Issue Brief #3:

Using Data to Improve 

SIF Programs: Lessons 

from Practitioners 

A product of the National Assessment of 

the Social Innovation Fund (SIF)

September 2015
Issue Brief #3: 

Using Data to Improve SIF Programs: Lessons from Practitioners 

September 2015 

Authors 

Johanna Barrero, M.I.A., M.A. 

Janet Pershing, Ph.D. 

Janet Griffith, Ph.D. 

Prepared For 

Lily Zandniapour, Ph.D. 

Office of Research and Evaluation 

Corporation for National and Community Service 

This document is a product of the National Assessment of the SIF, which seeks to document and capture the impact the 

SIF has on key program stakeholders. Its findings will provide evidence and tell the story of the SIF as well as identify 

lessons learned. The National Assessment is sponsored by the Corporation for National and Community Service’s Social 

Innovation Fund, designed and managed by CNCS Office of Research and Evaluation, and conducted by ICF 

International. 

This report is in the public domain. Authorization to reproduce it in whole or in part is granted. Upon request, this 

material will be made available in alternative formats for people with disabilities. 
nationalservice.gov/research 1 

1. Introduction 

The Social Innovation Fund (SIF) leverages public and private 

resources to grow community solutions based on evidence of 

results. The National Assessment of the SIF seeks to document 

and capture the impact the SIF has on key program 

stakeholders. Findings from this multi-component independent assessment, sponsored by the 

Corporation for National and Community Service’s (CNCS) Office of Research and Evaluation and 

conducted by ICF International, will tell the story of the SIF and identify lessons learned. The SIF makes 

grants to experienced grant-making organizations, which identify promising programs within 

communities through an open and competitive process and distribute funds to high-performing 

nonprofit organizations that implement them, and match the federal funds dollar-for-dollar. SIF 

subgrantees also match the funding they receive dollar-for-dollar. All SIF-funded interventions undergo 

rigorous, independent evaluations to advance the base of evidence for the funded intervention. 

This issue brief shares lessons about how SIF grantees and subgrantees use data to improve their 

programs. It provides action-oriented recommendations for current, incoming, and prospective SIF 

grantees, private and nonprofit organizations that might implement a SIF model, and policy makers. This 

brief is informed by insights from three SIF “Classic” 1 grantees and six subgrantees. 

Over the course of their grants, many grantees and subgrantees have found ways to use data collected 

through their SIF evaluation efforts to improve their programs. This brief highlights the variety of ways 

in which SIF grantees and subgrantees have used data collected as a result of their participation in the SIF 

to continually adjust and improve their programs, long before the final results of the impact evaluation 

are available. 

2. Using Data to Build a “Data Culture”

One of the biggest challenges SIF subgrantees face in 

their efforts to use data to guide program improvement 

is building an organizational culture in which staff 

value data and embrace the opportunity to make databased program improvements. Subgrantees reported 

that sharing program data across the organization can 

be sensitive, because people may associate the program 

data with individual performance, and making 

adjustments based on those data can be challenging if 

staff are invested in the way they currently operate their existing programs. Many SIF grantees and 

subgrantees have tried to address these concerns head-on by working to build a “data culture” in their 

organizations, in which all staff discuss data regularly and openly, understand the value of data for 

 

1 The SIF has two grant programs: Classic and Pay for Success (PFS). The Classic program unites public and private 

resources to evaluate and grow innovative community-based solutions that have evidence of results in low-income 

communities. PFS is a strategy that seeks to better connect government funding of services with real world effects by 

tying funding for a service intervention to its impact in the community. The PFS contracting and financing model that 

leverages philanthropic and private dollars to fund services up front, with the government, or other entity, paying 

after they generate results is sometimes referred to as the Social Impact Bond. As part of both the 2014 and 2015 

Congressional appropriations, the SIF was given authority to use up to 20% of grant funds to implement a 

competition to test PFS approaches.

Key Research Question:

How do SIF grantees and subgrantees 

use data to improve their programs?

“You can't just look in the evaluation report and 

turn around and make that change. Depending 

on what the change is, different staff members 

will need to be educated on that. You need buyin. There are so many things that come into play 

that it really calls for a thoughtful approach.”

 --Jennifer Callans, SIF Grantee,

United Way for Southeastern Michigan
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program improvement, engage in analyzing the data and determining how to respond, and embrace the 

opportunity to make changes to improve outcomes for the clients they serve. 

One wide-spread tactic for creating a data culture among SIF subgrantees involved building datagrounded discussions into the day-to-day business of the organization. But subgrantees found that the 

data could be confusing to staff, and that if not presented and discussed effectively, staff could feel 

defensive about data related to their job functions. SIF subgrantees Madison Strategies Group (MSG) and 

Chrysalis, as well as grantee Venture Philanthropy Partners (VPP) all emphasized that regular staff 

meetings provide a great opportunity to ensure that staff across the organization discuss program data, 

internalize what the data show, and understand what those data imply for their individual roles, for their

programs, and for their organizations’ work. Leaders of these organizations believe that data can be an 

empowering tool for guiding staff toward ever-more-effective program delivery when shared in a 

constructive, problem-solving spirit. 

Several SIF grantees and subgrantees stressed the importance of discussing data in a positive way that 

centers on client outcomes rather than employee performance. Subgrantee leaders reported that staff in 

their organizations tend to be highly committed to the organizational mission and to serving clients 

effectively. They found that carefully collecting and 

analyzing data, then adjusting accordingly, improved 

outcomes for clients, and pointing this out was an excellent 

catalyst for engaging staff in the discussion and helping 

them keep open minds about possible ways to adjust the 

ways in which they had been carrying out existing 

programs. For example, the National Kidney Foundation of 

Michigan needed staff to make changes in their standard 

operating procedures in order to provide the level of detailed reporting that would be needed for the SIF 

evaluation – changes that were “adding components to individuals’ jobs, where they might have already 

felt maxed out.” They got the staff buy-in they needed by discussing why the changes were more than 

just added job responsibilities – they were vital for program improvements, enhancing services for 

participants, and ensuring program sustainability. 

One key to becoming an effective data-centric organization was to provide the right data to the right 

people at the right time. Too much data causes information overload and can’t be applied effectively to 

program improvements; too little data leaves staff without the information needed to make effective 

program improvement decisions. Chrysalis emphasized the importance of simplifying the available data 

and providing timely, relevant indicators to each line of business to allow managers to make datainformed decisions. Chrysalis asked staff within each line of business to identify their data needs, and 

now produces weekly and monthly dashboards with program performance data that employees can use 

to track progress and make adjustments. By involving the lines of business in the planning and design 

process, Chrysalis ensured that the dashboards would contain information that actually mattered to the 

program team, and that the program team understood exactly how to use the data. 

Another key to building a data-centric organization was 

involving the whole organization – not only top-level decisionmakers – in looking at data and envisioning next steps. For 

example, SIF grantee Corporation for Supportive Housing 

(CSH) highlighted the need to communicate with frontline 

staff about their role in the evaluation process. From a data 

collection perspective, it is easy for service providers who are 

“Connect with everybody’s desire to see 

the organization move forward. 

Communicate the value of how data 

helps us get grants and be sustainable.” 

--Lauren Nichols, SIF Subgrantee, 

National Kidney Foundation of Michigan

“Don’t be scared of the data, but embrace 

it and share it at all levels. Share it with 

staff, they are eager to know that they’re 

doing the very best that they can. Make 

them part of the process.” 

--Miranda Cook, SIF Subgrantee,

The Bridge Project
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focused on their daily work with clients to treat data entry as an afterthought. To address this, CSH 

suggested spelling out roles in the subgrantee agreements and ensuring that everyone in the organization 

understands their role in the evaluation efforts. 

Subgrantee Madison Strategies Group found that sharing data with front-line staff, engaging them in 

understanding what the data meant in context, and determining what the team might do about it added 

real value to their problem-solving conversations. It ensured that the team really thought through “the 

program goals in relation to their job responsibilities and priorities and metrics they are responsible to 

report.” Involving staff in the planning process also ensured their buy-in, because the program 

adjustments made sense to staff as ways to maximize positive client outcomes and increase program and 

organizational success. 

The Colorado Statewide Parent Coalition (CSPC) found 

value in establishing an inclusive process for reviewing 

data and developing program adjustments. CSPC initially 

implemented significant changes to program forms used 

for collecting child outcome data as well as training 

materials used with childcare providers based on data 

analysis conducted by the organization’s leadership. 

However, when rolling out the new forms, they 

encountered internal resistance. To address this challenge, 

CSPC brought the staff involved with the forms into the 

process and asked for their input and feedback on proposed changes. Leadership also took time to 

thoroughly explain the value of the new forms, and how the data would be essential for demonstrating 

the real impact of their work. Involving staff and focusing on benefits of the change to the program 

brought staff around to supporting the needed changes. 

A “data culture” also needs to be willing to experiment with new approaches to service delivery, assess 

their effectiveness, and make long-term decisions accordingly. Subgrantee Madison Strategies Group 

(MSG), which provides sector-based technical training, job placement and advancement services to 

individuals, traditionally had two staff positions interacting with clients. One was responsible for helping 

clients find jobs, while the other provided clients the support they needed to advance in their jobs. MSG 

experimented with combining both roles in one staff position. MSG monitored the results of this 

adjustment, and determined that combining the roles caused confusion among staff, employers, and 

clients. When MSG determined that this strategy was not proving effective, they returned to the prior 

model. 

Recommendations for Using Data to Build a “Data Culture”: 

 Secure buy in and commitment from the organization’s leadership to promote a “data culture” 

where data is routinely used to inform programmatic decisions. 

 Create an atmosphere where program performance data, good or bad, can be discussed openly 

and used as a basis for decision making by building data-sharing into the organization’s DNA. 

Share information at staff meetings, distribute dashboards with relevant indicators, and involve 

staff at all levels of the organization in interpreting data and developing strategies for continuous 

improvement. 

"We've gotten significantly better over the 

last two years at taking the sea of 

information that we have and putting it in 

monthly reports that managers can make 

decisions based on, or in reports that the 

board might be interested to see, really 

learning how to distill all that information." 

--Trevor Kale, SIF Subgrantee, Chrysalis
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 Get input from staff about what data they need to inform their work, and the most effective 

format for getting that information to them. 

 Get input from staff about what data they need to inform their work, and the most effective 

format for getting that information to them. 

 Make clear how the data analysis supports what staff value – serving clients more effectively by 

helping staff focus their efforts on what is working well and adjusting or discontinuing those 

things that aren’t.

 Communicate to staff the benefits of having reliable data to demonstrate the impact of their work 

to clients, partners, and funders. 

3. Using Data to Ensure Program Fidelity 

Attention to fidelity when replicating a program model is critical in working with evidence-based 

programs. Grantees used a variety of approaches to assess the fidelity or variations in the way their 

programs were implemented. The Colorado Statewide Parent Coalition, for example, enhanced the rigor 

of the home visit logs kept by staff working with home child care providers. This provided the 

information the Coalition needed to assess the number and duration of visits being accomplished – and to 

determine that there was lots of variation. They are now working with staff to ensure that the visits are 

taking place at appropriate intervals and are the needed length. Without the more detailed logs created 

because of participation in the SIF, the organization would not have identified that consistency of 

delivery was an issue. By tightening up their processes to ensure greater fidelity in program 

implementation, they will have both a better-implemented program and stronger data. 

Another example comes from the Bridge Project’s reading initiatives, in which the SIF evaluation process 

included classroom observations by an outside evaluator. Those observations revealed inconsistencies in 

the way educators were delivering the curriculum and guided the Bridge Project in determining what 

professional development opportunities they needed to offer to their educators to ensure that the same 

curriculum, the same number of sessions, and that similar 

quality trainings were offered at all four of their sites. The 

Bridge Project built on these process evaluations further, 

by having their educators use the observation form as a 

tool for peer observations. Peer observations helped the 

educators learn from others implementing their program, 

enhancing their skills and contributing to consistent 

delivery of the training. The Bridge Project reported that 

this peer observation and feedback model has 

significantly raised the consistency and quality of the 

educators’ teaching.

Recommendations for Using Data to Ensure Program Fidelity: 

 Develop clear protocols for program delivery, and train front line staff so they know both what 

they need to do and why it is important. 

 Use quality control mechanisms such as observations and logs to ensure that services are 

delivered as intended. 

“Being able within SIF to have a literacy 

intervention program has been amazing. 

Then being able to say we observed these 

educators this many sessions... that's been 

able to direct our professional development 

with educators so that all of our young 

people are getting the same kind of teaching 

and getting the exact curriculum delivered in 

a valid and reliable way.”

 --Miranda Cook, SIF Subgrantee,

The Bridge Project
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 Track program delivery metrics such as number and length of client contacts and the nature of 

the content delivered, and adjust as needed to ensure consistent program delivery. 

4. Using Data to Improve Program Delivery 

Grantees and subgrantees used data to identify areas of high performance to expand or replicate, as well 

as to make adjustments in areas where programs were not performing as expected. These data proved 

useful for program improvements at all points in the program delivery cycle, from client recruitment and 

placement, to program implementation, to long-term follow-up. 

4.1 Recruitment and Placement 

Several subgrantees made use of data to affect the very earliest points in the process, as they recruited 

and placed clients in their programs. AIDS Connecticut, for example, devised a formula to ensure that 

they were serving their most at risk homeless clients. With the help of their evaluator, NYU, they 

matched Homeless Management Information System 

data with state Medicaid information to identify 

potential clients who fit their selection criteria. When 

the established criteria did not produce the needed 

client base, AIDS Connecticut revisited the data to 

adjust their criteria accordingly. 

Early on, Madison Strategies Group focused on tracking 

the number of people who attended orientation for their 

sector-based career advancement program. After 

encountering higher-than-expected attrition rates resulting in low levels of enrollment after orientation, 

they did some careful analysis to gain insight into weaknesses in their program recruitment strategy. 

MSG used findings from a funnel analysis conducted by third party evaluator MDRC, to gain insight into 

effective recruitment strategies for successful candidates. MSG continues to use the findings of the funnel 

analysis and has performed subsequent similar analyses in order to target clients that have a higher 

chance of success in the program, manage client expectations when joining the program, and identify 

additional resources needed to help weaker candidates prepare for success before pursuing the program. 

4.2 Program Implementation 

SIF subgrantees used evaluation findings to identify effective interventions that could be adjusted and 

replicated in other communities. This was the case of United Way for Southeastern Michigan’s 

subgrantee Southwest Counseling Solutions. The organization runs a family literacy program with nonEnglish speaking households that incorporates interactive activities aimed at increasing parents’ capacity 

to support their children academically. Program outcomes showed great success in reducing truancy 

rates and increasing children’s test scores. Staff believe that a key factor is the 8 hours of classroom time 

that these parents spent with their children, reinforcing the importance of education and giving them 

skills to use in reinforcing this message at home. In an effort to obtain similar results in a community 

where ESL is not a significant issue, Southwest Counseling Solutions is now considering modifying this 

model for use with English-speaking parents, replacing ESL sessions with interactive life skills training. 

Several grantees and subgrantees provided examples of ways in which the programs successfully used 

data to identify ‘trouble spots’ and seek targeted solutions. For example, a Venture Philanthropy Partners 

subgrantee observed in the performance management data for their youth development project that 

“We really tried to choose providers that really 

understood the difficulty around engagement 

and for us, given that we're using data driven 

targeting, we never stop engaging. Someone 

may say no or they may drop off our radar for a 

little bit but that doesn't mean that they're out of 

the program for us and they can come back.”

--Sarah Gallagher, SIF Grantee,

Corporation for Supportive Housing
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sophomore year was a particularly critical point for keeping students from dropping out of school. As a 

result, they reallocated their resources to focus more intensively on providing support to 9th and 10th 

graders, followed by continuing support to 11th and 12th graders at somewhat lower levels. This 

reallocation of resources resulted in better student outcomes in high school and prepared students better 

for college. 

The Bridge Project combined child literacy data with data from observations of their tutoring sessions. 

They found that while tutors could benefit from additional support in teaching academic subjects such as 

reading and math, the areas in which they could most benefit from support were the ‘soft’ skills around 

behavior management, child engagement, and relationship building. They also found through systematic 

program observations that noise levels created significant distractions. With this information, they were 

able to secure a more appropriate space with lower noise levels through a partnership with the Denver 

Housing Authority, allowing the children to focus and engage more effectively in the program. 

Through data from client surveys, intake assessments and observations from patient navigators AIDS 

Connecticut identified higher-than-expected levels of substance abuse among their clients. Many of these 

clients required long-term treatment in order to prepare them for successful independent living, but this 

could lead to loss of stable housing situations. Based on this analysis, AIDS Connecticut began connecting 

clients with long-term treatment and worked to ensure extensions for housing arrangements to allow 

clients time to complete treatment. As a result of this intervention, their clients were in a better position to 

move on to independent living situations at the end of their work with AIDS Connecticut. 

A final example of data used to make mid-course 

adjustments also comes from AIDS Connecticut. In 

reviewing information about their clients’ barriers 

in a data dashboard, they found that many clients 

had criminal histories, and were unable to get 

housing assistance due to a pending court case on 

their records. AIDS Connecticut partnered with the 

office of court services to provide staff training 

about how to work with the court to clear up these 

records, and to help clients follow the necessary 

steps to obtain housing. By identifying this systematic barrier through their dashboard data, AIDS 

Connecticut was able to build staff skills and establish processes to help clients effectively work through 

this significant barr 

4.3 Program Follow-Up

As part of their SIF evaluation Chrysalis, a SIF subgrantee that provides employment support services, 

tracked clients to see if they were still employed one year after they had exited the program. The 

organization had invested in improving the employment placement and support services they provide 

during a client’s time in the program, but wanted to better understand what happened to those clients 

after they had left the program. “While we hoped and believed that our retention efforts were successful 

and that our clients stayed employed, we had limited data to support this conclusion. We wanted to 

know exactly what was going on with our clients post-employment.” By improving their data collection 

methods Chrysalis was able to obtain more reliable data that they used to adjust their programs and 

improve their services. Chrysalis established a new staff position to focus on post-employment supports 

with the goal of improving client retention rates and long-term client outcomes. Because of this change 

more clients have contact with Chrysalis post-employment, resulting in better information about their 

“Since our primary focus was patient navigation and 

improved health status, we were confronted by 

broader systemic inadequacies that thwarted our 

clients (such as transportation to appointments, 

behavioral healthcare, absence of primary care, 

limited housing case management, etc.) which 

required us to meet with community partners to 

round out our efforts and address these issues.”

--John Merz, SIF Subgrantee,

AIDS Connecticut
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employment outcomes, and a reconnection to Chrysalis services for those who have been unable to 

retain employment. 

Similarly, Madison Strategies Group looked at data from their WorkAdvance program and saw that they 

were doing a great job with job placement, but expected to see higher job retention rates. They used 

employer feedback to ascertain that the primary issue 

did not have to do with job skills, but with career 

readiness. Based on this information, they worked 

with a consultant to develop a highly interactive 

career readiness curriculum focusing on ways to 

enhance short and long term goal setting, decision 

making and ramifications, and critical thinking skills 

to help address those less tangible skills required for 

job retention. As a result of these gathering feedback 

from employers and modifying their career readiness 

curriculum, Madison Strategies Group has seen an 

increase in their job retention rates. 

Recommendations for using data to improve program delivery: 

 Collect data about all aspects of the program, not just the direct service delivery components. 

Information about recruitment (pre-program) and long term outcomes (post-program) can 

provide important insights for program improvement. 

 Look for barriers to client success, and focus on program modifications to address them –

whether that means providing extra support during the program, recommending “pre-work” to 

prepare for success in the program, or offering post-program support for longer-term success. 

 Use mixed method data collection techniques. While survey data can provide key information, 

focus groups, interviews, and observations can bring to light program needs and delivery 

inconsistencies that can be masked in a survey. 

 Collect data in a systematic way to ensure data reliability. Design a data collection strategy that is 

consistent and can be used to compare performance over time. 

 Design data dashboards that present data in a simple, graphic way to facilitate easy 

comprehension, then make sure that staff use them regularly. Pay attention to the data, consider 

possible options with an open mind, and be willing to take a risk by trying a new approach –

with data collection to inform choices about subsequent adjustments. 

5. Using Data to Increase Client Recruitment, Engagement, and Retention 

To document what works, SIF grantees must collect data about the effectiveness of their programs. But 

other types of data can be critically important for program improvement. In particular, grantees and 

subgrantees noted the importance of using data to identify problems with client recruitment, 

engagement, and retention, and for identifying solutions and gauging success. 

Early on, Madison Strategies Group made concerted efforts to recruit participants for their WorkAdvance 

program by doing personalized outreach through partner organizations and at community events, 

libraries, and apartment complexes in areas with high rates of unemployment and poverty. Then they 

“A big theme out of our SIF evaluation was that 

post-employment support was leading to 

significantly better outcomes at that one-year 

mark. We used to have all of our case managers 

calling their working caseload at certain 

checkpoints. We've now changed and hired 

someone who is our retention coordinator, whose

only duty is to track these people down, get their 

information, and steer them back into the program 

if need be, and it's not this extra thing at the end of 

the month that [they] have to do.”

--Trevor Kale, SIF Subgrantee, Chrysalis
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looked at their data. They found that their traditional recruiting avenues were yielding relatively few 

participants; Craigslist was their best resource. Based on these data, they began closely monitoring 

referral sources and adjusting their methods to incorporate newspaper, radio, and television. They 

became more sophisticated over time, gathering still more data to assess the results of advertising on 

different TV shows and radio stations. They also monitored the types of messages associated with 

increased responses, finding that longer ads with more specifics about the program’s impact on earnings 

were worth the investment. MSG’s investments in mainstream marketing strategies ran counter to their 

original assumptions about effective outreach, and were informed and refined over time through their 

data collection and analysis efforts. 

Subgrantee Chrysalis offers job readiness, employment, 

and post-employment support for homeless and lowand moderate-income (LMI) individuals. The 

organization originally opted not to require clients to 

participate in programming, but rather to allow clients 

to use services if they wanted to. They found that many 

clients signed up for services but did not actually use 

them – and therefore were not successfully transitioning 

to outside employment after leaving the program. To 

address this challenge, Chrysalis began requiring clients 

to use their employment services, and paid them to do 

so (as required by State law). They also invested in 

additional resources by hiring a job readiness 

coordinator and offering in-house legal and mental 

health services. With these new changes in place, 

Chrysalis expects to see an increase in the number of 

clients successfully transitioning to employment. 

United Way for Southeastern Michigan helped subgrantees set up tracking systems to capture client exit 

interview data to identify barriers that were causing clients to leave the program. One subgrantee found 

many respondents reporting that lack of transportation was a significant barrier. Although field staff had 

identified transportation as an issue based on anecdotal evidence, data from the exit interviews provided 

a tool that allowed program staff to say “All right, this is the number of people that we are losing because 

of this issue. Let's all sit down and figure it out." The discussion resulted in establishing a van service to 

assist clients with transportation. 

Recommendations for Increasing Client Recruitment, Engagement, and Retention 

 Use field staff observations, focus groups, and anecdotal information to gather preliminary 

information about program strengths and weaknesses; then gather quantitative data to test those 

observations. 

 After implementing a change to improve the program, collect more fine-grained data to test the 

effectiveness of the change, and to identify areas for further improvements. 

Managing engagement is a big area for us. 

We have special giveaways for baseball 

tickets and we use those to motivate folks to 

come in and stay engaged with us. It's really 

about building a meaningful relationship 

beyond work. We provide movie tickets for 

disengaged customers to come in a talk about 

their career path. We have giveaways for 

Thanksgiving dinners, because we know that 

the holidays are creating undue stress. All of 

that came (about), because we couldn’t 

understand why our great program had 30% of 

the people who didn’t care about it.

 -- Karen Pennington, SIF Subgrantee,

Madison Strategies Group
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6. About This Issue Brief 

This issue brief was informed by input from the following people from SIF Classic recipient organizations 

and their subgrantees: 

 Jennifer Callans and Jeff Miles, United Way for Southeastern Michigan (2011 SIF grantee) and 

Lauren Nichols and Crystal D’Agostino from subgrantee National Kidney Foundation of 

Michigan; 

 Sarah Gallagher, Corporation for Supportive Housing (2011 SIF grantee) and John Merz and 

Cecilia Woods from subgrantee AIDS Connecticut; 

 Ayo Atterberry, Venture Philanthropy Partners (VPP) (2010 SIF grantee); 

 Trevor Kale, Chrysalis, a subgrantee of REDF (2010 SIF grantee); 

 Richard Garcia and Valerie Gonzales, Colorado Statewide Parent Coalition, PASO (Providers 

Advancing Student Outcomes) Program, a subgrantee of Mile High United Way (2011 SIF 

grantee); 

 Jesse Burne and Miranda Cook, The Bridge Project, a subgrantee of Mile High United Way (2011

SIF grantee); and 

 Karen Pennington and Rachel Griffin, Madison Strategies Group, a subgrantee of the Mayor’s 

Fund to Advance New York City (2010 SIF grantee). 

7. About The Social Innovation Fund 

The Social Innovation Fund, an initiative of the Corporation for National and Community Service (CNCS) 

under the Edward M. Kennedy Serve America Act, is a new approach by the federal government to 

address urgent national challenges. The fund mobilizes public and private resources to grow the impact 

of promising, innovative community-based solutions that have evidence of compelling results in three 

areas of priority need: economic opportunity, healthy futures, and youth development. 

The operating model of the SIF is distinguished by the following six elements: 

Innovation │ Evidence │ Scale │ Grantmakers │ Match │ Knowledge Sharing
Corporation for National and Community Service 

1201 New York Avenue, NW 

Washington, D.C. 20525 

TEL: (202) 606-5000 

TTY: (202) 606-3472 

NationalService.gov