theory of change

Thinking More About Using Personas/Personae In Developing Theories of Change

I have previously advocated, here (and here), for taking a ‘persona’ or character-based approach to fleshing out a theory of change. This is a way of involving a variety of stakeholders (especially those closer to the ground, such as intended beneficiaries and street-level implementer’s) in discussions about program and theory of change development — even when they are not physically at the table, which is not always possible (though encouraged, of course).

This week, I had a new chance to put some of these ideas into action. A few lessons learned for future efforts:

  • This activity worked well in small groups. However, it may be too much to ask groups to fully develop their own personae, especially given possible time limits within the confines of a workshop.
    • It may be better to have some partially developed characters in mind (for example, that represent differing initial levels of the key outcomes of interest and variation on some of the hypothesized sub-groups of interest (explanatory variables). Groups can then take a shorter amount of time to elaborate — rather than develop — these dossiers and give a name to each of their creations (Mary, Bob, Fatima, etc). Alternatively, developing dossiers (and therefore articulating sub-groups of interest) could be a separate, opening activity.
  • Introducing any language about “role-playing” can lead to only one person in a group assuming the role of a given character and the group sort of playing ’20 Questions’ to that character, rather than everyone trying to consider and take on the thoughts, intentions, and decisions and steps a given character might take, confronted with a given intervention (as either a targeted beneficiary or an implementer). The idea is to get the team thinking about the potential barriers and enablers at multiple levels of influence (i.e. assumptions) that may be encountered on the path towards the outcomes of interest.
  • Speaking in “I” statements is helpful in helping people try to think like the different adopted personae. I really had to nag people on this in the beginning but I think it was ultimately useful to get people speaking in this way. In relation to this, there may be important lessons from cognitive interviewing (how-to here) practice, to get activity participants to think out loud about the chain of small decisions and actions they would need to take when confronted with a new program or policy.
  • I noted a marked tendency this time around for men to only speak for male characters and for women, the same! There may be some creative ways to discourage this (thoughts welcome).
  • There are two potential key goals of an activity like this, which should be kept distinct (and be articulated early and often during the activity) even though they are iterative.
    • A first relates to Elaborating Activities, that is, to develop a robust intervention, so that nuance to activities and ‘wrap-around’ support structures (to use Cartwright and Hardie’s terminology) and activities can be developed. This can lead to a laundry or wish list of activities — so if is at the brainstorming stage, this can be articulated as an ‘ok’ outcome or even an explicit goal.
    • A second relates to Explicating and Elaborating assumptions, filling in all the intermediate steps between the big milestones in a results chain. This second goal is bound up in the process of moving from a log-frame to a robust theory of change (as noted by John Mayne at the Canadian Evaluation Society, this is adding all the arrows to the results chain boxes) as well as a more robust and nuanced set of indicators to measure progress towards goals and uncover mechanisms leading to change.
      • A nice wrap-up activity here could include sorting out the assumptions for which evidence is already available and which should be collected and measured as part of research work.
  • It remains an important activity to elaborate and verbally illustrate how X character’s routines and surroundings will be different if the end-goals are reached — given that social, environmental, infrastructural and institutional change is often the goal of ‘development’ efforts. This last step of actually describing how settings and institutions may operate differently, and the implications on quotidian life, is an important wrap-up and time needs to be made for it.

Of course, the use of personae (or an agent-based perspective) is only one part of elaborating a theory of change. But it can play an important role in guiding the other efforts to provide nuance and evidence, including highlighting where to fill in ideas from theoretical and empirical work to end up with a robust theory of change that can guide the development of research methods and instruments.

Would be great to hear further ideas and inputs!

Thinking About Building Evaluation Ownership, Theories of Change — Back From Canadian Evaluation Society

This week I had the pleasure of attending the Canadian Evaluation Society (#EvalC2015) meeting in Montreal, which brought together a genuinely nice group of people thinking not just hard a-boot evaluation strategies and methodologies but also how evaluation can contribute to better and more transparent governance, improving our experience as global and national citizens — that is, evaluation as a political (and even social justice) as much as a technical act.

Similarly, there was some good conversation around the balance between the evaluation function being about accountability versus learning and improvement and concern about when the pendulum swings too far to an auditing rather than an elucidating and improving role.

For now, I want to zoom in on a two important themes and more own nascent reflections on them. I’ll be delighted to get feedback on these thoughts, as I am continuing to firm them up myself. my thoughts are in italics, below.

  1. Collaboration, neutrality and transparency. 
    1. There were several important calls relating to transparency, including a commitment to making evaluation results public (and taking steps to make sure citizens see these results (without influencing their interpretation of them or otherwise playing an advocacy role)) and for decision-makers claiming to have made use of evidence to inform their decisions to be more open about how and which evidence played this role. This is quite an important point and it echoes some of the points Suvojit and I made about thinking about the use of evaluative evidence ex ante. We’re continuing to write about this, so stay tuned.
    2. There was quite a bit of push back about whether evaluation should be ‘neutral’ or ‘arm’s length’ from the program — apparently this is the current standard practice in Canada (with government evaluations). This push back seems to echo several conversations in impact evaluation about beginning stakeholder engagement and collaboration far earlier in the evaluation process, including Howard White’s consideration of evaluative independence.
    3. Part of the push back on ‘arm’s length neutrality’ came from J. Bradley Cousins, who will have a paper and ‘stimulus document’ coming out in the near future on collaborative evaluation that seems likely to be quite interesting. In another session, it was noted that ‘collaboration has more integrity than arm’s length approaches. I particularly liked the idea of thinking about how engagement between researchers and program/implementation folks could improve a culture of evaluative thinking and organizational learning — a type of ‘capacity building’ we don’t talk about all that often. Overall, I am on board with the idea of collaborative evaluation, with the major caveat that evaluators need to report honestly about the role the play vis-a-vis refining program theory, refining the program contents, assisting with implementing the program, monitoring, etc.
  2. Building a theory of change and fostering ownership in an evaluation.
    1. There was a nice amount of discussion around making sure that program staff, implementers, and a variety of stakeholders could “see themselves” in the theory of change and logic model/results chain. This not only included that they could locate their roles but also that these planning and communication tools reflected the language with which they were used to talking about their work. Ideally, program staff can also understanding their roles and contributions in light of their spheres of direct and indirect influence.
    2. John Mayne and Steve Montague made some very interesting points about building a theory of change, which I will have to continue to process over the upcoming weeks. they include:
      1. Making sure to think about ‘who’ in addition to ‘what’ and ‘why’ — this includes, I believe, who is doing what (different types and levels of implementer’s) as well as defining intended reach, recognizing that some sub-groups may require different strategies and assumptions in order for an intervention to reach them.
      2. As was noted “frameworks that don’t consider reach conspire against equity and fairness” because “risks live on the margin.” I haven’t fully wrapped my head around the idea of ‘theories of reach’ embedded or nested within the theory of change but am absolutely on-board with considering distributional expectations and challenges from the beginning and articulating assumptions about when and why we might expect heterogeneous treatment effects — and deploying quantitative and qualitative measurement strategies accordingly.
    3. John Mayne advocated his early thoughts that for each assumption in a theory of change, the builders should articulate a justification for its:
      1. Necessity — why is this assumption needed?
      2. Realization — why is this assumption likely to be realized in this context?
      3. This sounds like an interesting way to plan exercises towards collaborative building of theories of change
    4. a productive discussion developed (fostered by John Mayne, Steve Montague and Kaireen Chaytor, among others) around how to get program staff involved in articulating the theory of change. A few key points were recurring — with strong implications for how long a lead time is needed to set up an evaluation properly (which will have longer-term benefits even if it seems to be slightly inefficient upfront):
      1. Making a theory of change and its assumptions explicit is part of a reflective practice of operations and implementation.
      2. Don’t try to start tabula rasa in articulating the theory of change (‘the arrows’) with the implementing and program staff. Start with the program documents, including their articulation of the logic model or results chain (the ‘boxes’ in a diagrammatic theory of change) and use this draft as the starting point for dialogue.
      3. It may help to start with one-on-ones with some key program informants, trying to unpack what lies in the arrows connecting the results boxes. This means digging into the ‘nitty girtty’ micro-steps and assumptions, avoiding magical leaps and miraculous interventions. Starting with one-on-ones, rather than gathering the whole group to consider the results chain, can help to manage some conflict and confusion and build a reasonable starting point — despite the fact that:
      4. Several commentators pointed out that it is unimportant whether the initial results chain was validated or correct — or was even set up as a straw-person. Rather, what is important was having something common and tangible that could serve as a touchstone or boundary object in bringing together the evaluators and implementer’s around a tough conversation. In fact, having some flaws in the initial evaluators’ depiction of the results chain and theory of change allows opportunities for program staff to be the experts and correct these misunderstandings, helping to ensure that program staff are not usurped in the evaluation design process.
      5. Initial disagreement around the assumptions (all the stuff behind the arrows) in the theory of change can be productive if they are allowed to lead to dialogue and consensus-building. Keep in mind that the theory of change can be a collaborative force. As Steve Montague noted, “building a theory of change is a team sport,” and needs to be an iterative process between multiple stakeholders all on a ‘collective learning journey.’
        1. One speaker suggested setting up a working group within the implementing agency to work on building the theory of change and, moreover, to make sure that everyone internally understands the program in the same way.
    5. This early engagement work is the time to get construct validity right.
    6. The data collection tools developed must, must, must align with the theory of change developed collectively. This is also a point Shagun and i made in our own presentation at the conference, where we discussed our working paper on meaningfully mixing methods in impact evaluation. stay tuned!
    7. The onus is on the evaluator to make sure that the theory of change is relevant to many stakeholders and that the language used is familiar to them.
    8. There was also a nice discussion about making sure to get leadership buy-in and cooperation early in the process on what the results reporting will look like. Ideally the reporting will also reflect the theory of change.

Overall, much to think about and points that I will definitely be coming back to in later work. Thanks again for a great conference.

theories of change, stakeholders, imagined beneficiaries, & stealing from product design. that is, meet ‘mary.’

this post is also available, lightly edited, here.

i have been thinking a lot about ‘theories of change’ this week (just did some presenting on them here!). actually, i have been thinking more about ‘conceptual models,’ which was the term by which i was first introduced to the general idea (via vic strecher in conceptual models 101) and the term i still prefer because it implies more uncertainty and greater scope for tinkering than does ‘theory.’ (i accept that ‘theory of change‘ has been branded and that i have to live with it but i don’t have to like it. when people start calling them “tocks,” it’ll be a really, really bad day. i can deal with the acronym “ToCs” but please, world, don’t pronounce it “tocks” or switch to writing “tox” or something else dreadful.)

regardless of the term, the approach of thinking seriously about how behavioral, social and economic change will happen is really important — and often overlooked during the planning stages of both projects/programs/policies and evaluations. (too often, the intricacies of how change actually happened (or didn’t) are left to academic speculation in the discussion section of an evaluation paper — a certainly not informed by talking systematically to those people who were intended to benefit from the program).

i think there is growing recognition that building a theory of change is something that should happen, at least in part, backwards (among other places where this is discussed is in ‘evidence-based policy‘ with the idea of a ‘pre-mortem‘ and ‘thinking step-by-step and thinking backwards‘). that is, you start with the end goal (usually some variant of ‘peace,’ ‘satisfaction,’ ‘wellbeing,’ ‘capabilities,’* etc) in mind and work backwards as to how you are going to get there. actually, it’s a bit more like the transcontinental railroad, where you start from both ends (where you are and where you want to get) and build backwards and forwards until the ideas meet in the middle and you have a sense of what needs to be done and what assumptions underlie one step translating to the next.

in teaching us about not only conceptual models but grant writing, vic used the analogy of an island. the island was where you wanted to get — the state of the world as things would be once your intervention was rolled-out, fully operational and lasting change affected. it wasn’t enough to just say that people would have more money or would be healthier. you had to describe how the state of the world would look, feel, and operate. how would someone’s day look in the new state of the world? what would be different about the way they undertook their daily activities, or indeed what their daily activities would be? then, once you had the new state of the world/island in mind, you could make sense of where you were currently (through one of those ex ante ‘needs assessment‘ things i so rarely hear about in planning development projects or building theories of change) and what needed to be done to build a bridge from where you are to the island.

some of this work in understanding where people are and where ‘they,’ and therefore, ‘we’ want to get is meant to be generated through the nebulous terms “stakeholder engagement” and “formative work.” i think we discuss much less how formative engagement and stakeholder work (probably not a great sign of specificity that all the words can be mixed up so easily) actually translates into a robust theory of change. in this regard, i have learnt quite a bit from product and engineering books like the inmates are running the asylum. these are books about product and service design and the ‘user experience’ — far-out concepts we probably (almost certainly) don’t spend enough time thinking about in ‘development’ and something that would probably really benefit our theories of change in detailed and ‘best-fitting’ a particular situation… not to mention, you know, benefit the beneficiaries.

one of the tools i like best is what is, effectively, imaginary prospective users — in cooper‘s terminology, ‘personas.’ here’s the idea, as i see it translating to development and theories of change. we know stakeholders are important but they cannot (realistically or effectively) all be in the same room, at the same table, at the same time. nor can they all be called up each time we make a small tweak in program design or the underlying assumptions. and, it is likely the intended beneficiaries that are hardest to call up and the most likely not to be at the table. but we can use personas to bring them to the table, so that what happened in ‘the field’ most certainly does not stay there.

let’s say that for a given project and evaluation, widowed women are a key sub-group of interest.

forget widowed women.

start thinking about “mary.”

mary is a widowed woman.

her husband had been a carpenter and died of c cause. she lives in x place while her n children live in z other places and provide her with s amount of support. mary can be a composite of widowed women you did meet in the field during deep, household level needs assessment and formative in-depth interviews with intended beneficiaries. that’s how you might have a picture of mary and know that she lives in h type of house, with e regular access to electricity and have g goats and l other livestock. it’s how you know she’s illiterate and has a mobile phone onto which she never adds credit. it’s how you know what time she wakes up, what her morning chores are, who she talks to, when and whether she has time to go to the market, how she gets her information, what aspects of her environment will enable change and which will hinder it, and so on.

so, all potential beneficiaries can’t be at the table but personas of key subgroups and heterogeneities of interest can be. if everyone in the room for the design (intervention and evaluation) process is introduced to the personas, then they can speak up for mary. she still gets a voice and the ability to ask, ‘what’s in all this for me?’ will she be able to deal with an extra goat if she gets one as part of a livestock program? does she have the means of transport to collect cash as part of a transfer program? is her neighborhood safe for walking so she can follow up on the health information you provide? is mary going to give a hoot about the sanitation information you provide her?

mary’s obstacles need to be dealt with in your program design and the places where mary might have trouble engaging with the program need to be put into your theory of change and monitored as part of your M&E (& e) plan. will mary help you think everything? no, of course not — she’s good but she’s not that good. but it’ll probably be nearer to something that can actually work (and don’t forget that street-level workers, other implementers and high-level stakeholders should have personas too!).

please invite mary to the table when you’re designing your intervention and constructing your theory of change. it doesn’t replace the need for actual monitoring and actually asking for beneficiary, implementer and stakeholder feedback.

but have mary describe to you how her life will be different (better!) with your program in place, how the actual structure of her day and decision-making have changed now that she’s on the aforementioned goal island. you’ll be a little closer to making it so.

this post is massively indebted to danielle giuseffi, who introduced me to some of the books above and with whom i have discussed building models more than anyone else! still one of my favorite business-partners-in-waiting, d-funk, and i still like our behavioral bridge.

*yes, i know that ‘capabilities’ were initially from amartya sen and that i should have linked to this. but for planning approaches, i find the 10 laid out by nussbaum more accessible.

back (and forward) from ‘the big push forward’ – thoughts on why evidence is political and what to do about it

i spent the beginning of the week in brighton at the ‘big push forward‘ conference, on the politics of evidence (#evpolitics) which mixed the need for venting and catharsis (about the “results agenda” and “results-based management” and “impact evaluation”) with some productive conversation, though no immediate concreteness on how the evidence from the conference would itself be used.

in the meantime, i offer some of my take-aways from the conference – based on some great back-and-forths with some great folks (thanks!), below.

for me, the two most useful catchphrases were trying to get to “relevant rigor” (being relevantly rigorous and rigorously relevant) and to pay attention to both “glossy policy and dusty implementation.” lots of other turns-of-phrase and key terms were offered, not all of them – to my mind – terribly useful.

there was general agreement that evidence could be political in multiple dimensions. these included in:

  • what questions are asked (and in skepticism of whose ideas they are directed), by whom, of whom, with whom in mind (who needs to be convinced), for whom – and why
  • the way questions are asked and how evidence is collected
  • how evidence is used and shared – by whom, where and why
  • how impact is attributed – to interventions or to organizations (and whether this fuels competitiveness for funds and recognition)
  • whether the originators of the idea (those who already ‘knew’ something was working in some way deemed insufficiently rigorous) or the folks who analyze evidence receive credit for the idea

questions and design. in terms of what evidence is collected and what questions are asked, a big part of the ‘push back’ relates to what questions are asked and whether they help goverments and organizations improve their practice. this requires getting input from many stakeholders on what questions are important to ask. in addition, it requires planning for how the evidence will be used, including what will be done if results are (a) null, (b) mixed, confused or inconclusive, and (c) negative. more generally, this requires recognizing that policy-makers aren’t making decisions about ‘average’ situations but rather decisions for specific situations. as such, impact evaluation and systematic reviews need to help them figure out what evidence applies to their situation. the sooner expectations are dispelled that an impact evaluation or a systematic review will provide a clear answer on the what should be done next, the better.

my sense, which was certainly not consensus, is that to be useful and to avoid being blocked by egos, impact questions need to shift away from “does X work?” to “does X work better than Y?” and/or “how an X be made to work better?” this also highlights the importance of monitoring and feedback of information into learning and decision-making (i.e.).

two more points on results for learning and decision-making. first, faced with the assertion that ‘impact evaluation doesn’t reveal *why* something works,’ it is unsatisfactory to say something along the lines of ‘we look for heterogenous treatment effects.’ it absolutely also requires asking front-line workers and program recipients why they think something is and is not working — not as the final word on the matter but as a very important source of information. second, as has been pointed about many places (e.g.), designing a good impact evaluation requires explication of a clear “Theory of Change” (still not my favorite term but apparently one that is here to stay). further, it is important to recognize that articulating a ToC (or LogFrame or use of any similar tool) should never be one person’s all-nighter for a funding proposal. rather, the tool is useful as a way of collectively building consensus around mission and why & how a certain idea is meant to work. as such, time and money need to allocated for a ToC to be developed.

collection. as for the actual collection of data, there was a reasonable amount of conversation about whether the method is extractive or empowering, though probably not enough on how to shift towards empowerment and the fact that extractive/empowering are not synonymous with quant/qual. an issue that received less attention than it should have was that data collection needs to align with an understanding of how long a program should take to work (and funding cycles should be realigned accordingly).

use. again, the conversation of the use of evidence was not as robust as i had hoped. however, it was pointed out early on (by duncan green) that organizations that have been comissioning systematic reviews in fact have no plan to use that evidence systematically. moreover, there was a reasonable amount of skepticism around whether such evidence would actually be used to make decisions to allocate resources to specific organizations or projects (for example, to kill or radically alter ineffective programs). rather, there is a sense that much impact evaluation is actually policy-based evidence-making, used to justify decisions already taken. alternatively, though, there was concern that the more such evidence was used to make specific funding decisions, the more organization would be incentivized to make ‘sausage‘ numbers that serve no one. thus, the learning, feedback and improving aspects of data need emphasis.

empowerment in the use of data (as opposed to its collection) was not as much a part of the conversation as i would have hoped, though certainly people raised issues of how monitoring and evaluation data were fed-back to and used by front-line workers, implementers, and ‘recipients.’  a few people stressed the importance of near-automated feedback mechanisms from monitoring data to generate ‘dashboards’ or other means of accessable data display, including alternatives to written reports.

a big concern on use of evidence was ownership and transparency of data (and results), including how this leads to the duplication/multiplication of data collection. surprisingly, with regards to transparency of data and analysis, no one mentioned the recent reinhart & rogoff mess, nor anything about mechanisms for improving data accessibility (e.g.)

finally, there was a sense that data collected needs to be useful – that the pendulum has swung too far from a dearth of data about development programs and processes to an unused glut, such that the collection of evidence feels like ‘feeding the beast.’ again, this loops back to planning how data will be broadly used and useful before it is collected.