Risk and Resilience: The Portfolio Approach to Fiscal Sponsorship, Part #3

[Note: This series was co-written by Josh Clement and Schulman Consulting. For more on Josh, click here or scroll to the end of this post.]

Welcome back. In the first and second posts of this series, we have discussed how fiscal sponsors can manage their budgeting and planning, specifically to address two fundamental questions of:

  • How can we meaningfully project our revenue for next year?
  • And what are the implications of that for our organization?

To answer these questions, we have been diving into the financial data of fiscally sponsored projects, breaking down their history to try and understand which projects are more likely to grow and why.

In the final post of the series we are going go a step deeper, looking at how we can use this financial data to answer a few more nuanced questions, such as:

  • Why has our portfolio grown?
  • How often do small projects grow?
  • How much revenue should we expect from new projects?
  • Where is the financial risk in our portfolio?

Diving Deep

Last time, we started with the table below to lay out projects’ revenue by year, which we then used to look at project revenues

Table 1 – Yearly Revenue Tracking Document

Project 20152016201720182019
Project A            –            –$159,220$161,198$349,413
Project B$700,000$1,188,626            –    $3,803    $7,571
Project C            –$164,516$80,986$165,150$336,235
Project D            –            –  $31,540$187,170$269,503
Project E            –            –$121,638  $63,628$267,235
Project F  $36,587  $79,329$171,318$124,707$235,230
Project G$170,469$196,984  $94,399  $73,941$204,308

With this table, it is incredibly helpful to add any other meaningful categorization. For example, if your fiscal sponsor groups projects by their current growth stage, or if they are grouped by the type of work that each project does, this information can be utilized later to look for trends and patterns. These classifications may show that programs that work primarily with youth have higher growth rates, or that projects that are categorized as “High Growth” have more volatile funding patterns.

However, for any additional classification to be effective, it must be applicable to the entire portfolio, as a partial analysis of the portfolio with additional categories is less useful.

[Not sure where to begin? Or which categories might make sense for your organization? Let us help you figure it all out.]

Category Analysis

This data can be used in a multitude of ways, but there are several easy, helpful methods to begin to assess the financial data to find useful information.

  1. Nuanced Portfolio Growth:  With the data in Table 1, particularly for fiscal sponsors with between 20-80 projects, it becomes easier to understand why the portfolio of projects grows or contracts. For example, the portfolio may have grown by 26-30 percent each year of a period of five years, but by laying out yearly revenues, we can see exactly which projects contributed to the growth.Perhaps most of the projects grew over this period, but only several projects experienced high growth levels and they were driving the portfolio’s growth. This analysis can highlight a portfolio’s reliance on large-project growth.
  2. Segmented Project Growth:  By laying out project revenue, projects can be grouped with similar sized projects (or any other categorization). This segmentation can be used to answer questions such as how likely small projects are to grow beyond $100,000 in revenue or long it typically takes for a small project to grow to $250,000 in revenue.
  3. New Project Performance:  For every fiscal sponsor, newly signed projects make up some component of their portfolio and projected revenue streams for the future. By assessing the yearly new project revenue, such as the average size of new projects, fiscal sponsors can better project how reliant they should be on new projects, or to determine whether or not current marketing efforts (if any) are effective or if marketing needs to be initiated or expanded.

Evaluating Risk and Forecasting

This analysis all leads to a more informed answer to the initial question, “How much revenue should we expect to bring in, in the next year?” But it does not answer why certain projects grow or contract.

A quantitative analysis cannot answer the why for each and every project. Project leaders, fundraising capacity, and funding giving patterns influence each project’s revenue capacity. This sort of contextual information is necessary to create a more informed understanding of what the yearly-revenue figures indicate, as well as how outlier projects contribute to this analysis.

However, project revenue analysis can provide a more in-depth understanding to help answer the “Why” and “How” questions. Why did certain projects grow? Why did certain projects see massive decreases in funding? How likely is it for certain projects to grow and decline?

To answer these questions, a revenue-type breakdown can be utilized. For example, by assembling all large projects in a given year, a pattern may emerge that large projects saw large decreases in funding were highly reliant upon foundation funding.

Project Name

% Foundation
Funding in 2018
20182019

Year-over-Year
Change

Project A57%$2,763,135$3,489,574$726,439
Project B73%$1,111,473$1,515,029$403,556
Project C86%$1,438,771$1,732,478$293,707
Project D35%$1,650,805$1,803,931$153,126
Project E94%$1,472,543$1,522,966$50,423
Project F93%$1,043,932$832,932$(211,000)
Project G94%$1,227,637$987,576$(240,061)
Project H99%$1,229,405$894,490$(334,915)
Project I97%$1,313,723$761,499$(552,224)
Project J98%$1,009,798$237,403$(772,395)
Project K99%$1,007,881$816$(1,007,065)

In the example above, all projects in this fiscal sponsor’s portfolio that had a budget with over $1 million in 2018 experienced some sort of change in funding the following year. For the projects with high reliance upon foundation dollars, there is a clear correlation to large (and, in this example, largely negative) funding changes from 2018 to 2019. This presents some questions that may be worth exploring further on a qualitative level:

  • Are there any other commonalities among Projects E-K?
  • Do they share funders?
  • Do they serve similar communities or provide similar types of services/activities?
  • Was there a broader economic downturn to consider?
  • How did all of these projects become so dependent on foundation funding?
  • Are there ways to help them diversify their funding streams?

This is just one example of how to use this kind of analysis. In this case, it shows how certain projects may provide the basis for high growth in the portfolio, they also can represent a certain risk – if their funding comes from a few concentrated sources.

While this all may seem overwhelming, particularly for fiscal sponsors who haven’t tackled these kinds of analyses before (or if you are simply a reasonable person who sees charts and numbers and skims to the end), the actual practice of collecting, evaluating, and analyzing this data can be pretty straightforward. All it takes is making sure the organization is collecting the right data and then utilizing it in a few different ways to answer questions about projects that are difficult to assess when looking at your project group as a whole.

But by working to answer these questions, your organization can grow having the peace of mind that you’re effectively ensuring its resiliency while mitigating risk.

[If you think this could benefit your organization, but you’re not sure where to begin, we can help you figure it all out. Click here to set up an initial call to discuss your situation.]


About Josh Clement: Josh Clement is the former Grants and Development Manager in the fiscal sponsorship sector. In his role, he designed a new approach to financial analysis, which he has since brought to others in our sector. He’s partnered with Schulman Consulting to share his expertise and knowledge. He’s also currently earning his Masters in Public Policy at the Humphrey School for Public Affairs at the University of Minnesota.

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