Leading the Pack, On Par or Shaky?: Benchmarking Loan Program Performance. By Luz Gomez and Joyce Klein

Transcription

1 Leading the Pack, On Par or Shaky?: Benchmarking Loan Program Performance By Luz Gomez and Joyce Klein September 2012

2 Leading the Pack, On Par or Shaky?: Benchmarking Loan Program Performance By Luz Gomez and Joyce Klein September 2012 FIELD The Aspen Institute One Dupont Circle, NW, Suite 700 Washington, DC Funded in part through a grant award with the U.S. Small Business Administration. All opinions, conclusions, or recommendations expressed are those of the authors and do not necessarily reflect the views of the SBA. Additional support is provided by the C.S. Mott Foundation. The Aspen Institute/FIELD. All rights reserved. 1

3 One of the hallmarks of a high-performing organization in the microenterprise or any other field is that its decision-making is informed by data. When deciding how to best allocate resources dedicated to lending, one useful tool for management and board members is data that describes how the organization s microenterprise lending activity compares to that of others in the microenterprise field. Answers to questions such as the following can help leaders to make better decisions about how to focus money, talent and other resources: Are you on par in terms of the number of loans made with lenders working in similar markets? Are your loans performing better, or worse? Are you more or less efficient than other microlenders? How does your ability to recoup your lending costs compare to peer organizations? What s the difference between MicroTest and the U.S. Microenterprise Census? MicroTest is a long-running data collection project that captures both performance and outcome measures submitted by microenterprise organizations across the country. MicroTest datasets are smaller, but contain a more robust set of performance measures. The Quick Reports and Raw Data available on microtracker present MicroTest data. U.S. Microenterprise Census has been conducted periodically since The census, as its name implies, attempts to capture data from a large segment of the industry. Historically, it has collected data on a more limited set of measures. This dataset fuels the report builder function on microtracker and allows for benchmarking with a wider group of organizations nationwide. microtracker brings together MicroTest (deep data) and the U.S. Microenterprise Census (broad data) in one spot. MicroTest data is now being collected through the U.S. Microenterprise Census so that deep data becomes available on more of the industry. microtracker provides data that can enable your organization to address these questions, comparing your lending activities to those of the industry as a whole, as well as to key peer groups or organizations. Specifically, microtracker enables you to benchmark your organization to other lenders using the following key indicators. MicroTest U.S. ME Census microtracker Scale of lending activity: Number of microloans disbursed during the fiscal year $ volume of microloans disbursed during the fiscal year Number of microloans outstanding at year end Number of microloans disbursed during the fiscal year Total $ available for microlending Microloan capital deployment rate (percent of total capital currently outstanding as loans to entrepreneurs) Average size of loans disbursed during the fiscal year The Aspen Institute/FIELD. All rights reserved. 2

4 Portfolio quality: Portfolio at risk (outstanding balance of loans greater than 30 days past due as a percent of total outstanding loans) Loan loss rate (net write-offs as a percent of average outstanding loans for the year) Restructured loan rate (percent of outstanding loans in the portfolio that have ever been restructured) Percent of outstanding loans made to start-ups (percent of outstanding loans made to businesses that were less than a year old at the time of the loan) Lending costs: Cost per loan (operating costs of the loan program/total number of loans disbursed) Operational cost rate (operating costs of the program/average outstanding loans for the year) Lending program cost recovery: Operational self-sufficiency (earned revenues from lending/operating costs of the loan program) Financial self-sufficiency (earned revenues from lending/operating and financial costs of the loan program) This guide illustrates a step-by-step process that organizations engaged in microlending can use to generate benchmarking data related to lending on the microtracker site. The Aspen Institute/FIELD. All rights reserved. 3

5 How Community Capital of Vermont Put Data to Work Community Capital of Vermont (CCVT) a CDFI that is engaged in lending across the state of Vermont came to microtracker interested in understanding how its work compared to that of its peers. The organization had gone through a recent transition in leadership and its staff, though experienced in community development lending, was new to the microenterprise field. In thinking through its strategy and priorities for the coming years, the staff and board wanted to begin with an understanding of how they compared to the rest of the U.S. microenterprise lending industry and, in particular, to organizations with a similar market and focus: operating statewide in largely rural settings. Staff hypothesized that the organization s loan performance was comparable to that of its peers, but that the organization was relatively inefficient in deploying its capital in other words, that its costs were high relative to the level of lending. To benchmark its performance, microtracker staff helped CCVT to generate data on its lending using the key indicators identified above. It also worked with the organization to identify key peer groups credit-led microenterprise organizations, statewide lending organizations, and rural lenders and a set of individual microlending organizations that it could consider as peers, against which to compare its data. The organizations selected included Mountain BizWorks in Asheville, NC; Mercy Corps Northwest in Portland, OR; and the Wisconsin Women s Business Initiative Corporation (WWBIC) in Milwaukee. All three organizations served large geographic regions that included rural markets. WWBIC, in particular, was a high-performing lender that had experienced significant recent growth. CCVT staff used the process described in this guide to compile data on the key lending indicators for these peer organizations. What the staff found surprised them: that contrary to their original hypotheses, the organization s loan performance was relatively weak compared to peer organizations, while its lending costs and level of cost recovery were relatively strong. Staff presented the benchmarking data to the board, which it found to be a useful process in terms of bringing a fresh set of eyes to the data. The ensuing discussion allowed the organization to identify what it did well and what it did less effectively. Concluding that its primary challenge was the low level of loan production, staff worked with a consultant to evaluate CCVT s loan product and develop a set of proposed changes to the loan program. These will be presented to the board in As executive director Martin Hahn notes, using microtracker to benchmark its lending performance has enabled us to see the path to making needed changes in our loan program. A Step-by-Step Guide Get your organization started in the benchmarking process by tapping into the resources at your disposal via the microtracker site. Here s a step-by-step guide on how to benchmark your loan program. The Aspen Institute/FIELD. All rights reserved. 4

6 Step 1: Organize the data First, review the metrics above that are available to you and choose those of most interest to your organization. CCVT set up this simple Excel spreadsheet to list out the data they mined on microtracker to get a visual comparison on how they stacked up against their peers: The first column should be filled out for your own organization input as much information as possible around these measures. To see how your organization compares, here are some common ways to look at the data in microtracker Step 2: Select your peers Create columns with the comparisons you d like to make. Remember that CCVT was most interested in looking at credit-led programs that lent statewide Common Comparisons and had a rural focus. But staff also wanted to see how top performers fared, and it is always useful to get a sense of the wider field and see the performance of all programs submitting information on this measure. All programs reporting: gives you the broadest look at the field with data for all programs reporting on that measure. Program focus: distinguishes between an organization s main line of business lending or training. Top performing: gives you the threshold value required to be among the top performing 20 percent of programs reporting on a specific measure. You can also cut the data by Geography, Budget, Staff Size, Volume etc. The Aspen Institute/FIELD. All rights reserved. 5

7 Step 3: Start mining the data First, let s focus on these three peer groups: all reporting programs, credit-led programs and top performers. Found in Raw Data Section All these measures can be found in the Raw Data sections of the Analyze page detailed below. In the toolbar, click the Analyze link and choose from several buckets of information Size and Diversity, Microfinance Volume and Performance, Business Development Services Volume and Performance, and the Cost and Sustainability of Micro. The Aspen Institute/FIELD. All rights reserved. 6

8 Once you ve chosen your content area, you ll have three choices to review the data the Raw Data tables of MicroTest data, some Quick Reports summarizing MicroTest data graphically, or a Report Builder tool to pick and choose U.S. Microenterprise Census measures that you re most interested in. Again, this last report tool draws from a wider data set on a more limited set of measures. For the first three peer comparisons, let s choose Raw Data. You ll get a data table that looks like the table excerpted below. Pull out the data points you re most interested in and fill in your Excel table in the columns for All Program Medians, Credit-Led Program Medians, and Top Performing 1/5 of Programs. The Aspen Institute/FIELD. All rights reserved. 7

9 For our next peer comparisons to statewide and rural organizations, and to build data for comparisons to individual peer organizations you ll need to use the Report Builder tool. Data for these comparisons found in Report Builder Follow each of the guided steps to build your report. You can choose from recent years of data and then select your indicators The Aspen Institute/FIELD. All rights reserved. 8

10 Next you can choose specific individual programs (those available via microtracker) to bring into your report. In CCVT s case we brought in Mountain BizWorks. And, finally, you can further refine your data search to meet your needs. In this case we selected programs that operate Statewide and also indicated that they were Lenders However, there are many other ways you can refine the data to analyze (i.e. budget size, staff size, percent of women served, etc.). Tip! Start by choosing one or two indicators to see how sizable the pool is that you are trying to evaluate. Here s your custom report looking at microenterprise volume/size and diversity. In blue you ll see the individual program we chose Mountain BizWorks, and in red you ll see national median data for lenders that indicate that they operate statewide. The Aspen Institute/FIELD. All rights reserved. 9

11 If you hover over the individual bars, you can see the number of organizations reporting into those variables and the median number for the group. In this example above looking at the percentage of women served by an MDO, there are 37 organizations reporting into this variable and the median for that that group is 51 percent. Let s go one step further. If you click on the link for Source Values, you will be taken to the list of those 37 organizations and you can see the data reported by the individual MDOs. Tip! This is also an excellent way of finding individual organizations against which to benchmark your organization. After going through several of the buckets of available data on microtracker, your Excel spreadsheet should now be complete. Now you have side-by-side comparisons with different peer groups to see where your organization s lending might be excelling, where it is on par or where there may be opportunities for improvement. The Aspen Institute/FIELD. All rights reserved. 10

12 FIELD The Aspen Institute One Dupont Circle, NW, Suite 700 Washington, DC