Tag Archives: randomized trials

New European Standard for Social Impact Measurement

geces_report_coffee_2_evalblog

 

Evaluation has truly become a global movement. The number of evaluators and evaluation associations around the world is growing, and they are becoming more interconnected. What affects evaluation in one part of the world increasingly affects how it is practiced in another.

That is why the European standard for social impact measurement, announced just a few weeks ago, is important for evaluators in the US.

According to the published report and its accompanying press release, the immediate purpose of the standard is to help social enterprises access EU financial support, especially in relation to the European Social Entrepreneurship Funds (EuSEFs) and the Programme for Employment and Social Innovation (EaSI).

But as László Andor, EU Commissioner for Employment, Social Affairs and Inclusion, pointed out, there is a larger purpose:

The new standard…sets the groundwork for social impact measurement in Europe. It also contributes to the work of the Taskforce on Social Impact Investment set up by the G7 to develop a set of general guidelines for impact measurement to be used by social impact investors globally.

That is big, and it has the potential to affect evaluation around the world.

What is impact measurement?

For evaluators in the US, the term impact measurement may be unfamiliar. It has greater currency in Europe and, of late, in Canada. Defining the term precisely is difficult because, as an area of practice, impact measurement is evolving quickly.

Around the world, there is a growing demand for evaluations that incorporate information about impact, values, and value. It is coming from government agencies, philanthropic foundations, and private investors who want to increase their social impact by allocating their public or private funds more efficiently.

Sometimes these funders are called impact investors. In some contexts, the label signals a commitment to grant making that incorporates the tools and techniques of financial investors. In others, it signals a commitment by private investors to a double bottom line—a social return on their investment for others and a financial return for themselves.

These funders want to know if people are better off in ways that they and other stakeholders believe are important. Moreover, they want to know whether those impacts are large enough and important enough to warrant the funds being spent to produce them. In other words, did the program add value?

Impact measurement may engage a wide range of stakeholders to define the outcomes of interest, but the overarching definition of success—that the program adds value—is typically driven by funders. Value may be assessed with quantitative, qualitative, or mixed methods, but almost all of the impact measurement work that I have seen has framed value in quantitative terms.

Is impact measurement the same as evaluation?

I consider impact measurement a specialized practice within evaluation. Others do not. Geographic and disciplinary boundaries have tended to isolate those who identify themselves as evaluators from those who conduct impact measurement—often referred to as impact analysts. These two groups are beginning to connect, like evaluators of every kind around the world.

I like to think of impact analysts and evaluators as twins who were separated at birth and then, as adults, accidentally bump into each other at the local coffee shop. They are delighted and confused, but mostly delighted. They have a great deal to talk about.

How is impact measurement different from impact evaluation?

There is more than one approach to impact evaluation. There is what we might call traditional impact evaluation—randomized control trials and quasi-experiments as described by Shadish, Cook, and Campbell. There are also many recently developed alternatives—contribution analysis, evaluation of collective impact, and others.

Impact measurement differs from traditional and alternative impact evaluation in a number of ways, among them:

  1. how impacts are estimated and
  2. a strong emphasis on valuation.

I discuss both in more detail below. Briefly, impacts are frequently estimated by adjusting outcomes for a pre-established set of potential biases, usually without reference to a comparison or control group. Valuation estimates the importance of impacts to stakeholders—the domain of human values—and expresses it in monetary units.

These two features are woven into the European standard and have the potential to become standard practices elsewhere, including the US. If they were to be incorporated into US practice, it would represent a substantial change in how we conduct evaluations.

What is the new European standard?

The standard creates a common process for conducting impact measurement, not a common set of impacts or indicators. The five-step process presented in the report is surprisingly similar to Tyler’s seven-step evaluation procedure, which he developed in the 1930s as he directed the evaluation of the Eight-Year Study across 30 schools. For its time, Tyler’s work was novel and the scale impressive.

tyler_geces_table_evalblog

Tyler’s evaluation procedure developed in the 1930s and the new European standard process: déjà vu all over again?

Tyler’s first two steps were formulating and classifying objectives (what do programs hope to achieve and which objectives can be shared across sites to facilitate comparability and learning). Deeply rooted in the philosophy of progressive education, he and his team identified the most important stakeholders—students, parents, educators, and the larger community—and conducted much of their work collaboratively (most often with teachers and school staff).

Similarly, the first two steps of the European standard process are identifying objectives and stakeholders (what does the program hope to achieve, who benefits, and who pays). They are to be implemented collaboratively with stakeholders (funders and program staff chief among them) with an explicit commitment to serving the interests of society more broadly.

Tyler’s third and fourth steps were defining outcomes in terms of behavior and identifying how and where the behaviors could be observed. The word behavior was trendy in Tyler’s day. What he meant was developing a way to observe or quantify outcomes. This is precisely setting relevant measures, the third step of the new European standard process.

Tyler’s fifth and sixth steps were selecting, trying, proving, and improving measures as they function in the evaluation. Today we would call this piloting, validation, and implementation. The corresponding step in the standard is measure, validate and value, only the last of these falling outside the scope of Tyler’s procedure.

Tyler concluded his procedure with interpreting results, which for him included analysis, reporting, and working with stakeholders to facilitate the effective use of results. The new European standard process concludes in much the same way, with reporting results, learning from them, and using them to improve the program.

How are impacts estimated?

Traditional impact evaluation defines an impact as the difference in potential outcomes—the outcomes participants realized with the program compared to the outcomes they would have realized without the program.

It is impossible to observe both of these mutually exclusive conditions at the same time. Thus, all research designs can be thought of as hacks, some more elegant than others, that allow us to approximate one condition while observing the other.

The European standard takes a similar view of impacts and describes a good research design as one that takes the following into account:

  • attribution,the extent to which the program, as opposed to other programs or factors, caused the outcomes;
  • deadweight, outcomes that, in the absence of the program, would have been realized anyway;
  • drop-off, the tendency of impacts to diminish over time; and
  • displacement, the extent to which outcomes realized by program participants prevent others from realizing those outcomes (for example, when participants of a job training program find employment, it reduces the number of open jobs and as a result may make it more difficult for non-participants to find employment).

For any given evaluation, many research designs may meet the above criteria, some with the potential to provide more credible findings than others.

However, impact analysts may not be free to choose the research design with the potential to provide the most credible results. According to the standard, the cost and complexity of the design must be proportionate to the size, scope, cost, potential risks, and potential benefits of the program being evaluated. In other words, impact analysts must make a difficult tradeoff between credibility and feasibility.

How well are analysts making the tradeoff between credibility and feasibility?

At the recent Canadian Evaluation Society Conference, my colleagues Cristina Tangonan, Anna Fagergren (not pictured), and I addressed this question. We described the potential weaknesses of research designs used in impact measurement generally and Social Return on Investment (SROI) analyses specifically. Our work is based on a review of publicly available SROI reports (to date, 107 of 156 identified reports) and theoretical work on the statistical properties of the estimates produced.

ces_2014_tangonan_gargani_evalblogAt the CES 2014 conference.

What we have found so far leads us to question whether the credibility-feasibility tradeoffs are being made in ways that adequately support the purposes of SROI analyses and other forms of impact measurement.

One design that we discussed starts with measuring the outcome realized by program participants. For example, how many participants of a job training program found employment, or the test scores realized by students who were enrolled in a new education program. Sometimes impact analysts will measure the outcome as a pre-program/post-program difference, often they measure the post-program outcome level on its own.

Once the outcome measure is in hand, impact analysts adjust it for attribution, deadweight, drop-off, and displacement by subtracting some amount or percentage for each potential bias. The adjustments may be based on interviews with past participants, prior academic or policy research, or sensitivity analysis. Rarely are they based on comparison or control groups constructed for the evaluation. The resulting adjusted outcome measure is taken as the impact estimate.

This is an example of a high-feasibility, low-credibility design. Is it good enough for the purposes that impact analysts have in mind? Perhaps, but I’m skeptical. There is a century of systematic research on estimating impacts—why didn’t this method, which is much more feasible than many alternatives, become a standard part of evaluation practice decades before? I believe it is because the credibility of the design (or more accurately, the results it can produce) is considered too low for most purposes.

From what I understand, this design–and others that are similar–would meet the European standard. That leads me to question whether the new standard has set the bar too low, unduly favoring feasibility over credibility.

What is valuation?

In the US, I believe we do far less valuation than is currently being done in Europe and Canada. Valuation expresses the value (importance) of impacts in monetary units (a measure of importance).

If the outcome, for example, were earned income, then valuation would entail estimating an impact as we usually would. If the outcome were health, happiness, or well-being, valuation would be more complicated. In this case, we would need to translate non-monetary units to monetary units in a way that accurately reflects the relative value of impacts to stakeholders. No easy feat.

In some cases, valuation may help us gauge whether the monetized value of a program’s impact is large enough to matter. It is difficult to defend spending $2,000 per participant of a job training program that, on average, results in additional earned income of $1,000 per participant. Participants would be better off if we gave $2,000 to each.

At other times, valuation may not be useful. For example, if one health program saves more lives than another, I don’t believe we need to value lives in dollars to judge their relative effectiveness.

Another concern is that valuation reduces the certainty of the final estimate (in monetary units) as compared to an impact estimate on its own (in its original units). That is a topic that I discussed at the CES conference, and will again at the conferences of the European Evaluation Society, Social Impact Analysts Association, and the American Evaluation Association .

There is more to this than I can hope to address here. In brief—the credibility of a valuation can never be greater than the credibility of the impact estimate upon which it is based. Call that Gargani’s Law.

If ensuring the feasibility of an evaluation results in impact estimates with low credibility (see above), we should think carefully before reducing credibility further by expressing the impact in monetary units.

Where do we go from here?

The European standard sets out to solve a problem that is intrinsic to our profession–stakeholders with different perspectives are constantly struggling to come to agreement about what makes an evaluation good enough for the purposes they have in mind. In the case of the new standard, I fear the bar may be set too low, tipping the balance in favor of feasibility over credibility.

That is, of course, speculation. But so too is believing the balance is right or that it is tipped in the other direction. What is needed is a program of research—research on evaluation—that helps us understand whether the tradeoffs we make bear the fruit we expect.

The lack of research on evaluation is a weak link in the chain of reasoning that makes our work matter in Europe, the US, and around the world. My colleagues and I are hoping to strengthen that link a little, but we need others to join us. I hope you will.

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On the Recursive Nature of Recursion: Reflections on the AEA 2013 Conference

John Gargani Not Blogging

Recursion is when your local bookstore opens a café inside the store in order to attract more readers, and then the café opens a bookstore inside itself to attract more coffee drinkers.

Chris Lysy at Freshspectrum.com noticed, laughed at, and illustrated (above) the same phenomenon as it relates to my blogging (or rather lack of it) during the American Evaluation Association Conference last week.

I intended to harness the power of recursion by blogging about blogging at the conference. I reckoned that would nudge a few others to blog at the conference, which in turn would nudge me to do the same.

I ended up blogging very little during those hectic days, and none of it was about blogging at the conference. Giving up on that idea, I landed on blogging about not blogging, then not blogging about not blogging, then blogging about not blogging about not blogging, and so on.

Once Chris opened my eyes to the recursive nature of recursion, I noticed it all around me at the conference.

roe_aea_2013_evalblogFor example, the Research on Evaluation TIG (Topical Interest Group) discussed using evaluation methods to evaluate how we evaluate. Is that merely academic navel gazing? It isn’t. I would argue that it may be the most important area of evaluation today.

As practitioners, we conduct evaluations because we believe they can make a positive impact in the world, and we choose how to evaluate in ways we believe produce the greatest impact. Ironically, we have little evidence upon which to base our choices. We rarely measure our own impact or study how we can best achieve it.

ROE (research on evaluation, for those in the know) is setting that right. And the growing community of ROE researchers and practitioners is attempting to do so in an organized fashion. I find it quite inspiring.

A great example of ROE and the power of recursion is the work of Tom Cook and his colleagues (chief among them Will Shadish).tom_cook_aea_2103_evalblogI must confess that Tom is a hero of mine. A wonderful person who finds tremendous joy in his work and shares that joy with others. So I can’t help but smile every time I think of him using experimental and quasi-experimental methods to evaluate experimental and quasi-experimental methods.

Experiments and quasi-experiments follow the same general logic. Create two (or more) comparable groups of people (or whatever may be of interest). Provide one experience to one group and a different experience to the other. Measure outcomes of interest for the two groups at the end of their experiences. Given that, differences in outcomes between the groups are attributable to differences in the experiences of the groups.

If on group received a program and the other did not, you have a very strong method for estimating program impacts. If on group received a program designed one way and the other a program designed another way, you have a strong basis for choosing between program designs.

Experiments and quasi-experiments differ principally in how they create comparable groups. Experiments assign people to groups at random. In essence, names are pulled from a hat (in reality, computers select names at random from a list). This yields two highly comparable but artificially constructed groups.

Quasi-experiments typically operate by allowing people to choose experiences as they do in everyday life. This yields naturally constructed groups that are less comparable. Why are they less comparable? The groups are comprised of people who made difference choices, and these choice may be associated with other factors that affect outcomes. The good news is that the groups can be made more comparable–to some degree–by using a variety of statistical methods.

four_arm_study_aea_2013_evalblogIs one approach better than another? At the AEA Conference, Tom described his involvement with efforts to answer that question. One way that is done is by randomly assigning people to two groups–one group that will be part of an experiment or another group that will be part of a quasi-experiment (referred to as an observational study in the picture above). Within the experimental group, participants are randomly assigned to either a treatment group (e.g., math training) or control group (vocabulary training). Within the quasi-experimental group, participants choose between the same two experiences, forming treatment and comparison groups according to their preference.

Program impact estimates are compared for the experimental and quasi-experimental groups. Differences at this level are attributable to the evaluation method and can indicate whether one method is biased with respect to the other. So far, there seems to be pretty good agreement between the methods (when implemented well–no small achievement), but much work remains to be done.

coming_together_aea_2013_evalblog

Perhaps the most important form of recursion at the AEA Conference is membership. AEA is comprised of members who manage themselves by forming groups of members who manage themselves by forming groups of members who manage themselves. The board of AEA, TIGs, local affiliates, task forces, working groups, volunteer committees, and conference sessions are all organized by and comprised of groups of members who manage themselves. That is power of recursion–3,500 strangers coming together to create a community dedicated to making the world a better place. And what a joy to watch them pull it off.

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Conference Blog: The Harvard Social Enterprise Conference (Day 1)

What follows is a series of short posts written while I attended the Social Enterprise Conference (#SECON12).  The conference (February 25-26) was presented by the Harvard Business School and the Harvard Kennedy School.

What is a social enterprise?

The concept of a social enterprise is messy.  By various definitions, it can include:

  • A for-profit company that seeks to benefit society;
  • a nonprofit organization that uses business-like methods;
  • a foundation that employs market investing principles; and
  • a government agency that leverages the work of private-sector partners.

The concept of a social enterprise is disruptive. It blurs the lines separating organizations that do good for stakeholders, do well for shareholders, and do right by constituents.

The concept of a social enterprise is inspiring.  It can foster flexible, creative solutions to our most pressing problems.

The concept of a social enterprise is dangerous.  It can attach the patina of altruism to organizations motivated solely by profits.

The concept of a social enterprise is catching fire.  The evaluation community needs to learn how it fits into this increasingly common type of organization.

The conference started with a young entrepreneurs keynote panel that was moderated by Daniel Epstein (Unreasonable Institute).

Kavita Shukla of Fenugreen discussed the product she invented.  Amazing.  It is a piece of paper permeated with organic, biodegradable herbs.  So what?  It keeps produce fresh 2-4 times longer.  The potential social and financial impact of the product—especially in parts of the world where food is in short supply and refrigeration scarce—is tremendous. Watch a TED talk about it here.

Next, Taylor Conroy (Destroy Normal Consulting) discussed his fundraising platform that allows people to raise $10,000 in three hours for projects like building schools in developing countries.  Sound crazy?  Check it out here and decide for yourself.

Finally, Lauren Bush (FEED Projects) discussed how she has used the sale of FEED bags and other fashion items to provide over 60 million meals for children in need around the world.

Evaluation moment #1: The panelists were asked how they measured the social impact of their enterprises.  Disappointingly, they do not seem to be doing so in a systematic way beyond counting units of service provided or number of products sold—a focus on outputs, not outcomes.

The first session I attended had the provocative title Social Enterprise: Myth or Reality?: Measuring Social Impact and Attracting Capital. Jim Bildner did an outstanding job as moderator.  Panelists included Kimberlee Cornett (Kresge Foundation), Clara Miller (F. B. Heron Foundation), Margaret McKenna (Harvard Kennedy School), and David Wood (Hauser Center for Nonprofit Organizations).

The discussion addressed three questions.

Q: What is social enterprise?

A: It apparently can be anything, but it should be something that is more precisely defined.

Q: How are foundations and financial investors getting involved?

A: By making loans and taking equity stakes in social enterprises.  That promotes social impact through the enterprise and generates more cash to invest in other social enterprises.

Evalution moment #2: Q: How can the social impact of enterprises be measured?

A: It isn’t.  One panelist suggested that measuring social impact is such a tough nut to crack that, if someone could figure out how, it would make for a fantastic new social enterprise.  I was both shocked and flattered, given I have been doing just that for decades.  Why were there no evaluators on this panel?


Ami Dalal and Jo-Ann Tan of Acumen Fund conducted a “bootcamp” on the approach their firm uses to make social investments.  They focused on methods of due diligence and valuation (that is, how they attach a dollar value to a social enterprise).

I found their approach to measuring the economic impact of the their investments very interesting—perhaps evaluators would benefit from learning more about it.  There are details at their website.

Evaluation moment #3

When the topic of measuring the social impact of their investments came up, the presenters provided the most direct answer I have heard so far.  They always measure outputs—those are easy to measure and can indicate if something is going wrong.  In some cases they also measure outcomes (impacts) using randomized control trials.  Given the cost, they do this infrequently.

Looking back on the day

A social enterprise that measures social impact but does not measure financial success would be considered ridiculous.  Yet a social enterprise that measures financial success but does not measure social impact is not.  Why?

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Fruitility (or Why Evaluations Showing “No Effects” Are a Good Thing)

sisyphus

The mythical character Sisyphus was punished by the gods for his cleverness.   As mythological crimes go, cleverness hardly rates and his punishment was lenient — all he had to do was place a large boulder on top of a hill and then he could be on his way.

The first time Sisyphus rolled the boulder to the hilltop I imagine he was intrigued as he watched it roll back down on its own.  Clever Sisyphus confidently tried again, but the gods, intent on condemning him to an eternity of mindless labor, had used their magic to ensure that the rock always rolled back down.

Could there be a better way to punish the clever?

Perhaps not. Nonetheless, my money is on Sisyphus because sometimes the only way to get it right is to get it wrong. A lot.

This is the principle of fruitful futility, or as I call it fruitility. Continue reading

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The Most Difficult Part of Science

tesla

I recently participated in a panel discussion at the annual meeting of the California Postsecondary Education Commission (CPEC) for recipients of Improving Teacher Quality Grants.  We were discussing the practical challenges of conducting what has been dubbed scientifically-based research (SBR).  While there is some debate over what types of research should fall under this heading, SBR almost always includes randomized trials (experiments) and quasi-experiments (close approximations to experiments) that are used to establish whether a program made a difference. 

SBR is a hot topic because it has found favor with a number of influential funding organizations.  Perhaps the most famous example is the US Department of Education, which vigorously advocates SBR and at times has made it a requirement for funding.  The push for SBR is part of a larger, longer-term trend in which funders have been seeking greater certainty about the social utility of programs they fund.

However, SBR is not the only way to evaluate whether a program made a difference, and not all evaluations set out to do so (as is the case with needs assessment and formative evaluation).  At the same time, not all evaluators want to or can conduct randomized trials.  Consequently, the push for SBR has sparked considerable debate in the evaluation community. Continue reading

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Randomized Trials: Old School, New Trend

surfers

To my mind, surfing hit its peak in the 1950s when relatively light longboards first became available.

Enthusiastic longboarders still ride the waves, of course, but their numbers have dwindled as shorter more maneuverable boards became more fashionable. Happily, longboards are now making a comeback, mostly because they possess a property that shortboards do not: stability. With a stable board novices can quickly experience the thrill of the sport and experts can show off skills like nose walks, drag turns, and tandem riding that are unthinkable using today’s light-as-air shortboards.

The new longboards are different — and, I think, better — because their designs take advantage of modern materials and are more affordable and easier to handle than their predecessors. It just goes to show that everything old becomes new again, and with renewed interest comes the opportunity for improvement.

The same can be said for randomized trials (RTs). They were introduced to the wider field of social sciences in the 1930s, about the time that surfing was being introduced outside of Hawaii. RTs became popular through the 1950s, at least in concept because they can be challenging and expensive to implement. During the 60s, 70s and 80s, RTs were supplanted by simpler and cheaper types of evaluation. But a small and dedicated cadre of evaluators stuck with RTs because of a property that no other form of evaluation has: strong internal validity. RTs make it possible to ascertain with a high degree of certainty — higher than any other type of evaluation — whether a program made a difference. Continue reading

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What Is An Evaluation?

whatsit

One of my first evaluation projects started with a phone call (e-mail was rare in those long ago days). The conversion went something like this …

“John, we have this grant that requires that we do an evaluation. Sounds great. Love it. Can’t wait to get started. Just one question—What’s an evaluation?”

While a great deal has changed in the years since I fielded that call, I still like to joke that evaluation is the largest profession that no one has heard of. The American Evaluation Association has over 6,000 members, and during the past five years their ranks swelled by 40 percent. Virtually every grant awarded today by a government funding agency, philanthropic foundation or corporation requires an evaluation. Yet evaluators and their work are unknown to most Americans, so much so that at dinner parties I find myself feeling uncomfortable for the poor soul seated next to me who innocently asks, “What do you do?” How can I possibly explain before the table is cleared?

My standard answer is that I help professionals who manage educational and social programs figure out how effective their programs are and find ways to make their programs more effective. I go on to explain that I run a firm in which I and my colleagues specialize in something rather particular and technical called randomized trials. Essentially, these are experiments similar to the ones that doctors and drug companies conduct to ensure that medical treatments are effective. Continue reading

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