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A Clean Sweep. Delivering cleaner streets in diverse neighbourhoods. Nigel Tyrrell London Borough of Lewisham.

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A Clean Sweep

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A clean sweep

A Clean Sweep

Delivering cleaner streetsin diverse neighbourhoods

Nigel TyrrellLondon Borough of Lewisham


A clean sweep

A Clean Sweep?Narrowing the gap between deprived and better off neighbourhoodsAnnette HastingsGlen BramleyNick BaileyRob Croudace David WatkinsUniversity of GlasgowHeriot-Watt University


Research aims

Research aims

To understand more about how different neighbourhood contexts predict environmental problems;

To explore the organisational challenges and financial costs involved of meeting different kinds and levels of need ;

To examine different approaches to narrowing the gap;

To provide ideas, strategies and tools which local authorities can use to design policy and practices capable of narrowing the gap with relation to street cleanliness.


Research methods

Research methods

Three case-study local authorities – contrasting urban locations

Street-level analysis

Quantitative and qualitative methods

Assessment of distribution of service inputs and cleanliness outcomes by area deprivation

Test hypotheses from previous research on neighbourhood context and environmental challenges

Research funded by Joseph Rowntree Foundation


Why try to narrow the gap

Why try to narrow the gap?

Different neighbourhoods present distinctive challenges – one size doesn’t fit all

Need to show ‘continuous improvement’

Moral imperative – consistency or ‘justice’

2009 Social Mobility White Paper :

“tackling socio-economic disadvantage and narrowing gaps in outcomes for people from different backgrounds is a core function of key public services”


Outcomes the big picture

Outcomes: the big picture

All three case studies:

meet or exceed national benchmarks

have shown improvement over time

where is there scope for further improvement?

But what about the distribution of outcomes?


A clean sweep

Outcomes by deprivation


Percent of transects falling below acceptable litter threshold by street deprivation

Percent of transects falling below acceptable litter threshold by street deprivation

45%

Fife

40%

Lewisham

Leeds

35%

30%

25%

20%

15%

10%

5%

0%

Least

2

3

4

5

6

7

8

9

Most

Street deprivation (estd.)


Percent of transects gaining an a grade by street deprivation

Percent of transects gaining an A grade by street deprivation

45%

Fife

40%

Lewisham

Leeds

35%

30%

25%

20%

15%

10%

5%

0%

Least

2

3

4

5

6

7

8

9

Most

Street deprivation (estd.)


Deprivation profile of the case studies

Deprivation profile of the case studies


Relationship between high grade average and inequality of outcomes

Relationship between high grade average and inequality of outcomes

  • LAs with high average grades tend to have more unequal outcomes

  • LAs with low average grades more equal outcomes

  • Need to avoid a ‘leveling down’

  • Should we aim to be in the middle, therefore?


How does neighbourhood context affect outcomes

How does neighbourhood context affect outcomes?

Physical environment:

- Flats and non-traditional forms of housing; small properties

Open spaces; Physical regeneration

On-street parking

Alleys; unfenced gardens

Housing density

Social environment

Economic inactivity; Poverty

Overcrowding; Population density

Child/youth density; Lone parent density

Density of vulnerable households

Turnover


Evidence on environmental difficulty the first case study

Evidence on environmental difficulty: the first case study

Using national data sets

density, overcrowding, flats and lone parents associatedwith litter, rubbish, weed growth

non-employment, lone parents associated with graffiti and vandalism

(n=1030, range of correlations at the 10% significance level)

Detailed bespoke survey

Hedged gardens, open areas, wind tunnels, derelict sites associated with litter, rubbish and weeds

Grass verges, planted beds, alleys, on street parking, street furniture, bus shelters, open areas, building sites associated with flytipping, flyposting and graffiti

(n=52, range of correlations at 10% significance level)


Deprivation and environmental difficulty the first case study

Deprivation and environmental difficulty:the first case study

Deprived streets have much higher incidence of the factors thought to be associated with more challenging service context

N=1030, using national data sets


Achieving a clean sweep three pathways

Achieving a Clean Sweep: three pathways

Pathway one: topping up standardised services

dedicated ‘beat’ sweepers, topped up with responsive mobile squads

Informal targeting of problem areas by operatives

“I can get away with giving (place A) only one sweep, but would give (place B) three .. Don’t tell my supervisor, but he probably knows anyway”


A clean sweep

Standardised programmed services??


Programmed services topped up in deprived areas

Programmed services topped up in deprived areas

  • Overall, positive skew in expenditure

  • Programmed services skewed towards less deprived streets

  • Responsive services skewed to more deprived streets


Achieving a clean sweep three pathways1

Achieving a Clean Sweep: three pathways

Pathway two: using non-mainstream resources and services

May be based on standardised or targeted programmed service

Our example: targeted mechanical and manual sweeping

Topped up by ‘additional’ resources in the most disadvantaged areas

Additional resources involved new ways of working


Additional resources associated with narrowing the gap

Additional resources associated with narrowing the gap


Targeting of programmed services

Targeting of programmed services?


Achieving a clean sweep three pathways2

Achieving a Clean Sweep: three pathways

Pathway Three: Programmed adjustments to standardised services

Core services engineered to target need

May involve dedicated ‘beat’ operatives (squads or individuals)

May involve a ‘cover up’ of the extent of targeting

All streets swept twice weekly

But sweepers with more challenging areas, given smaller workload

Operatives in affluent areas work smartly


Inputs beat size by deprivation fig 4 2

Inputs – beat size by deprivation (Fig 4.2)


Working smartly in affluent areas

Working smartly in affluent areas

In an affluent and high workload (in street length) beat, Clive contends with ‘moany people’ as well as comments like “don’t you come down here anymore”.

He consciously leaves his barrow on show in prominent places to show that he is around and tries to work “in ways to keep people happy”, which include doing “extras” (unpaid).

NB Recall the lack of ‘A’s in this case study


Conclusions cross cutting issues

Conclusions: Cross cutting issues

Absolute levels of resources as well as distribution

Requires sufficient basic service in most needy areas – otherwise doomed to fail

May mean less ‘A’ grades elsewhere

Different modes of working may suit particular neighbourhood contexts

Know your area – multiple sources of intelligence?

Challenges of achieving a ‘win win’ situation


Further information

Further information

Final report to be published by Joseph Rowntree summer/autumn 2009 as

A Clean Sweep: Narrowing the gap between deprived and better off neighbourhoods

Download for free a www.jrf.org.uk or email [email protected]

Previous report: Cleaning up Neighbourhoods: Environmental problems and service provision in deprived areas free download www.jrf.org.uk


Nigel tyrell lb lewisham

Nigel Tyrell

LB Lewisham


A clean sweep

Resident Satisfaction

Resident Satisfaction


Key factors

Key Factors

Staff management

Performance

Sickness

Work planning

Resident Engagement

Love Lewisham etc.


Budget

Budget

£3.92 Million

£25 per resident PA


Activity

Activity

All streets swept at least once a week

– over 700 miles of roads (135 beats)

10,000 tonnes of fly tips cleared

6,000 tonnes of litter

Filled 900,000 blue bags

2,500 litter bins emptied 364 days a year


Staff

Staff

144 Street Sweepers

22 mobile team workers

26 mobile estate sweepers

4 mechanical broom/mini RCV drivers

I Scarab driver

14 managers


Sickness

Sickness

4.9 days per operative p.a.

Lower than the Council ‘office worker average’

Key element of our approach to efficiency


Everyone on board

Everyone on-board

Love Lewisham, staff & community engagement


Community engagement

Community Engagement

Clean & Green Schools Programme

Business Environmental Excellence

Streetleaders

NEAT’s

Graffiti Busters

River Clean Up’s

Awareness Raising Community Groups

Letters to markets traders


Councillor involvement

Councillor involvement


Love lewisham

Love Lewisham

Ability to show "before" and "after" pictures

Staff can demonstrate what has been achieved

Councillors and citizens can see that a problem has been dealt with


Love lewisham benefits

Love Lewisham Benefits

Environmental issues are now far easier to report.

More staff report problems - fewer issues to irritate residents

Open resident/Member engagement

Our response is public and accountable


Practical partnerships

Practical Partnerships


Cross service collaboration

Cross-service collaboration


Love lewisham results

Love Lewisham Results

Dramatic improvement in the time taken to remove graffiti

From 2.78 days in 2003 (before ‘Love Lewisham’) to 0.50 days to complete now


Love lewisham results1

Love Lewisham Results

Reports of graffiti have fallen by about 30% this year.

Metres removed and the number of jobs has also fallen.

Less graffiti has been observed from our own monitoring, down from 18% (05/06) to 9.43% this year


Love lewisham results2

Love Lewisham Results

In the same period the number of graffiti removal jobs reported has trebled.

The resources to do the job stayed the same.


Love clean streets

Love Clean Streets

Building on Love Lewisham


Encams survey data live

EnCams Survey Data. Live


Blogging the borough

Blogging the Borough

SEND LINK

EMBED


Blogging the borough1

Blogging the Borough


Http lovelewisham wordpress com

http://lovelewisham.wordpress.com/


A clean sweep

Resident Satisfaction

Resident Satisfaction


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