Category Archives: User experience

User-centred design for energy efficiency in buildings: TSB competition

The deadline’s fast approaching (mid-day 17th Dec) for the UK Technology Strategy Board‘s ‘User-centred design for energy efficiency in buildings’ competition [PDF] – there’s an introduction from Fionnuala Costello here.

This is an exciting initiative which aims to bring together (in a 5-day ‘sandpit’) people from different disciplines and different sectors to address the problems of influencing user behaviour to improve the energy efficiency of offices and other non-domestic buildings, and generate commercially viable collaborative solutions to develop, some of which will then be part-funded by the TSB. Fionnuala’s blog, People in Buildings has some great posts and discussions exploring aspects of how human factors and technology together might be used to help people use energy more effectively. If you or your organisation are interested in these kinds of issues – and using design to address them – it’d be well worth getting an application in over the next few days.

Thoughts on the ‘fun theory’


The ‘Piano Staircase’ from Volkswagen’s thefuntheory.com

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 both design-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.

Bottle bank arcadeWorld's deepest bin

Triggers

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.

Perhaps the most relevant pattern in all these examples, and the “fun theory” concept itself, is that of emotional or affective engagement. The user experience of each is designed to evoke an emotional response, to motivate engagement through enjoyment or delight – and this is an area of design where a lot of great (and commercially applicable) research work has been done, by people such as Pieter Desmet (whose doctoral dissertation is a model for this kind of design research), Pat Jordan, Marco van Hout, Trevor van Gorp, Don Norman and MIT’s Affective Computing group. Taking a slightly different slant, David Gargiulo’s work on creating drama through interaction design (found via Harry Brignull‘s Twitter) is also pertinent here, as is Daniel Pink’s collection of ‘emotionally intelligent signage’ (thanks to Larry Cheng for bringing this to my attention).

What sort of behaviour change, though?

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?

Project by Stephen Intille & House_n, MITProject by Stephen Intille & House_n, MIT

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.)

Persuasive Trash Cans by de Kort et alLast year I mentioned Finland’s “Kiitos, Tack, Thank you” bins, and in the comments (which are well worth reading), Kaleberg mentioned Parisian litter bins with SVP (s’il vous plaît) on them; most notable here is the work of Yvonne de Kort, Teddy McCalley and Cees Midden at Eindhoven on ‘persuasive trash cans‘ [PDF], looking at the effects of different kinds of norms on littering behaviour, expressed through the design or messages used on litter bins (shown to the left here).

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.

Many thanks to everyone who sent me the Fun Theory links, including Kimberley Crofts, Brian Cugelman and Dan Jenkins (apologies if I’ve missed anyone out).

Cialdini on the Beach

Self-monitoring is one of the most common persuasive techniques used in interface design: basically, giving people feedback on what they’re doing and what they’ve done. There are lots of issues about which kinds of feedback work best, in what circumstances, pairing it with feedforward, i.e. ‘What would happen if I did this?’ information, and so on. My recent long post about smart energy meters looks at some of the ideas within a particular application.

But sometimes it takes an example that’s not at first sight a ‘user interface’ or a ‘product’ to highlight how much difference certain design techniques can make.

Encouraging donations, Santa BarbaraThis unattended layout of things on the beach at Santa Barbara, California, soliciting donations, is an interface, too. It’s been designed, cleverly, both to invite passers-by to participate (by throwing coins from an adjacent walkway) and to give them feedback on their throwing ability.

That target – the bright red Folger’s tub on the bright red square of fabric in the middle of the white sheet – is a crucial way of engaging people and getting them to contribute. Who, throwing a coin, isn’t going to try and get it in the tub? (Unless you’re trying to knock over the vases or the little surfers.) And when you miss, you’re going to try again. And again. (I know I did.) You get entertainment and a challenge which seems like it’s worth pursuing, and you can see your track record.

Encouraging donations, Santa Barbara

It mustn’t be too difficult. It’s Csíkszentmihályi’s flow, it’s fairground games theory applied to the simplest of begging sitations, but it works, in terms of getting people to contribute.

What it shows me from a design point of view is that explicitly using targets ought to be included as a Design with Intent technique / pattern in addition to related ones such as self-monitoring, in future versions of the toolkit. The target effect – and other game-related techniques – are sufficiently distinct to inspire plenty of design ideas on their own.

Encouraging donations, Santa Barbara

Of course this particular setup also uses a number of other techniques – affective engagement with the ‘Just Plain Hungry’ card, reciprocation with the ‘Make a Wish’ offer, colour & contrast and prominence & visibility with the way the arrangement draws the eye, operant conditioning in terms of a ‘reward’ when you succeed (the wish, or a sense of satisfaction) and social proof in the way that everyone can see that others have thrown coins (and even a note), and that everyone can see you contributing when you throw your coins (or if you decide not to) – a kind of peer surveillance. The plate of sand is an additional affective touch which also works well.

It’s almost like Robert Cialdini put the whole thing together.

It also makes me think it would be worth cataloguing the design techniques employed in the design of charity collecting boxes and games which offer donors (often children) something exciting or engaging in return for their money. I used to love spiral wishing wells and, in general, ones that did something (like this wonderful RSPCA example, though from before my time). There have to be lessons there for other designers interested in engaging users and motivating them to contribute, or behave in a particular way.

I hope whoever set all that up on that beach in Santa Barbara made some money that day. It would have been well deserved.

Sort some cards and win a copy of The Hidden Dimension

The Hidden Dimension

UPDATE: Thanks everyone – 10 participants in just a few hours! The study’s closed now – congratulations to Ville Hjelm whose book is now on its way…

If you’ve got a few minutes spare, are interested in the Design with Intent techniques, and fancy having a 1/10 chance of winning a brand-new copy of The Hidden Dimension, Edward T Hall’s classic 1966 work on proxemics (very worthwhile reading if you’re involved in any way with the design of environments, either architecturally or in an interaction design sense), then please do have a go at this quick card-sorting exercise [now closed].

It makes use of the pinball / shortcut / thoughtful user models I introduced in the last post, so it would probably make sense to have that page open alongside the exercise. The DwI techniques will be presented to you distinct from the ‘lenses’ (Errorproofing, Cognitive etc) so don’t worry about them.

The free WebSort account I’m using for this only allows 10 participants, so be quick and get a chance of winning the book! Once 10 people have done it, I’ll draw one of the participants out of some kind of hat or bucket and email you to get your postal address.

The purpose here (a closed card-sort, to use Donna Spencer‘s terminology) is, basically, to find out whether the pinball / shortcut / thoughtful models allow the DwI techniques to be assigned to particular ways of thinking about users – that make sense to a reasonable proportion of designers. There’s no right or wrong answer, but if 80% of you tell me that one technique seems to fit well with one model, while for another there’s no agreement at all, then that’s useful for me to know in developing the method.

Thanks for your help!

Card sorting

Cover photo from Amazon

Modelling users: Pinballs, shortcuts and thoughtfulness

The different approaches to influencing people’s behaviour outlined in the Design with Intent toolkit are pretty diverse. Working out how to apply them to your design problem, and when they might be useful, probably requires you, as a designer, to think of “the user” or “users” in a number of different ways in relation to the behaviour you’re trying to influence. I’ve thought about this a bit, and reckon there are maybe three main ways of thinking about users – models, if you like – that are relevant here. (These are distinct from the enabling / motivating / constraining idea.)

The ‘Pinball’ User

In this case, you think of users as, pretty much, very simple components of your system, to be shunted and pushed and pulled around by what you design, whether it’s physical or digital architecture. This view basically doesn’t assume that the user thinks at all, beyond basic reflex responses: the user’s a pinball (maybe a slightly spongey one) pushed and pulled this way and that, but with no requirement for understanding coming from within [1,2].

While things like deliberately uncomfortable benches or the Mosquito act against the Pinball User – effectively treating users like animals – this view need not always take such a negative approach – lots of safety systems, even down to making sure different shape connectors are used on medical equipment to prevent mistaken connections, don’t mind whether the user understands what’s going on or not: it’s in everyone’s interests to influence behaviour on the most basic level possible, without requiring thought.

The ‘Shortcut’ User

Here, you think of users as being primarily interested in getting things done in the easiest way possible, with the least effort. So you assume that they’ll take shortcuts [3], or make decisions based on intuitive judgements (Is this like something I’ve used before? How does everyone else use this? I expect this does what it looks like it does), habits, and recognising simple patterns that influence how they behave.

The Shortcut User is assumed not to want to think too much about what’s going on behind the scenes, beyond getting things done. He or she’s not always thinking about the best way of doing things, but a way that seems to work [4]. If systems are designed well to accommodate this, they can feel very easy to use, intuitively usable, and influence user behaviour through these kinds of shortcut mechanisms rather than anything deeper [5]. But there’s clearly potential for manipulation, or leading users into behaviour they wouldn’t choose for themselves if they weren’t taking the shortcuts.

The ‘Thoughtful’ User

Thoughtful Users are assumed to think about what they are doing, and why, analytically: open to being persuaded through reasoned arguments [6] about why some behaviours are better than others, maybe motivating them to change their attitudes about a subject as a precursor to changing their behaviour mindfully. If you think of your users as being Thoughtful, you will probably be presenting them with information and feedback which allows them to explore the implications of what they’re doing, and understand the world around them better.

Most of us like to model ourselves as Thoughtful Users, even though we know we don’t always fit the model. It’s probably the same with most people: so knowing when it’s appropriate to assume that users are being mindful of their behaviour, and when they’re not, will be important for the ‘success’ of a design.

_______________________________________

Of course there are many other ways you can model the user. But these seem like they might be useful ways of thinking, and of classifying the actual design techniques for influencing behaviour [PDF] according to what assumptions they make about users. I will try to test their validity / usefulness as part of my trials.

See the next post for how you can get involved with that…

Note:
From an academic psychology (or behavioural economics) point of view, the boundaries between these models of the user are maybe too blurry. Shortcut User is assumed to be pretty much like a System 1 thinker, while Thoughtful User is System 2. Straying inadvisedly into areas I know little about, Pinball User may well be assumed to be a user only using the R-complex, though I’m not sure this fits especially well. But if the distinctions are useful to designers, in the context of actually developing products and services, that (to be honest) is what matters from my point of view.

To develop the three models described above, I was inspired by this Interactions article (also here) by Hugh Dubberly, Paul Pangaro and Usman Haque, which draws on some of Kenneth Boulding’s General Systems Theory [PDF] to characterise a range of ordered system ‘combinations’ in which the user can be a part. The Pinball User corresponds pretty much to the ‘Reacting’ system; the Thoughtful User is a ‘Learning’ system; the Shortcut User is perhaps a special case of a ‘Regulating’ system (self-regulating negative feedback to damp variation, to minimise effort, boundedly rational).

I haven’t yet explored applying Leonard Talmy’s Force Dynamics, as suggested by Simon Winter to these aspects of modelling the user / interaction. I will do, in due course.

[1] Perhaps analogous to Lawrence Lessig’s ‘pathetic dot’
[2] I’m grateful to Sebastian Deterding for the explicit concept of user-as-pinball
[3] Heuristics & biases (Kahneman & Tversky)
[4] Satisficing (Simon)
[5] Peripheral route persuasion (Petty & Cacioppo)
[6] Central route persuasion (Petty & Cacioppo)

Pinball photo by ktpupp on Flickr, CC-licensed. Shortcut photo (desire path) by Alan Stanton on Flickr, CC-licensed. Thoughtful photo by Esther Dyson on Flickr, CC-licensed.

‘Smart meters': some thoughts from a design point of view

Here’s my (rather verbose) response to the three most design-related questions in DECC’s smart meter consultation that I mentioned earlier today. Please do get involved in the discussion that Jamie Young’s started on the Design & Behaviour group and on his blog at the RSA.

Q12 Do you agree with the Government’s position that a standalone display should be provided with a smart meter?

Meter in the cupboard

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 [6], 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 [5]) 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 [8]) – 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)?

Low targets?
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 [9]). 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:

(1) Simple feedback on current (& cumulative) energy use / cost (self-monitoring)
(2) Social / normative feedback on others’ energy use and costs (social proof + self-monitoring)
(3) Feedforward, giving information about the future impacts of behavioural decisions (simulation & feedforward + kairos + self-monitoring)

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.

Simple feedback on current (& cumulative) energy use, cost
(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 [10], 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.

Social / normative feedback on others’ energy use and costs

(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 [13] 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.

Feedforward, giving information about the future impacts of behavioural decisions

(3) Feedforward, giving information about the future impacts of behavioural decisions

A level (3) display would give consumers feedforward [14] – 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 [15] 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).

Disaggregated data dashboard

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.

Now, Sentec’s Coracle technology [16] is presumably ready for mainstream use, with an agreement signed with Onzo [17], and ISE’s signal-processing algorithms can identify devices down to the level of makes and models [18], so it’s quite likely that this kind of technology will be available for smart meters for consumers fairly soon. But the question is whether it will be something that all customers get – i.e. as a recommendation of the outcome of the DECC consultation – or an expensive ‘upgrade’. The fact that the consultation doesn’t mention disaggregation very much worries me slightly.

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 [19] 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 [9] 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

[1] Meadows, D. Leverage Points: Places to Intervene in a System. Sustainability Institute, 1999.

[2] DECC. Impact Assessment of smart / advanced meters roll out to small and medium businesses, May 2009.

[3] DECC. A Consultation on Smart Metering for Electricity and Gas, May 2009.

[4] DECC. Impact Assessment of a GB-wide smart meter roll out for the domestic sector, May 2009.

[5] Fischer, J. and Kestner, J. ‘Watt Watchers’, 2008.

[6] DOTT / live|work studio. ‘Low Carb Lane’, 2007.

[7] BERR. Impact Assessment of Smart Metering Roll Out for Domestic Consumers and for Small Businesses, April 2008.

[8] O’Leary, N. and Reynolds, R. ‘Current Cost: Observations and Thoughts from Interested Hackers’. Presentation at OpenTech 2008, London. July 2008.

[9] Darby S. The effectiveness of feedback on energy consumption. A review for DEFRA of the literature on metering, billing and direct displays. Environmental Change Institute, University of Oxford. April 2006.

[10] Kingston University, CHARM Project. 2009

[11] Socolow, R.H. Saving Energy in the Home: Princeton’s Experiments at Twin Rivers. Ballinger Publishing, Cambridge MA, 1978

[12] 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.

[13] Schultz, P.W., Nolan, J.M., Cialdini, R.B., Goldstein, N.J. and Griskevicius, V., 2007.
‘The Constructive, Destructive and Reconstructive Power of Social Norms’. Psychological Science, 18 (5), p. 429-434.

[14] Djajadiningrat, T., Overbeeke, K. and Wensveen, S., 2002. ‘But how, Donald, tell us how?: on the creation of meaning in interaction design through feedforward and inherent feedback’. Proceedings of the 4th conference on Designing interactive systems: processes, practices, methods, and techniques. ACM Press, New York, p. 285-291.

[15] Business of Software discussion community (part of ‘Joel on Software’), ‘”Tip of the Day” on startup, value to the customer’, August 2006

[16] Sentec. ‘Coracle: a new level of information on energy consumption’, undated.

[17] Sentec. ‘Sentec and Onzo agree UK deal for home energy displays’, 28th April 2008

[18] ISE Intelligent Sustainable Energy, ‘Technology’, undated

[19] Engineering Design Centre, University of Cambridge. Inclusive Design Toolkit: Exclusion Calculator, 2007-8