How to Use Logic Models to Show Outcomes from Correlations w/ Steve Boland
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Steve Boland, Managing Partner in Next in Profits, is a nonprofit veteran with over twenty-five years of experience helping charities grow with new ideas in fundraising and communications. Steve has presented over 100 learning sessions on topics such as crowdfunding, engaging corporate philanthropy, and social media strategy for nonprofits.
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How to Use Logic Models to Show Outcomes from Correlations - Grant Training Transcription
Will: Hello, everyone and welcome to How to Use Logic Models to Show Outcomes from Correlations with Steve Boland. This workshop is being recorded and slides will be shared afterwards; so keep your eyes peeled for a follow up email later in terms of reviewing anything from today.
In case it's your first time here this free grant workshop is an Instrumentl partner webinar. These are collaborations between Instrumentl and our community partners to provide free educational opportunities for grant professionals. Our goal is to tackle some sort of problem that you guys often have to face while sharing different ways that Instrumentl's platform can help grant writers win more grants.
Instrumentl is the institutional fundraising platform. If you want to bring grant prospecting, tracking, and management into one place, we can help you do that and save you three hours a week on average while doing so. You can set up your own personalized grant recommendations by using Steve's link on the screen here.
It'll also be shared at the end of the presentation as well. Now, with that housekeeping out of the way, I'm very excited to introduce Steve. Steve is the managing partner in Next in Nonprofits. And they, with over 25 years of experience, helping charities grow with new ideas and fundraising and communications. He's also presented over a hundred learning sessions on topics such as crowdfunding, engaging corporate philanthropy, and social media strategy for nonprofits.
Steve, take it away.
Steve: Will, thanks a lot for the invitation to join you. And again, thanks to everybody who's come into the room. I think that it is so exciting to be able to share some of these ideas and keep learning about how we can better do things. I'm really excited in particular that Austin's here with us as a data intern.
We'll talk more about that in a little bit, but glad everyone's able to join us. Just a quick before we -- as we're getting started here, we've already asked you to throw in your name and organization, if you would, in the chat book. Love to hear some examples of what you're hearing as you're looking at grants or what people are asking to see in terms of their outcomes data.
We're going to go over logic models and a few other things in a minute, differentiating outputs and outcomes, but I'm more interested for those of you that are familiar with that difference already in what grant organizations are seeking in that kind of long-term outcomes, impact, change space. We'll get into the precursors to all those things as we move forward.
But love to hear what you're seeing and what people are asking for. So throw that in the chat. We'll try to come back to it as we go through these things. Oh, yeah. I'm looking right now about policy think tanks are looking at, you know, really connecting their work to a long-term change versus their short-term work and how difficult that is.
I hear you. That's a really interesting challenge. So keep throwing those ideas and I'm going to move forward. We'll come back to those in a little bit. As Will said, my name is Steve Boland. I started working in logic models when I did a graduate program in nonprofit management at Hamline University in 2009, and have been so excited to carry that work forward to the clients that we serve at Next to Nonprofits because I love the idea of it, but I do think that the implementation with our grantmaking partners is a challenge.
And I think that as we think about how we seek for the right partners in the grants world, how we're using tools like Instrumentl to find them, understanding that relationship of are we lining up on the impact side of things is just a really important part of what we do. And I just love doing that part of the work.
So we're going to talk a little bit today just about logic models. First, a little review for those of you that haven't been really introduced to the concepts before more of that, but then talk a little bit more about data sources that we currently have access to.
Talking about how we can look at what we know about ourselves and connect that information with outside existing data sources and start learning from that to make connections that are a little bit shy of, you know, like rock solid science, but something that could really help move the conversation forward with our grantmaking partners to understand our work.
So I said let's kick it old school because my first introduction to logic models was really back at the W.K. Kellogg Foundations model and guide still available on their website. There's a link here in the program. So as you get these slides later, if you haven't downloaded their logic model guide from W.K. Kellogg, I highly recommend it as a resource in thinking about both logic models and more specifically the long-term impact from your data.
But I think it's good for us to just review for a moment for people that are newer to this. And even those of us that have been around a little while, what's the thinking behind that that grantmakers may want to understand about our work. And this very simplified version that's in the W.K. Kellogg Foundation work, kind of thinks about the idea of a family trip as your non-profit program.
Just to have everybody have a frame of reference, thinking that to get anything done we need inputs, we need outputs or activities, and looking at what those are. And then there's going to be some outcomes and long-term impact that we really want to be able to share with the world about why we're doing what we're doing.
So as we look at this example here, if we want to have a family vacation, there's going to be some inputs that we need. You know information on flight schedules if we're going to leave town, when we could go, information on our own family's schedules to be able to coordinate those things.
All of these pieces are necessary inputs. I find it fun that in this particular example, they didn't mention money. So certainly this is a necessary input for an awful lot of what we do which is our conversation with our grant partners, right? We take that input of financial resources and create something with it that leads to impact, leads to change.
But in this example, keeping it simple, a few things that we need for inputs. We then take those inputs and do something with them. We create a specific flight schedule. We get tickets, we arrange for ground transportation. We do all of those things so that we can have the outputs of money saved and family members having a really good time. But the idea of family members having a really good time and actually going on vacation, that's not the end of the story.
And I think that's where our grantmaking partners are hoping we can lead them further to why do we do family vacations? It's not just about that one day that we happen to be on the beach relaxing somewhere. It's about creating that family relationship that lasts a long time, that has a common bond, that has these things that we reflect on that build connection to people.
And most of us have that opportunity in our work, too, to think about that long-term, what are we really trying to get done in the world? So I think reviewing inputs, we need resources, people, money, volunteers, information, whatever those inputs may be to create some short-term outputs to look at where those outcomes are going to change in the long run to a real impact that we're trying to get to.
So I think going through that exercise and using that format as described in the W.K. Kellogg piece or any other tool that you like for building logic models is a really good idea to do independent of any one grantmaker's request. Do that for the organization to really think through what we are trying to do here?
So at Next to Nonprofits, we serve a few different nonprofit organizations at any given moment, seven or eight at a time. And those organizations all have different visions of what their outcomes are. But those visions can get a little work the moment you tell them that the grantmaker is seeking this long-term impact, the grantmaker wants that.
And then immediately the nonprofit is like, oh, yeah, we do that. Completely. That's absolutely us. We've been doing that since the beginning. It's who we are. And you're like, wait a minute. If we go back and do the logic model work independent of what that grantmaker wants and think about our impact, how much are we really aligning with that?
Are we really the right fit? Or should we be moving on to another opportunity that's maybe a better fit for who we are. So getting that work done early and saving it in your Instrumentl profile so that as you're reviewing any individual opportunity that may surface from using the tool, you can quickly access and look in your document library and go, right.
Let me just review our language against what this funder is thinking and really see are we in the same space or should we be taking a pass on this application and looking down a little bit more at other things that could be a better fit rather than trying to build a logic model that actually transmogrifies our work into what we think they want to see.
Have I ever done that in my life? Oh, yes, I have. I sure, absolutely have. And I'm sure there's people on the call going, yep. I've done that before. But our hope being that as you sort through all of the opportunities that surface using your grant development tool, I use Instrumentl, but whatever the one may be that you're using, that we're going through that with the eye on our logic model is already got these outcomes in mind. These are the impacts we're talking about. How are we lining up with that?
Impact on, I see from Lee Stewart in the chat that impact timelines are hardly ever funded. Right. They're really looking at funding the outputs you're doing this year towards the vision that those outcomes and impacts later are going to be what you're shooting for.
But I absolutely agree that not every funder and in fact, most of them, aren't willing to put the money down to really think about a longitudinal impact over a 15, 20, whatever year period. Good for us to keep in mind. All right. I do want to just take one more moment on the logic model thing before we move on to differentiate that output, outcomes, impact conversation.
Because I do think that mostly what I see when I look at notices of funding availability, or other types of requests for proposals, anything that may be available in our grant seeking work an awful lot of the language is really talking about outputs. They want to know how many of a thing you're going to do in a period that they are funding you for.
So I pulled a quick example from one thing here to just say, you know, in this we're going to serve 86 active agreement stakeholders as of this date, 49 in the partnership fund as of that time, estimated total program participation of these numbers. This is what I see most often when I'm doing my work.
I'm guessing a lot of you also are just seeing a lot of focus on outputs. It's not that every funder doesn't really want to look at outcomes from that work, but I do think that we see this as one component of the full logic model story, and it's good for us to help those funders connect the dots, too, that if they're only asking for this, then, you know, what are we really getting to?
As opposed to the outcome of the work. If the output of the work is to help a family get access to a job this year, for example, that's great. They got a job. We have a checkbox to say we delivered a service that we think has a good impact, but the outcomes over the longer term that we're really thinking about is, you know, how is that household income improving for that family over time?
Is this job going to be the thing that helps them see an increase in overall ability to meet their needs and goals? Or are they part of this declining curve that we see over multiple years of the impact of real median household income in the United States sort of dropping against a 1984 average. Those are important things for us to be able to bring into the conversation with our funding partners.
Yes, we absolutely think that today's job is a good step forward, but our long-term goal with this client is to see that household income improve over time. And that's an outcome, not necessarily an output that they may not be measuring in their request. Towards the idea of impact that, you know, that long-term outcome of improved household income is a wonderful thing, but the impact that we're looking for is an elimination of poverty within that family or community or whatever it might be.
And that's the big deal at the end of this whole logic model that somebody had indicated Lee, I think earlier, that long-term impact doesn't usually get funded in any individual grant cycle. And that's all right for what it is. But it's good for us to be able to make that connection of getting people on that improved household income thing towards the idea of they're going to stabilize their lives out of cycles of poverty, for example, or whatever your particular nonprofit mission may be, to be able to talk about that our real impact here isn't just this one family got a job or that family had this thing, but we're nudging the needle a little bit on poverty in America in at least our community or whatever the longer-term impact you're trying to raise.
So with that said, it would be wonderful if all of us that are on this call right now could be talking about longitudinal studies of impact, right? What we want to do is have those outcomes that we're seeking, or even the outputs that we've created, measuring their impact over some time, assuming that our impact takes time to create and mostly impact takes time to create. I'm sure there are some non-profits on this video right now that are thinking, well, our outcomes, our impact, really, actually fairly quick to get to.
And that's great, but a lot of us are probably looking at much longer term change. And then we'd really love to be able to talk about the gold standard of a longitudinal study, where we have a control group, we have our group that we've had impact on, and we follow them over a period of time to be able to see, can we understand a differentiation between the folks we've interacted with and folks that we haven't interacted with and are we making that impact?
Or is it some other change? Because if you just look at the trend in and of itself does household income, you know, continue to sort of peter out in America right now? Yes. That's not to say that your charity didn't do good work. It is to say that the broader community is suffering and all of us are having that challenge right now.
So can we look at how our people fare against that broader community or against some control group or whatnot? That'd be the wonderful thing to get to. However, the real problem with that gold standard is it takes a lot of gold to make that kind of thing happen. That we absolutely don't have the resources in most cases to revisit survey data with past clients, to track them as they move, to talk to them as they have lots of life changes and to keep coming and going.
And most of our granting partners honestly, are not putting dollars on the table to do that kind of funding with us. One of the things I like about Instrumentl is it does make academic research opportunities more visible, and it's easier to see if there are things that might really partner out and see that impact over time.
But for most of the charities that I work with anyway, we don't get to do the longitudinal study. So that's unfortunate, but it's what we often see. So, what do we do? We're in this world where sometimes our funding partners want to talk about impact. Sometimes they are more focused on outcomes, but we could bring them to that impact conversation, which may make us a more competitive application.
But we also probably are not going to be able to do independent, verifiable longitudinal studies to demonstrate that we're the only cause of that impact. So where's our cheat in the meantime? I think our first thing to do is to get our own data together about our outcomes. And we've been probably gathering that for our grants anyway.
We know that we served X number of people in the jobs program or Y number of people in the housing program or X number of visitors to the theater program this year. We probably have those output data sets. What we need is some comparison data to talk about that and then understand where we can go from there.
So many of you may have already used this, but I'm a big fan of going to the U.S. Census Bureau, not just for the direct census data, but more impactfully and I think importantly for the American community survey data. And the link is on this page, again, when you get the slides later on, you'll be able to click through and see these pieces where I'm in Minnesota.
I may do a geo select to narrow down my data to Minnesota geographies to learn about the nature of populations like the ones I serve. Getting the best available public information that's accessible. And the American community survey does a pretty good job of using statistical modeling to get at stuff that the census itself doesn't often report.
And doesn't give us that data. So if you're looking at the quality of life issues or the long-term impact issues for your particular client base, and you're thinking, the census doesn't ask those questions. The American community survey might. And it's a really good way of beginning to get a comparative data set of the people I serve look like this, the people in my community that we could have served have these characteristics.
And here's what their income looks like or their ability to participate in childcare or whatever the question you're trying to solve. We can get a lot of that data through places like the U.S. Census Bureau and the American community survey. I will caution that this is not the easiest site to use. So if you're not terribly comfortable with it, it can be a little bit of a frustrating experience.
And we are going to talk a little bit about getting some help to interpret sites like this. But it's here and it's no cost to you to create the kinds of filters that would do what you want to do down to the census track level if you want to do that. It's possible to go ahead and collect sites down to that level and it gives us some really good information.
International sources of data like the U.S. Census. I'm afraid I'm not a good person for that. If there's anybody on the call that knows if there are other sources of data that help try to do statistical modeling on baseline, stuff like that outside of the United States, please share them in the chat.
We'll try to highlight them. Will, if you see something like that, come through. Let me know so that we can make sure to highlight that answer to that question as it came in. Thanks, Will. So that's one source. I like to double check that the philanthropic organizations I'm working with don't in fact already have their own sources that they're sharing and making available.
Here in Minnesota, we've been very fortunate that the Wilder Foundation has put a fair amount of resources into something they call Minnesota Compass, which is a lot of publicly accessible data that has a much easier front-end to use where the American community survey and the census bureau stuff is a little bit harder to navigate.
These folks have already sort of pulled together traditional neighborhoods within large metropolitan areas as a group, counties are very easily navigable already pretty easy to do. But you can also draw your own custom geography with this tool. And I've seen other philanthropic organizations that do similar things where they've kind of taken all of that data that's a little bit harder to understand and brought it together into something that's more solvable for their community to use.
Which in turn means that they know that they've got some comfort with the data set you were showing them because it's their own information. You're just bringing it together in a way that shows our data from the people that we serve, it looks like this population over here, a potential service, and then we'll get into extrapolation about the impacts in a little bit.
But I think checking out what might be available from our philanthropic partners is a wonderful way to bridge a gap between what the American community survey can do and what is more publicly available.
Just another quick version of that same data as it looks into the ability to draw from a distance out of a central point, where it starts breaking down age by customer profile. And it shows that within this geography of that circle around St. Paul, Minnesota, you know, I'm capturing about 800,000 people.
So if that's a little too broad or a little too narrow, I can change that circle a little bit, but I love the ability to see very quickly. I want a data set that's meaningful, but I don't want it to be overwhelming. And sometimes I need to adjust my profile a little bit based on what's actually being shown.
So again, quick examples of what that looks like there. Shannon from Rochester. Yeah, Minnesota! Shannon, I don't know if you're using the Minnesota compass tool. Take a look. Very helpful, I think, but available almost anywhere in the United States. And again, I don't know if this is an international company, so presumably similar access to other places.
Which has a nonprofit program to make a more affordable version of their product available to charities. It's known primarily as a GIS solution, you know, geographic information systems where it's thinking more about mapping. And absolutely you can create some really interesting mapping solutions from this tool. And I think it's great.
So take a look at their costs for their nonprofit program and see whether it might be worth it to you to do what I have often done with SRI, because a lot of this comparative data set thing is pretty good for a year or two at a time is just to try the free trial. Grab some information that I need. And exit the free trial rather than having to think about, do I justify the cost of the nonprofit program?
The for-profit program is a fairly expensive tool. This is something that major corporations pay a lot of money for. So, you know, several thousands of dollars a month can be a not unusual subscription fee. The nonprofit program is going to, you know, range into the hundreds of dollars a month sometimes. Depends on the level of access you need. Definitely check with them about what that looks like. If you're doing a lot of customized reporting and you really want to have something that functions extremely well, this may be the thing that saves you a lot of time against the census or other tools.
But more importantly, I think it gives us access to data that isn't necessarily collected or available in those spaces to help us draw our analogies about impact. So I love this one in particular. But I'm going to mention the business analyst tool within ArcGIS that is an SRI product as a specific thing that functions on spatial business analytics. And that's great gobbledygook speak, but what it really means if you pull out profiles from this is a lot more in-depth information pulled from multiple for-profit sources augmenting government sources.
So it takes information about cell phone subscriptions and who's got access to internet service in what areas at what pricing structures and how those people all interrelate and use their resources, where it can indicate to you those questions about if they have a really good job and they're earning a fair amount of money, does that mean they're out of poverty?
Or do we look at rental income against those costs against the cost of mobile phone and internet access and food, and find out that even that higher level of service leads and with very little disposable income to actually do anything with because these tools are linking into those other sources and allowing you to build customized versions of reports based on both geography.
Like I want to see this county or whatever, or a census track or whatever level, but also on more independent features like drive time. And for communities that are really dependent on automobile traffic for peoples being able to get to services, those are meaningful statistics more than just I live in this county, but rather how long does it take me to get from here to there if I use an automobile because then I might actually find better access to the services and things that make sense to me over a county border than I would in my own county than it would be to go somewhere else.
And those drive time stats are tremendously helpful in talking about who really has access to who I am as a service provider? It's not just people that live within a 10-mile radius, but it might be people that live within a 15-minute drive. And that's a very different measure in some parts of our communities.
And I think it's really interesting that SRI has built all of the customization of pulling that information together about education levels, subscriptions to different types of services, access to types of shops. It will actually show people that have access to healthy, lower cost food options by drive time, rather than just necessarily the independent list of, you know, I have X amount of money to buy food.
Which is great, but if you happen to live in a food desert, it doesn't really help you. If you know you have to drive 20 minutes to get anywhere that has healthy food choices. So these tools can be really useful in pulling that information together. I think it's really interesting. Oh, I do see in the chat, we've got some international database options for social sciences that have been shared.
So direction of open access journals, [Indistinct] publishing that one I'd actually have used in the past through Google. Interesting pieces. So, yep. Take a look at all that for access to where do we get our comparative data sets? So we've got our own data that we've gathered in our output section.
We've got the data of people that are around us that we can learn about what people like them look like and what they look like over time, both from American community surveys and private sources and our philanthropic partners. Now we have to do a little bit of magic for them to extrapolate how we think our impact looks on populations like that over time, based on the outputs that we're producing.
So where do I go to learn about how changes happen over time within populations? Google Scholar is a fabulous place to start to get that extrapolated data to say who has studied things like household inequality or income inequality. What might that look like? Housing access over time, people that have access to the arts in communities, social movements. Earlier today, as we were looking about, somebody said you're running a C4 organization that their partners really want to talk about social impacts over time that they're creating. Who's studying which tactics are the most effective in creating social change that measures those tactics over time that we can grab their data and run with.
So I like to start with a simple scholar.google.com search because it really does eliminate a tremendous amount of cruft out of the way when we're looking for our impact information. And then we can start doing some quick searches for responses within. These days and this kind of gets to that EBSCO piece in other words. Krysta just has, in other words, make friends with your local reference librarian and other people and institutions at academia. We're going to cover that. Really good call, Krysta, that we want to look at the raw data access to be able to do our own interpretations. And in some cases that is publicly accessible when we just go do the research about who's gathered the data set.
In this particular version about income inequality over time, these folks have put their data sets into GitHub. And GitHub as a free data depository across the world often used for software development, but also academics. People are sharing their results because they need them to be verified independently.
They want their peers to see the actual reference stuff, and you might be able to go in and just get access to the raw data. That assumes that you're capable of interpreting and moving the raw data around and not every nonprofit has that expertise and that skill. So Austin, our data scientists, that's interning right now, you know, here's where you step in, we're going to give you large data sets.
You're going to help us interpret them. Those of us that don't have that available right now, though, there are often very inexpensive ways to get access to the original offers interpretation through their academic study. Just a quick 48-hour access, $10 purchase kind of thing to do this if you don't have access is a great way of getting that comparative data set to say, we see these changes over time in populations like this, we serve this kind of a population that mirrors that. We can make a difference.
So to that point of people like Austin being out there and available, faculty and staff at higher education institutions often have access to those databases and all those sources as a part of their participation in those schools. And you maybe can get their help in accessing that information and interpreting it.
I'm a big fan of internships and data. I think it's a really important thing. Here in Minnesota, a lot of our academic partners use Handshake as a place to get access to those interns where you can, I hope, pair them, pay them a fair wage. Don't just expect that it's going to be a free college project for them.
But pay somebody for their time, but get somebody who understands that data piece to do a short term project to connect those data sources into your smaller set of output data and be able to draw some comparisons. So, join handshake.com is one way to find people like that. Connecting to academics is certainly another way to do it.
But I think that what we're looking at here is lacking that gold standard of a longitudinal study with our own data. What we can do is say we have a population of people that look like this and we provide these or outputs to those populations. And we can demonstrate that pretty easily.
But we can also take a look at B, which has those same population characteristics, and they've modeled it over time towards impact and say, is it an absolute guarantee that we're going to have the same impact on all of our same people? Because there's -- no, it's not. Is it the closest thing that we can get without spending a tremendous amount of money?
Yeah, probably it is. And there's a really good argument to be made that if we know that there's outside information that verifies that our outcomes on our short-term outputs create impact over time in other populations that are just like ours, but that grant partner that sees that will understand that's the information we can provide them. They can read the study, they can see the outside data source. They can look at the American community survey. They can also help draw those connections.
So I put an example together of some long-term outcome things like mental health services, for example. And that we can say in our grant applications, hey, we can look at this study. And so that this monitoring system sees efficiencies over time in statistical models, predicting local variations, blah da da da da. All of that is available for other people to go check out what happens when these patients are treated consistently over time. And then, come back and say, we nonprofit clinic, aren't going to provide that longitudinal study at this point. If you'd like to invest in us to do that, we'd be happy to take your money and talk about doing that. Right. But they're probably not making that grant funding available to do the longitudinal study. So I think it says lacking that, we believe that these positive outcomes that are demonstrated in these other fields are things that we can replicate here with our populations.
So here's the information about why we choose the outcomes and the outputs that we choose because we see those leading towards impact, and we're agreed with these other sources and think that those are important places to take this conversation.
All right. I do think that in terms of making friends with your local reference librarian that Krysta mentioned a little while ago, there is no reason not to go to your local academic professional directly as well.
When you were looking at who did this study, many of these professionals I've found when reaching out to them directly are more than happy to talk with you about their methodologies, their experiences, what they came up with in order to help you learn from their dataset, that if you go into this particular issue of the Lancet and see this study was conducted with a lead author listed as David M. Clark.
And we go find David Clark at Oxford, I guess it is. And health in the UK, to reach out to professor or Dr. Clark, professor Clark, pardon me. And say, hey, we're doing implementation work on services that are very similar to what you talked about. Could we just have a half an hour of your time to think through this impact data that we want to present to our grant partners and maybe even get a quote from you about why you think you saw what you saw in your stuff.
I'm constantly pleased with the amount of information that I've been able to get by just asking academics in the field about their work. Many of them are more than willing to share that in a reasonable amount of time, of course, half an hour conversation once kind of deal.
Many of them are, of course, interested in looking at joint funding for additional research. So if you really want to get into the weeds and you really want to think about that, then having them as a partner in your long-term longitudinal study is a great idea. But I think most of the charities that I work with are not in that space, we want to get into those weeds.
We just want to define our data set against their data set in the best possible way we can to help people see impact. So, I see a link in the chat on some research data tools, community commons at the University of Missouri. So interesting, not another tool to kind of look through that research data collection and see what might be available.
Thanks very much for sharing that tip, Patrice. Thank you. I've kind of rushed through a little faster than intended to, but I'm happy to start working fairly soon into questions. I am going to ask Will pretty soon to kind of take us through a little bit more about Instrumentl, and then we will have some time to talk through those questions and examples that you may want to share 'cause I'd love to be able to talk about success in addition to we're still struggling with how our grant partners want to see this information and how difficult it is for us to present it. But I do think it's important for us to think about how we are using those inputs. Certainly donations, grant money, for sure, but volunteers, staff, time, data, whatever the other inputs are.
To create those outputs, a number of things that we can look at and to think through about those long-term outcomes and impact over time that we can connect to other people's data sources and show we're not the only ones that think this. We believe that this is something that's accepted in a community that has done additional research on this and that we are trying to model those practices locally to bring that change to our community.
And please provide us the support we need to kind of do that work. And I think those are great opportunities for us to extend the grant work that we do to help make our best possible case in our application and to see if we can't really demonstrate that to the broader community, as well as to our grant partners.
So you'll all get a copy of these slides. My contact information is here. Very much like to stay in touch with people as you're going through this. I do have a link on my website at nexttononprofits.com for a free consultation. So if people are interested in following up to just talk through these ideas a little bit more, we can spend an hour together and that won't cost you anything to just talk through your specific cases and go through that.
But do think that, and of course, if you're not yet using Instrumentl and you're interested in pursuing how this tool helps surface those things with those outcome questions, my link is here. Will will go over that a little bit more, right now.
Will: Awesome, Steve, and we want to go over the next slide on that'd be great. And I can just go over there and then take over the screen share after that. So in terms of Instrumentl, like we mentioned at the very beginning of this workshop, we are the institutional fundraising platform that brings grant prospecting, tracking, and management into one place. And so, the reason why that's really powerful is because a lot of folks are using a variety of different tools to achieve these three things. Whereas we bring it all into a single workflow. What we're going to do is we're going to essentially be able to set up a customized list of personalized matches for your nonprofits, different programs and initiatives, and actively maintain those searches for you with our unique matching algorithms.
So if you've never tried it out, you can use Steve's link in the chat. Ashley, appreciate the shout out as well. But essentially what a lot of folks find when they create their projects on Instrumentl is they find that they are able to get a lot better results than pretty much any past database that they've used.
And so, when you're creating your account on Instrumentl, you're going to go through a project setup process, and it's going to look something like this in which when you log into your account, you're going to be able to set up your project. In this case, I've got an animal welfare project. And what I can do is I can essentially tell Instrumentl more about this respective project.
And as I go and set things up, I will then tell exactly where this project is taking place. In California in San Francisco county, as well as some different fields of work. And then once I set this project up, Instrumentl will output for me, this Matches tab and what this Matches tab does for you is it essentially gives you a list of 216 potentially good fit funders that you can immediately start working on.
So one of the themes of today's discussion and presentation from Steve is the importance of data and being able to parse through data more quickly. And so, something that's really cool about Instrumentl is not only do you see these active opportunities that are constantly being updated every single week for you, but also when it's a private foundation and there's more information about the funder, we will parse through the 990 report for you. And so when you're going through these different potential funders and things like that, you'll be able to essentially identify things like this, where I've got the Black Dog Private Foundation.
And then as I scroll through here, you can essentially see the giving average and median through the years. You'll see things like the grant amounts, which are really important when you're trying to align it to whatever your fundraising efforts are. As well as you'll think, see things like a map of the U.S. and exactly where past grantees are coming from.
So this can be really useful when it's coming down to the question of, is there a geographic focus in supporting funders similar to me in which if I wanted to just go ahead and parse through for all the past recipients in California, I can do that and start to work through these results to see exactly what the purpose was of the funding. And in the case where you're looking for other statistics that might be a little bit harder to find, we also break down things such as the openness to new grantees, which no other platform tool actually does out there.
And what this is useful for is really answering the question of when a funder says they're open to new grantees, do they actually mean that in their data? Like, does it support that statement? And that can be really useful when it comes to prioritization as well when it comes to answering questions such as what's the breakdown between new grantees and repeat grantees, what funding areas are these funders giving to the most? So when you set up a project on Instrumentl like I have here on the animal welfare side of things, I have one set of matches that are going to be open and active opportunities that I can actively manage.
And then in the second tab in Funder Matches, these are going to be funders that may be invite only, or do not have a website. In other words, these are the folks that you might want to start building relationships with over the six to 12-month time period or something like that. And what we'll do for you here is we'll essentially parse through that same data.
And make it easy for you to make that assessment as to whether or not this is a relationship you want to begin building. So super, super useful when it comes to finding good fit funders beyond active opportunities and also in just streamlining your search process. So if you ever want to do research on a particular funder, click the quick find the top left corner, and then go ahead and type in an EIN or a name, and you can just pull up a funder's profile from there.
And from there, we'll do all the parsing for you. And essentially, I'll put some key trends that you need in terms of support there. Something I also want to emphasize is our team is always here for you. So in the case where you ever have a question, you create your account today or tomorrow, feel free to use the chat bubble in the bottom right corner.
We are very responsive in terms of any questions that you may have, which I know that some folks really appreciate whenever they connect with us. So yeah, and then with that Matches side of things, once you start saving things into your tracker, you're going to get something like this. This is going to be kind of like the excel spreadsheet that some of you guys often use, but the reason why it's so much more powerful than that is because it allows for cross team collaboration and easier reporting. So what I mean by that is if, for example, I open up this Doris Day Animal Foundation Grant, I can see how I can actually update the year that I'm working on it, assign an owner on this respective account, as well as leave different notes for my teammates, or even just set my submission deadlines and tasks all in the same place.
And this is a callback to one of Steve's earliest slides on the document library. What you can do on Instrumentl is you can actually organize all your proposals here as well. So that if, for example, I was working on this in the next year, all I need to do is click duplicate, select 2023. I plan to work on this. And then from here, my team would be able to see that I have this plan for the next year, while I'm still working on it in the current year, and have all the proposals in the same place as well.
So super useful when it comes to project managing and getting that proposal through the finish line. In the case where you ever want to add any of the opportunities that you already know of, just click the add one, add new button, and then you can add one or upload many and just download our template and import your existing tracker into Instrumentl.
The benefit of this is several fold. The first one is we actually allow you to customize your fiscal year. So if you're a grant writing consultant and you're working with 10 different clients, you can actually change the fiscal years for each of the respective profiles. And then secondly, once you set up all of your tasks and your grant applications in your tracker. Once a week, we're going to summarize for you all the tasks and deadlines that you have coming up to save you the time that you might be spending right now in terms of setting up a separate tracker for all of these sorts of things. And then lastly, with your tracker, you can download a report at any time.
So if you want to go ahead, for example, and just pull a report for this, in this case, I was looking at the animal welfare project. I can select whatever statuses I want, select a date range, too, and then go ahead and click create a report. And now I've got a customized PDF report that I can essentially send to my board, send to my executive director, and send to whoever is needed in terms of a key stakeholder when it comes to the next team meeting.
So if you never try to sell a feel free to use Steve link. We'll leave it in the chat as well. And I think what we'll do at this point, as well, is we'll cut back into the presentation. I'll talk about some next steps in terms of some freebies. And then we'll open up to some of the questions. I have one from Debra earlier to go over as well.
We've got a ton of freebies for today. I have a feedback form that I'll be sharing in the zoom chat for today's workshop. This is how we know what sort of content you guys want to see. So if you want to go ahead and complete that, you can do so with the second link in the zoom chat. And with that, let's go ahead and start digging into some questions.
So, Steve, the first question we had was from Debra, which is how do you develop a logic model when the powers that be are reluctant to track data? I can't get numbers served, let alone what they've ordered.
Steve: So I'm assuming you mean your own data as a nonprofit, that your team, for whatever reason is concerned about trying to collect how many folks came in, what kind of service they got or any real kind of personally identifiable information about them as a client.
And I can certainly think of a number of charities where that would be challenging to do. So Debra, if you're still on and you want to just chat a little bit, I'm assuming right now that that's about we can't collect our own original data set in order to then compare it to other data sets that we can research out there.
And I think it's still better to understand what research or other data sets are available, that you can say, these folks are producing these outcomes based on these outputs in other spaces. And we work in a very similar vein. But for reasons X, Y, and Z, we choose not to collect identifiable information about the people we serve.
It inhibits them from asking for help, you know, whatever the challenge may be that you're experiencing. So I do think it's still not a bad step to go back and get that publicly accessible sources for others who may be serving similar populations and at least talk about their outcomes and why you can argue that your work is trying to use a similar path to those outputs.
But we are, for these reasons, intentional about not trying to collect this type of information and we feel it's important and here's why. I think it's good to be that honest and that forthwith what most of the grantmaking partners that I've worked with have that conversation. If they're in that space with you and they really understand why internal data collection is a problem, then hopefully understanding that you still know something about long-term outcomes and why you believe you're creating a logic model that says these services lead to these changes, lead to these impacts over time. And we think that we're doing those things but have barriers to demonstrating it because of these reasons that they should see those reasons and be on board with you.
Not every organization will come there with you and that's unfortunate, but I hear the challenge that you're saying. So I'm going to bring up chat and say, oh, that Deborah says yes, exactly that. That is going to be a thing where the communication really has to be focused on why we can't do any outputs collection of meaningful sources, why we feel that impact services or the people that we're trying to help and therefore, we can't provide that direct link to what we're doing. However, here's why we think it's the best step forward to provide those services. Not everything we do in charities, by the way, has to necessarily create a long-term impact on somebody.
I work with an organization that does a hunger relief locally that is really focused on providing healthy access to food and not necessarily tracking those long-term outcomes of that person's just hungry today. The problem that we're solving is today's problem. Might they have a problem later? Maybe.
That's absolutely possible. But it's okay to just say there is value in providing just that output today because that's who we are as an organization. And are there other organizations that are then working with them to stabilize income, get better housing, get better jobs, and be able to provide better food sources?
Yeah, sure. But it's also all right to just do today's thing assuming that somebody is still gonna fund that. And I'm guessing some of our partners will. So I appreciate Deborah where you're coming from and how to do that.
Will: Awesome. And then Rev Birmingham had the question: we serve small businesses and data is harder to access on something like an American community survey. Funders often ask for outcomes like job creation, which are very difficult for us to track because they require us to follow up with clients and ask for very detailed information. Do you have any recommendations for communicating with funders that we don't have a realistic way to acquire this data?
Steve: Right. You have absolutely signed up for the right conversation today Rev Birmingham 'cause it is exactly that that we were talking about that there is information available about the impact of job creation in small businesses over time from the bureau of labor statistics, from other studies that are out there, you just don't have access to constantly going back to the people that you've tried to start businesses with.
And I think I saw a follow-up comment from somebody else in the chat who said, yeah, we also do this work and it takes time to develop a small business to the point of hiring other people. It's a couple of three years and in many cases sometimes more. So you really gotta be able to track them over time and you don't necessarily have the resources to track your specific data to prove that.
However, there is public data available about the creation of jobs in the small business market that you can extrapolate from. Going to the bureau of labor statistics and looking at job creation numbers and looking at how many of those jobs are created by businesses that have fewer than 10 employees, or that have fewer than a million dollars in revenue or whatever the small business starter definition is that you want to work with.
And then say, we can see that in the past, you know, five years, X number of jobs have been created by businesses like those across the country. We're doing that same job creation work with small business owners here. We can't necessarily demonstrate specifically that this one person hired one more person, 18 months later, and then hired two people 36 months after that, because that would take a lot of staff time to go back and forth.
But we can show you that correlative data, that small businesses are the engine that create most job growth in the United States. And here's what it looks like when those smaller businesses hire people over time, they tend to be in these kinds of batches. They tend to stay employed at this length of time and we can presume our same connection.
Will: Susanna asked the question around Instrumentl if we do anything in terms of showing who else is working on similar topics for partnership possibilities. That's a great idea, Susanna. And that's actually something where we're looking to test out new event types where we put together different groups of nonprofits that are pretty similar in their work together.
And so, that's definitely something that we would probably do through these sort of community events, but not necessarily through our platform itself. But a great suggestion there. And I'd love to hear more from you. If you want to email me some thoughts that you have there. And my email's at [email protected] as well.
And Steve, did you have something to add there?
Steve: Well, yeah, in fact, I've used Instrumentl for that very purpose. I mean, it is possible to do, because if you look at funder profiles, they will show you who else that funder is funding. Not everything, but they will show you like, these are the grants that they are making and you can go, oh, we're applying for this opportunity.
We see that in the past years, they've funded the junior chamber of commerce or whoever else it might be. That is available. So you really can, if you find that you're a good match for a funder, when you do the rest of the research about that funder and scroll down a little bit, you really can see, oh, they also fund X, Y, and Z that are in my community. And I might want to be in touch with them. If I see that this good potential for me has also funded this other group.
Will: Yeah. That's actually a great call out, Steve and just to show folks where to do that. Let's say, for example, I'm in an after-school tutoring program. There's a local one nearby me, which is Tutoring Chicago. I volunteer for it. What you can do is you can pull up that organization and then on the right hand side, click Past Awards Received. And you can actually see specifically who is funding that respective nonprofit that's similar to yours and another strategy that I've shared in other workshops around how to find new, good fit funders in your backyard or just similar organizations to yours for partnership if you can literally go on Charity Navigator. Search in some keyword phrases and isolated by your respective state. So if, for example, I wanted to search for tutoring and then I wanted to rate it, go for the ones that are compass rated. And then filter by a particular state.
So let's go with California in this case. You can then look up these organizations in Instrumentl and just run their EINs through Instrumentl. And that can be a way in which you could see whether or not there's alignment to the sort of grants that they're receiving funding from as well as grants that you might be interested in or funders that might be good for you. So that's a great call out in terms of a connection there.
Jim asked a question of what constitutes a funding opportunity match beyond a foundation. Well, a funding opportunity match means that that is an open and active grant opportunity that you can start working on today.
So in other words, this is actively accepting applications, whereas the funder matches are people that might not have a website because some foundations don't quite have websites or they are invite only, and they don't have an active opportunity. So that is the distinction between the two there in which your first tab is going to show you active and open opportunities.
And something else I didn't mention earlier is when the funder has not set a hard deadline, we will look at the historical pattern and give you a predicted deadline and then update that for you when it is more finalized by the funder. So we are actively tracking any of the active opportunities on Instrumentl for you.
Let's see some other questions that have been coming in. And I'm also gonna put in the chat, a few of those helpful resources. Like Steve mentioned, he's got a contact page where you can follow up and get some questions answered through a consultation with Next to Nonprofits as well. So don't hesitate to take advantage of that.
Let's see here.
Steve: Just as you're looking, Will, let me just answer about state funding opportunities. I do see those surfaced in the Instrumentl tool, the Minnesota Department of AG Employment and Economic Development and Minnesota Housing. Those types of funders do show up in the tool for me and surfaces opportunities that I can track. So in my state anyway, they're showing up. So I assume that that's happening in other states, too.
Will: Yeah, to speak to that, what you can do is when you're in your results, so let's say for example, I'm looking at a bigger environmental project. You go to your filter and then here you will see government opportunities as well.
You can filter down for those. And that will go through some of those, some government opportunities as well. And you can also filter by different types of funders, too. So if you're looking for just associations, or corporate, private and so on. Miami Valley Meals asked you, Steve, if you have any recommendations for software or CRM to track data internally. Right now, they're using multiple spreadsheets as they grow and it's starting to get overwhelming.
Steve: Yeah, the client impact stuff. There's so much going on. I'm a big fan of the reports of organizations like Tech Impact and what not to do comparative side-by-sides of the different CRMs that are available. There's a low-cost CRM guide from Tech Impact that helps you do a really good grid view of what I need to collect in my data impact these things.
And I have this many seats needed because some charge by the number of participants that you want to be able to access the source versus number of records that you're tracking or whatever. So you can kind of examine the many, many, I mean, there's the things like CiviCRM that are really powerful and useful, but take a little more customization and data knowledge versus the more off the shelf things that are extremely powerful in gathering that information, but they cost a fair amount more to work with. And I know that's always a challenge for most of the nonprofits that I work with anyway to think about what makes it easier.
I mean, some people will get into a Salesforce implementation for CRM data collection stuff, but again, I think the real challenge with that is customizing it for the data that you need. It can absolutely be customized for the data that you need to get the 10 seats for free from Salesforce. That's great.
But making it work the way you want it to work can be a consuming and difficult process. So I think looking at things like Tech Impact's low- cost CRM guide, and I don't have the direct link, but if you search tech impact.org and look for low-cost CRM, you'll find it. To be able to get a good sense of for us, we need more seats and fewer data records. So this is going to be the lowest cost solution that really is easiest for data input. And these days, I'm really excited that most of those organizations have gotten mobile input options for data collection where you can use a mobile phone or a tablet in the field connected to a mobile phone to be able to do real-time data entry work as you're talking to people wherever they may be.
It doesn't require a desktop. So you can really get that good sourcing of your own information pretty easily through some of those sources. But boy, we could have a full hour conversation about that one. There's a lot of tools out there that can do that.
Will: Awesome. It looks like we have tackled all the main questions for today. So thank you so much, everybody, for attending today. If you enjoyed this grant workshop, please do join us on the 25th for Find the Right Grants and Learn How to Stand Out with Funders with Meredith Noble. You can register using the events calendar that you RSVP for this event on or just in the zoom chat with some of those follow-up links.
Feel free to book a consultation with Next to Nonprofits as well or create a free Instrumentl account with Steve's link and submit that feedback form so that you get some extra grant writing resources along the way. Other than that, thanks so much, everybody. And we'll see you guys all next time.
Steve: Thanks, everybody.