failure and frequent battery changes. And it needed to be able to communicate wirelessly despite unreliable wireless networks in remote locations. Most of all, it needed to be affordable and scalable.

We’ve now been able to produce the first-ever scalable remote sensor to monitor rural water points. The device is tamper-proof, easy

to install, runs for 10 years without a battery change, and costs only $250—which is less than 2 percent of the cost of a new hand pump. The sensor’s wireless roaming agreement automatically offers cov erage in more than 200 countries. We’ve included a pair of powerful antennas in the device that allow us to connect to cellular networks, even if signal strength is weak.

The technological innovation extends far beyond the device hardware itself. The sensor transmits data over the local mobile phone network to a powerful cloud computing platform housed by AWS. The platform processes, stores, and analyzes millions of bits of data and detects anomalies. Once the data is in the cloud, it becomes available to users in the field, producing customizable automated reports that can be set up to be sent to stakeholders as needed. The data generates meaning ful insights for field technicians, who can be deployed for repairs the moment a problem is identified. It means that we can publicly share the functionality of our water projects. Most importantly, it means clean, safe drinking water continues to flow in communities around the world.

Since our water-sensor journey began, we have successfully manufactured and deployed our original IoT device to thousands of project locations around the world. We believe that sensors have the potential to be a powerful tool in the fight to make sure that everyone in the world has access to a reliable source of clean water.

Our water sensor is another step in the history of charity: water using technology to provide accountability and transparency in everything we do, from connecting donors to the projects they support to deliver ing sustainable water access to some of the world’s most vulnerable communities. With the installation of water-sensor technology, we are able to extend this approach even further, moving faster toward a future where everyone not only has access to clean water but can tap into innovative technological advances to ensure that this access continues without interruption.

◆

technologies like the

of

remote sensing, and AI

public services.

Next Steps & Resources

The articles in this supplement showcase the innovative ways that nonprofit organizations have leveraged cloud technology to advance their respective missions. We hope they have given you insights into how your organization might be able

WORKING BACKWARDS

Central to Amazon’s culture, this process focuses on bring ing employees together, across disciplines, to benefit from each individual’s distinct background and experience. Together, the pro cess helps organizations challenge assumptions as well as take a closer look at the unique contexts that your customers—for nonprofits, your beneficiaries, donors, volun teers, and field staff—operate in. The result is gaining clarity around significant challenges and defin ing a vision for how technology can enhance the customer experience.

Working Backwards also helps create a culture that cultivates employee contribution. AWS leads envisioning sessions with nonprof its using the Working Backwards method where we see teams and employees raising issues and con tributing to shaping solutions. This work creates commitment and con nectivity as well as supports grow ing, together. Learn more by reading our Powered by Purpose eBook.1

REVIEW COMMON AWS USE CASES

Two of the most common ways nonprofits use AWS are to reduce the time employees spend on rote, manual tasks and to make their data

to raise more money, use data more strategically, or develop new ways of engaging your audience.

How can you get started with AWS? Here are four resources that will help you get closer to the technology and its benefits, and jump-start your success:

more actionable. Automated tools can help nonprofits avoid burnout and focus on the health and wellbeing of employees and volunteers. By leveraging AWS technologies like AI and machine learning, the nonprofit sector can remake human-centered work. Check out our on-demand webinar, “How Nonprofits Reimagine Work Using Smart Technology,” 2 to learn more about how AWS tools can help automatize routine tasks and enable your team to focus on what really matters.

Secondly, when data is managed correctly, nonprofits can gain the actionable insights they need to make smart decisions. Another recent, on-demand webinar, “AWS for Data: Unifying Data to Boost Fundraising Outcomes,”3 spotlights some of the ways your nonprofit can leverage cloud solutions to enhance fundraising initiatives, donor engagement, and program services, as well as improve overall organizational performance.

LEARN FROM AWS EXPERTS

Embarking on this cloud jour ney requires planning. AWS has a dedicated team of nonprofit experts who have worked with thousands of organizations. Watch our on-demand webinar, “Design

a Roadmap for Your Nonprofit Cloud Journey with AWS,”4 to learn best practices on organizational transformation, cloud foundations establishment, migration method ology, and application landscape optimization from AWS experts. Benchmark where you are now, learn how to identify and prioritize transformation opportunities in line with your strategic objectives, and find out how to align your organiza tion on next steps.

LEARN MORE FROM NONPROFITS

The AWS IMAGINE: Nonprofit con ference5 is held annually and is a no-cost event that brings together nonprofit leaders, purpose-focused technologists, and impact innova tors to discuss how technology can help drive a positive impact for both people and the planet. The event features diverse voices from across the nonprofit community to enable organizations to learn and grow together. ◆

NOTES

1 https://pages.awscloud.com/NAMER-field-DL-imaginegrant-ebook-2021-learn.html

2 https://pages.awscloud.com/NAMER-event-OE-reimaginework-using-smart-tech-2022-reg-event.html

3 https://pages.awscloud.com/NAMER-event-OE-unify-databoost-fundraising-2022-reg-event.html

4 https://pages.awscloud.com/NAMER-event-OE-imaginenonprofit-design-roadmap-2022-reg.html

5 https://aws.amazon.com/government-education/nonprofits /imagine-nonprofit

Nonprofits of all sizes are using Amazon Web Services (AWS) to increase support, expand awareness, and advance mission impact locally and globally. Start using AWS to advance mission impact and innovation with cloud technology, today.