Powering change through data
For councils, identifying and targeting problematic waste areas and targeting interventions to these places is an ongoing challenge. Rob Cole looks at how three local authorities are using data to generate change
While for some the thought of government collecting and using data may conjure up nightmares of an Orwellian dystopia, sophisticated data is a key untapped resource for local authorities as they seek to solve issues with recycling such as high contamination and low participation rates.
While councils are well-versed in the collection of waste data on a general level, such as that which they are required to submit to Waste Data Flow on tonnages and types of materials collected, some are going right down to street level to gain as accurate a picture as possible of what is happening in their local authority.
On top of this, there is now a proliferation of socio-demographic data available to help councils get a betteridea of their area. Datasets such as the Index of Multiple Deprivation (IMD) and the consumer classification service Acorn give an idea of the socio-economic status of a given area, right down to ward level, including the likely preferences of residents and the most effective means of communications.
For example, Acorn segments postcodes and neighbourhoods into six categories: affluent achievers, rising prosperity, comfortable communities, financially stretched and urban adversity – 18 groups and 62 types.
They use a variety of data sources, from the Land Registry to private rental information, to provide precise information of different types of people and their preferences –a potentially indispensable resource for local authorities. Knowing who is doing what, where and how they are likely to respond to certain communications or interventions provides the basis for local authorities to target messages to those residents that remain confused or resistant and make significant gains.
The importance of data as a resource to provide local authorities with an ever more accurate picture of their areas and what residents are throwing out is becoming increasingly appreciated.
Environmental consultancy Eunomia and the Waste and Resources Action Programme (WRAP) recently published what they call the most detailed UK-wide waste composition study to date, while the Waste Data Flow User Group is to survey English councils about the different ways in which they manage waste data in a bid to get local authorities to work together to create a standardised waste data management system.
While there is much more to learn about how data can help councils, some local authorities are already pioneering its innovative use in their operations, and are enjoying considerable success worth shouting about.
Seeing the bigger picture
Cornwall Council embarked on what it dubbed its Big Waste Data project in 2016 to see how data could be used to improve its waste and recycling services. The council brought together weighbridge data and round-by-round street level collection data and combined it with socio-demographic data from the IMD and Acorn to build an accurate picture of how waste services are being used in Cornwall.
Paul Martin, Waste Policy and Projects Team Leader at Cornwall Council, maintains it’s all about building up as big a picture as possible. “You need many datasets to form different pictures. One dataset will tell you something, but it won’t tell you everything you need to know,” he says. “It’s not all just council waste information. When you combine all this with socio-demographic data, for example, you can get a much bigger picture.”
This is none more evident than in its communications for its garden waste subscription service. The data collected allowed the council to target specific areas based on historic participation rates, current subscriber levels, how they compared to similar areas on the IMD and their rurality, as well as more recently looking at the CO2 impacts of kerbside garden waste collections against regular visits to Household Waste Recycling Centres (HWRCs).
This was done in order to focus communications and encourage residents, where appropriate, to subscribe to the council’s paid-for garden waste service. This engagement in one ward had a 25 per cent success rate in getting people to sign up to the garden waste subscription
“Using our own mapping information we can see how many garden waste subscribers there are on one street versus another and direct our community engagementteam to these areas, whether this is through a door- knocking exercise or other forms of communication,”recalls Martin.
“We know who our subscribers are and where they are, and through using the Acorn data, we can then tailor campaigns more precisely to the people we are aiming at, knowing what forms of communications and marketing approach will be appropriate to their particular household.”
As “each area is dynamic and changes all the time” new data is collected on a monthly basis, evaluated and analysed to try to make comparisons. This is done using the PowerBI processing system, which cuts down the resources needed to understand the data.
On a wider scale, the collection and mapping of data across Cornwall is certainly helpful in allocating resources, which, similar to other local authorities, are limited – “Whilst we acknowledge that this system will not have a 100 per cent success rate, or even close to that figure, it will be a more efficient use of resource than we would otherwise have had” – and has proved very useful in the council’s tendering for a new waste service contract. “The higher the quality of the information we have, the more effective any performance monitoring system can be.
For example, if you have 3,000 litter bins to pick up and say you know the size, the frequency of their collections and where they are being collected from, the better quality information for a bidder and then hopefully the better quality of their bid, as hopefully they will not over resource a service, as as they will know exactly what will need to provide the service.”
Building up an evidence base
Norfolk Waste Partnership (NWP), a group of all eight Norfolk councils, is another authority that has sought to use data to gain a better picture of where problems in its waste service lie.
Following a countywide recycling round audit in 2016, NWP observed that certain areas were recording significant levels of contamination, consistently above 12 per cent in some areas, with many people bagging their recycling, resulting in it being rejected at the Materials Recycling Facility (MRF) at an annual cost of £500,000 to the councils.
In order to tackle this, NWP used the results of the audit, combined with Acorn socio-demographic data and the WRAP’s waste communications report that advised on which forms of communications certain groups respond best to, to devise targeted campaigns to address the issue of contamination.
As part of a pilot, NWP selected five different streets covered by one collection round in an area of Norwich that registered more than 20 per cent contamination. On three streets, three different types of communications – leaflets, door-knocking and a bin sticker – were piloted, while two streets were designated control areas, receiving regular communications.
A ‘no bagged recycling’ message was conveyed, with the results monitored using three audits – one pre-intervention and two post-intervention. The pilot found that bin stickers were most effective, achieving an average 50 per cent contamination reduction, and NWP is now preparing to roll the bin stickers out across a larger area.
While Alun Housago, Business and Community Waste Officer at Norfolk County Council, praises the use of the socio-demographic data in being useful in giving “an idea of the types of messages we might want to put out in certain areas as opposed to others”, setting up and trialing data-based campaigns isn’t cheap.
“When we divided a round into five areas, each of the five areas had to be collected and sampled separately,” Houssago recalls. “That meant the crew that would normally go round and collect the whole lot in one day, were making five separate trips in the vehicle, that added extra time onto their day. To try and do that more often would be really expensive.”
However, by demonstrating the undoubted value of taking such an approach in being able to identify precisely where problems are arising and target resources to address them, it is not unreasonable to think that council budget decision-makers would be willing to free up more funds for data collection and targeted campaigns with this evidence that it works. “Having an actual evidence base is much more useful in persuading budget holders to part with their cash,” added Housago.
There is only so much money that budget holders will release for this, however, and knowing that limits inevitably have to be placed on the work you can do can bring frustration – imagine what could be achieved if the time and money was available to find out exactly what each resident were putting in their bin and tailor communications to each individual?
“You look at a round that you would label as highly contaminated, and you want to pinpoint within a couple of thousand houses collected in a given round if there is one particular hotspot,” adds Housago. “It may just be very few people in a given area that are causing a problem for everyone else. But it’s the logistics of drilling ever deeper down that’s the problem.”
Making impressions
South Cambridgeshire District and Cambridge City Councils, working together under Greater Cambridge Shared Waste Service took a similar approach to tackling contamination, using data collected to target communications such as door-knocking and paid- for Facebook ads in areas that were found to have particularly high rates of contamination.
Data on contamination was collected using both data from Yotta Alloy, an asset management platform, which recorded which bins were contaminated on a particular round, and data from the local MRF on which rounds were experiencing highest contamination, which then allowed the councils to identify specific pilot areas to trial the new targeted communications approach.
The data-based campaign meant that areas with around seven per cent contamination – the worst affected in the area – saw their contamination fall by about one per cent. Meanwhile, general communications served to the rest of the districts saw their contamination rates remain static.
Being able to see exactly where contamination was coming from allowed Greater Cambridge Shared Waste service to get across a message that played on social norming, and getting residents to interact with their neighbours. “It allowed us to tell people that people in their area had been contaminating their recycling, and think about their own actions,” says Trevor Nicoll, Head of Greater Cambridge Shared Waste Service. “It gets people to think, ‘Of course, we wouldn’t put a nappy in our recycling bin, or did we?’ or ‘Did I wash my yoghurt pot up’. It gets people to change by thinking about their actions in relation to those around them.”
The use of Facebook by Greater Cambridge Shared Waste Service was particularly useful in being able to prove that communications were actually reaching residents and residents were engaging in it – useful when making an argument for budget allocations. On one hand they were able to target their door-knocking campaign, which was “ridiculously expensive” and cost thousands of pounds on the most contaminated areas, ensuring that the cost was limited to the worst affected areas, while on the other, they have been able to measure engagement thanks to Facebook’s ability to record impressions.
“We spent £500 on our paid-for advertising over a number of villages and on that we got a return of 413 people click right through the link – almost a pound a click,” says Nicoll. “Of those people, we got more than 100 reactions and 24 comments, which is a much higher response than we normally get. We were impressed with the return, knowing people were actually clicking on it and getting actual impressions.”
Potential untapped
Despite the evident benefits of using data to identify problematic waste areas in a local authority, the most revolutionary use of data remains untapped. Though identified as something local authorities would like to do, the use of socio-demographic data from the likes of Acorn or the IMD to curate communications and messages for specific groups of people in problem waste areas remains underutilised.
“We want to go further, we want to get better. All the time you are refining and improving the information you’re getting, so you hopefully get better at it,” says Martin on Cornwall’s aim to explore this area further. “Some will respond more directly to direct marketing, some will respond better to personalised letters, some will be happy with email, some prefer face-to-face”.
Nicoll remarks how Greater Cambridge Shared Waste Service had noticed that certain groups tend to respond to council ads because it’s the council, whereas others don’t react with it because it’s the council. Being able to identify those people and then serve the same advert but in a different style, with the council branding less prominent, may be something they would try. Nicoll says: “That’s the next stage for us. We want to target a similar message in different ways to different groups of people, to try and get the maximum number of people to engage.”
The opportunities for data to improve waste and recycling services are limitless, and it is hard not to get excited about the potential it could have for local authorities for whom any incremental improvement is vital.
And certainly, this isn’t a zero-sum arms race with local authorities competing against each other to get ahead. Housago says: “If there’s a similarity in what we’ve done and what others have done it would be good to compare the best approaches to see if there are ways we can improve.”
While each has its own local considerations, budgetary resources and constituents for which they are responsible, local authorities sharing best practice means all can at least explore how data can help recycling intervention and take their first steps along the data revolution.