In the earlier days of this blog, many of the posts were about code, in the Lawrence Lessig sense: the idea that the structure of software and the internet and the rules designed into these systems don’t just parallel the law (in a legal sense) in influencing and restricting public behaviour, but are qualitatively different, enabling distinct forms of affordance and constraint. Designers (and developers) — or in many cases those overseeing the process — in this sense potentially wield a lot of (political) power.
Continuing the meta-auto-behaviour-change effort started here, I’m publishing a few extracts from my PhD thesis as I write it up (mostly from the literature review, and before any rigorous editing) as blog posts over the next few months. The idea of how architecture can be used to influence behaviour was central to this blog when it started, and so it’s pleasing to revisit it, even if makes me realise how little I still know.
“There is no doubt whatever about the influence of architecture and structure upon human character and action. We make our buildings and afterwards they make us. They regulate the course of our lives.” Winston Churchill, addressing the English Architectural Association, 1924
In designing and constructing environments in which people live and work, architects and planners are necessarily involved in influencing human behaviour. While Sommer (1969, p.3) asserted that the architect “in his training and practice, learns to look at buildings without people in them,” it is clear that from, for example, Howard’s Garden Cities of To-morrow (1902), through Le Corbusier’s Ville Contemporaine and La Ville radieuse, to the Smithsons’ ‘Streets in the sky’, there has been a long-standing thread of recognition that the way people live their lives is directly linked to the designed environments in which they live. Whether the explicit intention to influence behaviour drives the design process—architectural determinism (Broady, 1966: see future blog post ‘POSIWID and determinism’)—or whether the behaviour consequences of design decisions are only revealed and considered as part of a post-occupancy evaluation (e.g. Zeisel, 2006) or by social scientists or psychologists studying the impact of a development, there are links between the design of the built environment and our behaviour, both individually and socially.
The Fun Theory (Rolighetsteorin), a competition / campaign / initiative from Volkswagen Sweden – created by DDB Stockholm – has been getting a lot of attention in the last couple of weeks from bothdesign-related people and other commentators with an interest in influencing behaviour: it presents a series of clever ‘design interventions’ aimed at influencing behaviour through making things “fun to do” – taking the stairs instead of the escalator, recycling glass via a bottle bank and using a litter bin. The stairs are turned into a giant piano keyboard, with audio accompaniment; the bottle bank is turned into an arcade game, with sound effects and scores prominently displayed; and the litter bin has a “deep pit” effect created through sound effects played as items are dropped into it. It’s exciting to see that exploring design for behaviour change is being so enthusiastically pursued and explored, especially by ad agencies, since – if we’re honest – advertisers have long been the most successful at influencing human behaviour effectively (in the contexts intended). There’s an awful lot designers can learn from this, but I digress…
As a provocation and inspiration to enter the competition, these are great projects. The competition itself is interesting because it encourages entrants to “find [their] own evidence for the theory that fun is best way to change behaviour for the better”, suggesting that entries with some kind of demonstrated / tested element are preferred over purely conceptual submissions (however clever they might be) which have often been a hallmark of creative design competitions in the past. While the examples created and tested for the campaign are by no means “controlled experiments” (e.g. the stats in the videos about the extra amount of rubbish or glass deposited give little context about the background levels of waste deposition in that area, whether people have gone out of their way to use the ‘special’ bins, and so on), they do demonstrate very well the (perhaps obvious) effect that making something fun, or engaging, is a way to get people interested in using it.
Going a bit deeper, though, into what “the theory of fun” might really mean, it’s clear there are a few different effects going on here. To use concepts from B J Fogg’s Behaviour Model, assuming the ability to use the stairs, bottle bank or bin is already there, the remaining factors are motivation and triggers. Motivation is, on some level, presumably also present in each case, in the sense that someone carrying bottles to be recycled already wants to get rid of them, someone standing at the bottom of the stairs or escalator wants to get to the top, and someone with a piece of litter in her hand wants to discard it somehow (even if that’s just on the ground).
(But note that if, for example, people start picking up litter from elsewhere in order to use the bin because they’re excited by it, or if – as in the video – kids run up and down the stairs to enjoy the effect, this is something slightly different: the motivation has changed from “I’m motivated to get rid of the litter in my hand” to “I’m motivated to keep playing with this thing.” While no doubt useful results, these are slightly different target behaviours to the ones expressed at the start of the videos. “Can we get more people to take the stairs over the escalator by making it fun to do?” is not quite the same as “Can we get people so interested in running up and down the stairs that they want to do it repeatedly?”)
So the triggers are what the interventions are really about redesigning: adding some feature or cue which causes people who already have the ability and the motivation to choose this particular way of getting out of the railway station to the street above, or disposing of litter, or recycling glass. All three examples deliberately, prominently, attract the interest of passers-by (“World’s deepest bin” graphics, otherwise incongruous black steps, illuminated 7-segment displays above the bottle bank) quite apart from the effect of seeing lots of other people gathered around, or using something in an unusual way.
And once they’ve triggered someone to get involved, to use them, there are different elements that come into play in each example. For example, the bottle bank – by using a game metaphor – effectively challenges the user into continuing (perhaps even entering a flow state, though this is surely more likely with the stairs) and gives feedback on how well you’re doing as well as a kind of reward. The reward element is present in all three examples, in fact.
I suppose the biggest and most obvious criticism of projects such as the Rolighetsteorin examples is that they are merely one-time gimmicks, that a novelty effect is the most (maybe only) significant thing at work here. It’s not possible to say whether this is true or not without carrying out a longitudinal study of the members of the public involved over a period of time, or of the actual installations themselves. Does having fun using the stairs once (when they’re a giant piano) translate into taking the (boring) normal stairs in preference to an escalator on other occasions? (i.e. does it lead to attitude or preference change?) Or does the effect go away when the fun stairs do?
It may be, of course, that interventions with explicitly pro-social rhetoric embedded in them (such as the bottle bank) have an effect which bleeds over into other areas of people’s lives: do they think more about the environment, or being less wasteful, in other contexts? Have attitudes been changed beyond simply the specific context of recycling glass bottles using this particular bottle bank?
How others have done it
This campaign isn’t the first to have tried to address these problems through design, of course. Without researching too thoroughly, a few pieces of work spring to mind, and I’m sure there are many more. Stephen Intille, Ron MacNeil, Jason Nawyn and Jacob Hyman in MIT’s House_n group have done work using a sign with the ‘just-in-time‘ message “Your heart needs exercise – here’s your chance” (shown above) positioned over the stairs in a subway, flashing in people’s line-of-sight as they approach the decision point (between taking stairs or escalator) linked to a system which can record the effects in terms of people actually making one choice or the other, and hence compare the effect the intervention actually has. As cited in this paper [PDF], previous research by K D Brownell, A J Stunkard, and J M Albaum, using the same message, in a similar situation, but statically displayed for three weeks before being removed, demonstrated that some effect remains on people’s choice of the stairs for the next couple of months. (That is, the effect didn’t go away immediately when the sign did – though we can’t say whether that’s necessarily applicable to the piano stairs too.)
Work on the design of recycling bins is, I think, worthy of a post of its own, since it starts to touch more on perceived affordances (the shape of different kinds of slots, and so on) so I’ll get round to that at some point.
Q12 Do you agree with the Government’s position that a standalone display should be provided with a smart meter?
Free-standing displays (presumably wirelessly connected to the meter itself, as proposed in [7, p.16]) could be an effective way of bringing the meter ‘out of the cupboard‘, making an information flow visible which was previously hidden. As Donella Meadows put it when comparing electricity meter placements [1, pp. 14-15] this provides a new feedback loop, “delivering information to a place where it wasn’t going before” and thus allowing consumers to modify their behaviour in response.
“An accessible display device connected to the meter” [2, p.8] or “series of modules connected to a meter” [3, p. 28] would be preferable to something where an extra step has to be taken for a consumer to access the data, such as only having a TV or internet interface for the information, but as noted [3, p.31] “flexibility for information to be provided through other formats (for example through the internet, TV) in addition to the provision of a display” via an open API, publicly documented, would be the ideal situation. Interesting ‘energy dashboard’ TV interfaces have been trialled in projects such as live|work‘s Low Carb Lane, and offer the potential for interactivity and extra information display supported by the digital television platform, but it would be a mistake to rely on this solely (even if simply because it will necessarily interfere with the primary reason that people have a television).
The question suggests that a single display unit would be provided with each meter, presumably with the householder free to position it wherever he or she likes (perhaps a unit with interchangeable provision for a support stand, a magnet to allow positioning on a refrigerator, a sucker for use on a window and hook to allow hanging up on the wall would be ideal – the location of the display could be important, as noted [4, p. 49]) but the ability to connect multiple display units would certainly afford more possibilities for consumer engagement with the information displayed as well as reducing the likelihood of a display unit being mislaid. For example, in shared accommodation where there are multiple residents all of whom are expected to contribute to a communal electricity bill, each person being aware of others’ energy use (as in, for example, the Watt Watchers project ) could have an important social proof effect among peers.
Open APIs and data standards would permit ranges of aftermarket energy displays to be produced, ranging from simple readouts (or even pager-style alerters) to devices and kits which could allow consumers to perform more complex analysis of their data (along the lines of the user-led innovative uses of the Current Cost, for example ) – another route to having multiple displays per household.
Q13 Do you have any comments on what sort of data should be provided to consumers as a minimum to help them best act to save energy (e.g. information on energy use, money, CO2 etc)?
This really is the central question of the whole project, since the fundamental assumption throughout is that provision of this information will “empower consumers” and thereby “change our energy habits” [3, p.13]. It is assumed that feedback, including real-time feedback, on electricity usage will lead to behaviour change: “Smart metering will provide consumers with tools with which to manage their energy consumption, enabling them to take greater personal responsibility for the environmental impacts of their own behaviour” [4, p.46]; “Access to the consumption data in real time provided by smart meters will provide consumers with the information they need to take informed action to save energy and carbon” [3, p.31].
Nevertheless, with “the predicted energy saving to consumers… as low as 2.8%” [4, p.18], the actual effects of the information on consumer behaviour are clearly not considered likely to be especially significant (this figure is more conservative than the 5-15% range identified by Sarah Darby ). It would, of course, be interesting to know whether certain types of data or feedback, if provided in the context of a well-designed interface could improve on this rather low figure: given the scale of the proposed roll-out of these meters (every household in the country) and the cost commitment involved, it would seem incredibly short-sighted not to take this opportunity to design and test better feedback displays which can, perhaps, improve significantly on the 2.8% figure.
(Part of the problem with a suggested figure as low as 2.8% is that it makes it much more difficult to defend the claim that the meters will offer consumers “important benefits” [3, p.27]. The benefits to electricity suppliers are clearer, but ‘selling’ the idea of smart meters to the public is, I would suggest, going to be difficult when the supposed benefits are so meagre.)
If we consider the use context of the smart meter from a consumer’s point of view, it should allow us to identify better which aspects are most important. What is a consumer going to do with the information received? How does the feedback loop actually occur in practice? How would this differ with different kinds of information?
Levels of display
Even aside from the actual ‘units’ debate (money / energy / CO2), there are many possible types and combinations of information that the display could show consumers, but for the purposes of this discussion, I’ll divide them into three levels:
These are by no means mutually exclusive and I’d assume that any system providing (3) would also include (1), for example.
Nevertheless, it is likely that (1) would be the cheapest, lowest-common-denominator system to roll out to millions of homes, without (2) or (3) included – so if thought isn’t given to these other levels, it may be that (1) is all consumers get.
I’ve done mock-ups of the sort of thing each level might display (of course these are just ideas, and I’m aware that a) I’m not especially skilled in interface design, despite being very interested in it; and b) there’s no real research behind these) in order to have something to visualise / refer to when discussing them.
(1) Simple feedback on current (& cumulative) energy use and cost
I’ve tried to express some of the concerns I have over a very simple, cheap implementation of (1) in a scenario, which I’m not claiming to be representative of what will actually happen – but the narrative is intended to address some of the ways this kind of display might be useful (or not) in practice:
Jenny has just had a ‘smart meter’ installed by someone working on behalf of her electricity supplier. It comes with a little display unit that looks a bit like a digital alarm clock. There’s a button to change the display mode to ‘cumulative’ or ‘historic’ but at present it’s set on ‘realtime’: that’s the default setting.
Jenny attaches it to her kitchen fridge with the magnet on the back. It’s 4pm and it’s showing a fairly steady value of 0.5 kW, 6 pence per hour. She opens the fridge to check how much milk is left, and when she closes the door again Jenny notices the figure’s gone up to 0.7 kW but drops again soon after the door’s closed, first to 0.6 kW but then back down to 0.5 kW again after a few minutes. Then her two teenage children, Kim and Laurie arrive home from school – they switch on the TV in the living room and the meter reading shoots up to 0.8 kW, then 1.1 kW suddenly. What’s happened? Jenny’s not sure why it’s changed so much. She walks into the living room and Kim tells her that Laurie’s gone upstairs to play on his computer. So it must be the computer, monitor, etc.
Two hours later, while the family’s sitting down eating dinner (with the TV on in the background), Jenny glances across at the display and sees that it’s still reading 1.1 kW, 13 pence per hour.
“Is your PC still switched on, Laurie?” she asks.
“Yeah, Mum,” he replies
“You should switch it off when you’re not using it; it’s costing us money.”
“But it needs to be on, it’s downloading stuff.”
Jenny’s not quite sure how to respond. She can’t argue with Laurie: he knows a lot more than her about computers. The phone rings and Kim puts the TV on standby to reduce the noise while talking. Jenny notices the display reading has gone down slightly to 1.0 kW, 12 pence per hour. She walks over and switches the TV off fully, and sees the reading go down to 0.8 kW.
Later, as it gets dark and lights are switched on all over the house, along with the TV being switched on again, and Kim using a hairdryer after washing her hair, with her stereo on in the background and Laurie back at his computer, Jenny notices (as she loads the tumble dryer) that the display has shot up to 6.5 kW, 78 pence per hour. When the tumble dryer’s switched on, that goes up even further to 8.5 kW, £1.02 per hour. The sight of the £ sign shocks her slightly – can they really be using that much electricity? It seems like the kids are costing her even more than she thought!
But what can she really do about it? She switches off the TV and sees the display go down to 8.2 kW, 98 pence per hour, but the difference seems so slight that she switches it on again – it seems worth 4 pence per hour. She decides to have a cup of tea and boils the kettle that she filled earlier in the day. The display shoots up to 10.5 kW, £1.26 pence per hour. Jenny glances at the display with a pained expression, and settles down to watch TV with her tea. She needs a rest: paying attention to the display has stressed her out quite a lot, and she doesn’t seem to have been able to do anything obvious to save money.
Six months later, although Jenny’s replaced some light bulbs with compact fluorescents that were being given away at the supermarket, and Laurie’s new laptop has replaced the desktop PC, a new plasma TV has more than cancelled out the reductions. The display is still there on the fridge door, but when the batteries powering the display run out, and it goes blank, no-one notices.
The main point I’m trying to get across there is that with a very simple display, the possible feedback loop is very weak. It relies on the consumer experimenting with switching items on and off and seeing the effect it has on the readings, which – while it will initially have a certain degree of investigatory, exploratory interest – may well quickly pall when everyday life gets in the way. Now, without the kind of evidence that’s likely to come out of research programmes such as the CHARM project, it’s not possible to say whether levels (2) or (3) would fare any better, but giving a display the ability to provide more detailed levels of information – particularly if it can be updated remotely – massively increases the potential for effective use of the display to help consumers decide what to do, or even to think about what they’re doing in the first place, over the longer term.
(2) Social / normative feedback on others’ energy use and costs
A level (2) display would (in a much less cluttered form than what I’ve drawn above!) combine information about ‘what we’re doing’ (self-monitoring) with a reference, a norm – what other people are doing (social proof), either people in the same neighbourhood (to facilitate community discussion), or a more representative comparison such as ‘other families like us’, e.g. people with the same number of children of roughly the same age, living in similar size houses. There are studies going back to the 1970s (e.g. [11, 12]) showing dramatic (2 × or 3 ×) differences in the amount of energy used by similar families living in identical homes, suggesting that the behavioural component of energy use can be significant. A display allowing this kind of comparison could help make consumers aware of their own standing in this context.
However, as Wesley Schultz et al  showed in California, this kind of feedback can lead to a ‘boomerang effect’, where people who are told they’re doing better than average then start to care less about their energy use, leading to it increasing back up to the norm. It’s important, then, that any display using this kind of feedback treats a norm as a goal to achieve only on the way down. Schultz et al went on to show that by using a smiley face to demonstrate social approval of what people had done – affective engagement – the boomerang effect can be mitigated.
(3) Feedforward, giving information about the future impacts of behavioural decisions
A level (3) display would give consumers feedforward  – effectively, simulation of what the impact of their behaviour would be (switching on this device now rather than at a time when there’s a lower tariff – Economy 7 or a successor), and tips about how to use things more efficiently at the right moment (kairos), and in the right kind of environment, for them to be useful. Whereas ‘Tips of the Day’ in software frequently annoy users because they get in the way of a user’s immediate task, with something relatively passive such as a smart meter display, this could be a more useful application for them. The networked capability of the smart meter means that the display could be updated frequently with new sets of tips, perhaps based on seasonal or weather conditions (“It’s going to be especially cold tonight – make sure you close all the curtains before you go to bed, and save 20p on heating”) or even special tariff changes for particular periods of high demand (“Everyone’s going to be putting the kettle on during the next ad break in [major event on TV]. If you’re making tea, do it now instead of in 10 minutes; time, and get a 50p discount on your next bill”).
Disaggregated data: identifying devices
This level (3) display doesn’t require any ability to know what devices a consumer has, or to be able to disaggregate electricity use by device. It can make general suggestions that, if not relevant, a consumer can ignore.
But what about actually disaggregating the data for particular devices? Surely this must be an aim for a really ‘smart’ meter display. Since [4, p.52] notes – in the context of discussing privacy – that “information from smart meters could… make it possible…to determine…to a degree, the types of technology that were being used in a property,” this information should clearly be offered to consumers themselves, if the electricity suppliers are going to do the analysis (I’ve done a bit of a possible mockup, using a more analogue dashboard style).
Whether the data are processed in the meter itself, or upstream at the supplier and then sent back down to individual displays, and whether the devices are identified from some kind of signature in their energy use patterns, or individual tags or extra plugs of some kind, are interesting technology questions, but from a consumer’s point of view (so long as privacy is respected), the mechanism perhaps doesn’t matter so much. Having the ability to see what device is using what amount of electricity, from a single display, would be very useful indeed. It removes the guesswork element.
If disaggregated data by device were to be available for the mass-distributed displays, clearly this would significantly affect the interface design used: combining this with, say a level (2) type social proof display could – even if via a website rather than on the display itself – let a consumer compare how efficient particular models of electrical goods are in use, by using the information from other customers of the supplier.
In summary, for Q13 – and I’m aware I haven’t addressed the “energy use, money, CO2 etc” aspect directly – there are people much better qualified to do that – I feel that the more ability any display has to provide information of different kinds to consumers, the more opportunities there will be to do interesting and useful things with that information (and the data format and API must be open enough to allow this). In the absence of more definitive information about what kind of feedback has the most behaviour-influencing effect on what kind of consumer, in what context, and so on, it’s important that the display be as adaptable as possible.
Q14 Do you have comments regarding the accessibility of meters/display units for particular consumers (e.g. vulnerable consumers such as the disabled, partially sighted/blind)?
The inclusive design aspects of the meters and displays could be addressed through an exclusion audit, applying something such as the University of Cambridge’s Exclusion Calculator to any proposed designs. Many solutions which would benefit particular consumers with special needs would also potentially be useful for the population as a whole – e.g. a buzzer or alarm signalling that a device has been left on overnight which isn’t normally, or (with disaggregation capability) notifying the consumer that, say, the fridge has been left open, would be pretty useful for everyone, not just the visually impaired or people with poor memory.
It seems clear that having open data formats and interfaces for any device will allow a wider range of things to be done with the data, many of which could be very useful for vulnerable users. Still, fundamental physical design questions about the device – how long the batteries last for, how easy they are to replace for someone with poor eyesight or arthritis, how heavy the unit is, whether it will break if dropped from hand height – will all have an impact on its overall accessibility (and usefulness).
Thinking of ‘particular consumers’ more generally, as the question asks, suggests a few other issues which need to be addressed:
- A website-only version of the display data (as suggested at points in the consultation document) would exclude a lot of consumers who are without internet access, without computer understanding, with only dial-up (metered) internet, or simply not motivated or interested enough to check – i.e., it would be significantly exclusionary.
- Time-of-Use (ToU) pricing will rely heavily on consumers actually understanding it, and what the implications are, and changing their behaviour in accordance. Simply charging consumers more automatically, without them having good enough feedback to understand what’s going on, only benefits electricity suppliers. If demand- or ToU-related pricing is introduced – “the potential for customer confusion… as a result of the greater range of energy tariffs and energy related information” [4, p. 49] is going to be significant. The design of the interface, and how the pricing structure works, is going to be extremely important here, and even so may still exclude a great many consumers who do not or cannot understand the structure.
- The ability to disable supply remotely [4, p. 12, p.20] will no doubt provoke significant reaction from consumers, quite apart from the terrible impact it will have on the most vulnerable consumers (the elderly, the very poor, and people for whom a reliable electricity supply is essential for medical reasons), regardless of whether they are at fault (i.e. non-payment) or not. There WILL inevitably be errors: there is no reason to suppose that they will not occur. Imagine the newspaper headlines when an elderly person dies from hypothermia. Disconnection may only occur in “certain well-defined circumstances” [3, p. 28] but these will need to be made very explicit.
- “Smart metering potentially offers scope for remote intervention… [which] could involve direct supplier or distribution company interface with equipment, such as refrigerators, within a property, overriding the control of the householder” [4, p. 52] – this simply offers further fuel for consumer distrust of the meter programme (rightly so, to be honest). As Darby  notes, “the prospect of ceding control over consumption does not appeal to all customers”. Again, this remote intervention, however well-regulated it might be supposed to be if actually implemented, will not be free from error. “Creating consumer confidence and awareness will be a key element of successfully delivering smart meters” [4, p.50] does not sit well with the realities of installing this kind of channel for remote disconnection or manipulation in consumers’ homes, and attempting to bury these issues by presenting the whole thing as entirely beneficial for consumers will be seen through by intelligent people very quickly indeed.
- Many consumers will simply not trust such new meters with any extra remote disconnection ability – it completely removes the human, the compassion, the potential to reason with a real person. Especially if the predicted energy saving to consumers is as low as 2.8% [4, p.18], many consumers will (perhaps rightly) conclude that the smart meter is being installed primarily for the benefit of the electricity company, and simply refuse to allow the contractors into their homes. Whether this will lead to a niche for a supplier which does not mandate installation of a meter – and whether this would be legal – are interesting questions.
Dan Lockton, Researcher, Design for Sustainable Behaviour
Cleaner Electronics Research Group, Brunel Design, Brunel University, London, June 2009
 Socolow, R.H. Saving Energy in the Home: Princeton’s Experiments at Twin Rivers. Ballinger Publishing, Cambridge MA, 1978
 Winett, R.A., Neale, M.S., Williams, K.R., Yokley, J. and Kauder, H., 1979 ‘The effects of individual and group feedback on residential electricity consumption: three replications’. Journal of Environmental Systems, 8, p. 217-233.
The week after (4th June) I’ll be giving a presentation at UFI in Sheffield, best known for its Learndirect courses. I’m hoping to be able to run a bit of a very rapid idea-generation workshop as part of this talk, something of an ultra-quick trial of the DwI toolkit…
In a lot of the debate and discussion about energy, future electricity generation and metering, improved efficiency and influencing consumer behaviour – at least from an engineering perspective – the term “demand” is used, in conjunction with “supply”, to represent the energy required to be supplied to consumers, much as in conventional “supply and demand” economics.
Now, I’m sure others have investigated this and characterised it economically much better than I can, but it seems to me that demand for energy (and sometimes water) is significantly different to, say, demand for most consumer products in that, for the most part, consumers only “demand” it indirectly. It is the products and systems around us which draw the current: they are important actors and have the agency, in a sense (at least unless we really understand the impacts of how they operate).
While with, say, a car’s fuel consumption, we experience the car’s demand for fuel, and pay for it, directly in proportion to our demand for travel, with most household electricity use, we not only generally wait a month or more before having to confront the “demand” (via the bill), but separating the background demand (such as a refrigerator’s continuous energy use simply to operate) from conscious demand (such as our decision to use a fan heater all day) is very difficult for us to do as consumers: from a very simple consumer perspective (ignoring things like reactive power flow), electricity is interchangeable, and the feedback we get on our behaviour is only very weakly linked to the specifics of that behaviour.
Basically, then, a lot of “demand” is not conscious demand at all. Most consumers don’t make an in-the-moment decision to use more electricity if it gets cheaper (though it may happen over time, e.g. if someone decides to get electric heating because oil heating has become more expensive) or vice versa. The demand is a function of the products and systems around us, our habits, lifestyle and behaviours but it is very difficult for us to see this, and make decisions which have an impact on this. If there are major changes, such as a massively changed price, then real conscious demand changes may happen (so a kind of stepped curve rather than anything smooth) but this is surely not what happens in everyday life. At least at present.
Maybe, then, part of what design could offer here is to help translate this unconscious, product-led, delayed payment demand into a visible, tangible, immediate demand which makes us consider it like any other everyday buying / consumption choice. Real-time self-monitoring feedback from clever metering technology (e.g. Onzo or Wattson) could go a long way here, but what about feedforward? Can we go as far as on-off switches with price labels on them? (Digital, updated, real-time, of course.) Would it make us more price-sensitive to energy costs? Would that influence our behaviour?