In a world where every penny counts, young nonprofits face the daunting task of securing funding. Traditional sources are dwindling, digital options are proliferating, and competition is fiercer than ever. For Impact Space, making the most of our resources is imperative.
To navigate this complex landscape, we turned to data and analytics, specifically linear optimization, to refine our grant application strategy and maximize our limited resources in achieving our fundraising goals.
However, initial results from our optimization model presented a sobering reality: projections indicated we might secure only around $10,000 in grant funding—a stark contrast to our ambitious $500,000 target. This powerful analytical approach revealed our capacity limitations and the need for diversification, allowing us to make informed decisions about expanding our fundraising strategy.
Follow along as we detail the steps we took, the lessons we learned, and the strategies we’re implementing moving forward.
Step 1: Setting Goals and Recognizing Constraints
Our objective was ambitious but necessary: raise $500,000 in grant funding. However, our resources were limited– our team could dedicate a maximum of 480 hours to grant applications per quarter, which meant we had to be strategic. This led us to the fundamental question: Which grants should we pursue to maximize our funding while staying within our time and resource limits?
We identified two primary constraints:
- Time: The total hours required for grant applications couldn’t exceed our 480-hour limit.
- Diversity: To reduce risk, we needed to apply for at least one grant in each of our core funding categories (from small community grants to federal-level opportunities).
With these constraints in mind, we set out to develop a model that could guide us toward the optimal mix of grants.
Step 2: Collecting and Structuring Data
Before diving into linear optimization, we needed reliable data on each grant opportunity and downloaded historical data on grants from NIH, grants.gov and a few other sources online:
- Grant Amounts: We categorized grants based on potential funding, ranging from $5,000 to $250,000.
- Probability of Success: Based on historical data, we estimated each grant’s success rate. These probabilities ranged from 1% for highly competitive federal grants to 5% for smaller, community-focused grants.
- Application Hours: Some grants required 10 hours to apply, while others took up to 50 hours due to extensive requirements.
We entered this information into a structured spreadsheet, creating key columns for:
- Expected Value: Calculated by multiplying the grant amount by the probability of success, providing a forecast of each grant’s potential return.
- Total Cost: Factoring in both the time investment and any fees associated with the application.
This data was the backbone of our linear optimization model, allowing us to focus on the grants that aligned best with our objectives.
Step 3: Building and Solving the Optimization Model
With our data in place, we used Google’s Open Solver, a powerful linear programming tool, to calculate the optimal mix of grants. Our objective was simple: maximize the sum of the expected values of all grants while respecting our constraints on time and diversity.
Our Model’s Key Components:
- Objective Function: Maximize the expected funding, the sum of the products of each grant’s amount and probability of success.
- Constraints:
- Time Limit: Ensure total application hours don’t exceed 480.
- Diversity Requirement: Apply for at least one grant in each funding category to maintain a spread across different sources.
- Time Limit: Ensure total application hours don’t exceed 480.
Step 4: Insights from the Model
The optimization results were enlightening and shaped our entire approach to fundraising. Here’s what we discovered:
- Realistic Funding Projections: Our model projected we’d secure around $10,000 in grant funding within our current constraints—far from our original $500,000 target. While this was a sobering figure, it gave us a realistic outlook on the returns we could expect purely from grants.
- Capacity as a Limiting Factor: The results underscored a critical insight: our grant funding potential was directly limited by our available hours. If we could increase our team’s capacity, we could realistically pursue more funding opportunities. Additionally, if we could reduce the cost per hour utilized we could improve the expected amount.
- Need for Diversified Funding Sources: Given the constraints, our model emphasized the need to diversify. Grants alone wouldn’t suffice. To reach our overall funding goal, we would need to look beyond traditional grant applications.
Step 5: Implementing New Strategies and Expanding Our Approach
Armed with these insights, we expanded our fundraising strategy to include additional revenue streams. Here’s how we broadened our approach:
- Crowdfunding Campaigns: We launched online campaigns on platforms with high engagement to attract individual donations. We focused on storytelling to increase visibility and connect with potential donors worldwide.
- Merchandise Initiatives: Our “Impact Shop” offered branded apparel and merchandise aligned with our mission, tapping into consumer interest in sustainability.
- Enhanced Digital Presence: We streamlined our digital engagement using content automation tools, freeing up time to focus on impactful storytelling.
Moving Forward: Embracing Advanced Analytics
Linear optimization gave us a solid foundation, but we’re excited to explore even more advanced analytics to further enhance our strategy. Machine learning, for example, could help us refine our probability estimates and adapt our model to changing conditions in real time. With predictive analytics, we can fine-tune the timing of campaigns and identify which donor segments are most likely to engage with specific initiatives.
Our experience at Impact Space has demonstrated the power of data-driven decision-making. Through linear optimization, we’ve developed a sustainable and efficient fundraising approach that aligns with our capacity and amplifies our impact. For nonprofits navigating today’s challenging landscape, data analytics offers a path to not only survive but thrive.
By sharing our journey, we hope to inspire other nonprofits to adopt similar strategies, turning data into actionable insights and maximizing their impact. If you’d like to learn more about our process or explore how data-driven tools can elevate your fundraising, reach out to us!
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We’ve made our grant optimization spreadsheet template available for download, so you can see our process in action and apply these strategies to your own organization. Impact Space Grant Application Optimization Model – Excel