A guide to using behavioural insights in local government

I wrote this for Sunderland City Council, following some work using behavioural insights in a range of projects. Although written for an internal audience, they’re happy to share it. I really enjoyed working there, especially all the co-production with wonderful front-line staff; I got a lot out of it and I hope that by sharing these insights, you will too – if you work on local public services and are interested in how behavioural insights (BI) can help.

There’s not much in here on demand management (which is the theme for most of my BI work in local government), since all the projects it was based on were for the Health & Wellbeing Board. But there is a section on how demand management (DM) work differs. I guess the next thing I need to write should cover DM in more detail and include the dozens of non-Sunderland examples I have.

You can download a copy here: A guide to using behavioural insights in Sunderland or from the Sunderland Partnership here.

Ideas Generation and Behavioural Insights

Here is the ideas grid I use when working with local authorities to co-produce ways of using behavioural insights. Each effect has a ‘how can we use it?’ challenge; we use it to develop ideas. Some of the ideas generated feel counter-intuitive, some feel run-of-the-mill, some feel like breakthroughs straightaway. We play them back, and pick the ones that feel like the best bets to build into a trial approach.

Behavioural effects are chunked into four main groups:

• Norm effects: making your target behaviour seem normal
• Ease effects: making your target behaviour easy
• Reward effects: increasing the sense of reward for your target behaviour
• Obligation effects: helping people feel an imperative to choose your target behaviour

This is the full list. It’s not an exhaustive list of effects, but if it were any longer, I think it’d be too daunting for staff who are new to the behavioural perspective. In practice, in project workshops, I often use a shorter, more targeted list and grid of effects, reflecting what I’ve learned tends to work best for different contexts. It’s easier for people to use.

If you’re involved in improving public services, feel free to use this grid yourself.

I’ve been using this since 2010, with a few tweaks over the years. This version is taken from the soon-to-be-published Guide To Using Behavioural Insights In Local Government, that I’ve written with Sunderland City Council.

The Brexit Referendum Through a Behavioural Lens

I’ve written previously about the gap between mainstream policy-making and systematic, knowledgeable use or understanding of behavioural science. And here I am again, suggesting that the wording of the Brexit referendum could have been smarter, and that the Leave campaign tapped into our cognitive biases much more effectively than did the Remain camp. So … was it cognitive bias wot won it?

The Wording

My interest from a behavioural perspective was first piqued back in September, when it was reported that the draft referendum wording had been changed. My instinct was to agree that the Yes/No question initially drafted (“Should the United Kingdom remain a member of the European Union?”) would indeed favour stay, due to status quo bias. But I was concerned about the agreed final version, which I felt had an inbuilt bias the other way. I tweeted this at the time, to – let’s be honest – very little interest:

My rationale is that if you were looking for a balanced choice, the key words would form a semantic pair. I think that, technically, we are talking here about complementary antonyms. On/off is an example. Stay/leave works, in my view. But Remain/Leave doesn’t; remain carries a higher cognitive load to process than does leave, as it is less idiomatic. Depart would be a better pair with Remain.

This matters because, when faced with a higher cognitive load, we process information less well. It’s why a lot of my work with local authorities includes an element of making sure that we use everyday language. We want people to make good decisions.

Is it a big deal, though? The more reflective a decision is, the more it relies on  System Two thinking, so the less significant are the biases and heuristics of System One. And this decision, considered over many months, perhaps shouldn’t be influenced by something as seemingly ephemeral as the question wording. But, in the privacy of the polling booth, particularly if you enter it as a ‘don’t know’ …We’ll never know, because there is no control sample – and no voter would be aware of the effect influencing their decision.

Effects triggered by Leave campaign

“Vote Leave, Take Control” was very, very clever. Chris Dillow at Stumbling and Mumbling recently wrote on cognitive bias and politics and called it a ‘stroke of genius’. My rationale is different to his, which focused more on how people feel about inequality.

My thoughts refer particularly to the ‘Take Back Control‘ slogan, or, as shown here, ‘Taking Back Control From Brussels’.

I think two powerful behavioural effects are at work here. And I partly recognise them because I’ve used them – together – to great effect in my work. But before I explain, put yourself in this scenario:

Imagine calling a mobile phone company to cancel your contract. You might half-expect to be put through to a Retentions team who might offer you more texts or 100 extra minutes per month as an incentive to stay. With me so far? But what happens is that Retentions say, “Oh, look. There are 100 extra minutes per month on your account. What do you want me to do with them?”. Pause for a second and think about it. They’ve completely reframed your call: you now immediately understand that you have this thing, that you are at risk of losing. It wouldn’t work on everyone, but I’m pretty sure I’d be more likely to stick with my current provider if they tried this, than if they didn’t.

What this imaginary phone company and ‘Take Back Control’ have in common is combining Endowment effect and Loss Aversion. In a nutshell, endowment effect is the value I instinctively ascribe to something simply because it is mine. Coupled with the (more widely understood) loss aversion, whereby I acutely feel the potential loss of what is mine, this is a powerful combination. The expertise with endowment effect often lies in communicating very succinctly that there is something I have, that I may not have been aware of at the start of the sentence (or, in my  phone contract example, at the start of the call). In Public Health, we are using endowment effect when we write to someone to say ‘Your NHS health check is due’ (my italics) which, all other things being equal, gets more people attending. So what is so clever about the use of endowment effect in the concept of ‘taking back control’? It is the way that a status quo ante is implied by the word ‘back’, a time when I had control. Further, it is very hard to contradict once it has been used; as they didn’t reframe with an alternative, vivid understanding of what it was to be ‘in control’, Remain were essentially saying “it’s OK to have lost control”.

Finally, think how much more effective ‘take back control’ is than ‘take control’. That, as Jonathan Flowers said to me when we were discussing this, sounds like hard work.

Leave’s missed opportunities

It’s not hard to make a case that the main flaw of the Remain campaign was in allowing the debate to be framed by the Leave camp. Framing isn’t a behavioural effect as such, but how something is framed provides the context for decision-making – and biases – to play. Taking just one example, the Leave side managed to get ‘freedom of movement’ spoken about as though it’s a one-way street. And this is still true; listen to news pieces even today about the issue, and it’s all about EU citizens’ right to move to the UK, not about UK citizens being able to live in any of 28 countries, as a result of being EU citizens.

How could the campaign have been run to reframe this? I’ll offer just one example: loss aversion is good to tap into. For UK citizens like me and my family, the Leave campaign was about removing our right to live in 27 of those 28 countries. Expressing it more vividly, they want to take 95% of my/your passport away. Leigh Caldwell, a fellow behavioural practitioner, wrote about this, evocatively and emotionally, before the vote. But I’m trying to be hard-nosed here, and I don’t think you have be a super-creative at Saatchi to imagine something visual and vivid to bring this home. I’m picturing something involving Mr Farage, a passport and pair of scissors. Alternatively, for the more nostalgic among you, how about a “No more Auf Wiedersehen Pet” message, with a picture of that nice Jimmy Naill?

Clearly, some good ideas – that would have worked hard behaviourally – were around, but not acted on, as this article in Campaign makes clear. This draft poster, in particular, could have been expected to trigger status quo bias effectively:

 

So – was it cognitive bias wot won it?

I’m not saying that these were the issues that settled the vote – that with more self-awareness of our cognitive biases, the result would be different. We don’t know; there’s no control sample. But I do hope that people in the Remain campaign would now look back and inwardly facepalm.

 Is it too late to reframe the debate and decisions?

Most, if not all, readers will have witnessed the emotional fallout from the Brexit vote, even if they did not feel it themselves; the sense of voicelessness and loss that has even led to the publication at short order of a new national weekly newspaper. It’s not clear what will happen now, as many authoritative voices advise us, so perhaps there is time for those who are in favour of the UK staying in the EU to move away from using purely economic language, and begin to talk about these issues in a way that recognises how we really make decisions.

Before I go …

One rider to all of this: friends have encouraged me to write down what I’ve been saying out loud recently, and here it is. I hope these things are worth saying, because the referendum did happen. Sure, it could have been done better. But my view, for what it’s worth, is that referendums are almost always the wrong thing to do; so no referendum at all is preferential to a behaviourally literate referendum. This 2010 post by Paul Evans is a good overview of why, though Noel Gallagher puts it more vividly.

 

 

 

 

 

 

 

Using behavioural insights to manage demand for public services

This is about an award-winning project carried out by the Housing team at the London Borough of Ealing, supported by With The Grain (that’s me). We think we achieved a 70% reduction in the number of families being placed in temporary accommodation by the Council, and the main principles are now being scaled into the Council’s ‘business as usual’ approach. We think it has the potential to save millions and improve the wellbeing of hundreds of families. So, if you’re working out how to do Demand Management in practice, or wondering how to make the most of behavioural insights in local public services, you need to read this.

The approach we took was co-designed. Council staff were involved in developing ideas, drafting scripts and specifying content. Get in touch if you want to know more about how we did it.

Helping people take control

We did this by helping families who are likely to become homeless (typically due to eviction or a breakdown of an existing household), to take control of their situation: to look for a new home for themselves if they are able to, rather than being funnelled into Bed & Breakfast (B&B) and Temporary Accommodation (TA) to wait for the Council to find them a home. This matters, because the reality of living in TA and B&B is not good for families’ wellbeing. It is also expensive to provide at a time of unprecedented cuts in local government budgets.

Our approach

Our ‘Reframing First Contact’ pilot consists of a conversation. We call it an advice session, with potential follow up phone calls and sometimes meetings.

We use a number of materials:

• a script for officers to use
• a leaflet shown by Customer Services Advisors to callers, to help residents frame the conversation. This helps identify people who are eligible for the pilot
• a tablet computer with a front page of hyperlinks to the most useful sites/pages when searching for a home
• an action plan for residents to take away.

I’ll explain the process, so you can see how the materials are used:

• Resident arrives at Customer Services front door and is given a ticket for housing advice
• When called, the housing Advisor makes eye contact and shows them the framing leaflet, to immediately establish whether they meet the criteria set out:
• they say they risk becoming homeless
• they have dependent children
• they indicate that they do – or might – need to find a new home
• If the Advisor judges (usually within a minute) that someone is eligible, the Advisor calls a pilot officer and asks them to help the residents as part of “our new service”
• The officer collects the resident, and takes them to a room where they sit alongside the resident. When they can, they give the resident the best chair, to help them feel ‘in control’

Photo posed by officers

• They then have a conversation based on the agreed script, with a tablet computer available – so they can search for homes and other information
• We don’t collect any personal data, except contact information. We found collecting personal data tended to steer conversations away from residents’ capabilities, and also enforced an unequal power balance between the expert/gatekeeper officer and inexpert resident.

Behavioural Effects we used

Throughout, our intention has always been to present it as normal for people to look for their own home – one that they can afford – and then to make doing so as easy as we can. To achieve this, we used around twenty identifiable heuristics, including the ones listed below. We also stopped the inadvertent use of effects that were having an adverse impact on behaviour.

• People are primed to frame the conversation. The What Do You Want To Do? framing leaflet tests that the resident is comfortable saying they are someone who needs to find a home, as distinct from being given one. (The business as usual – BAU – approach is to assume that someone wants to be a ‘homeless applicant’ – and therefore a customer.)

• Scarcity effect – when the Customer Services Advisor calls the pilot officer, she says: “I know the new service is really busy, but it would be great if you could squeeze in Mr A right now”.
• Talking about looking for a home, we set the default as ‘looking for yourself’
• We increase salience by referring to a time-limit. “This is about finding the home where you’ll be tucking up the kids at the end of next month”
• We have an emotional ‘reward’ in mind – settling down and being happy – and we talk about a ‘home’ (whereas the BAU approach is to refer to a ‘property’)
• We make social proof available – to demonstrate that others like have done this and are happy
• We reduce cognitive load – avoiding jargon and unnecessary concepts (of which there are many in the BAU approach)
• We avoid endowment, like “duty” and “entitlement” (which anchor the conversation unhelpfully in the BAU approach)
• We avoid scarcity effect when it’s unhelpful, like telling people how tough it is to get a council home. (In the BAU approach, this was seen as “managing people’s expectations”; however, Prospect Theory predicts that this encourages risk-taking behaviour).
• We have a commitment device – an Action Plan – so that residents can note the websites, agents, etc they will contact

• We increase the salience of, and of plans and information by asking people to write them down themselves
• We help people visualise their plans – asking them to explain where and when they are going to search – so they’re more likely to do them
• Reciprocation – “when you find somewhere, we will be able to help you with the deposit”

What did we find out?

We think the approach we took, and the way it worked, showed three main things:

1. Co-production works for behavioural techniques. Drawing from a wide range of behavioural effects, council officers worked alongside a behavioural practitioner to create a new approach. It’s their project.
2. Using behavioural insights, we can increase demand for an ‘upstream’ service that supports independence and self-sufficiency, and so reduce demand ‘downstream’ for services that are expensive to provide, may not improve wellbeing and may increase dependency.
3. Local services can use behavioural insights at an operational level. It doesn’t depend on developing or changing local policy. This work has been commissioned and sponsored by a Director and service heads.

What was the impact?

We didn’t have enough control over the front door of Customer Services to set up a randomised control trial. However, we think the two main measures we do have are pretty conclusive:

• First, a qualitative measure at the end of the advice session, asking the resident if they plan to look for a home themselves (and whether they will look further afield if they cannot find somewhere local they can afford). Over a four month period from November 2014 to February 2015, the vast majority of residents who took part agreed to look for a home themselves (31 out of 34), including 21 who explicitly agreed to look for somewhere they could afford even if it wasn’t in the area they were living.
• Second, a hard Demand Management measure. Officers checked whether residents who take part in the advice session went on to become a ‘homeless applicant’ by cross-checking with application records. Just 2 of the 34 became homeless applicants, far fewer than would normally be the case.

How does this compare with Business As Usual? During the same period as the pilot, Ealing Council accepted 234 other families as homeless . These families did not benefit from the behavioural pilot service. This table compares the outcomes.

November 2014 to February 2014	Behavioural Pilot	Normal (BAU) method
Number of approaches about potential homelessness	34	1127
Number of homeless applications taken and accepted (leading to B&B/TA)	2	234
Acceptances as %age of approaches	6%*	21%

*NB small base

These results suggest that our behavioural approach has the potential to reduce demand – in the form of provision of B&B & TA to families designated as homeless – by up to 70%.

Why this matters

When families are helped to find their own homes, in areas of their choice, that they can afford, they are able to settle down and begin to re-establish the family life that households in B&B/TA often find difficult to sustain. For more on the impact on families of homelessness and living in B&B and Temporary Accommodation, see Shelter and this report on the impact of temporary accommodation on health.

There is another driver of course. Like most of my work, this is about Demand Management. The London Borough of Ealing has faced severe cuts of £96m over a four-year period. However, demand for homelessness services is rising – due to a vanishingly small supply of social housing, and rising evictions in the private rented sector. So reducing the number of families in temporary accommodation is vital to reducing the cost of this multi-million pound service.

Our behavioural pilot points to significant savings, more practical to measure than an increase in wellbeing. Accommodating a family of 1 adult and 3 children in London for a year typically costs the Council between £18,000 and £27,000 plus officer time. So the potential saving to the Council, if it is able to assist at least 100 families to find their own homes, is £1,800,000. No wonder the Council is working out how to scale up the approach.

Award-winning

We’re proud that our project won the Grand Prix at the inaugural Nudge Awards, ahead of projects from the world of advertising and finance. My thanks to everyone at Ealing who played such a big part, and to Professor Richard Thaler for choosing a local government project as the Grand Prix winner. Those of us who work in and with #localgov know that it’s rarely seen as glamorous, but it makes a positive difference to the lives of millions. And, right now, we need to ramp up the use of behavioural analysis and insights to deal with the reality of major budget cuts.

Deep blue water between policy and behavioural insights

Some stark news today illustrates a point I’ve been making for a while. Sadly, this is life and death stuff.

Last October, it was reported that Britain would “not support any future search and rescue operations to prevent migrants and refugees drowning in the Mediterranean, claiming they simply encourage more people to attempt the dangerous sea crossing”

This seemed like the Rational Actor Model gone mad to me. Even without the benefit of any ethnographic research (without which it’s often best to reserver opinion), was it even remotely plausible that demand for these crossings would be reduced by this decision? I thought not, so I tweeted:

UK axes £s for Med migrant rescues because 'it encourage Xings'. Evidence?? Or is this 'Rational Actor' nonsense? http://t.co/pfkGeCkbpN

— Warren Hatter is With The Grain (@warrenhatter) October 27, 2014

The flow of refugees has of course continued since this decision, with tragic consequences. A lead item on the news, amid much hand-wringing.

My point is not: I told you so. My point is about how immature the use of behavioural insights is in government and policy making. If government were systematically applying insights from behavioural sciences to policy-making, this policy (not rescuing people, in order to influence the behaviour of potential refugees) wouldn’t have got off the drawing-board. Not because it’s immoral, but because – in behavioural terms – it’s illiterate.

Yet we’re told how influential behavioural practitioners are these days (the Independent, for example, claiming a “profound effect on Whitehall” for the BIT). That’s not how it looks to me. I’d say that we’ve influence when commissioned, in a strict supplier-client relationship. This is not real influence.

Some of us in the behavioural trade have a chuckle from time to time at attempts to influence behaviour that don’t cut the mustard. Now, it’s about time we started calling out policy that is clearly flawed.

Beat The Clock

The clocks go back on Sunday morning, as British Summer Time comes to an end. We’ll all do it. It’s so normal to join in with it, that none of us considers not doing so. It’s a brilliant ‘behaviour change intervention’; it’s so easy and so normal to do, that we don’t even recognise that our behaviour is being changed. This got me thinking …

A few of my projects involve introducing a behavioural layer to local authority communications. To do it, I have to read through current comms (letters, leaflets, press releases) and identify why they don’t work behaviourally.

For fun, I’ve taken some of the tropes I’ve spotted in existing comms and used them to write a fake Council magazine article or web page trying to get people to delay starting their day by one hour for the next six months, in a parallel universe where the clocks don’t change seasonally.

Why? Because some of you might find it amusing. And because it might help me make my point that much current comms is not behaviour-smart.

‘One Hour Delay’ Project

As part of its policy to ensure that daylight hours are used as effectively as possible, the Council is preparing to launch an initiative aimed at increasing the number of residents who start their day an hour later.

Beginning every day an hour later is an easy way for us all to make a difference to the way light is used and help meet the targets in the Council’s Light Use Strategy.

Councillor Jones said: “Residents will need to set their alarms an hour later than they currently do. Unfortunately, we will not be able to provide this service, due to cuts in our government funding.”

The tendencies I’m clumsily trying to illustrate here are:

• Not being analytical enough in identifying the target behaviour, so losing the chance to ask directly for the act that will make the most difference (in this case, changing the time on clocks and other devices).
• Describing the ‘reward’ for the behaviour in terms which relate to policy, rather than emotions that are vivid to people.
• Featuring the Council (and its decision-making) prominently, though this distracts from the ‘ask’.
• Introducing a ‘loss frame’, where we tell residents what we can’t do for them.
• Using convoluted language and concepts which (though many are familiar to officers) add to the ‘cognitive load’ of the piece, and so make behaviour change less likely.
• Not presenting a way of making the desired behaviour easy.
• Not having as the central message either the emotional reward for the target behaviour (“you’ll arrive at the right time”) or the clear behavioural ask (“put your clocks back on Saturday night”).
• Not using social proof or referring to social norms, when these would fall in our favour. “Everyone else is doing this,” is a useful message, as hardly any of us is comfortable being the odd one out.

OK, OK, I’m exaggerating in my imagined article. And I know I’m treading a fine line. Lots of Council communications is good now, and it has improved rapidly in recent years. Respect to those responsible (including LG Comms and Dan Slee). But, in my experience, very little of it yet reveals a sophisticated understanding of human behaviour, clarity around target behaviours, or an appreciation of what makes a real difference in influencing what we do. It’s no surprise: much of the evidence I draw on is recent and challenges the assumptions of many professions, that people are, essentially, ‘rational’.

Many of my workshops have as their main takeaway message: “stop trying to change people’s minds: make your target behaviour easy and normal“. I think that’s what I’m trying to say.

Policing in a Behaviour-Smart Place

I’ve made a rod for my own back in saying that my aim is to help develop ‘behaviour-smart places’, haven’t I? I really should start to flesh this out beyond the local government world.

This is my first attempt. A short, imperfectly formed vision of how a Police Service could become behaviour-smart. It is based on a few things that struck me during a recent workshop with staff from a police service and its Police and Crime Commissioner’s (PCC’s) office.

The big question, then: what would a behaviourally-smart police service look like in ten years’ time?

In a nutshell, at a strategic level, it would be serious about taking an evidence-based, behavioural approach to policy; and it would have developed practice drawing on insights from behavioural sciences.

The detail of this would depend on what the fundamentals of the service are. My starter for ten is that the societal value of a police service centres on social capital, on which it depends, and which it creates. Without ‘policing by consent’, we don’t, effectively, have a police service; and the loss of social capital creates unsustainable demand for a wide range of local services – in social care and health as much as in policing and the legal system.

So my hunch is that the evidence-based police service of the future will, first, identify the behaviours that underpin social capital and policing by consent – and those which undermine it. Second, it will have a detailed understanding of these, informed by data and observation. This list would be much more nuanced than whether or not a crime is being committed. It will develop models and metrics to identify and enumerate the impacts and outcomes of these behaviours, and related costs: what demand is created? If we were doing this today, we’d call it a ‘behavioural audit’, I think.

Third, it will have a culture of experimentation, employing design thinking, comfortable with failing quickly and randomised control trials (RCTs).

So far, so pie in the sky.

What could research, insight and engagement teams – and Chief Constable’s Offices – do now to start down this road? I’d suggest that they:

• build the ability and confidence to research and discuss behaviours in a smart way, in particular:
• – identifying the triggers and contexts that drive behaviour and suggesting ways of addressing them that draw on evidence from elsewhere; and
• – starting to describe behaviours to officers in this way (while drawing less on, for example, qualitative evidence, in which people often post-rationalise their actions);
• use insights from behavioural science in the short term to carry out experiments that, though they may not be fundamental to the service’s success, help build understanding of behavioural insights and their use within the service;
• start to use some behavioural metrics based on observation (so, if you want to track behaviour on Bonfire Night, select a random sample of events, decide what the target (non-) behaviours are and how to identify and enumerate them – then report back and track over time. This should provide much better information than a survey to assess awareness of your campaign);
• oh, and wean yourself off of communications work predicated on ‘educating the public’ or ‘changing people’s minds’. We don’t need to change people’s minds; we need to make our target behaviours easy and normal.

This leaves a lot of things unsaid and unconsidered; in particular, how to take place-based approaches with other parts of the local public service and other sectors. And how to phase out unproductive approaches. But I hope it’s a start.

I can see that things have moved on in the decade since I headed up MORI’s Crime & Policing research. But I don’t think that change is yet fast enough to cope with the need to manage demand and maintain/increase social capital in the face of growing inequality, unless the police service is able to reframe its approach to behaviour. We now know that people are much less in control of their actions than we would all like to think, so processes and communications which assume the discredited ‘rational actor model’ of behaviour have to be updated. I think I’m saying here that there is a chance we can do it strategically.

This is What We’re Like: how the most counter-intuitive thing you’ll hear all week will help you manage demand

(Originally published by the i-Network following my talk at their recent Shaping Demand conference)

You know how you sometimes lie awake at night planning to do something the next day – and then fail to do it? Well, you’re not the only one. We all do it.

Me, too. I’ll resolve not to have butter on my toast in the morning. Or walk to work. Or decide that, tomorrow night, I’ll wind down for sleep by doing the cryptic crossword instead of flicking through TV channels, because I know that screen time before bed makes sleep harder. And what’s more, I really, really, really mean it. Every time. But I almost never follow through on these decisions. Why not? It’s not because I change my mind and decide that I was wrong.

Here’s the counter-intuitive thing. The reason we don’t follow through on these good intentions of ours is that one of the main ways we understand human nature is wrong.

We’ve all grown up with a clear sense of self, believing that we’re in control of our actions. We take account of facts and opinions, make up our mind, then enact the decision we’ve made. And because I think I’m in control, I think everyone else is, too. So, when I want to influence someone’s behaviour, my instinct is to persuade them. If they’re doing something different, I assume that they’re doing it for a reason. So I try to change their mind.

Though we grow up with this understanding, there is a mountain of evidence that this isn’t what we humans are really like. Our evolution to be arguably* the most successful species on the planet has many quirks we’re beginning to understand better, but which are not yet in the mainstream and which overwhelmingly haven’t been reflected in how we have designed public services and shaped localities.

So what are we really like? Well, we have loads of mental shortcuts. Why? Because it gave our ancestors an evolutionary advantage to leave much of their brain’s cognitive capacity available to spot and instantly deal with predators. This is why you find it harder to apply your willpower if you’re already doing an ‘effortful’ mental task. It’s also why you’re really good at pattern recognition; your ancestors who realised that the leaves rustling nearby might be due to a predator were the ones who got to influence the human gene pool by running for cover and living long enough to pass on their genes.

Life expectancy has typically been under 20-30 years for most of human existence, so it’s no surprise that we also have mental shortcuts that help us grab the resources that will help us through the night, or the winter, and hold on to what we’ve got.

We also have plenty of short-cuts that help us be social, since human co-operation has also give us a real advantage. These biases have a much bigger influence on us all than we’d like to admit; in short, no-one likes to be the odd one out.

As I said a few times in my session at iNetwork’s recent Shaping Demand conference: this is what we’re like. And I think these insights are really helpful in taking new approaches to managing demand.

Freed from believing that people always have a reason for their actions, we can try to systematically examine what people do that creates demand for public services, and understand how it happens (not why).Freed from the need to change people’s minds when we want to influence their behaviour, we can concentrate instead on making self-sufficient behaviours easier and seem more normal.

And we can make this evidence-based understanding of human nature accessible, in order to involve staff, citizens and others in co-producing new designs and approaches.

The question for each of us is: how are we going to make sure this happens, rather than going the same way as my late-night commitment to walk to work tomorrow?

[*ants might beg to differ]

When @futuregov asked the questions

I did a talk for local government heroes Future Gov recently, on the back of which they interviewed me. This is the result:

http://wearefuturegov.com/2014/04/behavioural-effects-demand-management-and-local-government-an-interview-with-warren-hatter/

Doing demand management better, with behavioural insights

There may still be local authority chief execs and directors in local government who think they can steer a course through the financial challenges to come (the handy headline figure is a forecast £14.4bn shortfall in services by 2020) by reducing staff numbers and service levels, raising efficiency and changing eligibility criteria, but I don’t know them and I’m pretty sure they don’t exist. And, encouragingly, neither do the authors of Managing Demand: Building Future Public Services, Anna Randle and Henry Kippin. As they point out, these measures realise immediate savings but don’t shape services for the long-term.

This report is essential reading if you’re interested in the future of local public services. To me, it marks out the territory that should be occupied by anyone working on developing local public policy and practice. It should be, of necessity, the new black.

Anna and Henry cover a lot of territory – perhaps too much. There are dozens of aspects worth writing about, but I’m focused here on the topic closest to my heart, as its my job: using behavioural insights.

Managing Demand and the emerging practice it reveals, is particularly interesting to me because of the coincidence of this stark challenge to public finances and the rapid growth of evidence from behavioural sciences. As I’ve explained to many people, I’d be promoting the use of behavioural insights to policy makers and practitioners right now, even if public finances were in rude health. The fact that they are not, though, provides even more of an opportunity for us to design services that reflect what people are really like: demand management done well means reframing public services and places – and we can knit into this redesign our rapidly improving understanding of just how context-dependent human behaviour is, and of how much less control we have over our actions than we like to think. If local government budgets were ticking along nicely, and the demographics were in our favour, the rationale for change simply wouldn’t exist.

If anything, Managing Demand understates the extent to which public services’ approaches are behaviourally naïve. Here are some examples I’ve come across recently:

• Experienced Housing officers will often explain to cititzens likely to become homeless what the limitations are to what the Council can do for them, in effect anchoring the conversation at the level of service that used to be possible when supply and demand were less unevenly matched. When resources are scarce, we want them more, for good evolutionary reasons, so officers may be inadvertently encouraging demand that is costly to manage and damaging for residents’ wellbeing.
• Waste and recycling communications are often framed around the needs of the service, describing the benefits in terms that give the citizen no emotional reward, and using terms (like ‘food waste’) that are at best ambiguous to most people.
• Letters to a tenant in the process of reducing their arrears often don’t provide feedback in a way that acknowledges their success; they may receive an identically-worded letter to that sent to tenants with increasing arrears. So we miss the chance to embed the key behaviour: paying off the arrears.
• Councils involved in projects to give away home efficiency measures often have limited success. One reason is endowment effect: our inclination to see something free as valueless. But it is also because they tend to introduce cognitive barriers into the conversation immediately, referring to ‘retrofitting’, not the emotional reward to the resident: a cosy, draught-free home.

There are plenty of demand management approaches to issues like these which don’t utilise the insights from behavioural economics and psychology that are needed to reframe what’s on offer in a way that works with the grain of human nature. So what are the emerging approaches that do explore these, and which look like becoming part of the toolkit of the behaviour-smart local authority?

One is behavioural auditing. This is a way of examining the way a service works to identify where demand is created, track this back to the need that the demand expresses, and use this as a starting point. For many services, apparently identical need will lead to differing levels of demand from different residents; analysing the behaviours of those who create little or no demand helps re-design in a behaviourally-smart way, as it give us insight into which behaviours to encourage.

Another important aspect (not new, of course) is ethnographic research and observation. When we focus in on the behaviours that create service demand, understanding what it is that people do and how they do it is much more important to re-design than the reasons people give to explain them – and the rationale that officers apply. There is plenty of evidence that we adjust our views to accord with what we do, much as we would like to believe the opposite to be true!

A third is co-production. Guided by a behavioural practitioner, officers, managers, service users, citizens, community representatives, etc (I’ve worked with teachers and nurses, for example) are able to understand and work with real insights from behavioural sciences and generate many of the approaches that they go on to put into practice.

A word of caution, though. We are realising how difficult a behaviourally-smart approach can be to put into practice – for good reason.

Why shouldn’t we be surprised at this? Individually and collectively, our default model for influencing people is to try to change their mind and persuade them. It’s based on the rational actor model. My experience on a wide range of demand management projects with local government and public health is that policy-makers and managers can accept the overwhelming evidence that behaviour is context-dependent and so target behaviours need to be made easier and appear more normal … but implementing this, when it challenges the mental models we have worked with since we were toddlers, is not straightforward.

My view? Let’s keep the focus on demand management; let’s make our approaches as behaviourally-smart as possible; and let’s build the capacity in local government and communities to use behavioural insights.