Draft findings from fellowship

Research question

What is the difference that Policy Lab’s approach makes to policy making?

1 What the Lab approach is/does

Lab’s approach problematises policy making – it’s not just exploring new tools, techniques and new data. Policy Lab connects/reassembles/tweens actualities and potentialities, problems and solutions, thinking and doing, inside and outside.

The key characteristics of this approach are that it is based in:

  • Abductive discovery, through which insights, guesses, framings and concepts emerge eg ethnographic research, co-design, prototyping in the fuzzy front end of policy making.
  • Collective inquiry – through which problems and solutions co-evolve, which is participatory, and through which constituents of an issue are identified and recognised, and solutions are tested eg prototyping.
  • Recombining experiences, resources and policies – the constituents of an issue – into new (temporary) configurations.

2 What Lab approach results in – its impact which we can seek proxy measures for

Project level – Relating to the policy area

  • New insights, guesses, framings
  • Plausible concepts for artifact-experience bundles
  • Prototyped proofs of concept – “proto policies”
  • An issue team/public engaged in a collective inquiry engaging with a more ordered problem

Capabilities in within the policy profession and wider ecosystem

  • Reordered relations between actors in an issue (inside and outside an issue)
  • Reordered relations between actors and evidence
  • Reordered timings
  • Ability to set up and participate effectively in collective inquiries and early-stage abductive exploration
  • Awareness of the interdependencies between experiences, resources and policies

Abductive policy making. Draft section of report from research fellowship

Image from Policy Lab/Strange Telemetry project with Government Office for Science
Image from Policy Lab/Strange Telemetry project with Government Office for Science

Between discovery and justification

The aim of this section is to help clarify what kinds of experiments are going on in the work of Policy Lab. This section draws on the work of philosopher Charles Sanders Peirce who developed the term abduction. First it will describe what abduction is, and how abduction relates to the other kinds of inference, deduction and induction, which are well-established in policy development. It will then discuss Policy Lab’s work through the lens of abduction and show how policy experimentation via abductive reasoning intersects with the other logics shaping policy making.

Deduction and induction

The term abduction is associated with the philosopher CS Peirce, who explored the term over some decades[1]. Like other Pragmatists such as Dewey, Peirce’s approach has an orientation toward our experiences of what happens in practice, rather than proposing an idealized analysis. To explain why Peirce’s work is a useful contribution to understanding Policy Lab’s approach requires a brief detour into the two other logics through which reasoning is usually understood to proceed.

Deduction is the process of taking a principle (a rule) and then inferring a result in a particular case. For example:

Rule: People living in the Midlands are friendly.

Case: These people are from the Midlands.

Result: These people are friendly.

Deductions offer reliability if the initial statements are true, but Peirce argued they do not generate anything new.

Induction starts with surveying data (the case) and generalising across many observations (the result) to identify a pattern (the rule). For example:

Case: These people are from the Midlands.

Result: These people are friendly.

Rule: People from the Midlands are friendly.

Inductions indicate probability about patterns in the data. They suggest that something is the case. Depending on the research methods used, they offer some kind of validity. As with deduction, Peirce argued inductive reasoning does not generate new concepts or knowledge.

In the context of experimental research, knowledge building typically proceeds by developing a hypothesis based on the stock of existing knowledge via deduction and then seeking confirmation by induction if it holds in a particular case.

The logics of policy making

Much of the evidence used to inform policy making uses mixed methods based on deductive or inductive reasoning in various combinations. Neither are right – they do different things and offer different kinds of validity, to allow policy officials and ministers to help reach decisions. But in the culture of policy making, the deductive logic offers the allure of offering definitive evidence. For one civil servant, “Trials are the gold standard for policy making”[2] because they are able to prove whether something is true or not, providing sound evidence that decision makers want about whether to go ahead with a policy.

Deductive reasoning underpins work in the natural and physical sciences and also shapes research in the social sciences. For example the methodological approach “Test, Learn Adapt” advocated by the Behavioural Insights Team is grounded in deductive logic[3]. BIT helps civil servants design and construct trials of policy by demonstrating whether an intervention will achieve intended outcomes, informed by existing knowledge about human behavior. Randomised control trials (RCTs) are one way to test systematically, in a particular case, whether a hypothesis underpinning an intervention is true or not. In policy terms, RCTs can prove whether a proposed intervention will lead to the desired change in a particular case. It generates statistically valid data about changes to variables associated with the outcome that result from the intervention.

Inductive reasoning is also very familiar within the policy environment. It underpins much of the research in the social sciences and the humanities. Inductive research does not have to use qualitative data but it is strongly associated with it. Researchers specialising in research methods working within this logic make efforts to show to what extent their findings have validity. They make careful claims about whether they can show links between cause and effect and discuss the extent to which their findings are generalisable to other contexts.


But where do hypotheses and new ideas come from in the first place? What happens in the context of massive uncertainty, when there is very little data, or much of it is in disagreement? What if you have a desired outcome that you want to achieve but are not sure of the constituent elements that might help you achieve it or how they relate? How do researchers get to the point that they are able to isolate an outcome variable which could be tested through a trial?

Recognising a gap in the philosophy of science, Peirce developed the idea of abduction as a logic of discovery within scientific inquiry, in contrast to the logic of justification associated with deductive reasoning. He argued that philosophers of science had paid insufficient attention to where ideas come from. Informed by ancient Greek thought, he developed the concept of abduction to explain how new concepts and hypothesis are created.

Abduction takes a result and a rule, and then jumps to making an interference that links the two. For example:

Rule: People from the Midlands are friendly.

Result: These people are friendly.

Case: These people are from the Midlands.

In abduction, we link things together in new ways. We can’t say if the interference is true or not, as is the case with deduction. Nor can we say it has strong validity because of the observations we made, as with induction. But with abductive reasoning, what we do get is a new insight or concept that we can explore further with the other two logics.

Hypotheses are not out there waiting to be discovered. Instead, Peirce argued, they are the outputs of a process of sensemaking. As we make observations through our own experience of the world, we compare these to the existing stock of knowledge. We may find something surprising that we can’t account for, resulting in a tentative guess – an embryonic hypothesis. Social researcher Jo Reichertz explains, “Something unintelligible is discovered in the data and, on the basis of the mental design of a new rule, the rule is discovered or invented and, simultaneously, it becomes clear what the case is.”[4] In contrast to deduction, which offers reliability, abduction offers possibility by generating something new, which can then be explored further through induction and deduction.

With the concept of abduction, Peirce was able reconnect creativity in science with the well-established idea that scientific reasoning can prove things. Other researchers such as Karl Popper separated the logic of discovery from the logic of justification. They focused on how science can make more reliable truth claims, paying less attention to how novel concepts are generated[5]. In Peirce’s own words, “Abduction is the process of forming an explanatory hypothesis. It is the only logical operation that introduces new ideas, for induction does nothing but determine a value, and deduction merely evolves the necessary consequences of a pure hypothesis.”[6] Table 1 shows the differences between the three logics, based on Peirce’s work. In his view there is an order: abduction precedes deduction and induction[7].

Table 1: Peirce’s ordering of the logics of scientific inquiry [7]

Table 1: Peirce’s ordering of the logics of scientific inquiry

Producing plausible, provisional results

Abduction reasons from effects to causes with incomplete data. It constructs plausible guesses and insights, shaped by our existing stocks of knowledge and in responses to effects gathered through observations or experiences. For management researcher Hans Hansen, “We take disparate elements and place them into relationships that are meaningful for us. Abduction generates hypothesis (sic) in the absence of any existing construct to interpret observation.”[8] Abduction shows something may be, but does not prove it, whereas deduction shows something is true in a particular case. Abductive inferences are plausible but are not justified by the structure of the argument. But they are plausible enough to move a project forward[9].

Abduction results in a new order that takes surprising observations and offers a way to make sense of them – for now – which is still productive. However for social researcher Jo Reichertz,

“The search for order is never definitively complete and is always undertaken provisionally. So long as the new order is helpful in the completion of a task it is allowed to remain in force: if its value is limited, distinctions must be made; if it shows itself to be useless, it is abandoned. In this sense, abductively discovered orders are neither (preferred) constructions nor (valid) reconstructions, but usable (re-) constructions.”[10]

At first glance there is a relationship here with the work of Karl Popper. He argued that science proceeds by hypotheses being challenged or upheld by subsequent research, a process he called falsification. But abductive interferences are never as firm as hypotheses in the first place. They are provisional, plausible constructs that are usable – they move a process of inquiry along – but do not offer a truth claim.

Participants in Policy Lab workshop discussing their hopes and fears in relation to a policy area
Participants in Policy Lab workshop discussing their hopes and fears in relation to a policy area

Creating the conditions for abduction

When developing his theory of abduction, Peirce discussed the conditions that gave rise it to it, which can be seen as broader principles for enabling the generation of new ideas. Rather than arguing that coming up with new insights is simply the result of chance, he identified strategies or enabling conditions for making it more systematic[11].

Peirce developed his thoughts on abduction as a result of a personal experience[12]. This was when a Tiffany watch was stolen from him after he left it behind by accident on a ship to New York. Initially he had no idea who was responsible[13]. In his account of the stolen watch, Peirce asked the captain of the ship to line up all the crew for him to talk to. At first he found himself unable to work out who might have taken his watch. Reflecting on what happened, Peirce described how this experience prompted him to reconsider how knowledge is generated.

The first condition conducive to the presence of developing an abductive inference is genuine doubt, uncertainty or great pressure to act[14]. The Tiffany watch was a gift, and a valuable one. But the fear motivating Peirce was not fear of its loss, but of professional disgrace for not being able at first to work out who might be guilty.

The second condition conducive to abduction Peirce identified was to let his mind wander with no specific goal – what he called “musement”. Instead of trying to use deductive logic to work out who had stolen his watch, Peirce gave into a state that was not controlled by his conscious mind. As a result, he concluded that his consciously working mind, which usually relied on logical rules, was outmaneovoured[15].

The third condition to make abduction more likely was to decide to act, even if the direction seemed arbitrary. As he tried to work out who had stolen the watch by walking up and down the lined up crew of the ship, Peirce concluded he must fasten on someone even through it would be almost a random choice[16]. The guess that Peirce made turned out later to be true and eventually he got the watch back. Management researcher Hans Hansen summarises, “At the point of being surprised by a surprising fact, if we can make a guess, any guess, we can make progress.”[17]

Recent interest in abduction

Researchers and practitioners in several domains are using abduction to help them distinguish between different kinds of research activity and practical experimentation. In business, Roger Martin[18] argued that managers need to use abductive as well as deductive and inductive reasoning as tools to achieve competitive advantage. In design[19], researchers have used the theory of abduction to explain how designers come up with new concepts. In social research, especially in fields such as nursing, researchers have turned to abduction to better understand how themes, codes and categories emerge during research[20]. In artificial intelligence and data science, there is a longstanding interest in abduction and induction and how they relate to one other in algorithmic machine learning[21].

Participants in a Policy Lab prototyping workshop
Participants in a Policy Lab prototyping workshop

Abduction in policy making

Drawing these argument together, the concept of abduction helps those involved in policy experimentation distinguish between the logic of discovery and the logic of justification. What Peirce’s ideas do is highlight the often invisible work that goes on during what we might call the “fuzzy front end” of policy making[22].

This discussion highlights the different kinds of reasoning produce different results at different phases of the policy making cycle. They are not directly comparable and further, if Peirce is right, then there are interdependencies between them. Peirce’s view is that there is a sequence which starts with abduction. The exploratory insights and guesses produced through abductive reasoning with limited data but with are nonetheless plausible can then be further developed through deductive and inductive reasoning. Abduction produces the provisional insights and guesses linking things together in new ways, that become hypotheses that be tested through experimentation and other research based in deductive and inductive logics. Deductive research can answer if a policy intervention works or not; inductive research helps explain why it does[23]; but abductive reasoning enables the discovery of insights and guesses when there is not yet theory or evidence but a desired policy outcome.

This highlights the mostly invisible work that policy makers do, where they are required to rapidly gather and assess evidence and come up with options for ministers. Looking at this through the lens of Peirce’s work, we might pay more attention to this early, hypothesis-free, exploratory phase. Trials test policy interventions in particular kinds of case when there is a hypothesis to test. In contrast design and prototyping support policy inventiveness by making plausible links between elements of an issue to achieve an intended outcome. If RCTs are a robust way establishing if a policy is working[24], the abductive cycle of generating and exploring insights and guesses is the best way of developing and iterating plausible early-stage policy ideas.

This is where Policy Lab’s approach comes in. It is rooted in the practical experimentation of design going through cycles of rapid insight generation, idea generation and exploration via prototyping. Working within this tradition, Policy Lab foregrounds the abductive early stage of policy making – where “early stage” includes revisiting persistent, complex policy issues. Alongside data science, and agile approaches also used in government, Policy Lab reveals and supports the often neglected abductive work that policy makers do, but opens it up to a wider group of participants and new sources of evidence and inspiration which the next section will illustrate.

References (not complete or checked)

[1] Scholars make a distinction between his earlier work using the term and his later work, which is what I draw on here. See Roozenburg, N. (1993). On the pattern of reasoning in innovative design. Design Issues 14(1): 4-18.

[2] The speaker was a participant in a workshop organised by the What Works network held at the Institute for Government in June 2015.

[3] Haynes, Laura, Service, Owain, Goldacre, Ben and Torgerson, David. (2012). Test, Learn, Adapt: Developing Public Policy with Randomised Controlled Trial. London: Cabinet Office.

[4] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 1(13). Italics in original.

[5] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 1(13).

[6] CS Peirce cited in Hansen, Hans. (2008). Abduction. In Barry, David and Hansen, Hans (eds). The Sage Handbook of New Approaches in Management and Organization. p.456

[7] Table developed from Table 3.5.1 in Hansen, Hans. (2008). Abduction. In Barry, David and Hansen, Hans (eds). The Sage Handbook of New Approaches in Management and Organization. p.457.

[8] Hansen, Hans. (2008). Abduction. In Barry, David and Hansen, Hans (eds). The Sage Handbook of New Approaches in Management and Organization. p.457

[9] This is the underpinning to lean start up and agile software development.

[10] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 11(1). Article 13. http://nbn-resolving.de/urn:nbn:de:0114-fqs1001135.

[11] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 11(1). Article 13. http://nbn-resolving.de/urn:nbn:de:0114-fqs1001135.

[12] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 11(1). Article 13. http://nbn-resolving.de/urn:nbn:de:0114-fqs1001135.

[13] Boje, D. (2014). Storytelling Organizational Practices: Managing in the Quantum Age. Abingdon: Routledge. p.39-40.

[14] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 11(1). Article 13. http://nbn-resolving.de/urn:nbn:de:0114-fqs1001135.

[15] Reichertz, Jo. (2010). Abduction: The Logic of Discovery of Grounded Theory. Forum: Qualitative Social Research. 11(1). Article 13. http://nbn-resolving.de/urn:nbn:de:0114-fqs1001135.

[16] Boje, D. (2014). Storytelling Organizational Practices: Managing in the Quantum Age. Abingdon: Routledge. p.39-40.

[17] Hansen ibid p.461.

[18] Martin, Roger. (2009). The Design of Business: Why Design Thinking is the Next Competitive Advantage. Harvard Business Press.

[19] See for example, Roozenburg op cit; Kolko, John. (2010). Abductive Thinking and Sensemaking: The Drivers of Design Synthesis. Design Issues, 26(1); and Dorst, K. (2015). Frame Innovation: Create New Thinking By Design. MIT Press.

[20] See for example Tavory, Iddo and Timmermans, Stefan (2014). Abductive Analysis: Theorising Qualitative Research. Chicago University Press.

[21] See for example Flach, Peter and Kakas, Antonis (eds). (2000). Abduction and Induction. Essays on Their Relation and Integration. Springer.

[22] Fuzzy front end is a term describing the early stage of product development, introduced in Khurana, Anil and Rosenthal, S. (1997). Integrating the Fuzzy Front End of New Product Develpoment. Sloan Management Review, Winter. pp. 103-120.

[23] https://www.ipsos-mori.com/Assets/Docs/Scotland/Approach%20Summer%202012/SRI_Scotland_Newsletter_Summer2011_Test_Learn_Adapt.pdf

[24] Haynes, Laura, Service, Owain, Goldacre, Ben and Torgerson, David. (2012). Test, Learn, Adapt: Developing Public Policy with Randomised Controlled Trial. London: Cabinet Office. p.4.

Policy making as a collective inquiry. Draft section of report from research fellowship

Policy Lab prototyping workshop

This is a draft section from the report I’m writing for Policy Lab in which I’ve been embedded for 10 months. The primary audience will be policy makers and others involved in public sector experimentation. The final report will be published in late August/early September.

The workshop: Experiencing policy making as a collective inquiry

In a windowless conference room in the basement of the Department for Business, Innovation and Skills, about 20 civil servants are sitting on chairs arranged in rows facing a raised stage. On tables to one side are piles of brightly coloured materials such as pens, Play-Doh, straws, cardboard boxes and pipe cleaners. Andrea Siodmok, head of Policy Lab, and I arrive slightly late from running a workshop elsewhere. She checks with our Policy Lab colleagues who are already present if the Powerpoint slides she planned to use are ready on the computer to be projected. They are. This is a two-hour event on prototyping in government organised by Policy Lab as part of Open Policy 2015, a week-long series of practical workshops and talks aimed at policy makers.


Andrea does not go on to the raised stage but instead stays on the same level as the seated participants. She moves in front of the people and starts talking. She apologises for being slightly late, says the workshop will be mostly practical and invites people to ask what they want to find out today about prototyping in government. As she talks and listens she hands out some of the coloured Play-Doh to participants and starts molding some in her own hands. Pretty soon all the people in the room are molding Play-Doh in their hands. The mood is open, relaxed and expectant.


She leads a discussion on prototyping to which people in the room are contributing unselfconsciously and in an open manner. She instructs people to make a particular shape with the Play-Doh – a duck – and people do and then are willing to hold up and share what they’ve done with others. She then says “One of you is going to shout out what you are going to make next” and we hear someone say “monkey”. Andrea says “Ok, 15 seconds” and everyone quickly makes a monkey shape and again shares them. Then someone calls out “Fox”. One man holds up his shape: “It’s part fox, part monkey and I’m very proud of him” and we laugh.


About ten minutes in, it feels as if the workshop has not yet started but participants in the room continue to be attentive. Any skepticism they might feel is not evident in their behaviour. Andrea shares observations on prototyping drawing on the work of UK manufacturer Dyson as well as her early career as a product designer. She says “The purpose of prototyping is to come up with something tangible we can test, share and improve” and talks about how Policy Lab is working with departments to explore how to use this approach at the early stages of policy making, exploring what policy ideas might looks like at the point of delivery and experience. She then instructs, “One last prototype – in 15 seconds. Make a prototype of how to integrate health care and social care.” People laugh at the shift in register from the childlike to the very serious policy challenge, but carry out the request. Andrea then asks people to share their prototypes. “Mine’s a car crash – the incentives are misaligned,” says one woman. Another says, “I’m really trying to join them up.”


Andrea invites people to share reflections on what they think prototyping is. “It’s quick and easy – you can see the result,” says one woman. Another says, “There are lots of levels of abstraction”. Someone else points out that participants’ experiences were impacted by their capabilities with using Play-Doh. Another person reflects, “What it did was force us to do something – often in policy making we sit around trying to come up with the perfect idea.”


Participants in the workshop continue to be very engaged. Andrea moves to the stage and starts showing the Powerpoint slides which are projected on to a large screen. One of the slides includes a screengrab of the text of a recent speech by the Home Secretary in which she refers to prototyping a new service for people reporting crime, one of Policy Lab’s projects[1], possibly the first time a minister has used the term prototyping in public. Andrea shows photographs, many from local government projects, of exploring new policy or public service concepts at a very early stage by mocking up what the experience would be like for end users or citizens.


About an hour in to the workshop, Andrea sets a challenge for participants. This is to work together create a prototype of a new kind of GP surgery based on the principle of “the patient will see you now” rather than the current model of “the doctor will see you now”. Over the next hour participants work together in small teams of about five, producing ideas they share in a two-minute pitch to the rest of the group which is also an opportunity for feedback. To facilitate this, some of us arrange chairs around some large tables so that people can work together around a flat surface.


Most of the participants, all civil servants, are strangers to one another. They come from a range of departments and policy areas but they succeed in quickly self-organising into teams and collaborating to generate and prioritise ideas. They help themselves to the materials and get on with making small models of alternative GP surgeries, responding to the items made available such as cardboard boxes, pens, feathers and pipecleaners. As I move from group to group, I hear them discuss things like patients’ needs, frustrations they themselves have with visiting GP surgeries and concepts from other service contexts.


Everyone seems engrossed in the flow of exploring what a new primary healthcare experience might be and what the infrastructure and resources are required to deliver it. When they come to share their models, some of them use role play to show the new patient experience but they also refer to some of the resources and infrastructure associated with delivering it. One group communicates their concept through a woman performing as if in a TV advert. After each team presents we all have an opportunity to give feedback on the ideas they have presented or query details.


The workshop ends with a brief discussion led by Andrea. She emphasizes that prototyping is an early stage, exploratory and collaborative activity that can be done very early on when concepts are very malleable, as well as later on when concepts are more defined. It’s striking how she continues not to offer a definitive set of proposals as to what prototyping might mean in the context of policy making. Instead, the workshop has involved a practical exploration of the question in relation to a policy challenge. To conclude, she asks, “How many of you are creative?” Nearly everyone puts a hand up. The workshop is over. The Policy Lab team gather up the materials, put the room back to its arrangement of tidy rows of chairs facing the front, and leave.

There are many ways of discussing what was going on in this workshop. In what follows I will draw on the work of Pragmatist philosopher John Dewey to illuminate what made this workshop hang together: how it was that playing around with Play-Doh and pipecleaners became an appropriate and productive way of exploring the issue of prototyping in government and what it offers to conventional ways of thinking about policy making.

Making sense of Policy Lab: Policy making as inquiring

John Dewey made an important contribution to philosophy by focusing on how knowledge is developed in practice, rather than formulating concepts or generating facts without connecting with what goes on in the world. Dewey was one of several Pragmatist philosophers working in the early 20th century who challenged the well-established mind-body dualism in which thinking was maintained as separate from the world. Dewey’s thought was shaped by the idea that humans exist through interacting with their surroundings.

Much of Dewey’s work was in the realm of the theory of knowledge, although he preferred to use the term inquiry. For Dewey and other Pragmatists, what mattered was knowledge being put into use in the world to achieve human ends, rather than more abstract discussions of logic and truth. The point of inquiry is to provide a basis for action. Our knowing is a result of our interacting with our surroundings. Dewey’s work has been extremely influential, including shaping student-centred learning in education and professional development as well as action research and participatory community development.

Dewey’s definition of inquiry can be summarized as the controlled or directed transformation of an indeterminate situation into one that is determinate enough to hang together[2]. Dewey says the process of inquiry involves these steps

  • recognition that there is a problem, which could have a solution
  • working out what the constituents of the problem are
  • making observations about the problem
  • allowing a possible relevant solution to present itself; through so doing, more aspects of the problem become clear
  • exploring the meanings of possible solution to see if they are relevant to the problem at hand
  • finding facts to see if they link up with other facts to produce a coherent whole of problem and solution
  • further developing a new ordering of the facts which suggests a modified idea (or hypothesis), which results in new observations, which results in a new ordering; and
  • continuing this cycle until a new order is judged to be complete. In the course of this “the ideas that represent possible solutions are tested or ‘proved’.”[3]

So for Dewey, in inquiry the problem and a solution emerge together through practical interventions into and observations of the world. Instead of this being a linear process in which first a problem is defined and then solutions are found, in inquiry, the problems and solutions co-evolve together. Dewey’s philosophical argument has since been demonstrated through academic research into how designers approach their work, sometimes called “design thinking”. Researchers have shown that during designing, the problem and the solution emerge together[4].

However Dewey was writing about how knowledge is created in science. To explore how this is relevant to policy making which, like design, is a practical endeavor that involves lots of stakeholders, it’s worth going into a little more detail about how ideas are generated and how they are used.

“Because inquiry is a progressive determination of a problem and its possible solution, ideas differ in grade according to the stage of inquiry reached. At first, save in highly familiar matters, they are vague. They occur at first simply as suggestions; suggestions just spring up, flash upon us, occur to us. They may then become stimuli to direct an overt activity but they have as yet no logical status. Every idea originates as a suggestion, but not every suggestion is an idea. The suggestion becomes an idea when it is examined with reference to its functional fitness; its capacity as a means of resolving the given situation.”[5]

So for Dewey, ideas are not just abstractions; they act in and on the world. And in acting in the world, ideas help re-organize the current understanding of a problem. Through generating ideas and exploring them in relation to the problem, a better understanding emerges of its nature as well as its possible solution.

Dewey’s argument highlights the provisionality of ideas. What matters is how ideas are put into operation to check their fitness.

“Ideas are operational in that they instigate and direct further operations of observation; they are proposals and plans for acting upon existing conditions to bring new facts to light and to organize all the selected facts into a coherent whole.”[6]

To summarise, the key ideas from Dewey’s work relevant to this discussion about Policy Lab and its way of working are as follows.

  • An inquiry is a process of creating knowledge which is always purposeful, rather than concerned with generating abstractions that are not connected to practical situations.
  • The process of inquiry does not start with a problem and then move to solutions. Rather, the problem and the solution co-evolve together.
  • The constituents of an issue are not known in advance; they are discovered through inquiry.
  • Inquiring into a problem by generating ideas helps clarify the nature of the problem.
  • Ideas are always provisional and can be put to work.
  • Exploring ideas helps organize the understanding of the problem and its solution.

Dewey’s work offers a way of thinking about what Andrea was doing in the workshop that helps explain (a) Policy Lab’s experiential approach and (b) what prototyping is.

Staging a collective inquiry. Rather than talking from a position in which she held the knowledge, Andrea constructed the workshop as a collective inquiry. While Andrea is a Senior Civil Servant and has extensive experience of leading strategic design projects, she did not invoke her position in the hierarchy or her expertise to make an argument from authority. There was just one occasion where Andrea did use an argument from authority, when she showed on screen the text of a recent speech by the Home Secretary using the word “prototyping”. Other than this, from the outset of the workshop, she involved participants in exploring together what prototyping in government might be. Instead of telling them what she knew – a kind of one-way knowledge transfer – she enabled people to explore through discussion and practical, embodied interaction with the question of what prototyping in government is or could be. Instead of problem-solving for or with participants, she involved them in inventive “problem making” in the sense of collectively working out what the constituents of the problem might be[7]. Through so doing, she created space for participants to share their lack of knowledge along with their knowledge and ideas. Through the practical activities accompanying the discussion, she invited them to progressively develop their own understanding of the question.

A grounding in practice. Andrea’s design and facilitation of the workshop oriented participants towards action, rather than abstract discussion. For example she set them a challenge in which they could practically explore what prototyping might mean in the context of policy making. By choosing the topic of healthcare, this enabled people to draw on their own lived experience of healthcare. Since most likely everyone in the room had direct relevant experience of implications of the policy question, this enabled the workshop’s inquiry to proceed quickly, as everyone was a ‘user’ of a primary health care service. Further, when setting the challenge, Andrea asked people to make a model of the new GP surgery service and try to communicate what the experience it would offer to a patient. Rather than designing an ideal form such as a healthcare system, positioning themselves as outside of it, participants were asked to describe someone’s future experience of primary healthcare, and to communicate what it would be like inside of it.

Exploring the problem by iteratively exploring ideas and making observations towards coherence. Participants were empowered and supported to explore the question of prototyping in policy making by trying out the techniques Andrea introduced. Unexpected in the context of government, the Play-Doh exercise was extremely simple and accessible to everyone present. Through several rounds of making animal shapes, followed by a policy challenge of health and social care, the activity normalized the idea that it was possible and even worthwhile to give tangible form to your ideas. Then, through collectively making and sharing simple physical models of new kinds of GP services, participants developed a deeper understanding of the nature of healthcare service delivery and experience. By spending an hour making the models, they went through cycles of understanding the problem, making observations (based in some cases on their own experiences), generating ideas, exploring the ideas in relation to the problem, further developing the ideas, making new observations and building towards a (temporary) coherence between the problem and the solution.

Participatory leadership. The way the workshop was delivered resulted in handing over much of the responsibility for its success to participants. Throughout the workshop, participants were constructed as having to find their own answers to the question at the heart of the workshop about prototyping in government, rather than being persuaded (or not) by Andrea’s expert position.

All the way through, participants were invited to share what they wanted to learn, what they believed and what they knew. Andrea offered many opportunities for them to shape the activities, for example, calling out what animal to make next with Play-Doh, deciding which challenge they should work on together, or inviting them to move to another group if they wanted to.

Andrea’s use of humour and her self-deprecating stance further emphasized her rejection of holding an expert position. This opened up the question for participants about their degree of participation in the workshop.

Experiencing policy making. The design and facilitation of the workshop invited people to manipulate and organize material things – the Play-Doh, the cardboard boxes, the feathers. Andrea and the rest of us in the Policy Lab team intervened to reorganize the room to enable people to work together at tables, rather than being bounded by the conventional format of the room as we found it with rows of chairs facing a stage. Rather than operating in the domain of manipulating symbols, with which civil servants are very comfortable, the workshop foregrounded the material, the spatial and experiential. This decentred the civil servants from their own expertise. It also invited people to reflect on their own experiences as civil servants – the things they take for granted in the material and spatial organisation of their work and how it enables or inhibits how they approach problem finding and exploration in their day to day routines.

The next section will go on to explore what this approach offers to policy makers.


Note – the references are not yet checked or complete

[1] https://openpolicy.blog.gov.uk/2015/02/03/prototyping-an-online-crime-reporting-service-a-policy-lab-success-story/

[2] Dewey, J. Logic: The Theory of Inquiry. pp 104-105

[3] Dewey p 113-114

[4] Dorst and Cross 2001

[5] Dewey p 110

[6] Dewey pp 112-113

[7] In sociological research exploring the public understanding of science, Mike Michael and others have developed the concept of “inventive problem making” to describe bringing together distinct perspectives on an issue in material and discursive form. See Michael, M. (2012). “What Are We Busy Doing?” Engaging the. Idiot.” Science, Technology & Human Values 37, no. 5 (2012): 528-54.