Monthly Archives: December 2008

The worse it is, the better it is: Your grant story needs to get the money

A client recently said that she was moved by a description Isaac wrote of her target area in the needs assessment of her proposal, but she asked if we could make it more hopeful. Isaac strongly discouraged her—not as a way of disparaging her neighborhood, but because describing an area as terribly depressed makes the application more likely to be funded. Consequently, a grant writer has a strong incentive to paint as bleak a word picture as possible. Paradoxically, the worse a target area is, the better it is for grant writers, and the smart strategy is to tell a story about doom and gloom that can only be alleviated by the creation of the program being proposed in the application.*

Some programs will even come and out say that the worse things are, the more points you’ll get. For example, when HUD ran Youthbuild, the RFPs did this explicitly; the 2005 RFP has a subsection of need entitled “Poverty” and gave this point breakdown:

1) Less than the national average—0 points.
(2) Equal to but less than twice the national average—1 points.
(3) Twice but less than three times the national average—3 points.
(4) Three or more times the national average—5 points.

Although most RFPs won’t give particular point values to particular numbers, reviewers will tend to do so: if they read about one application from an agency proposing to serve an area where the poverty rate is 33%, and they know the national average is around 12%, they’re more likely to want to fund that application than one serving an area with a poverty rate of, say, 15%. It

It’s important not to lie, but you can and should be selective in how you present data; there is even a funny book called How to Lie With Statistics regarding the subject, and Amazon says the book shows how the “terror [of numbers] translate[s] to blind acceptance of authority.” If you master statistics, you can make the reviewer think that visiting your target area would be terrifying and that he or she should therefore shower it with money.

In any event, the main point is that you shouldn’t lie about a target area’s characteristics: if the official unemployment rate for Dubuque is eight percent—two percent higher than the national average—it’s unethical to say it’s twelve percent, and even were that not unethical, it would also be a fantastically bad idea to make up easily verifiable statistics like unemployment rates. But if the unemployment rate is eight percent for Dubuque as a city, you could argue that it’s probably twice as high for the target population, which is less educated, lives in a worse part of town, and has members whose criminal records will likely prevent them from obtaining living-wage jobs. Then you’re telling a story and extrapolating from the data, and the worse you can make that story sound, the better off you’ll be when funding decisions are made. If you make an educated guess that, although the Dubuque unemployment rate is 8%, the rate among the target population might be closer to 25%, you’re being a smart grant writer.

You can go further: unemployment rates count only people who are actively looking for work. Those who have given up and no longer seek employment aren’t considered unemployed. Although this is well-known among economists and others who study issues around unemployment, this is the kind of fact you can argue, as a lawyer might, that understates the Dubuque unemployment rate more than it would the national rate. Suddenly, things look even grimmer than official statistics indicate and you haven’t lied. Think of yourself as a lawyer: a defense attorney isn’t trying to decide whether his or her client is guilty. The attorney’s job is make the best case for his or her client. Legal ethics prevent the lawyer from lying altogether—insert lawyer joke here—but not from arguing that the facts should be seen in the light most favorable to the lawyer’s client.

The grant writer should make the most compelling case for funding the application in question, and part of that is through writing a needs assessment that makes it seem the world is ending, as Isaac wrote about in the linked post. If Census data, for example, says that median household income is relatively high, but the percentage of high school graduates is relatively low, you should leave off household income and write about education and its link to income. If median household income is high relative to the state but low relative to the nation, construct a table comparing median household income from the target area to the national averages, which will make the situation look worse than it actually is.

We’ve discussed this issue before: for example, in Surfing the Grant Waves: How to Deal with Social and Funding Wind Shifts, we note that “In some ways, the worse things are, the better they are for nonprofits, because funding is likely to follow the broad contours of social issues.” That’s true at the level of an individual agency too. In our November Links post, we write:

* The New Republic has an article based on a Brookings Institute piece that deconstructs the small-town USA mythology regularly propagated in proposals:

But the idea that we are a nation of small towns is fundamentally incorrect. The real America isn’t found in cities or suburbs or small towns, but in the metropolitan areas or “metros” that bring all these places into economic and social union.

Think of this as a prelude to an eventual post on the subject of grantwriter as mythmaker. And if you’re interested in myth as a broader subject, see Joseph Campbell’s Myths to Live By. He’s the same guy who wrote Hero With a Thousand Faces, the book that, most famously, provided the outline for Star Wars.

A few caveats on the above are, however, in order. This post helps explain how the myth of a place is created. I’ve given one version of the myth, involving a target area being as bad as anywhere, which is usually but not always a good strategy. Some places that seem statistically and culturally average in many ways can come to represent a problem taken as a whole, and an ordinary client can become a representative sample whose problems reflect vast swaths of America, so whatever problems they have, everyone has. This style of argument became representative when suburban public schools applied for grants post-Columbine, as we describe in Surfing the Grant Waves.

Consequently, one can construct an argument for urban, rural, or suburban school districts: for the first, one argues about bad test scores, low family incomes, low educational attainment, and the like. For the second, one argues that long distances, hidden drug abuse, and the paucity of resources combine to create educational failure. For suburban districts, one argues that the malaise of contemporary society exists beneath the veneer of happy teenagers, and that when one lifts up and peers beneath the rock, a whole angry ecology seethes. Think of the various books about suburban disappointment and disillusionment: Richard Yates’ Revolutionary Road, Tom Perrotta’s Little Children, John O’Hara’s Appointment in Samarra, and much of Sinclair Lewis. Zenith City in Lewis’ Babbitt is a particularly good example. One can portray even fairly tony suburbs as caldrons of discontent.

Another factor might discourage using the blasted wastelands argument, and this objection is most often raised by city managers, mayors, and school superintendents, because they’ve often spent their careers running around trying to promote their version of Babbitt’s Zenith City, claiming that the sewage plant between the school house and police station is actually quite aesthetically pleasing and lends character to Zenith, despite the smell. If they sign an application saying that Zenith City is hell’s half acre, that its citizens are illiterate, and that meth production and distribution is the primary industry, and that application’s content hits the local paper or bigwig blogger, then the Zenith city manager, mayor, or superintendent is going to be very uncomfortable in the resulting squall. On the other hand, if the city manager, mayor, or superintendent doesn’t note the illiteracy of its citizens and meth problem, he or she might not be funded. Smart city managers, mayors, or superintendents seize the money.

Sometimes these other considerations can outweigh the grant. When I told Isaac about the post, he responded with a story** about his time working for the City of Lynwood in California, when he wrote a funded proposal to exterminate rats that the city manager declined because he’d rather have the rats than the publicity about getting rid of the rats. In addition, a few years ago, a client wanted money for a giant mammogram machine because the women in the target area were a bit on the large side from eating the local cheeses and dairy products. So we wrote about that in the needs section, but the client demanded we take it out because it might offend local sensibilities, and we couldn’t use the best argument in favor of the expensive machine. The proposal wasn’t funded—maybe not for that reason, but not using it couldn’t have helped. Your job as a grant writer is most frequently to portray blasted wastelands that the proposed program will turn into a harmonious Dionysian garden.

* All this also helps explain why a “batting average” or “track record” figure is useless regarding general purpose grant writers, as we describe in this FAQ question. We don’t know if our clients are going to come from Beverly Hills or from places where most residents haven’t graduated from high school. From a grant writing perspective, a client from the latter place might be more likely to be funded than someone from Beverly Hills.

** Virtually anytime I mention something grant-related, Isaac has a story about it.

The Secrets of Matching Funds Exposed: Release the Hounds and Let the Scavenger Hunt Begin

This is YouthBuild season at Seliger + Associates, so I spent most of the weekend slaving over a hot YouthBuild proposal. YouthBuild has a curious take on the somewhat mysterious concept of “matching funds.” Newly minted grant writers will soon learn that there are two basic types of matching funds: in-kind and cash. The former can be anything from the value of food given to clients to volunteer time,* while the latter is just as it sounds, real money, which most agencies are as likely to encounter as a unicorn.

In working with matching funds, the following concepts are essential to understand, particularly for federal proposals:

  • Matching funds can be calculated in two ways: as a percentage of the grant amount or of the project cost. If the RFP specifies 25% of the grant and the maximum grant is $100,000, the required match is $25,000. But, if the RFP specifies 25% of the project cost and you have a match of $25,000, the project cost is $125,000 and the required match is $31,250, so get your tin cup out and look for more match.
  • Previously received funds, along with already expended funds, usually cannot be used as matches.
  • Estimated values for in-kind resources should be included in commitment letters and should be realistic. Several years ago, we wrote a proposal for a small school district in Illinois that claimed (against our advice) the value of its high school, about $5 million or so, as a match. The proposal was not funded.
  • Keep in mind that, if you are funded, you will have to track and account for all matching funds. If you don’t and you are unlucky enough to get a program audit, any matching funds for which you cannot account will be disallowed and you will have to pay an equivalent amount back to the feds. This is likely to ruin your day and maybe put your agency out of business, so be prepared to track those matching funds!
  • Unless the RFP says that you will receive additional points for a match above the minimum, there is no reason to go over the minimum. Similarly, if there is no matching requirement, don’t waste time getting match letters. Savor a fine single malt scotch instead (I like 18-Year-Old or Nadurra Cask Strength Glenlivet).
  • When your agency cannot come up with enough matching funds, be creative. You can try to claim indirect costs as a match. For example, if you have an approved or imagined indirect cost rate of 25% and the required match is 20%, voilà: you have your match. While not strictly in keeping with federal regulations, I’ve made this work lots of times, because federal program officers are often not exactly up to speed on their own regs and grant reviewers almost never are. A strong argument can be made that this counts—unlike in the example of the hapless school district above. Another strategy is to imagine in-kind support from the applicant (e.g., use of facilities, equipment, training et al), which usually does not require a letter, since applicants can self-certify their own support.

Confused yet? For YouthBuild, the Department of Labor has managed to take this fairly convoluted concept and add yet more knots. In the YouthBuild SGA*, there are actually two kinds of matching funds: “match” and “leveraged funds.” The “match” is more or less as described above, except that you can only use funds as a match that is “an allowable charge for Federal grant funds.” So you can’t count those free escort services that have been offered to your trainees by the local branch of the Emperors Club VIP, unless you’re Eliot Spitzer.

“Leveraged funds,” however, can be pretty much anything you can dream up, so you may want to visit the local Porsche dealer to see if they will donate a 911 for use in transporting clients. After the grant award, one only has to account for the claimed match, not leveraged funds, so YouthBuild applicants often come up with tons of leveraged funds. But, what the DOL gives, the DOL also taketh away by effectively limiting the number of match/leveraging letters to 16 pages. In YouthBuild proposals, the real fun is in trying to decide which letters should be designated as match and which as leveraged funds, a process that usually takes place under extreme pressure right before the deadline. After this process, it’s a good time to return to the Glenlivet.

When planning a proposal, look at the matching requirements at the start of the process and line up your letters. It is a time honored tradition for nonprofits to “trade” match letters with each other for the same or different submissions, so feel free to engage in some creative mutual back scratching. Think of matching funds as an elaborate scavenger hunt game and you’ll be fine.

One other important point: make the match realistic relative to the size of grant. Claim to leverage $3 million for a $150,000 application is silly. If you do something like that, the reviewer will pop up like a prairie dog and say, “Look at this guy!”, so all her colleagues can laugh at your expense. There isn’t a hard and fast limit to this, but leveraging more than $1:$1 is very uncommon.

* Unless your volunteer is a physician or has just won the Nobel Prize in physics, it is standard to value volunteer time at $10/hour, so a FTE volunteer is worth $20,800 @ 2,080 hours in a person year.

** For reasons that are not clear, the Department of Labor uses the cryptic phrase, “Solicitation for Grant Applications” (SGA) instead of the much more commonly used “Request for Proposals” (RFP). Whatever they call it, DOL SGAs are still mostly gobbledygook.

‘Tis the Season for Government Folly, Fa La La La La La La La L.A.!

Christmas comes but once a year, but there is no end to misguided federal efforts to solve the crisis of the day. Leaving aside the collapsing financial sector, doomed US car industry, etc., the crisis de jure is the housing meltdown.* Lost in the current hysteria is the $4 billion Neighborhood Stabilization Program (NSP) passed by Congress in July to address the boatloads of vacant and abandoned housing caused by the subprime lending mess.** “Housing-Crisis Grants Force Cities to Make Tough Choices,” a December 5, 2008 Wall Street Journal article by Michael M. Phillips and Bobby White, highlights some of the problems with NSP while also illustrating the folderol that always emerges when the feds try to solve a problem quickly.

NSP funds are awarded on a “formula” basis, which means that HUD used some sort of alchemy to divvy up the $4 billion, probably to CDBG-eligible cities and counties. Of course, when tons of jurisdictions dip their cup in into the same punch bowl, it’s not surprising that some only get a sip. And, unlike competitive programs in which applicants actually have to demonstrate real need and workable solutions, the cities and counties just have to prepare a so called “action plan” for the NSP. As Hamlet so eloquently said, “ay, there’s the rub“.

The WSJ article tells the tale of Avondale, AZ, which “got” $2.5 million in NSP funds. So far, so good. The city is thinking about using 25% of these funds to rehab two vacant townhouses, fill in an abandoned pool and build two units on the site. That only leaves about 2,600 other vacant, foreclosed or nearly foreclosed housing units in the city to take care of. If I’ve done my math right, at this rate Avondale only needs $1.625 billion to solve their problem. Better still, despite the obvious crisis, no jurisdictions have been able to spend their NSP money because they have to have an approved action plan to get the funds, and HUD recently announced that all the submitted action plans required “substantial amendments,” which were due December 1. Who knows when the action plans, which are sounding more like inaction plans, will be approved, since even HUD drones have to take time off for a little shopping and egg nog this time of year.

Avondale’s start and stop efforts are playing out all across America. I was talking to one of our clients in South Central Los Angeles on Friday about the WSJ article and the slow motion Danse Macabre going on with public and private efforts to address the housing problems in L.A. Our client has been going to endless meetings to discuss the NSP program and is still waiting around for the amended action plans to be approved. When the plans are finally approved, the City and County will have to run RFP processes to select nonprofits like his to spend the money and do the work. In the meantime, this agency, which is an experienced YouthBuild provider that has built and rehabilitated hundreds of houses over the years, is doing nothing.

One irony of the housing crisis is that HUD has a perfectly good program, Section 203(k), to recycle vacant HUD houses by letting nonprofits, like our South Central client, buy them for a nominal amount, rehab them, and resell them to low-income buyers. Since there are thousands of vacant and foreclosed houses in LA, one would think the 203(k) program would be booming. Not so according to our client, who told me that virtually no 203(k) houses are available in LA. To use the 203(k) program, HUD must own the vacant house, meaning that the house must have been originally financed through the Federal Housing Administration (FHA). Due to the huge housing price increases in L.A. during the boom years, as a practical matter FHA financing could not be used because its loan limits were too low. So subprime private sector loans, sold to Fannie Mae and Freddie Mac, were used to finance the transactions, with the vacant foreclosed houses ending up owned by a gaggle of private lenders and investors, not HUD. Despite the established infrastructure for the 203(k) program, it is not being used to recycle the tsunami of vacant houses in L.A. and other cities, leaving our client and thousands of other similar nonprofit housing rehab organizations sitting on the sidelines.

This sad tale of woe does not make me optimistic about the really big stimulus programs that will emerge from Congress shortly. While it will be Fat City for grant writers and lots of grants will be available for frisky nonprofit and public agencies, don’t expect the funds to fix many problems.

Now that I’ve depressed you sufficiently, how about joining me in a Mai Tai or three, as I’ve recently reacquired a taste for aged rum. A fine Mai Tai helps pass the time waiting for action plans to be approved.

* For an earlier post on the current housing fiasco, see Déjà vu All Over Again—Vacant Houses and What Not to Do About Them.

**After the financial industry $700 billion October bailout and up to $35 billion possible for the auto industry, doesn’t $4 billion seem like a trifle only six months later?