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>> Annie Donovan: Good morning, everybody! We're going to get started. So, I am Annie
Donovan, and I am the incoming CEO of CoopMetrics, and I'm going to be your moderator for today.
Before we get started I just want to think the Heron Foundation, Clara and Dana and Buzz
and everybody else, for putting together this fantastic, fantastically stimulating meeting
on this important subject. It's really the cutting edge, where we need to go to move
forward in the social space, and just holds so much promise, and I'm really really excited
about it. So thank you for including me and CoopMetrics in this adventure.
I also just want to thank Maurice, Mauricio Lim Miller, for your comments last night,
and for reminding us why we're all here. Sometimes we get into such intellectual conversations
and we're so in our intellectual brain that we forget the heart space from which a lot
of us are motivated, and from which the true purpose of that work is. So thank you for
that reminder and for all your fantastic results.
So we're going to get started, and as Dana says this is enterprise, we're going to take
an enterprise view. And Dana hinted at this when she said, we don't think we actually
have any enterprise-level data so I don't know what we're going to talk about guys!
The data at the enterprise level is a big mystery that we need to solve, so we're going
to delve into it to the extent that we know. We're really looking for, what's the state
of play here? And this is a fantastic panel, because they are all themselves entrepreneurs,
founders and CEOs. They have been working either at the edges or in the heart of this
matter so we're going to hear from them.
So we're going to start off the panel with Elizabeth Dreicer—I'm sorry, I think I said
it wrong, Dreicer—she is the CEO of Kuity, and what we're going to do in this panel is
I'll introduce each of the panelists one by one, and they'll start with probing into the
question of why? Why did you start your company? And what are you trying to accomplish?
>> Elizabeth Dreicer: Happy to. I'll just briefly touch on why I started Kuity, and
then I'll dig into why we started serving the social sector in the last, almost 2 years
I guess that we've been thinking about this sector. By way of background though, I think
this is sort of pertinent: I've been thinking about how to improve society for the better
part of 20 years. Directly out of college what my inspiration was, and Mauricio sort
of touched on it: I have a schizophrenic brother, who ended up in foster care early in life,
and it had a profound impact on my family. So I felt compelled early in my career to
start giving back, and I started to participate in nonprofit boards, and then eventually ended
up on a foundation board 12 years ago, now almost 13 years ago, and for much of that
time I chaired an investment committee on that board.
So I just share that by way of background before I get into my professional life. I've
been leading analytic science-oriented companies for about 15 years. Prior to starting Kuity,
which we started about 7 years ago I worked on a project relating to medicine: how do
we encode medicine and know what's wrong with us more regularly? It's a reducable problem
using analytic science, and I think that we are just on the tip today of what's possible.
People have been looking at this for many many years.
We sold that company to Healthways, a disease management company, and I was sitting around
thinking about what do I really care about, and I think decision science and how we make
decisions in the world, can greatly improve. And Kuity started with the idea that there'stronger
sense of contribution, if you wills this huge raft of enterprise data, and that data are
largely inaccessible to the people who need to use it. And if you think about it, we have
so many political aspects of what gets decided, it's not optimized. So the inspiration I had
was, so we have a flight simulator system in gaming, and yet we don't have anything
even close to that in the enterprise world.
So the whole idea was to build dynamic enterprise simulation. That's what Kuity started on,
and we built a practice in financial services, defense, cyber security. And about two years
ago on one of the boards I'm on, Kathlyn Mead, the Chief Operating Officer of the California
Endowment, challenged me and said, hey Elizabeth, you're working on all this great stuff over
here and, PS, we're really struggling in this space! And so what Heron is saying is I think
true for a lot of folks. So what can we do here?
In that context I started to think about it. And we have been contemplating, if we had
to imagine, blank slate, what would we develop for this sector?
And what we've been working on is going to be unveiled as Posiba, for Possible. We've
been working on an enterprise platform that can, we think, transform enterprise-level
intelligence for the foundation world and nonprofit world. And we can talk more about
that.
But my inspiration I guess on a very simple level is, I've been making a lot of bad decisions
for a long time in my philanthropic work. We have scant data, it's a lot of gut reaction:
what gets presented, who knows if that was the best thing or not?
During a stint I had, we invested in things like baby doll therapy to try to reduce teen
pregnancy, and I know it doesn't work. I know! It's laughable now! It just didn't seem so
obvious to us at the time. So it's a personal desire. I'd like to do more of the good stuff,
do less of the bad stuff and kind of know the difference.
[laughter]
Sorry, just being honest!
>> [man off camera]: That's crazy talk!
[laughter]
>> Elizabeth Dreicer: Sorry.
>> Annie Donovan: I think we can find common cause in that, Elizabeth.
So, let's move on to Tim Ferguson. Tim is the founder and CEO of NextStreet, and Tim,
why don't you tell us a little bit about NextStreet and what you're trying to accomplish.
>> Tim Ferguson: So, NextStreet was formed about 8 years ago, with a specific attempt
to try and fill a gap, fill a gap for smaller businesses initially, but it's also extended
to nonprofits, to provide them with what wecall world-class advisory services and access to
capital. And these entities are all based, or serve, the inner-city communities that
we work within. So for the most part we're in what I think of as the ___ 7:40] corridor
with offices in Boston, New York, and about 50 professionals covering a variety of different
competencies and skills.
>> Annie Donovan: Great. Next up we have Richard Ling, and Richard is the founder and partner
at Rembrandt Venture Partners, in addition to several other ventures that you've created,
so, why don't you tell us about your path.
>> Richard Ling: Sure. So years ago I started several startups, starting in 1995, focus
on ad targeting, email search company, companies of that ilk. Then in '04 started a venture
fund, so I've been doing that for about eight years—essentially joined the dark side.
Even though they did fund most of these companies, and these all sold to big large public corporations.
And about a year and a half ago I ended up helping to start a company called Impact,
which was to essentially help to change up the way that nonprofits are able to go and
acquire and engage their user base: donor base, volunteer base, you know, whatever constituency
groups they're trying to reach. They were utilizing a lot of techniques that I had learned
were very very effective in ad targeting, in consumer-user funnel conversions, into
getting somebody to buy something, right?
So one of the things we did at Impulse Buy, which is way back in the 1996 timeframe, was
essentially drop federated cookies across 800 different websites, and tracking, by crawling
the contents of these pages, understanding what the pages were about. So if you were
reading an article about golfing, or you went to Golf Digest or golfing.com, we were going
to infer that you were a golfer and therefore show you golf ads as opposed to, you know,
*** ads or something, right?
And so you would probably get—
>> Annie Donovan: Just for example!
[laughter]
>> Richard Ling: [laughs] As an example!
[laughter]
But you would probably get three to five percent click-through, right? Even back in those days,
right? And click-through rates were horrible then and they're even worse now. But that
level of targeting, even that rudimentary level of targeting, was sort of working.
And then we do all sorts of testing on these websites to convert people to making an actual
purchase, if you will. We would find that you could literally change two words on some
of this copy, and you would get like 37% higher click-through rates, but only on a Wednesday
through Friday afternoon, and only for certain age groups, demographic age groups of people,
right?
But you were trying to really start to capture a lot of data and infer, at that level, the
demographic, psychographic information of people. And it absolutely does help to get
people more activated, and tremendous amounts of effort has been put into these kinds of
technologies over the last fifteen years. And it is quite a competitive arena out there
for most retailers and even mainstream brand advertising has started to adopt a lot of
these things, right? So our thought was, hey, why don't we start to do this, except instead
of a call to action and getting people to buy more golf clubs or handbags, get them
to be much more active and participate in nonprofits or the causes they care about?
But deployed in a way that makes it so easy for them to do. Because one of the other things
we learned about is, most of these, even the larger nonprofit enterprises, have very limited
technical resources, and they really don't know how to do these things themselves. So
what we did was, we actually called ourselves back then a shopping affiliate network. Which
is now quite, a fairly common practice among most major e-commerce companies, right? Amazon
has their own. There's a company called LinkShare; there's a company called Commission Junction
and they do this for now thousands of online retailers, even the very large ones, right?
Macys.com, Target, they all use LinkShare. And other outsourced capabilities, services
like that.
So what we found is the nonprofits don't know what they're doing in terms of having the
resources to understand, and to utilize some of these tools. And the problem is you can't
even just buy these tools as a nonprofit, because the ontologies that are mapped are
all about shopping. It's all about identifying somebody as a golfer, and they will buy a
high-end purse.
Whereas the calls to action for nonprofits are, hey, it's about getting somebody to donate
money. And some people will donate small amounts, because that's what they're capable of, and
some would donate larger amounts. And oh by the way others may not be able to donate much,
but they're willing to volunteer large amounts of time, right?
We wanted to start having these nonprofits drop their cookies, so that, one, we can understand
people's activity across the entire website. We also wanted to start to track social media
interactions because we think this is the one arena where we think people are willing
to outreach to their friends, right? One of the things with shopping, I mean there have
been a lot of startups I've looked at that have been trying to bring the social media
shopping into play, right? "Tell your friends that you bought this handbag, and we'll give
you 5% for every handbag they buy." And a lot of people aren't really willing to ***
out handbags to their friends to make—
[laughter]
—you know, five dollars on facebook. "Hey, everybody, buy this handbag!" Right?
What I think most people's experiences are is that if your brother-in-law asks you, "Hey,
will you share this video about a human rights issue, and put it on Facebook and tell your
friends about it?" you are much more likely to do that than somebody asking you to share
a product you bought.
So if that's the case, the problem is there's a missed opportunity in terms of understanding
what happens once that gets shared. So one of the things that we're doing is we are tracking
the, we create a unique URL, so when you share that video for example, about a human rights
issue, and you ask your friends, "hey, this is a really important issue. Please watch
this little three-minute video clip." We actually can track, because it's a persistent, unique
URL, tied to that video and tied to that individual person.
And so Elizabeth would share it out, and we can actually now, later on, tell that nonprofit,
"Did you know in three weeks Elizabeth got 27 people to come back to your website? Oh
by the way. and Facebook doesn't even know that because they lose you once you leave
, right? And oh by the way, because we're tracking everything across this website, and
it's actually deployed, I should state that, as almost, it's basically copy-pasting JavaScript
on a website, so from the point of view of the nonprofit, they really don't have to do
much, right? They're not doing all this analytics on the back end. It's very similar to the
way Amazon does their affiliate program. Where fashion bloggers can copy and paste JavaScript
and they all know how, they have a million affiliate partners, right?
But back to what we do. Once you track that you can now start to understand what these
users who come back—who actually was able to get 27 people back, versus three, right?
And oh by the way, of those 27 people, four of them actually donated money, and they donated
in total $125! And oh by the way, that nonprofit didn't even know that you got four people
to donate $125. Because they would have gone back and—they didn't even tell you, right?
Nobody's calling you, "Hey Elizabeth, guess what? I donated $25 to this cause I saw on
your Facebook post."
So now, all of a sudden, you can start to identify champions for people, for the nonprofits
and then our goal is to actually give them a really simple way where they click a button—and
again all these things involve clicking buttons, right? And send an automatic message to Elizabeth
saying, "Hey Elizabeth, Thank you so much! Did you know three weeks ago you got 27 people
to come back to our website, and watch this video about this issue, and you also got us
$125." And so start giving that feedback. And making this type of activity much more
transparent and visible. Not even just for the nonprofit, but to the participants, the
users themselves.
We think that can engender much much stronger sense of contribution, if you will. Hence
the name of the company is impact, our goal is to say, hey, you know, everybody in a world,
times millions of people doing it, can create massive impact, right? Today, it's not transparent,
nobody knows what's going on, it's completely lost. And this is a way to capture data that
we think can ultimately be much more effectively used to now understand what people care about.
Who actually gets more people to volunteer? Who actually has more time? Who actually is
more influential? Who actually gets more money donated? And really change up that whole conversation
so that you're not relying upon just sources of grants from organizations like Clara's
and etc. But now you can—what you're also doing is creating that ability to have a much
greater audience out there, right, that understands your mission.
>> Annie Donovan: Ok. Thank you.
>> Richard Ling: Sorry for the length of that talk.
>> Annie Donovan: So, the first question I want to ask you is, all three of you have
experience in the for-profit space, and you ventured into the nonprofit space. So tell
us a little bit about what you see. What's your diagnosis, in terms of the nonprofit
space and what's needed?
>> Elizabeth Dreicer: Well, I think we have to distinguish the funders from the grantees
and the people who are actually operators. And in some places, I know in Europe for example,
most of the foundations, or a lot of them are operating foundations, so I'm really speaking
to the US audience. On the funders side, I think there's no burning need. Even though
there's a lot of talk, and I think that there's a lot of good intent, I think that nobody's
earnings, nobody's worried about posting earnings, nobody's worried about sort of the business
pace, and so as a result, I think that the process is slow.
I think that on the grantees side, or the funds-seekers side, I think they're very hungry
for ways to produce intel that will generate awareness among funders and donors both that
they're a good operation and that they are creating value. And I think that they have
a real challenge telling their story, because they don't think in terms that the financial
folks or even people who think about impact, think about.
And I'll make this concrete. During my stint on the 211 San Diego board of directors, we,
it's a, I don't know if you guys know what 211 is but it's sort of like a social service
line in terms of gathering the thousands of different service providers in a region. It's
sort of mimicked off of, instead of 911 being emergency services, 211 is really around providing
intel around, if I need services for an Alzheimer's parent, or if I have trouble getting health
insurance, you can call this and they've got thousands of agencies.
Well what's interesting is that they have no way of really thinking about what in our
business world we think about as Balanced Scorecard or some sort of—how are we moving?
We can think about profit. Well, in their case, what's the value you're unlocking? And
I almost feel like, it's just a language that's not present. So I actually during my tenure
helped them get somebody who was Six Sigma black belt, come in, really put them through
the discipline of Balanced Scorecard, and we really were able to suss out our value,
and really change a lot of the operations, but it took that sort of business thinking
coming in to look at that.
Annie, getting back to the point, I guess, they're hungry, less resources, not necessarily
able to put the money necessary to have the high-priced expensive talent that does this
important work. And so you have the funders who have capability to fund, you have nonprofits
that I think want, my assessment largely is, I'm optimistic that both sides actually want
it, it's just a matter of figuring out how to play at the match. But it's—
>> Annie Donovan: Since there's not a compelling—there's no compeller in there, there's nobody saying,
"we have to have that or--!"
>> Elizabeth Dreicer: Yeah. We're not trying to hit our quarterly numbers. If you walk
in and somebody, I think the analogy, I think Amanda who works with Cisco, if I got a call
from many of the corporate clients that we work with, usually the calls are, we're in
trouble. We need this right now. And in a matter of literally a couple days, it's deployed
and going. You've got a team. You're working it.
I don't think we have that kind of time paradigm in the funder community.
>> Annie Donovan: Tim. What do you think?
>> Tim Ferguson: So, I kind of want to draw on two things. One is, what worked in the
world that I was in before. And then bring it specific to NextStreet, some of the things
that we've seen. I think that there's been a lot of discussion about what the foundations,
the funders and the nonprofits do or don't have, so I'm not going to repeat that. Because
I don't think that it's necessarily going to move the conversation forward. I mean,
I think one of the single most important things is terminology. The lexicon is not at all
clear, whether its standards or whatever else it happens to be, and when I look back on
my own past, it's when we agreed collectively to create standards for the industry, that
it began to actually change the way that we operated with regard to the collection of
data, and then its utilization. The transparency was really really important.
As Clara said yesterday, how we incent, or the word "compel" was used, that's not, you
know, Wall Street people understand incent; they don't understand "compel".
[laughter]
>> Tim Ferguson: [laughs]—everyone to fall into line, is really really important, and
probably from the funders' perspective, it is actually about the funding, the single
biggest tool that you wield at the end of the day is the funds that you control as an
institution, as an organization. And I actually don't feel that funders use that as effectively
as they could do to build the infrastructure components of the market that you are operating.
In my experience, transparency will create private markets. One of the goals that we've
heard consistently over the last two days is not just to have philanthropy flow into
these markets, but also to leverage that many times, to have the private capital as well,
flowing into the marketplace as well. And if we don't have transparency, it will not
happen. Or it will happen, but it will be in dribbles. It won't be in a flood, and something
that becomes serious. Investors and others, if they have the information, they'll see
opportunity, and it will bring other participants.
And that has good points to it, and it has bad points to it. But other people will come
into the market space, so what Mauricio was talking about last night, as he begins to
prove that, he has data to show it, it's really hard for people to say, well, show me! Which
is so often the response of someone who's thinking about changing a paradigm or funding
something that's trying to do that.
In the investment world, to make it specific, to direct experience that I've had: on the
research side, one of the problems was that all of the big Wall Street investment banks
provided research to us, in very many different formats, and they also provided it in print
copy. So you could walk around the investment floors and you would see piles and piles of
research papers. And what we did is that we basically brought a group together of the
big, so-called buy-side firms, or the big fund managers who control the flow of money
through the Wall Street houses at that point in time, this was before the rise of the hedge
funds, and we agreed that what we wanted was to create a set of common standards, that
meant that they were being asked to chart all of their analytical work with a particular
set of terminology, standards, whatever you want to call it. That would then allow us
to mix and match, as analysts, if that's what we wanted to do, so we could take the revenue
analysis from Morgan Stanley and couple it with the cost analysis of Goldman Sachs, or
whatever it happened to be. So that just made it far far more efficient, and it made the
models fungible.
The buy side, we had a common interest. We wanted to do that; we needed to do it. So
we didn't care about the fact that we were all going to have fundamentally the same base
model, that we were asking them to work from.
And it happened. And from Wall Street's point of view, they had an economic interest. We
controlled, with Morgan, Merrill and Goldman, a hundred million dollars each of revenues
that were flowing to them over the course of a 12 month period. Fidelity, three or four
times that, Wellington, etc. so they had an interest to do it.
I want to share a failure with you, because failure also is something that we learn from.
We tried to do something called Bond Book, because we were very concerned about lack
of liquidity in the high-yield bond market, which is the junk bond market. There was poor
liquidity, there were small size of issues, and it was expensive. Transparency would have
dramatically changed the economics of the market, and in this particular case, we couldn't
get a coalition of the buy-side firms to agree that that was the right thing to do, and to
this day I still don't know why, so the investment banks were able to protect their interests,
which they did. Solomon sat and told me, "I've been doing this longer and—before you were
in short pants," is what he actually said to me—
[laughter]
"—It is not going to change on my watch." He's passed away now, and it still hasn't
changed.
[laughter]
It's kind of interesting that the economic interest is very strong.
Now, a parallel in the marketplace that I'm now involved in would be something like new
market tax credits, where, for those of you who may or may not know, is a program that's
run by the Treasury called the—by the CDFI, the Community Development Financial Institution—Fund,
sorry, CDFI Fund—and in their particular case, they issue tax credits. The people who
are responsible for administering them are community development enterprises. In effect,
CDFIs. That marketplace, the commissions, the fees that are paid, represent 10% of the
amount of principal that it's effectively issued. And one of think reasons for that
is that there's no transparency to the market space.
Contrast it to low income housing tax credits, which has been around for ten years longer,
which is the same in the beginning, and now is a very cost-efficient market, and something
that works reasonably well.
So transparency, data, is extremely important. Bloomberg—I mean everyone knows about Bloomberg,
and I'm not talking about the Mayor, I'm talking about his company. They're one of the things
that he recognized is that good clean data, consistency, and the integrity of that information,
instills confidence in investors, and that is something which, to this day, is a very
strong tool, and a bunch of information that's available in the investment world.
Indices. Morgan Stanley Capital International Index, and the FT World indices. They created
benchmarks. They came from data; they came from enterprise data that came up to Big Data,
that allowed investors to be measured, sorry, fund managers to be measured, in terms of
their performance.
And effectively, whilst, yes, Dana, you're right, it's not impact from the way that we're
talking about impact, and that I now understand impact, but performance at the end of the
day is impact, from their perspective.
In terms of us, data analytics are fundamental to everything we do. And it's been a nightmare
trying to get it, particularly at a market-level. It's been very very difficult. And because
we can't get it, it's difficult to unlock the sources of capital that would allow us
to fund some of these small enterprises and nonprofits. That would allow them to grow
in a different way than they've had before.
And part of that is because it's simply not being collected, or its being self-reported.
Many of the things that we heard yesterday. With our clients, we're always trying to find
data that can help them to understand, because if you're an ornery owner or entrepreneur
of a business, sometimes you're going to resist the "this is what you need to do" because
it shows that you're not actually getting sales around the particular branch office
that you've got. So you've got to show them a heat map that shows the number of houses,
and what their market share is in that sort of area, can sometimes change their perception,
and move them to action, which can lead to a better business. Pricing. Hiring. Managing
seasonality. If they don't have information, they don't have data, it's very very difficult
to do.
Internally for us, we use it for pipeline relationship management, client impact assessment.
We initially overly customized it, and I think that keeping it simple is really really important.
we simplified it, and it meant that adoption, because you know, getting our own internal
people to adopt, you can't just mandate it—went from 60% to 95%, and it helps us as well,
I think, with risk management.
Externally, it's important because we need to be able to demonstrate our own impact.
And for me, what we do now is really really simplistic. And part of the reason is because
it's very very difficult to collect the data and the information to have a framework that's
consistent across other players like us.
Now, I can tell you that we created 8% job growth in the businesses that we worked with
in 2011-2012. I can tell you that that was 984 jobs that were either created or retained.
I can tell you that there was 14% revenue growth in the businesses that we worked with.
I can tell you that the combined revenue was 606 million dollars in 2012, and I can tell
you that we supported businesses that represented 4365 jobs. But I can't tell you much more
than that, and more importantly, I can't tell you that every single month, and that's a
problem, because I know that people like Heron and others are going to want to drill on those
sorts of numbers, and I want to drill on those sorts of numbers, because I want to know,
to Mauricio's point yesterday, that what we're doing is actually having an impact and making
a difference.
And we can measure that at multiple levels. We have a company who grows their revenue
who's in the inner city—we do have one—a company called Roxview Technology. Roxview
Technology, which is run by an African American woman, that remanufactures toner cartridges.
In the time that she's been a client of ours, she's gone from 4 or 5 million of revenues
to 19 or 20 million. From 18 or 19 employees to 64 employees. Sixteen of them have criminal
records. That's a big deal. Seventy percent of them walk to work from their neighborhoods.
I would like to be able to do that for every single entity that we work with. That level
of granularity. And it's very difficult to do because we have to figure out how to actually
incent those entities to report that information to us.
I would say, just finally, that I think that for the social sector, I see some entities
that are actually investing a lot in the nonprofits in what I think of as management information
systems, theta, measuring what they do. But they tend to be the organizations with quite
a lot of revenue, so maybe I can think of one that's 115 million dollars now. And they
can demonstrate the impact that they're having within the school system.
I think it helps to create more efficiency. I think tracking and measuring impact is important
and leads to, at the end of the day, better decision-making, and allows the organization
itself to focus on what really matters, so you don't get lost in the noise.
Just as a final thought, I wonder whether there's not a role that the community foundations
can actually play in this regard? So if you look at someone like the Boston Foundation,
they fund a number of annual data-gathering exercises that actually are important to the
city and the community, that are sort of the beginning of something that could become more
of a bigger type of movement.
>> Annie Donovan: Great. Thank you. Richard?
>> Richard Ling: What was the question again? Sorry! [laughs] I'm the second-string replacement,
I'm the second-string replacement, so I didn't know last night I was speaking.
[laughter]
>> Annie Donovan: Translate—so you've been, and you've hinted at this in your opening
remarks. You have a view of the for-profit space, and then you entered the nonprofit
space. What's your diagnosis of the nonprofit space and why we aren't moving faster?
>> Richard Ling: I mean, I guess my perspective is more—I'm from a part of the country where
speed is everything, so it's probably even more accentuated in terms of the difference,
but what I like about being from Silicon Valley is everybody tries to disrupt some existing
enterprise of some sort. And that engenders both the innovation part of it, as well as
it actually causes the large organizations to be much more responsive and ultimately
much more competitive. And these upstarts are relentless, and they get funded, relatively
easily, so it attracts a lot of very talented people to go and tackle these things. Even
though they're very talented people, there's still tremendous difficulties in really being
successful. But people keep trying it and trying it and trying it.
I think in the nonprofit space we're starting to see some of that, where there are upstarts
that are really starting to change the way they do things. Now some are controversial;
you probably know many of these guys. The Kivas and Charity Waters and even Change.org,
and some of them are my friends who've started these things, right? But what they're trying
to do is change the way that these nonprofits go about being successful, and not just doing
the same old thing over and over again. And of course there's going to be a lot of failures
because that's what happens with startups.
So I think this is—we're at a great moment in time, where I think it's much easier, even
in this sector, to start to do some of these things, right? Even on the side of, you know,
earlier I talked about how you can acquire more donors and volunteers and things like
that. I think there's tremendous opportunity really trying to outreach and help the beneficiaries
of this aid be much more effected, right. So when Mauricio was talking about his lending
thing, I thought, wow, some of the things you can do is, with the ubiquity of mobile
smartphones, and it is going to be everywhere, I think it's at 70% penetration in the US,
you can create simple little foursquare-like check-in things so that, hey, if you actually
made your payment on time for that loan, for example, or mortgage, you can check in that
you did it. And then you can actually automate a lot of the feedback. And you can actually
have their friends and peers give them a thumbs-up if they do. And oh by the way, if they're
seven days late, to give them a thumbs down. And that kind of feedback is utilized right
now in social gaming; there's all sorts of things that it's incredibly effective at doing,
right?
We funded one social gaming company, and so I learned from that experience, what that
peer pressure does even in a silly thing, so it's a company called Lucky Train, and
they did a game called Lucky Train, which is exactly like FarmVille. And FarmVille has
whatever, 200 million people playing this silly thing, right? And what you do is, in
this particular game, you try to build your trains and you build a little town. So the
more passengers you have on your train, you get more money, fares and all that, and you
can build now a bank, and schools, and all sorts of things, right? But the way you play
is because they're all social games, is you have to invite your friends to be passengers
on this train. It's the way Farmville works too, right? You have to buy your crops and
things like that. And so what you do is when you're first playing, and the guy who started
FarmVille is an old friend of mine, he's a really smart guys about using small little
progress bars to enact behavior change, right? And using peer pressure to do that as well,
and it absolutely works.
So what happens is, you invite your friends to play this train game. And we were investors
so that's kindof the only reason I was playing the game, just to be clear.
[laughter]
So you send off these little trains. You invite your friends, and so now you get on level
three. And it takes you five minutes to hit level three, so it makes it really easy to
sort of get sucked into this thing, right? And now you want to get on level ten. And
they don't show leaders, where it's really top players, they just show the levels of
your friends, so it's more of a community thing, right? And the problem is after a couple
of weeks you kindof get bored, and you don't really want to play. But what happens is,
when you are passengers on your friends trains, because there's reciprocity, they, you actually
can't get more points until they send their train to you, and you send it back to them,
and that's the way the game works. You have to send it to each other. And so all of a
sudden you stop playing, and your friends will start pinging you: hey Richard. Can you
send your train tomorrow? I really need 50 more points to get to this thing? and they'll
send you little messages. And all of a sudden now you have tremendous guilt to go and keep
playing this game.
So I found myself every morning checking in and playing for three minutes, sending out
a whole bunch of trains that I really couldn't care less about, but those kinds of mechanisms
are really effective, right? And that's how these games work. And some people now want
to get ahead more quickly, and therefore they're willing to—and they always have two levels
of currency, so that's how they make money. I mean, Zynga last year did 600 million dollars
in revenue. And this is a four-year-old company, getting people to buy virtual currencies and
things like that. And this train game worked the same way. but a lot of it was using peer
pressure.
So I think a lot of this can be applied, at least in this country, for you know, for aid
to these kind of things, right? Clever ways to try to utilize these same mechanisms that
have worked in the commercial world, if you will.
>> Annie Donovan: We're going to open it up in a minute for audience questions, but just
one last question from me. So, if you were advising a foundation about the critical path
to opening up enterprise-level data, what would you advise them to do?
>> Elizabeth Dreicer: First I would say that they have some enterprise-level data today.
And I think that somebody said good and perfect can't be enemies, so we've got to get started.
I think the single biggest factor that you look at, it doesn't matter whether you're
looking at the performance of a fund, or whether you're looking at the performance of a company
or you're looking at any organization, it's leadership. We have to have the will. Do we
want to solve this problem or not? If we do, there's no technical hurdle. It's a choice!
So yes, there are obstacles; yes, transparency is critical, ultimately; but I think—I'm
pretty simplistic about this. We've got lots of evidence that there's stuff that will work.
And I know that there's this allure of getting hooked into thinking, well if we all speak
Greek, we're going be able to figure it all out, and I think that's a fallacy! Or if we
all get in the same system we're going to be able to figure it out; I also think that's
a trap. We live in a heterogeneous world; we live in a world where people speak lots
of languages! You might call something "violence prevention"; you might call something "harm
reduction". Ok, I understand the allure of the ontology, but the fact is that, and I
think you're right that transparency is important, but we cannot let this idea that we've got
to build this lexicon before we can start moving—I just reject it. I think we start,
and we decide, that's the critical thing, that we need to do this. And if that's what
we decide that we need to do, then we instrument ourselves—my feeling is, the field at large
needs to instrument itself for learning. And that's the decision to make.
And then how you do it, it will be messy, you'll make some bad choices; that's life.
You know? Everybody who's gone down the path knows that it's an iterative process.
>> Tim Ferguson: So, I wouldn't actually say anything else that I didn't say before.
[laughter]
And I still believe that if you want to unlock the capital—
>> Elizabeth Dreicer: Yeah.
>> Tim Ferguson: —which is actually the issue that I think we're being asked to address,
if you don't have standards, and you don't have some broad agreement on lexicon—that
doesn't mean to say everyone has to play in the same space—it's not going to happen.
Not in terms of the longer-term capital. And I believe that the foundations, at least as
far as this world is concerned, and if they're trying to move to impact-based investing,
and mission-based investing, that they're going to have to provide some of the leadership
to make that happen, and I think it's going to have to be through their own, the hold
that they've got over the funding dollars.
>> Elizabeth Dreicer: Just to sort of draw a circle around that—I think we're actually—I
think it's just a question of who does that work. Bloomberg used really, if you look at
how that got done, it neither got done by the players in the market, nor—if you think
about the funders versus the nonprofit, I think the issue is if you try to actually
do the connection direct. I don't think that's the path. I think the idea that you have service
providers, that's what made it possible, right?
>> Tim Ferguson: Absolutely. Yep.
>> Elizabeth Dreicer: And I think that that's, some people get confused by that. And I just
want to draw that distinction.
>> Tim Ferguson: Yep, I would agree with that. That's why I think actually—
>> Elizabeth Dreicer: So Bloomberg translated. And made sure it was clean.
>> Tim Ferguson: Got it, got it. But there was a demand for it from both parties—
>> Elizabeth Dreicer: Absolutely.
>> Tim Ferguson: —and then I would say that CoopMetrics could play that role. And I'm
certain as far as the world that I'm in, they could definitely play it. Because they, you
know, we can't do it. Because we're not independent.
>> Elizabeth Dreicer: Right.
>> Tim Ferguson: And if you're not seen to be independent, it's very very difficult to
create that information.
>> Elizabeth Dreicer: And I think that it's important that there's also two distinct pieces
of intel that we want. One is around the health of the organization, as measured by financial
well-being, and the other is related to impact. And these are not the same. And I mean, social
impact, there are many frail organizations that are actually quite good. And that doesn't
mean they're ready for capital, either. So there's questions. I understand. But I think
we have to realize, we want two different flavors of data, and ultimately, those need
to come together.
>> Richard Ling: I'm not as familiar with the nonprofit world, but at least in the for-profit
world, and I've been on quite a number of boards, and it's very goal-driven for startups,
right? And they don't have to be profitable; that's usually not a goal—
[laughter]
—for almost any startup I've been involved in! But they are very, there is a board, and
that board is very aggressive about seeing that the entrepreneurs or the management in
that company achieves their goals. And I don't know if that's sort of the same ethos or the
same culture within nonprofits, is like, and here the goals are not, you know, sell more
handbags, or whatever it is, right? But it could be help more people in poverty, in whatever,
however you describe, whatever the lexicon is to describe it. But there is usually a
very active board of directors who take their responsibilities very seriously about, are
you making your goal? And every week, every quarter, you can—you sometimes get called
by your board guys, sometimes once a week, and they hate that! The entrepreneurs hate
that—
[laughter]
—but it really, again, it's that peer pressure, right? And I think if there's more of a culture
of that in nonprofits, and there again the goal, set those goals and make sure that delivery
happens, and on the foundation side, is like, you know, since you're probably usually the
board members on these things, provide that sort of guidance. And of course for the for-profit,
for the startups, you're going to die if you don't meet your goals. Even if you just—because
you need to raise more rounds of funding. Happens every time. So if you start to miss
user acquisition, or enterprise sales, depending on what your product is, you will absolutely
not be able to reach that next round of funding, and you will be gone. And there's tremendous
amount of pressure on the part of entrepreneurs to be successful, because of that, right?
So it's really just goal-setting. As in the for-profit world. Anyway.
>> Annie Donovan: Let's open it up. Yes.
>> David Rabjohns: You said something earlier, you were talking about the toner [inaudible
44:49] when you were talking about the toner lady that you work with, and that was, we
have to think of ways to compel these people to give us the information. And it strikes
me in the for-profit or the for-revenue world, in Silicon Valley, you never have to compel
anybody to give you information. You'd be like, I'm giving you money. You need to give
me back data about your progress. What's the problem? What's the reason that's hard to
do in the social sector?
>> Tim Ferguson: —In the social sector or in...?
>> David Rabjohns: Yeah. Was it, when you said, I think you said, maybe I misunderstood
it but I think you said it's hard to get them to give you the information.
Tim Ferguson: In general it's hard. We can get it from our clients, because we have a
relationship with them, and then there's the whole confidentiality piece so you need to
then aggregate it up. But I'm actually interested in a much much bigger universe, so I want
multiple enterprises to be in there, because that then allows you to see what the histories
are, what the trends are likely to be, default rates across different sorts of businesses,
different sizes of businesses. Because there's a perception issue, right?
So in the bond markets you can get any data you want pretty much about a company. You
know what the probability of default is; you can do all sorts of analysis. In our world
you can't do that. So what it means is that when I go to see a prospective investor, in
us or in a fund or something like that, they're going to ask the question of, ok, what's the
probability of default? And I'm going to give them a statement, I'm going to make a statement.
And that statement is going to be based on something that's really really imperfect.
And they know it! Because they're accustomed to doing very very detailed regression analysis,
all sorts of different things. So it's collecting the information in a way that gives integrity
to what it is that's being looked at.
>> David Rabjohns: So it's aggregate data across the board that's the problem, not the
individual that you're investing in?
>> Tim Ferguson: Yes.
>> Annie Donovan: Clara.
>> Clara Miller: I just think it's worthwhile, talking for a moment about numbers and comparisons
between the for-profit and the nonprofit sector, the vast majority of all enterprise, and particularly
for-profit enterprise, is tiny. It's less than four FTEs. Its revenue size is less than
200,000 a year. That's the majority. So you wouldn't go, Richard, to your local bodega,
nice Italian restaurant, and say, we want information rights, we want reporting, and
we want you guys to be talking about both your social goals [laughs] and your financial—because
you know what? They're not going to give you—they don't go for—they don't care about the capital
markets; they kind of have a line of credit maybe from the local bank—and it's the same
for nonprofits. They're much more the same—they're much more similar to their counterparts of
the same size as enterprise.
So for example when you're talking about the board of directors, you know, Harvard would
say, here's a, what are they, an eight-billion dollar revenue expense based corporation per
year, they're kind of, they're not at a big public company level but they're sort of up
there. They're not multi-trillion. Then you start talking about a different set of board
behaviors and so on and so on. I just think it's very important to keep in perspective
the fact that when you're comparing public companies or future venture companies to small
[laughs] community-based organizations, it's sort of like comparing... so I think we've
got to just try to get the data right from a size perspective. The nature of the beast.
And when you're talking about—the organization itself has to actually have an incentive to
find this data useful. And what happens typically in foundations is that because the size of
a grant that goes from a foundation is tiny, from an enterprise point of view, they pick
tiny enterprises to have a quote "impact" on. Because they won't have an impact, you
know, if they're making an average grant size of $50,000 a year, they're not going to have
impact on anything much beyond $300,000 of expense base. So there's all sorts of things
that are about the numbers. They're not really about, oh, these be-knighted nonprofits don't
really want—they have no incentive, actually. So I just think it's important to understand
the nature of, not just the capital market, that's sort of, that's the advanced class.
Reliable revenue. Most nonprofits' reliable revenue is from earned revenue, 70%, so there's
differences in these markets, and there's size differences that I think we have to be
cognizant of if we're going to start talking about data, information rights, etc. etc.
Just think it's important.
>> Annie Donovan: We'll go here and then...
>> Victoria Vrana: Just to build off what Clara said, briefly, I mean there's also a
structural issue. The idea that the funders could just say, give me the data? It sounds
good theoretically, but there's a structural problem in how most philanthropic funders
fund, just as Clara was saying. Most philanthropic funders give small grants for programs. So
they do say, give me the data—give me the data on that program, for last year. So the
nonprofit collects the data on that program for last year, gives it to the funder. It
might be real; it might be not; it might be validated; it might—and that doesn't give
them enterprise-level data.
It doesn't give them enterprise-level data; it doesn't give the funder enterprise-level
data; it doesn't give the sector enterprise-level data. So, because there isn't capacity for
funding for multi-year at a size that allows for that, give me that kind of data, the idea
that the funders demanding it would change it sounds good in theory, but ultimately it
has to be about the leadership wanting to collect the data for their mission, and believing
that it will make them achieve their mission. That's where it ultimately has to live. And
the ways that funders could incent that or support that are important to look at, but
it's not going to be the ultimate key to solving it.
>> Tim Ferguson: but I think that if you were prepared to actually have that as a core part
of your funding yourselves, that that might actually change it. And I would argue that,
at least in the nonprofits that we work with, the vast majority of funding is not for any
form of infrastructure. Whether it's the technology underpin, the gathering of information, the
management structure—most foundations say, no, we don't fund that. We'll fund a program;
we won't fund that.
>> Richard Ling: Or my question would be if there's an opportunity there then, right,
for a company to go and provide some very very simple automated—because there's a
lot of long-tail stuff that happens, even for these kind of, you know, accounting things.
I mean, a good example, Marisa was using Mint, right. It's for individuals, but there are
many many—there are several startups that are essentially creating Mint for small businesses.
And we're talking about Mint for flower shops and things like that, which is like four people,
it maybe has two part-time employees, and of course they have to be, they usually, the
owners of these things are fairly diligent about tracking their profits because that's
how they make a living, right? They can't even eat dinner. So they are incented in that
way. But they obviously can't go hire, understand how to save their money, they're not investing
in capital markets to maintain their cash flow and all that kind of stuff, right? But
there are services and startups that are providing products that make it incredibly easy to track
the budgeting of all that stuff.
So is there maybe an opportunity for a company that does it primarily for the nonprofit world,
where you can set up some additional metrics that, a program that you would fund, and obviously
I know it's more complex because there's many different types of programs, and some are
climate change and some are for poverty or education or whatever it is. But there's probably
at some elvel, some way to distill it down to certain things, where the reporting is
literally pushing some buttons, which is why Mint was so successful. Getting college kids
to do budgeting, which is not something anybody really wants to do, but they do it because
it's actually giving interesting feedback to them as well, about where you spend your
money, right? So there might be an opportunity to really create something like that. And
I think at that point, that adoption might have to be driven by the foundations, because
they still, there still needs to be an incentive involved.
>> Arthur "Buzz" Schmidt: It strikes me that there's another structural issue. It's multi-faceted
and it's kind of a corollary to what Victoria was talking about. That the foundations ultimately
don't report to anybody, so our, the institutional investors—the Gates Foundation actually
is a bit of an exception, because the money cares. The money is, there's a shareholder
of the Gates Foundation, and the staff reports in a real way to a shareholder there. That's
very unusual in foundations. There really is—and the giving patterns are typically
short-term. Three years, maybe. And so there's not—the institutional investor is then really
not invested in a way. The program officers are not rewarded by the quality of their grant-making.
The foundations who request information are not necessarily requesting the same information
that other foundations are requesting. The grantees are not sure what really matters
to foundations, and really doubt whether anybody's reading the reports that they submit anyway.
There's no dynamic that reinforces the value of reporting internally, other than a board
of directors of an organization.
The quality of the boards of directors of organizations are hugely varying. And seldom
incisive, I'd say. So there are no dynamics that really reinforce, that are going to require
the extraction of something consistent, until we get into systems like CoopMetrics. And
it's how we're able to combine social indicators, social impact data, along with financial impact
data, in that kind of system. Otherwise—and it's reinforced by a large number of influential
funders, and program officers that are then rewarded on the basis of how well they do.
It's kindof—
We require almost a bifurcation in foundations of the money side and the program side. I
mean, I'd like to see more intermediary grant-making. So that the money doesn't have—the Gates
money doesn't have to go through the Gates program staff, for example, because that's
an incestuous thing that limits the power of the Gates money. But there are these structural
dynamics that are really in the way.
>> Tim Ferguson: And maybe, Buzz, it's a dream, but maybe if the corporates are forced, to
have to have the social element that's a part of how they're measured, that that will force
the pace to change, and have more funding coming in to build the different sorts of
intermediaries. I mean, it's a dream, but.
>> Paul Light: I would just say to Buzz that I was at the Pew Trust, and did a lot of grants,
and Pew does a lot of grants, 4.5 billion dollar endowment, and we didn't need any measures
because every grant we made was terrific!
[laughter]
>> Tim Ferguson: Of course!
>> Paul Light: Seriously, we never made a mistake, so,
[laughter]
>> Paul Light: I mean, I want to ask you all, everybody here, because I'm listening to Clara,
and if she says the word enterprise one more time I just don't know what I'm going to do!
[laughter]
Clara is not talking about the nonprofit sector only. She's saying, thinking about all the
investees you know, what do we know about their social impact? It's not restricted to
nonprofits, government's in there, and we're trying real hard with Performance.gov to get
some sort of a handle on how government agencies do. So I was wondering whether you all as
a group, or individuals, had an indicator of any kind? Because you talked about bad
decisions you made, good decisions you made, something that you saw, one indicator? A bellwether,
that was either positive or negative, that you wish you had paid a little more attention
to, and then had drilled a little bit deeper to see whether the other data was any good.
Do you know what I mean? Do you—it could be like in presidential political science,
scientists who study the presidency, we talk about bellwether counties which is kindof
unfashionable, but the type of dog the president has, is considered a small bellwether of potential
war-like activity. Beagles being a terrible warning.
[laughter]
That's actually half true.
>> Annie Donovan: I have a picture of Bo on my phone.
[laughter]
For real! I ran into him my last day at the White House. It was so awesome.
[laughter]
>> Paul Light: Great, great—
>> Annie Donovan: I mean, I would've taken—
>> Tim Ferguson: Let's sit here and call him!
>> Annie Donovan: I would've taken a picture with the president in the Oval Office, you
know, that would have been cool, but I ran into Bo.
[laughter]
>> Paul Light: But I mean, we're talking about bellwethers. Is there anything that you would
say to somebody looking for bellwethers, positive or negative, that you saw along that way that,
oh my God, if I had only looked more closely, that was the tip-off. Or not? I mean, maybe
there isn't such a thing.
>> Richard Ling: You mean for the companies we've been involved with or...?
>> Paul Light: Organizations that you know well enough, you know, they all have social
impact, anything that might have triggered a deeper look.
>> Elizabeth Dreicer: So, I perceive that we are, there's two pieces of correlate data
that are necessary. And what we are focused on primarily first, because it is, we've got
a lot of analogues in the for-profit sector, is the financial data. I mean, clearly there
are many mechanisms to discern the financial health of an organization, and so that's what
people go for.
And it's important. And could we get that in a Mint-like, easy, no-friction strategy,
where we don't have the negative incentive issues that are present and that we've got
more of a utility structure for the field? I think that's very doable. And not far off,
actually.
The harder question that I think you're asking is like, ok, what about real value in terms
of, to society? And we can count really well: we can count how many jobs have been created.
We can count duration. So we're good at counting, too. I think the question of things around
mental health, or I think about work that I've been involved with with foster youth
in terms of resiliency—how do we measure resiliency? Are they on track? Did they make
it through that program for that year, and seem to be doing well, but does that longitudinally
really work? And I think so much of our research is very narrow, that we don't really know,
and so the question around, are there bellwethers? Sure. There are. In different programmatic
layers, I think people have teased out different metrics that they think are indicative of
success, or value creation. But we I think as a field do not have an instrumentation
for learning, nor do I think we have that in a utility framework today, even remotely.
I think we're way closer on the financial side, even though I understand my colleague's
adamancy that we need to do it. I just think that's a layup. I think the challenge is,
how do we really extract the rest of the values structure?
>> Tim Ferguson: So, I would say...
[laughter]
...that it's gut feel. When I don't follow my gut feel, I make a mistake. And that may
not be a bellwether in the way that you're thinking about it?
>> Paul Light: [inaudible] enterprise..?
>> Tim Ferguson: No. but you're asking that if you don't--that the qualitative component
is really really important, that's what it comes down to. And I look, if someone's not
measuring and managing what they're doing, and they can't articulate that, that's a problem.
And that will become a problem at some point in time. It may take ten years to manifest
itself, but if you're not measuring it, it's really really hard to know whether it's right
or wrong or how much emphasis to put on it, more capital, more people, whatever it happens
to be. Whether you're a for-profit or a not-for-profit; plenty of the businesses—the businesses
that we work with—don't do that. And we're trying to get them there so they understand
that the power, the gut feel around whether 80% of their sales come from 20% of their
customers, it's much more powerful to say, well actually the real number is this. And
here is where the concentration is, and here's how you could expand it.
I do think that intuition is really really something to pay attention to, the qualitative
piece.
>> Richard Ling: And then sometimes these goals, the goal-setting, you can use proxies
of other things, because especially in startup companies you don't really have much revenue
to go by, because you're still building a product, and you're still trying out different
ideas even of what that product might be. So what I've seen actually, there are many
different ways to set up these sort of proxy metrics. So one company for example that I
was on the board of, they set up email addresses as a capture, because they were using it to
identify people as part of their database of information on people. And so every board
meeting, every month, they would report to us how many emails. Another one was how many
page views through cookie drops that they did on partner sites. And again, this is a
way where, it was difficult at that point, they didn't know how that really translated
into revenues, because they weren't sure what they would capture from each one of these
things, but they wanted to sustain at some level of growth, they set up some goals to
inform the board, hey next year we're going to get from this many page views and this
many cookies dropped, to this many, right?
Then what they were able to do is get that entire organization focused on we got to achieve
that metric. And that metric was primarily a proxy ultimately to get more customers and
get more money for whatever they were selling, right? But the ability to do that was helpful
to focus people.
>> James Lum: I wanted to get the panel's opinion on where is the biggest gap or biggest
opportunity you saw in the nonprofit information ecosystem? Some of the things that people
have talked about is obviously information gathering, information creation, and then
information aggregation: collecting data across various NPOs and putting it into one place,
and then there's information distribution, getting that information that's either aggregated
or from the individual parts to end users, and as Buzz was talking about, well, what
do the end users do with it? With the analytical tools that they have, what's the process that
they look at this data, what actionable items do you take, what further steps outside of
the board or whoever else is evaluating the data, how they use that data, and then to
Clara's point, framing question, is, if you have an information framework, and a mechanism,
then who do you apply this to? Is it every organization in the country, or in the world?
Whether it's for-profit or not-for-profit? Across those different kind of steps in the
circle, where do you think, from your viewpoint obviously, where the best gains are to be
made? Give me the different states of relative development everywhere.
>> Tim Ferguson: From my point of view, it's not about the nonprofits actually, because
I agree with Clara on that one. The single biggest problem is getting the data, what
Liz calls the smaller level, and figuring out that aggregates up and making sure there's
integrity in it. For our business, I would never believe Dunn & Bradstreet or Hoover,
which is what Kaufman says is the gold standard and I think, really? Doesn't do what I need
to do.
And I think that's probably the same for everybody, but I might be wrong.
>> Elizabeth Dreicer: In my limited experience on the nonprofit side, although, sitting on
four boards over the course of twenty years I think they didn't have enterprise data like
we think about it in the business context, so simple business intelligence of their own
organization. And what they had is many siloed systems, whether it's a relationship management
system, an accounting system, a donor management—there's lots of systems; they weren't really bridged
together. And I think the opportunity that my colleagues mentioned around leveraging
the potential for impact, they were just absolutely not clear who their champions were in this
space, and so there was great opportunity there, and we were probably leaving lots of
potential on the table.
On the foundation side, what I've seen is that the same is true. There's lots of siloed
information: there's finance, or grants management, or even outlook is an information set, because
there's all the social paradigms of what's in outlook, it's actually your network. It's
the network of the organization. And they're not brought together yet. So, to the question
of ecosystem, I think there's simple, pretty tried-and-true business intelligence strategies
that to me feel like step one. Most of these people have systems. Connecting those systems
together to have a more holistic understanding of the organism, the enterprise, is doable,
and is doable without a lot of effort, and thanks to a lot of great tools that have already
been forged in other spaces. I think that there's a big ecosystem question. I do believe
the utility player that can support both sides, the buy and the sell side of this market,
is really important and I don't think, to the point that Victoria was making about,
I mean, I know on both sides of it, if we make a $25,000 grant to an organization, and
then they have to do some special reporting to us, we have just spent our $25,000 on US!
I mean, this is the story! So we cannot do that.
And I literally was on an organization that granted the money and another, where they
received it, and I was like, we should just reject this money! This is not a good thing!
It was net—right?!
So. Sorry.
>> Diego May: Can I—it's a comment and a question, right? A comment about the indicators
that you mentioned: I think that for any project or any NGO that is there, we could come up
with ten indicators or twenty indictors that would tell us the health of that project or
the health of that organization, or even better, the learning that we can get out of one guy
working on malaria for three years in some place, right? So I think, indicators, I don't
think it should be a big issue. It can be solved. I think. Again, I am maybe naively
thinking about this sector. The other thing, we mentioned resources, and you mentioned
that again. I don't think that's an issue either. We may not focus on the organizations
where we give 25K... but let's think about those where we give one million dollars up,
at least, or 200,000. I think that there are technologies as Richard says that can get
this to a very very low cost.
Now the question I have is, assuming that there's not friction in finding the indicators,
or the money, do these NGOs or nonprofits or projects really want to share all this
data? Yes or no?
>> Elizabeth Dreicer: My experience, and again I think there's lots of other people in the
room who can say it, and who have a lot more experience, is, to a degree, some data, yes.
I think there's a false sense of partnership in this space. My perspective is the grantee
and the grantor don't always have a joint partnership like in the venture community,
you plunk your money down and you are going to try and make sure that that organization
is successful. Here, it's like, ok, I'm going to put my money down, and you're going to,
sort of, we're going to just see if you do ok, but not necessarily intervene, because
there's that perspective of not intruding or not pushing power, your power dynamic,
on that person. So it's not an authentic partnership always. Not always, sometimes it is. But often
it's not. So I think that if you're really in a partnership with somebody and more likely
to really open the kimono and really be present and say what's not working, but if you're
worried you're going to cut off your funding by being too open, then yes, people will be—so
I think trust and creating that partnership is actually quite important.
>> Diego May: If we go into [inaudible 1:11:44] probably ten years to go when you were with
your company, right? If we asked Richard, give me the secret sauce of your algorithm
to get the ads?
[laughter]
Of course you would not give that away, right? Because that was your power; that was what
made you unique, I guess. When I think about the NGO world, and I the about the project
working on malaria for three years, that's a person trying to solve a big problem, and
hopefully trying to build knowledge that others will be able to use afterward. So, I would
never ask that to the private sector or to a private company, but in the NGO world where
there's problems that need to be solved, and knowledge that has to be built, and data that
has to be generated that is usable, that's where I would think that this data has to
be really really open. And I'm not so sure, from what I've been talking these couple days,
that NGOs are really interested. I don't think it's really about indicators or about the
money, I think it's, do they really want to share all that knowledge with the world?
>> Annie Donovan: Now, this is stepping out of my facilitator's role for a second!
[laughter]
I think, whether somebody's in the for-profit sector or nonprofit sector, they're still
a human being. And they still have incentives. They still—so if you're in the nonprofit
world, it doesn't mean you're not competing. You are competing fiercely for money and the
way you get money is you get profile and you get attention. So his [indicating Richard
Lim] secret sauce is just as important as somebody in the nonprofit world who's coming
up with some breakthrough, because they're trying to raise the resources, and the way
they raise their resources is the way they raise their profile. So they want the spotlight.
So that dynamic is absolutely active.
>> Brad Langhorst: Isn't there a distinction with sharing information with, let's say,
your venture capitalist funders, you're willing to share with them, they've given you money,
you trust them, and sharing the information with the world. Or they say, this is how it's
gonna be. You're giving us this data. And you're willing to do it. I think it's important
to draw that distinction between willing to share up—and then, and it seems like we
haven't talked much at this event about, how do we deal with the confidentiality of this
data, and the ethics of, at what point is it ok for it to go out to the rest of the
world, or to other people, or to, how do we deal with those issues? I think that's an
important area for us to think about.
>> Dana Pancrazi: And rest assured, that's the next panel. Just saying.
[laughter]
>> Richard Ling: I've seen some organizations start to be very forthcoming and do a great
job of providing—like Kiva, for example, I don't know if you've seen their annual report?
It's tremendously detailed. They do really good infographics on the success of their
programs, and because of that, I think they are very successful at fundraising; they seem
to be very successful at getting even a donor base that's well outside just the traditional
foundations, but they are very very, they create a lot of importance around that transparency.
The effectiveness of where their dollars go, their funding.
>> Annie Donovan: We'll go to Clara, and then Liz.
>> Clara Miller: I think that one thing, I think there's a difference between—that's
not understood among most funders in the nonprofit world, as far as financial role is concerned.
So some of the people who provide funds to nonprofits are buying their services on behalf
of third parties or just directly, and some of them are capital investors. In the for-profit
world these roles are very clear. They're muddled and they're poorly understood. So
from the point of view of information rights, buyers don't have the information rights that
capital investors have. And I think that that's a perfectly reasonable way to look at the
nonprofit world; it goes through that kind of enterprise finance. And I think the Kiva
example, while wonderful, is not information; it's public relations, and it's terrific.
But it's not transparency! And that's reasonable. For-profits would do the same thing. They
want to get donors; they want to drive traffic to the website. That's what that's for. That's
not actually reporting.
>> Tim Ferguson: But sometimes people have the data, and they're not organized in a way
that they want to share it, so I'll give you a specific example. Initiative for a Competitive
Inner City. A small organization, three and a half to four million. They have 15 years
of history, of information, about Inner City 100 winners, every single year for those 15
years. They didn't think to say, we should go back to them every year and collect the
data. Can you imagine if they'd done that? They would have a data set that could prove
a lot of different things, and while it wouldn't be huge, it would be robust enough that people
would look at it and wow! Or they have something called the State of the Inner City Economy,
and they could create indices of the top 100 cities...
>> Clara Miller: I'm with you! And if they had been reporting it to a database like CoopMetrics,
where they could get comparables of similar organizations and be in a market and kind
of learn from each other, you know, it would have been even better!
>> Liz Luckett: I just wanted to make a point, I think one of the major distinctions between
mission-related investing and—
[laughter]
a—for-profit investing is that the impact investments measure their impact, and even
though it's not universal and we don't all have the same standards and there's no continuum
like there is for risk, there is within each organization a discrete set of objectives
that they're trying to hit.
What's distinctive about impact investing versus others is that, having invested many
times in for-profit companies, when they fail, you have a lease you don't want and some office
furniture. When an impact investment fails, and you lose your money, you can still point
to some incredible progress, and that's what I think is a huge distinction. So if you're
looking at digital—I'm thinking of some that are for-profit or nonprofit, but let's
just say you're training kids from slums, and those kids are getting jobs and moving
on and starting their own enterprises. You do that for five years. The impact is tremendous,
generationally tremendous. Then the organization shuts down. You have a lot to show for the
investment. Quite a lot.
And that's true in many areas, and it's something to think about when you make an investment,
because I think pointing to those impact indicators that you're measuring—acres under sustainable
management; children who didn't starve that year, etc. etc. All of those things are progress,
and they're valuable, and it's something that people ought to be talking about and they
don't. They say, this one didn't work. They did micro-insurance and it failed. Well, it
might have failed as a business model, but there, I look at those kinds of investments,
and particularly in nonprofit but also in the for-profit world, as R&D for commercial
markets.
[audience: mmmm]
And it's worth thinking about that as, what they failed, and all the people who picked
up in their place, and learned from what they failed, and kept going.
>> David Rabjohns: I may be being slow today, because I had too many wines last night,
[laughter]
—but I'm still, I'm confused at the differences between the Silicon Valley model and why you
can't apply that model, particularly to the point you were talking about where these are
small companies, because it seems that in Silicon Valley you have a lot of people that
are three-person companies, coming to the market looking for money to grow those companies.
And that in the social sector you have small companies that likewise, the best of them,
the ones that are ambitious, that have the ability to produce more jobs and really have
a bigger impact on poverty, are the ones you want to single out to say, those are the ones
that can have the biggest impact, and against those people, again, they have clear goals,
right? If their goal is to generate thirty jobs this year, just like in Silicon Valley
with the board, you'd sit there as the board and say, did you create thirty jobs or not?
Those were your goals. You'd have micro-indicators, right? Here are all the steps you were going
to take to create those thirty jobs. And to be able to evaluate that investment and say,
how are they doing?
And it seems that there's all sorts of things you can steal from Silicon Valley because
Silicon Valley works quite well, in terms of incenting people through peer pressure,
through board oversight, to grow quickly and be successful, that might be useful to port
across, even if it's not the norm in the category at the moment of social. And so perhaps you
can just talk to why it's not a model that can be overlaid?
>> Clara Miller: I'd also suggest that maybe taking some people from the nonprofit sector
and putting them on the board of Goldman Sachs would probably be helpful to Goldman Sachs.
[laughter]
Because they would learn something, like a little bit of, you know, moral—not even
humility! Just understanding that they are members of society. I think that there's some
good business practices that can be applied in the not-for-profit space, absolutely, and
vice versa. But I also think that, in Silicon Valley, how many organizations seek funding
from these venture capitaloids and don't make it? And how many of these venture firms succeed
or fail? They need two things that most nonprofits don't have just by nature of their commercial
proposition: one thing is high profitability, or at least the promise of eventual profitability,
and the second is, focus on a single, overriding goal. Most nonprofits don't have the first,
and never will. Harvard is a scaled nonprofit, it's 300 years old, and it will tell you that
when it charges $100,000 tuition every year, it actually costs them $300,000, and what
do they do about that? They have two scaled subsidy businesses alongside their other stuff,
and then, you know Harvard corporation and the subsidy businesses are investment management,
and doing basic research in science and whatever it is, patents, etc. They're a complex corporation.
And they're not profitable. So the nature of the beast—
>> David Rabjohns: Right. But their goal is not profit, right?
>> Clara Miller: No, their goal is not for profit, their goal is to fulfill a market
flaw, to do something that for some reason the for-profit economy can't or won't do.
It might be, provide services to people who can't pay for them. That's one of them. It
might be, do things for which, in the case of Harvard, scale is not going to actually
make them more profitable. For example, let's say, let's scale a string quartet by taking
two people only, and having them each play two instruments instead of one. And then there
are—
[laughter]
—there are nonprofits that do things for which there is absolutely no imagined profitability
in the future, like basic research in science, that nobody—there are things that they're
doing. And then there's finally the things where scale is never, you know, the kind of
scale because of technology that increases profitability. Some of which is applicable
in the nonprofit sector. Some of it is, you know, do you really want to have fewer nurses
in the intensive care unit when you're in there? I don't! And so there's certain things
about certain business models that don't scale, and Silicon Valley, they're not going to take
them on.
>> David Rabjohns: I understand that and I don't think my point was clear because my
point was just, goals, whatever the goals are, they don't have to be profit goals, but
take the goals—the way Silicon Valley works is they say, what are your goals as an organization?
And then they measure against that, right?
>> Clara Miller: But the goals aren't so simple as making a lot of money. And, I'm not saying
that those kinds of business processes aren't useful. They are, absolutely, and there are
some things that I think that nonprofit organizations have some of the most resourceful and successful
managers in the world. And I'd put them right now, I'd say, the idea of "move over honey,
we're gonna drive", has not worked. There has been venture philanthropy for a long time
now in the nonprofit sector, some of which has had a positive effect, but it is not by
any means a big—it's not like, why can't these people learn to have goals like the
rest of us? And just scale? You know? It's—you really have to understand the business side
of it, and when you do, a lot of it won't be so simple.
>> David Rabjohns: Alright, I'll try. I'll try and learn more; I'm not getting it. I'll
try. [laughs]
>> Annie Donovan: This is great to have a heated discussion. I think one thing people
maybe don't understand, necessarily: so as Clara was saying, in Silicon Valley, you're
picking, you're discarding, as you go along, because you're looking for that optimized
opportunity. And the nonprofit sector is kind of picking up what you've discarded, and trying
to do something with it, so that adds a level of complexity—
>> David Rabjohns: but in an impact situation, aren't you trying to pick the ones that will
have the biggest impact? Isn't it the same thing? You're trying to—
>> Annie Donovan: No it's not—I mean, I would say, it's not the same thing, because—
>> Clara Miller: Profitability is very simple to measure.
>> Catherine Havasi: But as Richard was saying, in Silicon Valley sometimes you use proxy
goals, or any startup environment, use proxy goals for profitability. Number of users,
number of whatever. But the thing is, when you're starting a business, the businesses
that get favored by investors are the businesses that can easily articulate the proxy goals.
If we look at the nonprofit world, there are certain verticals of nonprofits that will
much easier for them to articulate proxy goals than others. I think you were touching on
this with things like, foster care, all different kinds of different systems. So going toward
something that sort of adopted, at least on my coast, we need to actually have venture
investors favor things that could have proxy goals, which favors certain types of businesses,
certain verticals of businesses, things like that. And I think the same things would happen
if the nonprofit sector picked up something like that.
>> Liz Luckett: Did anyone ever watch Ali G? Remember Ali G?
[laughter and "yeah, yeah"]
So there's a, one of my favorite episodes, if you haven't seen it it's worth googling,
he goes into a venture capital firm and, at one point he walks in with the top of a skateboard
and he says I'd like to raise money. I have a great idea. I'm going to—did you see Back
to the Future, you know, how they fly around on the skateboards? And they said yeah, and
he's like well, he puts the top of the skateboard down and he said, I'd like to do that, and
they said well, that's the top of a skateboard, and he's like, that's where your money comes
in.
[laughter]
And that's what impact investing is to me, because I think of that all the time, and
I think, we're trying to get skateboards to fly, right? We're saying...
[laughter]
...We want to stop poverty, we're talking about an issue that seems obvious to everyone;
we should be flying around on skateboards—but it's incredibly difficult to get there. And
if I went to you, Richard, and said, I want to stop people from killing themselves with
kerosene fires and breathing bad oils and using them in small spaces, everyone understands
that. I'm going to put solar panels on every home in these poor villages in this country.
It's going to cost $400 to put one on each home. These people make $2 a day. They'll
pay me back in four years. And when I hit 75,000 people I'll break even. That is not—a
venture capitalist goes, oh awesome! Where do I sign up! Plus I'll be back to you in
twelve months for more money; I'll be back six months after that. I will put in endless
amounts of money. But at scale, it works.
That's why it's hard. That's exactly why. Because you're saying I'm selling something
to people who don't have any money. So that doesn't sound good, right? You're often saying,
who's your target audience, and what is their disposable income, and that's how a venture
is funded.
The only comparable in the venture market that I remember is in the late 90s, where
everybody is pouring money into internet companies, and it's eyeballs, we're amassing eyeballs,
it was a very intangible concept when there was no real internet, when there weren't aggregated
giant sites. I remember meeting Jeff Bezos in '96 and being like, that is the, why did
you give up your job on Wall Street? That is the stupidest thing I ever heard of!
[laughter]
And then you're thinking, you know, he's—and six years of investment, right, before one
dollar came back. It's the only comparable thing. You're amassing a population that wasn't
amassed yet. And that's what you're talking about when you're trying to solve issues around
poverty and inequality in society, you're trying to solve, you're amassing a population
that is disparate, that is very hard to find. There is no sales channel. There is no way
to reach them. That's what is so expensive. And there's often now a CapEx hurdle. I think
the best advantage we have is mobile phones, because they are prevalent, but again, you
can't find those people, you can't sell to them, you can't contact them on their phone.
They're all pre-paid cards. It's very hard to go door to door in these places, convince
them of what they need, sell them something. It's a HUGE investment cycle.
>> Annie Donovan: OK, so we'll go here, and then we'll go back there, and then we'll wrap
>> Mauricio Miller: So I hate to throw cold water on some of this, but—
[laughter]
—well, the dilemma is that the conversation is generally in these things always end up
in terms of how we fund nonprofits and the organizations, and those particular types
of organizations, I keep wondering why, and it's probably because we're used to those
kind of structures. They have board of directors—I don't know why. Anyway, we keep talking about
that, and in the life I've seen, in the lives I've seen, nonprofits play maybe a 10% role
in people's lives. Probably less than that. A nonprofit will impact one of 1000 people
that may need that service, or it impacts significantly maybe one person's life and
many of the others that is significant, so, a nonprofit is kind of like it provides service,
like my kids would go to a camp in summer. Going to camp in the summer was a really good
thing for my kid; it did not change my life. So those are—not that they're bad things,
those are good programs, recidivism programs, whatever, so I'm not saying anything terrible
about nonprofits, but we're not having the conversation in the right place.
I think what's most comparable to Richard is this woman, Jolly, who just started a business.
Now she's doing a nursing business in the middle of the night for mothers that, you
know because the nurses are gone or whatever, and remember how I showed you that these families
actually had accumulated $750,000. They're trying businesses. They're not sexy, okay,
they don't have these great ideas. It's like, delivery trucks for a bakery, but they bought
three trucks. They need investment.
Okay, so they're not sexy, but, we're still talking really of top down. Even if you go
to the nonprofits you're still talking about top down. What we need to do is get from bottom
up. And maybe they're not sexy, and what we don't have are the angel investors, that you
would talk to—the comparable to Richard and the startups are these families that we're
seeing, and the data that you saw. You want to get bottom-up, you have to invest in there.
And we need intermediary type of organizations that actually know how to invest in that.
Not service providers. Not top-down piece. So that's where the system has to really change,
because the activity is really at the bottom. These families are amazing in terms of all
the ideas and all the things they can do. We need to capture that information, otherwise
you don't have a conversation, because you don't have that information, so you keep having
conversation about the nonprofits. So somehow or other you gotta help me change this conversation!
[laughs] OK? and we gotta get that information out. That's it.
>> Jason Payne: I want to politely but strongly disagree with some of the comments made about
Kiva earlier. I actually think they're a paragon of excellence for open data, and they publish
every single loan that they make in real-time, as well as provide an ability, through every
single open data format that's used today, to access that information. In theory, it's
a net negative to them: what they have to pay for someone to pull GBs of data and to
maintain all those interfaces actually hurts them from their mission, but the externalities
and the value to folks like myself and money of us in the room and a plethora of other
organizations that can use that granular data as a valuable significant for all sorts of
other things, is extraordinarily important, and so overall if the ecosphere were inspiring
more organizations to actually release raw data, I think you'd see a radical improvement,
a radical change in outcomes, of different sets of data coming together.
>> Annie Donovan: Anyone, last comments?
>> Elizabeth Dreicer: I concur with the last comment that was made. I think the push toward
open intel is going to change a lot of what we know, and I think it's part of the apparatus
of what we need to do to instrument ourselves for learning. I'll leave it at that.
>> Annie Donovan: Ok, well that's a wrap. Thank you.
[applause]