Capital Ambition and LEDNET Street Services Productivity Review: detailed analysis March 2009.

Capital Ambition and LEDNET

Street Services Productivity Review: detailed analysis

March 2009

2

CONFIDENTIAL

Contents

• How to use this pack

• Context

• Objectives

• Methodology

• Street cleaning “diagnostics”

• Street cleaning blueprints

• Potential savings

• For participating Boroughs

• For Capital Ambition

A street cleaning

blueprint? Emerging findings

Introduction

Next steps

Overview of Street

Cleaning in London

• High-level comparison

• Value for Money overview

• Environmental factors influencing street cleaning performance

• Ease to serve and VfM performance

• Borough profiles

• Best practice summaries

• Supporting data

Appendix

3

CONFIDENTIAL

Introduction This pack has been designed to help local authorities to improve the value for money of their street cleaning services

How to use this pack

Contract manager

Head of Street Cleaning and/or Waste Management

Director of Environment Services

Chief Executive

If you are a…. You can use this pack to….

Review whether you are getting the best value from your contracted service, and whether specifying or monitoring differently might deliver better outcomes

Evaluate whether your operations are delivering value for money, and if they can be improved through using best practice approaches

Challenge your Head of Service, in a supportive way, to think about how they can improve the quality and cost-effectiveness of the service

Ask evidence-based questions of your street cleaning service, to ensure it is operating as efficiently and effectively as possible

4

CONFIDENTIAL

Introduction As one of the their most visible services, local authorities are under pressure to improve the quality of street cleaning services within an environment of reduced resources

Context

The street cleaning service

Visibility:

Street services is one of the most visible aspects of a Council’s business, and has a strong impact on customer satisfaction with the Council

Action:

Exploring the drivers of value for money services helps understand how resources can be deployed more effectively

Pressure:

Boroughs are under increasing pressure to improve quality of street cleaning services with reduced resources

How can we do more with less?

5

CONFIDENTIAL

Introduction

The aims of this project were:

To develop practical ideas to improve performance and efficiency in London boroughs’ street cleaning services

• To show what a “good Value for Money” street cleaning service might look like

Building a blueprint for value for money Street Cleaning services will help Boroughs across London target activity to reduce costs and improve performance

Objectives

We have developed emerging Street Cleaning Blueprints for different types of authorities which use these findings and

recommendations to show what a value for money Street Cleaning service might look

like

6

CONFIDENTIAL

Introduction The process we went through was designed to ensure that we gathered a solid evidence base of data

Methodology

Outcomes:Understand the main differences in expenditure and outputs in ten London boroughs.

Insight into the key factors driving the value for money position of Street Services in London.Discuss potential implications for other authorities in London and further activity for Capital Ambition.

Project Kick-offIntelligence gathering

Analysis ValidationFinal outputs and

presentation

Project Management

7

CONFIDENTIAL

Introduction Contrasting approaches were designed to test possible approaches to using comparison between boroughs to highlight improvements.

Methodology

High-level, qualitative analysisIn-depth, quantitative analysis

Street cleaning review

Recycling review

Approach

Time

Advantages

Limitations

• 22 days • 8 days

• High-level overview provides a useful snapshot of approaches and ideas for improvement

• More in-depth review of operations

• More specific findings and recommendations for use by authorities

• High level so may work may be required to explore issues in more detail

• In-depth nature may be more useful for Heads of Service than Directors and Chief Executives

8

CONFIDENTIAL

Introduction We have used this framework to assess the drivers of cost and performance of street cleaning service

Framework

Local Environment

Number of Town Centres Population density Population deprivation Km of road Condition of roads

People

Number of officers Structure of service Number of administrators Spans of control

Plant

Number of vehicles Types of vehicles Downtime of vehicles Manual / automatic split

Outputs

Tonnage of street sweeping arisings

Fly tipping incidents Fixed penalty notices

issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities

Approaches to litter prevention Extent of and approach to enforcement Deployment of cleaning resources Work with other services

Outcomes

Performance levels Customer satisfaction

9

CONFIDENTIAL

Introduction Though the data used in this report has some caveats, it is, in our judgement, still sufficiently robust to provide the basis for the key findings and recommendations

Notes on the data

Data source Notes

Public data: Best Value Performance Indicators, Revenue Account Return, National Statistics, Department for Transport

• Some differences and disputes in methodologies for collecting and assessing returns (e.g. population sizes, road lengths, BV 199a).

• However, the public data is broadly accurate enough to enable meaningful questions, implications and findings to be drawn.

Individual borough questionnaire responses

• Some minor variances occur in definitions of the questionnaire occur which does not always enable an exact like for like comparison.

• However, the data is more than comparable enough so as not to make the findings from the questionnaire benchmarking debateable.

10

CONFIDENTIAL

Contents


• Context

• Objectives

• Methodology






A street cleaning


Introduction

Next steps

Overview of Street

Cleaning in London







• Supporting data

Appendix

11

CONFIDENTIAL

Street cleaning in London High-level comparison

Source: London Councils website

The authorities involved in the review include 6 Outer London Boroughs and 4 Inner London Boroughs

Brent

Wandsworth

Waltham Forest

Croydon

Bromley

Tower Hamlets

Redbridge

Harrow

Lambeth

Southwark

12

CONFIDENTIAL

Inner/ Outer London Outer Outer

Outer

Outer Inner Outer Inner Inner Outer Inner

In-house? No No No Yes No Yes Yes No Yes No

Overall spend 07/08 £8.4m

£3.8m

£3.9m

£8.2m £3.6m £7.2m£6.03

m£4.7

m£5.02m

07/08 spend per km of road

£17.8k

£4.6k £9.8k £21.2k £7.4k £19.4k£12.2

k£10.4

k£12.2k

Street cleaning in London A wide range of boroughs were involved in the review. This pack contains analysis of seven boroughs from the current phase, and also includes the three original boroughs

High-level comparison

Source: RSe analysis of 2007/08 RA return and questionnaire response

Bre

nt

Cro

yd

on

Lam

beth

Red

bri

dg

e

Sou

thw

ark

Tow

er

Ham

lets

Wan

dsw

ort

h

Bro

mle

y

Harr

ow

Walt

ham

Fore

st

Please note: London Borough of Croydon was unable to provide all necessary data within the project timescales. This authority has been included in the analysis where possible, but there are some areas where data is missing for this council.

13

CONFIDENTIAL

Street cleaning in London The remit of “Street Cleaning” varies between Boroughs. Some are limited to street cleaning and fly tipping removal whereas others cover graffiti removal and enforcement.

High-level comparison

Source: RSe analysis of questionnaire responses

Graffiti removal No Yes No Yes Yes Yes Yes Yes Yes No

Fly posting removal

No Yes No Yes Yes Yes Yes Yes Yes No

Cleaning of bins

No Yes No Yes Yes Yes Yes Yes Yes Yes

Cleaning of other street furniture

No No No No Yes No No Yes No No

Highways Greensward - grass cutting

No No No Yes No No Yes No No No

Enforcement No No Yes Yes No Yes Yes No No No

Overall spend £8.4m£3.8m

£3.9m£8.2m

£3.6m £7.2m £6.0m £4.7m £5.0m

Spend per km of road

£17.8k

£4.6k £9.8k£21.2

k£7.4k £19.4k £12.2k £10.4k £12.2k

Bre

nt

Cro

yd

on

Lam

beth

Red

bri

dg

e

Sou

thw

ark

Tow

er

Ham

lets

Wan

dsw

ort

h

Bro

mle

y

Harr

ow

Walt

ham

Fore

st

The limited scope of the project has prevented us from isolating only the core street cleaning elements of activity and expenditure, however we believe the data enables a sufficiently “like for like” comparison to be made.

14

CONFIDENTIAL

Street cleaning in London Value for Money

There is a great deal of variance within London Street Cleaning outcomes and expenditure.

Sample London Borough spend on Street Cleaning & Litter Responsibilities varies from £2.7m to £17.5m.

Performance is equally variable, ranging from 2% to 40% of streets with unacceptable levels of litter and detritus.

Source: RSe analysis of 2007/08 RA return and 2006/07 BV 199a.

1 Kensington & Chelsea 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 02 Enfield 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 03 Sutton 8 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 04 Westminster 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 Bromley 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 06 Merton 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 07 Croydon 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 08 Redbridge 15 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 09 Barnet 16 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

10 Camden 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 011 Southwark 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 012 Wandsworth 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 013 Tower Hamlets 22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 014 Lewisham 24 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 015 Hammersmith & Fulham 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 016 Lambeth 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 017 Richmond Upon Thames 26 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 018 Hackney 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 019 Islington 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 020 Bexley 28 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 021 Newham 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 022 Brent 32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 023 Kingston Upon Thames 32 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 024 Waltham Forest 33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 025 Harrow 34 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 026 Ealing 35 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 027 Greenwich 35 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 028 Hillingdon 35 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 029 Hounslow 37 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 030 Barking & Dagenham 38 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 031 Havering 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 032 Haringey 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0

£2

,39

0

£2

,72

0

£3

,30

4

£3

,36

3

£4

,08

6

£4

,09

3

£4

,11

6

£4

,24

5

£4

,35

8

£4

,51

4

£4

,52

5

£4

,66

2

£4

,97

6

£4

,97

8

£5

,12

7

£5

,18

3

£5

,36

9

£5

,39

1

£5

,39

7

£5

,40

9

£6

,17

7

£6

,65

4

£7

,17

4

£7

,76

2

£8

,16

6

£8

,68

1

£8

,74

6

£1

0,0

19

£1

0,0

26

£1

0,4

86

£1

1,6

81

£1

7,5

95

1 2 3 4 5 6 7 8 9 # # # # # # # # # # # # # # # # # # # # # # #

Islin

gto

n

To

we

r H

am

lets

We

stm

inst

er

La

mb

eth

Bre

nt

Ne

wh

am

Ke

nsi

ng

ton

& C

he

lse

a

Ca

md

en

Ha

ckn

ey

Cro

ydo

n

So

uth

wa

rk

Le

wis

ha

m

Wa

ltha

m F

ore

st

Gre

en

wic

h

Su

tto

n

Ha

mm

ers

mith

& F

ulh

am

Bro

mle

y

Ha

rin

ge

y

Me

rto

n

Ba

rkin

g &

Da

ge

nh

am

Kin

gst

on

Up

on

Th

am

es

Ea

ling

Re

db

rid

ge

Ha

rro

w

Ho

un

slo

w

Ric

hm

on

d U

po

n T

ha

me

s

Hill

ing

do

n

Be

xle

y

Ba

rne

t

Ha

veri

ng

En

field

Wa

nd

swo

rth

Ra

nk o

f BV

19

9a

(from

top

)

Rank of Street Cleaning & Litter Responsibilities £'000 (from left)

15

CONFIDENTIAL

Street cleaning in London However, Value for Money analysis does not tell the whole story about cost and performance of Street Cleaning services

Value for Money

We have therefore developed a way of considering how easy to serve a Borough is, and how well Councils are performing (both in cost and performance terms) within this context.

Value for Money quadrant



£2

,39

0

£2

,72

0

£3

,30

4

£3

,36

3

£4

,08

6

£4

,09

3

£4

,11

6

£4

,24

5

£4

,35

8

£4

,51

4

£4

,52

5

£4

,66

2

£4

,97

6

£4

,97

8

£5

,12

7

£5

,18

3

£5

,36

9

£5

,39

1

£5

,39

7

£5

,40

9

£6

,17

7

£6

,65

4

£7

,17

4

£7

,76

2

£8

,16

6

£8

,68

1

£8

,74

6

£1

0,0

19

£1

0,0

26

£1

0,4

86

£1

1,6

81

£1

7,5

95

1 2 3 4 5 6 7 8 9 # # # # # # # # # # # # # # # # # # # # # # #

Islin

gto

n

To

we

r H

am

lets

We

stm

inst

er

La

mb

eth

Bre

nt

Ne

wh

am

Ke

nsi

ng

ton

& C

he

lse

a

Ca

md

en

Ha

ckn

ey

Cro

ydo

n

So

uth

wa

rk

Le

wis

ha

m

Wa

ltha

m F

ore

st

Gre

en

wic

h

Su

tto

n

Ha

mm

ers

mith

& F

ulh

am

Bro

mle

y

Ha

rin

ge

y

Me

rto

n

Ba

rkin

g &

Da

ge

nh

am

Kin

gst

on

Up

on

Th

am

es

Ea

ling

Re

db

rid

ge

Ha

rro

w

Ho

un

slo

w

Ric

hm

on

d U

po

n T

ha

me

s

Hill

ing

do

n

Be

xle

y

Ba

rne

t

Ha

veri

ng

En

field

Wa

nd

swo

rth

Ra

nk o

f BV

19

9a

(from

top

)


- BV199a performance

- Overall service spend

Contributing indicators:

Strengths:

- Provides a high level comparison of spend and performance

- Allows for straightforward comparison across London

Limitations:

- Does not reflect the different environments in which Councils work

- Provides a limited assessment of service performance Ease to Serve

Index

16

CONFIDENTIAL

Street cleaning in London There are several factors which are thought to shape the environment in which a street cleaning service operates

Environmental factors

Environmental factor Impact on street cleaning Used in index?

Deprivation of the population

Weak correlation between deprivation and street cleaning performance: more deprived areas are only slightly less likely to have clean streets

Density of the population

Correlation between density and street cleaning performance: Boroughs with a higher population density appear to have cleaner streets, but spend more per km of road to achieve this.

Condition of the local roads

Almost no correlation between street condition and street cleaning performance: Boroughs with roads in poor condition appear no less likely to have clean streets, but it is likely that their operations are designed to overcome this issue

Residents from other countries

Strong correlation between proportion of residents born outside the UK and street cleaning performance: Boroughs with a larger proportion of residents from other countries are more likely to have lower street cleaning performance, possibly due to different expectations about the roles of the Council and the citizen in maintaining street cleanliness

17

CONFIDENTIAL

Street cleaning in London We have calculated how easy to serve an area is and how well the Street Cleaning service is performing

Ease to serve

Value for Money quadrant



£2

,39

0

£2

,72

0

£3

,30

4

£3

,36

3

£4

,08

6

£4

,09

3

£4

,11

6

£4

,24

5

£4

,35

8

£4

,51

4

£4

,52

5

£4

,66

2

£4

,97

6

£4

,97

8

£5

,12

7

£5

,18

3

£5

,36

9

£5

,39

1

£5

,39

7

£5

,40

9

£6

,17

7

£6

,65

4

£7

,17

4

£7

,76

2

£8

,16

6

£8

,68

1

£8

,74

6

£1

0,0

19

£1

0,0

26

£1

0,4

86

£1

1,6

81

£1

7,5

95

1 2 3 4 5 6 7 8 9 # # # # # # # # # # # # # # # # # # # # # # #

Islin

gto

n

To

we

r H

am

lets

We

stm

inst

er

La

mb

eth

Bre

nt

Ne

wh

am

Ke

nsi

ng

ton

& C

he

lse

a

Ca

md

en

Ha

ckn

ey

Cro

ydo

n

So

uth

wa

rk

Le

wis

ha

m

Wa

ltha

m F

ore

st

Gre

en

wic

h

Su

tto

n

Ha

mm

ers

mith

& F

ulh

am

Bro

mle

y

Ha

rin

ge

y

Me

rto

n

Ba

rkin

g &

Da

ge

nh

am

Kin

gst

on

Up

on

Th

am

es

Ea

ling

Re

db

rid

ge

Ha

rro

w

Ho

un

slo

w

Ric

hm

on

d U

po

n T

ha

me

s

Hill

ing

do

n

Be

xle

y

Ba

rne

t

Ha

veri

ng

En

field

Wa

nd

swo

rth

Ra

nk o

f BV

19

9a

(from

top

)



- Overall service spend

Contributing indicators:

Strengths:

- Provides a high level comparison of spend and performance

- Allows for straightforward comparison across London

Limitations:

- Does not reflect the different environments in which Councils work

- Provides a limited assessment of service performance

Ease to serve index

RSe VfM performance vs ease to serve

Ease to serve

VfM

perf

orm

ance

Brent

Bromley

Croydon

Harrow

Lambeth

Redbridge

Southwark

Tower Hamlets

Waltham Forest

Wandsworth


- BV89 (Customer satisfaction)

- Spend per km of road

- Spend per tonne of arising

Contributing indicators – VfM performance:

Ease to serve:

- Level of population density

- % of population born outside the UK

Strengths:

- Provides context for each service

- Enables clear comparison between authorities in peer groups

- Highlights best practice services within each ease to serve category

Limitations:

- Cannot provide an exhaustive insight into performance and environment

- The environmental factors have been selected because of their relationship to performance

18

CONFIDENTIAL

Street cleaning in London Coupling this Ease to Serve index with VfM performance indicates that generally, the easier to serve an area is, the higher the VfM performance of the service will be. Some Boroughs are performing better than might be expected given their areas, whereas others are not performing as well as might be expected.

Ease to serve



Brent

Bromley

Croydon

Harrow

Lambeth

Redbridge

Southwark

Tower Hamlets

Waltham Forest

Wandsworth

Harder to serve

High VfM performanc

e

Easier to serve

Low VfM performanc

e

VfM Performance

Ease to serve

19

CONFIDENTIAL

Street cleaning in London This is a starting point for the Ease to Serve Index - in order to ensure it is as useful as possible, additional contributory indicators should be considered by London authorities

Ease to serve

Ease to serve index


Ease to serve

VfM

perf

orm

ance

Brent

Bromley

Croydon

Harrow

Lambeth

Redbridge

Southwark

Tower Hamlets

Waltham Forest

Wandsworth


- BV89 (Customer satisfaction)

- Spend per km of road

- Spend per tonne of arising

Contributing indicators – VfM performance:

Ease to serve:

- Level of population density

- % of population born outside the UK

Strengths:

- Provides context for each service

- Enables clear comparison between authorities in peer groups

- Highlights best practice services within each ease to serve category

Limitations:

- Cannot provide an exhaustive insight into performance and environment

- The environmental factors have been selected because of their relationship to performance

The Ease to Serve indicators were included due to their correlation with street cleaning performance (found in the previous phase of the project).

The following slides detail some of the other factors that could be considered when trying to improve the robustness of the index.

20

CONFIDENTIAL

Street cleaning in London Value for Money performance does not currently take into account the level of service each authority provides

Ease to serve

1. Assess appetite for the indicator’s inclusion

2. Identify the best way to reflect the issue

3. Collect more detailed cost breakdowns and frequency of service information

4. Include indicator in Index

Isolating cost data as required is likely to prove challenging, particularly for outsourced services.

Agreeing consistent definitions for frequency of service is crucial should this be factored into the index.

Authorities that have a thriving night-time economy are required to provide a night-time street cleaning service. This impacts on service expenditure but is not assessed as part of BV199a. As such, those authorities will be shown to be expensive but gain no VfM advantage for their extra service provision.

Isolating core, day-time spend from a service’s total budget would reflect relative expenditure more accurately.

Factoring required frequency of service into the environmental factors would also go some way to addressing the issue.

Why? Difficulties?

How?

Next Steps:

Proposed inclusion: An indicator that reflects the frequency of the service provided

21

CONFIDENTIAL

Street cleaning in London Environmental categorisation does not currently take into account the size of an authority’s day-time population

Ease to serve

1. Correlate daytime population figures against street cleaning performance

2. If there is a strong relationship then authorities should be ranked against this indicator and include it as part of the Ease to Serve index

This indicator should not replace population density. However, there is a danger that the index would be double-counting population levels if both were included as the authorities with high levels of population density are also likely to have a large day-time population.

An authority’s street cleaning workload is likely to be affected by the size of its day-time population. Some London authorities see a large day-time exodus out of the area, whilst others cater for large numbers of workers. The latter are likely to feel an impact on the cleanliness of their streets.

Daytime population figures can be taken from the Neighbourhood Statistics section of the ONS website. This could then be correlated against street cleaning performance in order to test its impact.

Why? Difficulties?

How?

Next Steps:

Proposed inclusion: An indicator that reflects the size of an authority’s day-time population

22

CONFIDENTIAL

Street cleaning in London Environmental categorisation does not currently take into account the number of major transport hubs located in each authority

Ease to serve

1. Agree definition of ‘major hub’

2. Correlate number of major hubs against street cleaning performance

3. Agree inclusion of indicator then authorities should be ranked against it and it be included as part of the Ease to Serve index

Entry & exit information is not available for bus stations.

Definitional problems are likely to arise as to what constitutes a ‘major hub’ e.g. are all tube stations included or just the busiest?

Major transport hubs have several implications for a street cleaning service, such as more people using the local streets and potentially littering. Accordingly, those authorities with a high number of major hubs face difficulties those without do not.

Locations of train/tube/bus stations are readily available from a number of sources. Tube station entry & exit information is available from the TfL website & rail information from the ORR website.

Why? Difficulties?

How?Next Steps:

Proposed inclusion: An indicator that reflects the number of major transport hubs within an authority’s area

23

CONFIDENTIAL

Street cleaning in London Environmental categorisation does not currently take into account the variation in road usage of each authority road network

Ease to serve

1. Agree definition of road types

2. Collate data from participating authorities

3. Correlate road type breakdown against street cleaning performance, rank authorities accordingly and include in Ease to Serve index

Department for Transport road type definitions does not provide enough detail to assess this indicator.

The usage of different roads affects the street cleaning requirement of those roads. Roads that have a primarily commercial use are likely to require greater frequency of cleaning and thus are at an environmental disadvantage.

Collecting a breakdown of road type/usage is best done through individual authorities, having agreed consistent definitions.

Why? Difficulties?

How?

Next Steps:

Proposed inclusion: An indicator that reflects the variation in road usage within an authority’s area

24

CONFIDENTIAL

Street cleaning in London The Ease to Serve index currently ranks authorities against each indicator, aggregates that rank and that score dictates an authority’s environmental ease to serve

Ease to serve

1. Agree the indicators to be included in the index

2. Correlate each indicator against street cleaning performance to provide the weighting

3. Rank authorities against each indicator and rank their aggregate, weighted score in order to finalise their position in the index

By weighting the indicators against their correlation to street cleaning performance, there is a danger that the index is self-referential.

The environmental factors have a varying impact on street cleaning performance: some are particularly important and some less so. The Ease to Serve index should therefore weight authorities’ rank against these indicators according to the degree of impact the factor has.

Each factor could be correlated against street cleaning performance in order to assess the impact of the factor. Authorities could then be ranked against the indicator and have that rank weighted by the correlation strength of the factor.

Why? Difficulties?

How?

Next Steps:

Proposed inclusion: To weight indicators due to the strength of correlation with street cleaning performance

25

CONFIDENTIAL

Street cleaning in London Data footnote

Although the performance data used relates to 2006/07, we are comfortable that it is still useful for this comparative exercise.

Source: RSe VfM analysis of 2005/06 and 2006/07 data

• We have carried out this analysis using BV199a performance data from 2006/07, as 2007/08 data was not available at the time of this review.

• Many boroughs are likely to have improved their street cleaning performance between 2006/07 and 2008

• The diagram on the right shows that the majority of London Boroughs have improved their BV199a performance from 05/06 to 06/07. We would expect this trend to continue for 2007/08 and as such the relative VfM positions of the sample authorities are unlikely to be substantially different in 2008.

Number of authorities that haveimproved performanceNumber of authorities that havemaintained performanceNumber of authorities that havedecreased performance

26

CONFIDENTIAL

Contents


• Context

• Objectives

• Methodology






A street cleaning


Introduction

Next steps

Overview of Street

Cleaning in London







• Supporting data

Appendix

27

CONFIDENTIAL

Emerging findings Blueprint process

We have developed “diagnostics” and “blueprints” to help build up a picture of a “good Value for Money” street cleaning service

Collect data

Carry out analysis

Develop diagnostic

s

Develop blueprints

What does a good Value for Money street cleaning service

look like?

28

CONFIDENTIAL

Emerging findings “Diagnostics”

We have developed “diagnostics” to provide an overview of the common characteristics of street cleaning services operating in different environments in London

23


A “hard to serve” and low performing Borough (e.g. Tower Hamlets) is likely to have the following characteristics. Tower Hamlets appears to be spending a lot on managers and vehicles but is not getting as much value (productivity) from them as higher performing authorities.


• Tonnage of arisings per km of road is lower in Tower Hamlets than any other authority – 9 tonnes vs an average of 24

• Number of litter bins per km of road is low (average is 2.9 vs 1.5 in Tower Hamlets)

• Number of recycling boxes/bags per km of road is lower than average (average is 195 per km vs 143 in Tower Hamlets)

• Spans of control are likely to be low (Tower Hamlets has 14 staff per manager vs an average of 20)

• Numbers of staff per km of road are in the middle range (0.4 staff per km of road – equals average)

• Have most managers per km of road (Tower Hamlets has 0.024 vs an average of 0.018)

• Frontline productivity is comparatively low – Tower Hamlets collects 26 tonnes per FTE

• No expenditure breakdown data was available for this authority

• Tower Hamlets has an outsourced service• Spend per km of road is average

• Tower Hamlets generates the fewest tonnes of arisings per vehicle of any of the authorities (117 tonnes)

• Tower Hamlets has a higher than average proportion of barrows (barrows account for 65% of Tower Hamlets fleet – the average is 60%)

• They have approximately average numbers of staff per mechanised vehicle (average is 4.3 staff per vehicle)

• The number of vehicles per km of road is high (0.23 for Tower Hamlets vs an average of 0.14)

• No cost per vehicle data was available for this authority

Expenditure People

Plant

Activities

The “diagnostics” slides show common characteristics for Expenditure, People, Plant and Activities across each ease to serve-performance category. These slides can be found in the detailed report.

You can use these

diagnostics to see how London

Boroughs are operating at

present

29

CONFIDENTIAL

Emerging findings The objectives of the two pieces of work were focused on producing outputs that would enable authorities to benchmark and improve their own performance

Street cleaning blueprints

• A suggestion for what a Value for Money street cleaning service would look like.

• A resource against which authorities can benchmark their own operations and performance.

• A first iteration, based on the diagnostics and available data.

What the ‘Blueprints’ are:

• A definitive direction as to how you must run and structure your street cleaning service.

• Static. It is likely that time will alter Value for Money best practice and the blueprints will evolve as more data becomes available.

What the ‘Blueprints’ are not:

30

CONFIDENTIAL

Emerging findings Street cleaning blueprints

A Value for Money service is likely to have the following expenditure characteristics, depending on the environment in which it operates.


• The service should have a low spend per km of road – targeting c.£5k per km is realistic – whilst only 50% of that budget needs be spent on staff

• Investing heavily in plant should provide quality vehicles and effective vehicle resilience

Easy to serve

• The street cleansing service should not under-spend but can expect to spend slightly below the average – c.£12k per km of road should suffice

• The service should spend c.65% of it’s budget on staff & 25% on plant

• Authorities will be required to spend a high amount per km of road – c.£20k – in order to properly fund the service

• A greater proportion of the spend will be required for people than in services in other environments – c.70%, with c.10% required for plant

Median to serve Hard to serve

Expenditure

31

CONFIDENTIAL


A Value for Money service is likely to have the following fleet characteristics, depending on the environment in which it operates.


• Over half of the service’s fleet should consist of mechanised sweepers, with far less reliance on barrows and tippers than services in other environments

• Accordingly, the spend per vehicle is likely to be above £25k

• The number of vehicles per 100km of road required is likely to be below 10

• No more than 2 FTEs per vehicle will be required in the service

Easy to serve

• A street cleaning service should use c.15 vehicles per 100km of road, reflecting a relatively high reliance upon mechanical sweepers – at least 30% of the fleet should be made up of mechanical sweepers

• The use of non-mechanical sweepers need not be high – no more than 25 barrows should be required

• Authorities should not spend on average more than c.£20k per vehicle

• The service should not employ more than 3 staff per vehicle

• The service will require a high number of vehicles per km of road – over 20 per 100km

• The fleet should contain c.2 mechanical sweepers per 100km of road

• No more than 50% of the fleet should be made up of barrows, whilst the staff to vehicle ratio should result in c.6 staff per vehicle

• On average, services should spend no more than £20k per vehicle


Plant

32

CONFIDENTIAL


A Value for Money service is likely to have the following staff characteristics, depending on the environment in which it operates.


• Spans of control will be low (below 12) as will the total number of staff required – 1 FTE per 10 km of road

• The numbers of managers required will also be low – 0.1 per 10km of road

• Due to the heavier reliance on mechanisation, it will be fair to expect that the average tonnage of arisings per frontline FTE will be high

Easy to serve

• Spans of control should be set at around 10-12 FTEs per manager

• The service should employ c.3 FTEs per 10km of road and c.0.21 managers per 10km of road

• With a relatively leanly staffed service, the average tonnage of arisings generated per FTE should be high – over 75 tonnes per FTE

• Spans of control should be relatively high – there should be between 25 & 30 FTEs per manager

• Numbers of staff per km of road should also be high – c.6 FTEs per 10km – as should numbers of managers - 0.22 managers per 10km

• Having productive front-line staff is key: services should look for their staff on average to generate over 75 tonnes of arisings per FTE


People

33

CONFIDENTIAL


A Value for Money service is likely to engage in the following activities, depending on the environment in which it operates.


• The tonnage of arisings a service collects per km of road will be below the London average

• The authority will not be required to provide a high number of litter bins per km of road – between 2 and 2.5 is likely to suffice – and should not expect to need to employ a high number of enforcement officers nor issue many FPNs

Easy to serve

• Collecting a high tonnage of arisings per km of road is important – services should look to outstrip the average and collect at least 25 tonnes per km of road

• Ensuring a high number of litter bins per km of road are in place is key – surpassing the average of 2.9 per km should be a minimum

• Enforcement does not seem to be as key for these authorities as it is for those in hard to serve areas – if it is adopted as a priority then it is important to employ a high number of officers issuing high numbers of FPNs

• Collecting a high tonnage of arisings is important for services within this environment – above average (24 tonnes per km of road) should be a minimum

• Effective enforcement policies are key. Services should employ a significant number of enforcement officers and aim to issue over 1,000 FPNs

• Alongside enforcement, services should ensure sufficient numbers of litter bins are provided – over 3.5 per km of road


Activities

34

CONFIDENTIAL

Emerging findings Best practice

During the course of the project we have discussed a number a best practice innovations that authorities currently undertake. This slide provides a snapshot of those whilst all the ideas can be found in the appendix.

Source: RSe interviews

Southwark currently issue the second highest number of Fixed Penalty Notices of any authority in the country. They tied this focus on enforcement with the installation of additional litter bins and adopted a ‘no grey areas’ approach to FPNs. The residents now know that if they drop litter it will cost them and professional fly tippers have been removed very quickly.

Lambeth monitors its staff productivity by requiring its staff to clean 550m2 per hour. This is a reduction from the previous target distance (800m2) and has led to a dramatic increase in street cleanliness.

Wandsworth has devised flexible contract terms in order to incentivise their contractors to improve performance. For example, the client team monitor complaints data and target the contractor to reduce these. If the contractor successfully reduces the number of complaints the service receives then Wandsworth rewards them financially.

Brent has increased its use of vehicles and has seen a measurable improvement in performance, particularly in industrial areas where detritus was previously a significant problem

Expenditure People

Plant

Activities

35

CONFIDENTIAL

Emerging findingsMany authorities consider outsourcing street cleaning to improve value for money. We have found no evidence to suggest that outsourcing will deliver a better VfM service

Street cleaning blueprints

Do in-house or outsourced services provide better value

for money street cleaning services?

• RSe’s VfM by environment ranking shows outsourced services to be both high (Bromley, Wandsworth), median (Croydon, Lambeth, Brent) and low performing (Tower Hamlets) and a similar pattern emerging for in-house services, with Southwark being high performing, Redbridge and Waltham Forest being median performing and Harrow low performing

• In-house services collect far more tonnes of arisings per km of road (29) than outsourced services (19) whilst at the same time spending less per km of road (£11.7k) than outsourced services (13.7k)

• Both in-house and outsourced services are likely to have c.0.34 FTEs per km of road, however, outsourced services have smaller spans of control (16 FTEs to managers) than in-house services (23) and lower spend per FTE (£25k per FTE in in-house services vs £24k in outsourced services – a saving of c.£150k per authority)

• Tonnage of arisings per FTE does not vary much between the two types of service (c.63 tonnes per FTE) but tonnage of arisings per vehicle does (324 tonnes per vehicle in in-house services vs 210 in outsourced services)

• Spend per vehicle shows no variation at all between the two types of service

36

CONFIDENTIAL

Emerging findingsThe findings from this review can be used to help assess the potential scope for efficiency savings in Street Cleaning services

Potential savings

• Realising efficiency savings is a key priority for the majority of local authorities - Boroughs can help identify areas for cost reduction by comparing their services against the blueprints in this pack

• We can also identify – at a high level – the Boroughs where there might be scope for reducing costs by comparing expenditure against average expenditure

• The following slide shows the potential value of savings that could be achieved if Boroughs spending above average for their “Ease to Serve” category were to reduce their costs to the average level for that category

• Authorities should note that this expenditure will not guarantee the highest level of performance but represents an acceptable level of funding with which to operate.

37

CONFIDENTIAL

Emerging findingsAnalysis indicates that if Boroughs spending above average for their “Ease to Serve” category reduced spend to the average level, approximately £2.8m could be saved

Potential savings

Current cost:

• How much is currently spent by the 10 London Boroughs reviewed on Street Cleaning in total?

Average cost:

• What is the average expenditure for each Ease to Serve category?

Potential saving:

• How many authorities currently spend more than the average for their Ease to Serve category?

Value of saving:

• How much could be saved across the 10 authorities if expenditure was brought down to the average level?

Approximately £51m p.a.

“Easy to serve”: £3.8m

“Median to serve”: £4.3m

“Hard to serve”: £7.5m

4 authorities:• Brent• Lambeth• Waltham

Forest• Wandsworth

Approximately £2.8m could be saved (equating to ~10% of each of these authorities’ Street Cleaning budget)

38

CONFIDENTIAL

Emerging findingsThe table below shows the potential savings that could be achieved if each authority reduced their expenditure in line with the average expenditure for their environment.

Potential savings

Ease to serve

Authority Current spend per

km

Average spend per km of road across

the category

Potential saving per km

of road

“Easy to serve”

Bromley £4,578£4,578

N/A

Croydon Unknown Unknown

“Median to serve”

Harrow £9,750

£9,843

-£93

Waltham Forest

£10,444 £602

Redbridge £7,370 -£2,472

Wandsworth £12,162 £2,319

“Hard to serve”

Southwark £19,423

£17,629

£1,794

Lambeth £21,247 £4,361

Brent £17,798 £169

Tower Hamlets

£12,745 -£4,884

39

CONFIDENTIAL

Contents


• Context

• Objectives

• Methodology






A street cleaning


Introduction

Next steps

Overview of Street

Cleaning in London







• Supporting data

Appendix

40

CONFIDENTIAL

Next steps

• Identify whether your authority operates in a “hard”, “median” or “easy to serve” environment

• Compare your expenditure, staff, plant and activities to the “Blueprint” for that environment

• Identify the changes you could make to your service to improve your VfM performance using the “blueprint”

Local authorities We recommend that local authorities take the following steps to make use of the findings from our report

Practical best-practice innovations are detailed in

the report - these might stimulate service

improvement ideas

41

CONFIDENTIAL

Next steps

• Disseminate this pack to Heads of Street Cleaning Services across London

• Encourage its use as a benchmarking tool

• Consider collecting cost and activity data from all Boroughs to carry out a pan-London benchmarking exercise

• Follow up with authorities in 6 months to find out how they have used the findings

Capital Ambition and LEDNET We recommend that Capital Ambition and LEDNET take the following steps to

make use of the findings from this report

42

CONFIDENTIAL

Contact details

Ben [email protected]

020 7808 1122

Olivia [email protected]

0207 808 1156

Andrew [email protected]

0207 808 1146

43

CONFIDENTIAL

Contents


• Context

• Objectives

• Methodology






A street cleaning


Introduction

Next steps

Overview of Street

Cleaning in London







• Supporting data

Appendix

44

CONFIDENTIAL

Appendix

Borough profiles

45

CONFIDENTIAL

Appendix

Brent

Population 271,400

Area 43km2

Population density 6,278 persons /km2

Km of road 472km

Annual tonnage of arisings 10,884

BV 199a score 32.0

BV 199b score 20

BV 199c score 3

BV 199d score 3

BV89 score 65

The boroughs involved each operate within a distinctive local environment

Borough profile: Brent

Source: Questionnaire response, ONS Census data, 2007/08 BV scores

46

CONFIDENTIAL

Appendix The boroughs involved each operate within a distinctive local environment

Bromley

Population 299,100

Area 150km2


Km of road 830km


BV 199a score 12.5

BV 199b score 4

BV 199c score 1

BV 199d score 3

BV89 score 67


Borough profile: Bromley

47

CONFIDENTIAL

Appendix

Croydon

Population 337,000

Area 87km2


Km of road km

Annual tonnage of arisings

BV 199a score 14.4

BV 199b score 2

BV 199c score 0

BV 199d score 2

BV89 score 61



Borough profile: Croydon

48

CONFIDENTIAL


Harrow

Population 214,600

Area 50km2

Population density 4292 persons /km2

Km of road 400km


BV 199a score 34

BV 199b score 8

BV 199c score 1

BV 199d score 3

BV89 score 56


Borough profile: Harrow

49

CONFIDENTIAL

Appendix

Lambeth

Population 272,000

Area 27km2


Km of road 385km

Annual tonnage of arisings Unknown

BV 199a score 25.0

BV 199b score 6

BV 199c score 1

BV 199d score 3

BV89 score 67



Borough profile: Lambeth

50

CONFIDENTIAL


Redbridge

Population 251,900

Area 56km2


Km of road 482km


BV 199a score 14.8

BV 199b score 19

BV 199c score 2

BV 199d score 4

BV89 score 59


Borough profile: Redbridge

51

CONFIDENTIAL

Appendix

Southwark

Population 269,200

Area 29km2


Km of road 370km


BV 199a score 19.2

BV 199b score 3

BV 199c score 2

BV 199d score 1

BV89 score 70



Borough profile: Southwark

52

CONFIDENTIAL


Tower Hamlets

Population 212,800

Area 20km2


Km of road 496km


BV 199a score 22.4

BV 199b score 13

BV 199c score 6

BV 199d score 4

BV89 score 60


Borough profile: Tower Hamlets

53

CONFIDENTIAL

Appendix

Waltham Forest

Population 221,700

Area 39km2


Km of road 450km


BV 199a score 33

BV 199b score 16

BV 199c score 3

BV 199d score 3

BV89 score 61



Borough profile: Waltham Forest

54

CONFIDENTIAL


Wandsworth

Population 279,000

Area 34km2


Km of road 413km


BV 199a score 22.0

BV 199b score 1

BV 199c score 6

BV 199d score 1

BV89 score 74


Borough profile: Wandsworth

55

CONFIDENTIAL

Appendix

Diagnostics

56

CONFIDENTIAL


A “hard to serve” and low performing Borough (e.g. Tower Hamlets) is likely to have the following characteristics. Tower Hamlets appears to be spending a lot on managers and vehicles but is not getting as much value (productivity) from them as higher performing authorities.


• Tonnage of arisings per km of road is lower in Tower Hamlets than any other authority – 9 tonnes vs an average of 24

• Number of litter bins per km of road is low (average is 2.9 vs 1.5 in Tower Hamlets)

• Number of recycling boxes/bags per km of road is lower than average (average is 195 per km vs 143 in Tower Hamlets)

• Spans of control are likely to be low (Tower Hamlets has 14 staff per manager vs an average of 20)

• Numbers of staff per km of road are in the middle range (0.4 staff per km of road – equals average)

• Have most managers per km of road (Tower Hamlets has 0.024 vs an average of 0.018)

• Frontline productivity is comparatively low – Tower Hamlets collects 26 tonnes per FTE

• No expenditure breakdown data was available for this authority

• Tower Hamlets has an outsourced service• Spend per km of road is average

• Tower Hamlets generates the fewest tonnes of arisings per vehicle of any of the authorities (117 tonnes)

• Tower Hamlets has a higher than average proportion of barrows (barrows account for 65% of Tower Hamlets fleet – the average is 60%)

• They have approximately average numbers of staff per mechanised vehicle (average is 4.3 staff per vehicle)

• The number of vehicles per km of road is high (0.23 for Tower Hamlets vs an average of 0.14)

• No cost per vehicle data was available for this authority

Expenditure People

Plant

Activities

57

CONFIDENTIAL


A “hard to serve” and median performing Borough (e.g. Brent, Lambeth and Southwark) is likely to have the following characteristics. Southwark and Lambeth spend more on frontline staff and vehicles than on management, and is reflected in their productivity.


• Tonnage of arisings are likely to be higher in this group – Southwark generate the most and Brent the third most

• The number of litter bins per km of road varies – Southwark has above average numbers whilst Brent and Lambeth have below average numbers of bins

• The number of FPNs issued varies greatly – Southwark issue 1,796; Lambeth issue 226 and Brent issue none despite Southwark and Brent employing similar numbers of enforcement staff

• Southwark & Lambeth have two of the highest spans of control, whilst Brent’s is below average

• Staff numbers per km of road are likely to be on (Brent 0.4) or above (Lambeth 0.6; Southwark 0.7) average

• Have above average numbers of managers per km of road – Brent has 0.03; Lambeth 0.023 and Southwark 0.022 vs an average of 0.018

• Have vastly varied frontline FTE productivity – Brent staff generate 60 tonnes of arisings per FTE compared to 119 in Southwark

• Brent and Lambeth are outsourced services whilst Southwark is in-house – all spend c.£8m p.a.

• Authorities in this peer group spend more per km of road than any other group (c.£19k per km)

• ~70% of budget spent on staff and ~10% on plant

• Authorities are likely to have 35 – 50 mechanical vehicles at a cost of c.£21k per vehicle

• The split between mechanical vehicles and barrows varies – 53% of Southwark’s fleet are barrows compared to 71% of Brent’s and 74% of Lambeth’s fleet

• These Boroughs have higher numbers of staff per vehicle (Lambeth has 7 staff per vehicle, Southwark 6 & Brent 4 vs an average of 4)

• Above average number of vehicles per km of road – Brent, Lambeth (both 0.36) & Southwark (0.23) all have above average (0.15) number of vehicles

Expenditure People

Plant

Activities

58

CONFIDENTIAL


A “median to serve” and low performing Borough (e.g. Harrow) is likely to have the following characteristics. Harrow appears to be investing less in its service than other authorities – its staff numbers also appear lower than expected yet are not counterbalanced with mechanised vehicles.


• Harrow’s tonnage of arisings per km of road (10) is low compared to the wider average (24)

• Harrow has a fairly average number of litter bins per km of road – 2.5 compared to 2.9 across the authorities

• Harrow has considerably more missed recycling & refuse collections per month than any other authority

• Harrow’s spans of control is only slightly below the average across the authorities – 18 staff per manager in Harrow vs an average of 20

• Staff numbers per km of road in Harrow (0.2) are below the average (0.4) and comparable to those in Redbridge and Bromley

• The numbers of managers per km of road in Harrow (0.013) are below average (0.018)

• Harrow’s frontline FTEs collect the second lowest tonnes of arisings per FTE (45) of any of the authorities studied

• Harrow is an in-house service spending a very low amount in overall terms (£3.9m) and per km of road (£10k)

• 65% of Harrow’s budget is spent on staff and 25% on plant

• Harrow has the lowest number of vehicles (22), but each vehicle proves very expensive c.£40k

• Harrow has the same number of staff per vehicle as the average across the authorities studied – 4 staff per vehicle

• Harrow has very low numbers of vehicles per km of road – 0.06 vs an average of 0.16

• 73% of Harrow’s vehicle fleet is made up of Tipper/Collection vehicles, more than any other authority

Expenditure People

Plant

Activities

59

CONFIDENTIAL


A “median to serve” and median performing Borough (e.g. Redbridge and Waltham Forest) is likely to have the following characteristics. They use a relatively low proportion of mechanised vehicles and staff numbers per km of road are also comparatively low.


• The authorities are likely to generate below average tonnage of arisings per km of road (Redbridge generate 10 tonnes and Waltham Forest 20 vs an average of 24)

• Both authorities have fewer litter bins per km of road (Redbridge has 2.6; Waltham Forest 1.6) than the average across the wider study (2.9)

• The authorities issued varying numbers of FPNs – Waltham Forest issued 12 whilst Redbridge issued 381

• Spans of control vary across this group, with Redbridge having 14 staff per manager and Waltham Forest having 32 – higher than any other authority

• Waltham Forest have an average number of staff per km of road (0.4) whereas Redbridge have below average (0.2) – both authorities have fewer managers per km of road than the average

• The frontline staff in these types of authorities are likely to generate c.55 tonnes of arisings per FTE

• Both authorities run street cleaning in-house and have below average overall spend and spend per km of road

• Likely to spend c.80% of their budget on staff costs and 15% on plant

• There is a wide variation in numbers of vehicles used (30 in Waltham Forest & 81 in Redbridge) and the number of vehicles per km of road (0.07 in Waltham Forest & 0.17 in Redbridge)

• Waltham Forest has more staff per vehicle (6) than average (4) whilst Redbridge has less (3)

• Redbridge has a low spend per vehicle (c.£14k) whereas Waltham Forest’s (c.£23k) is slightly below the average (c.£24k)

• Around 20% of these authorities’ fleets are likely to be made up of mechanical sweepers

Expenditure People

Plant

Activities

60

CONFIDENTIAL


A “median to serve” and high performing Borough (e.g. Wandsworth) is likely to have the following characteristics. Wandsworth makes more use of mechanical sweepers than other “median to serve” Boroughs. They also invest heavily in strong management.


• Wandsworth collects the second highest tonnage of arisings per km of road – 32 tonnnes per km compared to 75 in Southwark and an average of 24

• Similarly, they have the second highest number of litter bins per km of road – 3.4 bins per km compared to 7.6 in Southwark and an average of2.9

• Wandsworth employs relatively few enforcement officers (8) who issue a low number of FPNs (123)

• Wandsworth has the lowest spans of control – the service has just over seven staff per manager

• The number of staff Wandsworth employ per km of road (0.3) is slightly below the average (0.4), whereas the number of managers per km of road (0.036) is the highest of any of the Boroughs

• Wandsworth’s tonnage of arisings per frontline FTE are very high (132), second only to Bromley’s (148) and closely comparable to Southwark’s (119)

• Wandsworth contracts its street cleansing service to Connaught, spending (c.£5m) slightly less than the average across the authorities (c.£5.7m)

• 65% of Wandsworth’s budget is spent on staff and 25% on plant• Wandsworth is broadly in line with the total number of vehicles used on average (c.70) and the number of vehicles per km of road (c.0.15)

• Despite this, other than Bromley, Wandsworth has the fewest number of staff per vehicle of any of the authorities (2 staff per vehicle)

• On average, Wandsworth’s vehicles cost them less (c.£18k) than the wider average (c.£24k)

• Mechanical sweepers make up more of Wandsworth’s fleet than is common across the other authorities & they use fewer non-mechanical sweepers than any other authority

Expenditure People

Plant

Activities

61

CONFIDENTIAL


An “easy to serve” and high performing Borough (e.g. Bromley) is likely to have the following characteristics. Bromley’s high use of mechanical sweepers is suited to its local area. It also invests heavily in strong management.


• The tonnage of arisings Bromley collects per km of road is low – 13 tonnes per km vs an average of 24

• The number of litter bins per km of road in Bromley (2.3) is slightly below the average (2.9)

• Bromley employ fewer enforcement officers (3) than any other authority and issue a low number of FPNs (45)

• Bromley’s spans of control (9 staff per manager) are lower than any other authority’s and more than half the amount of the average (20)

• The number of staff Bromley employ per km of road (0.1) & the number of managers they employ per km of road (0.01) are fewer than any other authority

• The average tonnage of arising per frontline FTE is accordingly higher (148) than any of the other authorities and considerably above the average (78)

• Bromley runs an in-house street cleansing service which costs less than any of the services studied, particularly by spend per km of road (c.£5k)

• 50% of Bromley’s spend is on staff, whilst 30% is on plant

• Bromley has a below average number of vehicles (43 vs 72) & the lowest number of vehicles per km of road – 0.05

• Bromley has the fewest number of staff per vehicle – 1.9 vs an average of 4.3

• Bromley seem to use the most expensive vehicles – its average spend per vehicle is c.£28k vs an average of £24k

• Bromley’s fleet is made up of a higher proportion of mechanical sweepers than any of the other Boroughs

Expenditure People

Plant

Activities

62

CONFIDENTIAL

Appendix

Blueprints

63

CONFIDENTIAL


A Value for Money service in an “easy to serve” area is likely to have the following characteristics. It is likely to spend a smaller proportion of its budget on staff, and will use more mechanised vehicles.


• The tonnage of arisings a service collects per km of road will naturally be below the London average

• The authority will not be required to provide a high number of litter bins per km of road – between 2 and 2.5 is likely to suffice – and should not expect to need to employ a high number of enforcement officers nor issue many FPNs

• Spans of control will be low (below 12) as will the total number of staff required – 0.1 FTE per km of road

• The numbers of managers required will also be low – 0.01 per km of road

• Due to the heavier reliance on mechanisation, it will be fair to expect that the average tonnage of arisings per frontline FTE will be high

• The service should have a low spend per km of road – targeting c.£5k per km is realistic – whilst only 50% of that budget needs be spent on staff

• Investing heavily in plant should provide quality vehicles and effective vehicle resilience

• Over half of the service’s fleet should consist of mechanised sweepers, with far less reliance on barrows and tippers than services in other environments

• Accordingly, the spend per vehicle is likely to be above £25k

• The number of vehicles per km of road required is likely to be below 0.1

• No more than 2 FTEs per vehicle will be required in the service

Expenditure People

Plant

Activities

64

CONFIDENTIAL


A Value for Money service in a “median to serve” area is likely to have the following characteristics. It is likely to invest more in staff but approximately a third of its fleet should still be comprised of mechanised vehicles.


• Collecting a high tonnage of arisings per km of road is important – services should look to outstrip the average and collect at least 25 tonnes per km of road

• Ensuring a high number of litter bins per km of road are in place is key – surpassing the average of 2.9 per km should be a minimum

• Enforcement does not seem to be as key for these authorities as it is for those in hard to serve areas – if it is adopted as a priority then it is important to employ a high number of officers issuing high numbers of FPNs

• Spans of control should be set at around 10-12 FTEs per manager

• The service should employ c.0.3 FTEs per km of road and c.0.021 managers per km of road

• With a relatively leanly staffed service, the average tonnage of arisings generated per FTE should be high – over 75 tonnes per FTE

• The street cleansing service should not under-spend but can expect to spend slightly below the average – c.£12k per km of road should suffice

• The service should spend c.65% of it’s budget on staff & 25% on plant

• A street cleaning service should use c.0.15 vehicles per km of road, reflecting a relatively high reliance upon mechanical sweepers – at least 30% of the fleet should be made up of mechanical sweepers

• The use of non-mechanical sweepers need not be high – no more than 25 barrows should be required

• Authorities should not spend on average more than c.£20k per vehicle

• The service should not employ more than 3 staff per vehicle

Expenditure People

Plant

Activities

65

CONFIDENTIAL


A Value for Money service in a “hard to serve” area is likely to have the following characteristics. It is likely to have much higher staff numbers and an effective use of enforcement resources.


• Collecting a high tonnage of arisings is important for services within this environment – above average (24 tonnes per km of road) should be a minimum

• Effective enforcement policies are key. Services should employ a significant number of enforcement officers and aim to issue over 1,000 FPNs

• Alongside enforcement, services should ensure sufficient numbers of litter bins are provided – over 3.5 per km of road

• Spans of control should be relatively high – there should be between 25 & 30 FTEs per manager

• Numbers of staff per km of road should also be high – c.0.6 FTEs per km – as should numbers of managers - 0.022 managers per km

• Having productive front-line staff is key: services should look for their staff on average to generate over 75 tonnes of arisings per FTE

• Authorities will be required to spend a high amount per km of road – c.£20k – in order to properly fund the service

• A greater proportion of the spend will be required for people than in services in other environments – c.70%, with c.10% required for plant

• The service will require a high number of vehicles per km of road – over 0.2 per km

• The fleet should contain c.0.02 mechanical sweepers per km of road

• No more than 50% of the fleet should be made up of barrows, whilst the staff to vehicle ratio should result in c.6 staff per vehicle

• On average, services should spend no more than £20k per vehicle

Expenditure People

Plant

Activities

66

CONFIDENTIAL

Appendix

Best practice summari

es

67

CONFIDENTIAL

Appendix Best practice summaries

• Wandsworth have devised flexible contract terms in order to incentivise their contractors to improve performance. For example, the client team monitor complaints data and target the contractor to reduce these. If the contractor successfully reduces the number of complaints the service receives then Wandsworth rewards them financially.

• In 2003 Southwark’s street cleaning service was brought in-house. The department were told how much was available to spend and the service was designed from scratch at that point. There is a great deal of flexibility in the way the budget is split, allowing for and rewarding innovation on a yearly basis.

• Several authorities are very specific about how the contract should be delivered. Brent requested a move away from litter picking to street sweeping; Lambeth re-balanced their contract to provide a more continuous cleaning presence; Wandsworth specifies how often each street in the Borough should be cleaned and on which days

Expenditure


68

CONFIDENTIAL


• Southwark had poor detritus performance relative to its litter score. As a result they split the litter picking and detritus sweeping duties so that each FTE had a dedicated duty and that each road was both litter picked and detritus swept. Not only did this greatly improve the Borough’s detritus score, it also freed up resource that could be re-invested in increasing the number of supervisors the service employed.

• Lambeth monitors its staff productivity by requiring its staff to clean 550m2 per hour. This is a reduction from the previous target distance (800m2) and has led to a dramatic increase in street cleanliness

• Redbridge focuses heavily on staff development. For example, it has a “Golden Broom” award to reward street cleaning staff for good performance

People


69

CONFIDENTIAL


• One of the key stipulations in Wandsworth’s contract specification is that a new fleet is formed at the start of the contract period, made up entirely of brand new vehicles.

• Brent has increased its use of vehicles and has seen a measurable improvement in performance, particularly in industrial areas where detritus was previously a significant problem

Plant


70

CONFIDENTIAL


• Wandsworth employs a large client team that exhaustively monitors contractor performance

• Southwark currently issue the second highest number of Fixed Penalty Notices of any authority in the country. They tied this focus on enforcement with the installation of additional litter bins and adopted a ‘no grey areas’ approach to FPNs. The residents now know that if they drop litter it will cost them and professional fly tippers have been removed very quickly.

• Redbridge structures its service around its 7 area committee areas. A good relationship is built up with each area committee, so that street cleaning activity is tailored to specific needs in each area

Activities


71

CONFIDENTIAL

Appendix

Supporting data

72

CONFIDENTIAL

Appendix The following section contains supporting data to support the “diagnostics” and blueprints in each of the following areas

Supporting data

Local Environment


People


Plant


Outputs



issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities


Outcomes


73

CONFIDENTIAL

A street cleaning blueprint?There is a weak correlation between a borough’s deprivation index score and the cleanliness of its streets. However the most deprived borough in London has an equivalent level of cleanliness to the least deprived.

Environment

Source: 2007 Index of Deprivation average score (CLG); 2006/07 BVPI return; RSe analysis

Correlation between 2007 Index of Deprivation score and street cleanliness (BVPI 199a 2006/ 07)

0

5

10

15

20

25

30

35

40

0 10 20 30 40 50

2007 Index of Deprivation Average Score

BV

199a -

% o

f st

reets

wit

h

unacc

epta

ble

levels

of

litt

er

and

detr

itus

Brent

Bromley

Croydon

Harrow

Lambeth

Redbridge

Southwark

Tower Hamlets

Waltham Forest

Wandsworth

74

CONFIDENTIAL

A street cleaning blueprint?There is a weak correlation between population density and street cleanliness. Boroughs with a higher population density appear to have cleaner streets, but spend more per km of road to achieve this.

Environment

Source: 2006/07 BVPI return; ONS; RSe analysis

Correlation between population density and BV199a

0

5

10

15

20

25

30

35

40

0 2000 4000 6000 8000 10000 12000

Population density (based on 2006 mid year estimate population)

% o

f st

reets

wit

h u

nacc

epta

ble

leve

ls o

f litt

er

and d

etr

itus

Brent

BromleyCroydon

HarrowLambeth

RedbridgeSouthwarkTower Hamlets

Waltham ForestWandsworth

75

CONFIDENTIAL

A street cleaning blueprint?Unclassified road condition also has only a weak correlation to street cleanliness, with significant variance between boroughs above and below the trend line. If two outlying boroughs are removed, there is no correlation at all.

Environment

Source: 2006/07 BVPI return; RSe analysis

Correlation between condition of unclassified roads (BVPI 224b) and street cleanliness (BVPI 199a)

0

5

10

15

20

25

30

35

40

0 5 10 15 20BVPI 224b - % of the unclassified road network where structural

maintenance should be considered

% o

f st

reets

wit

h u

nacc

epta

ble

leve

ls

of lit

ter

and d

etr

itus

Brent

Bromley

Croydon

Harrow

Lambeth

Redbridge

Southwark

Tower Hamlets

WalthamForestWandsworth

76

CONFIDENTIAL

A street cleaning blueprint? There is a strong correlation between proportion of residents not born in the UK and BV199a performance, though Waltham Forest and Redbridge have similar proportions of non UK-born residents but very different BV199a scores, indicating it is not a limiting factor

Environment

Source: ONS Census data, 2007/08 BV199a

Correlation between residents who were born outside the UK and BV 199a

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

0% 10% 20% 30% 40% 50%

% of residents who were born outside the UK

BV199a -

% o

f st

reets

wit

h u

nacc

epta

ble

le

vels

of litt

er

and d

etr

itus

BrentBromleyCroydonHarrowLambethRedbridgeSouthwarkTower HamletsWaltham ForestWandsworth

77

CONFIDENTIAL

Appendix Supporting data

Local Environment


People


Plant


Outputs



issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities


Outcomes


78

CONFIDENTIAL

A street cleaning blueprint? Spend

Street cleaning spend per km of road

0

5,000

10,000

15,000

20,000

25,000

0.0 3.3 6.6 9.9

Ease to serve

Spend p

er

km

of ro

ad (

£)

Boroughs need to spend differing amounts per km of road depending upon how difficult to serve their environment is. Within each peer group it is not the authorities spending least per km of road that are delivering best value for money

79

CONFIDENTIAL

A street cleaning blueprint? Spend

Although staff is always the biggest area of spend, the proportion of budget spent on staff and plant varies across the group

Street cleaning service budget split

0% 20% 40% 60% 80% 100%

Bromley

Redbridge

Waltham Forest

Harrow

Wandsworth

Southwark

Lambeth

% of budget spent

% of budgetspent on staff

% of budgetspent onplant% of budgetspent on'other'

Ease to serve

High

Low

80

CONFIDENTIAL


Local Environment


People


Plant


Outputs



issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities


Outcomes


81

CONFIDENTIAL

A street cleaning blueprint? PeopleAs Boroughs become more difficult to serve, they are likely to need more staff and as such, wider spans of control. Currently some large variations exist amongst peer groups

Street cleaning spans of control

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of FT

Es

per

manager

BromleyRedbridgeWaltham ForestHarrowWandsworthSouthwarkLambethBrentTower Hamlets

82

CONFIDENTIAL

A street cleaning blueprint? People

Boroughs that are harder to serve require greater numbers of staff per km of road than those Boroughs that are easier to serve…

Street cleaning staff per km of road

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of st

aff

per

km

of ro

ad

BromleyRedbridge

Waltham ForestHarrow

WandsworthSouthwark

LambethBrentTower Hamlets

83

CONFIDENTIAL

A street cleaning blueprint? People

…and they also require also require more managers per km of road

Street cleaning managers per km of road

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of m

anagers

per

km

of ro

ad


84

CONFIDENTIAL

A street cleaning blueprint? PeopleThe top performing Boroughs, irrespective of the environment in which they serve, collect more tonnes of arisings per frontline FTE, indicating greater productivity.

Street cleaning frontline FTE productivity

0

20

40

60

80

100

120

140

160

0.0 3.3 6.6 9.9

Ease to serve

Avera

ge t

onnes

of ari

sing p

er

frontl

ine F

TE

BromleyRedbridge


WandsworthSouthwark


85

CONFIDENTIAL


Local Environment


People


Plant


Outputs



issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities


Outcomes


86

CONFIDENTIAL

A street cleaning blueprint? PlantAs was the case with staff, Boroughs that are harder to serve require more vehicles per km of road. It seems that some of the Boroughs we reviewed have too many vehicles per km of road, whilst some have too few given their local environment

Street cleaning vehicles per km of road

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of ve

hic

les

per

km

of ro

ad


87

CONFIDENTIAL

A street cleaning blueprint? PlantThis graph again indicates the importance of local environment when considering the make-up of your street cleaning service: the harder your area to serve, the greater reliance you will need on staff

Ratio of street cleaning staff to vehicles

0

1

2

3

4

5

6

7

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of st

aff

per

vehic

le Bromley

Redbridge

Waltham Forest

Harrow

Wandsworth

Southwark

Lambeth

Brent

Tower Hamlets

88

CONFIDENTIAL

A street cleaning blueprint? PlantWhilst some variation in vehicle spend can be explained by understanding the different types of vehicles authorities use, it is clear that some authorities are spending far more on their vehicles than they need be

Cost of street cleaning vehicles

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

0.0 3.3 6.6 9.9

Ease to serve

Spend p

er

vehic

le (

£) Bromley

Redbridge

Waltham Forest

Harrow

Wandsworth

Southwark

Lambeth

Brent

Tower Hamlets

89

CONFIDENTIAL

A street cleaning blueprint? Plant

The top performing Boroughs of those studied all have smaller proportions of non-mechanical sweepers than those authorities performing less well

Breakdown of Fleet

0% 20% 40% 60% 80% 100%

Bromley

Redbridge

Waltham Forest

Harrow

Wandsworth

Southwark

Lambeth

Brent

Tower Hamlets

% of Fleet

% mechanicalsweepers

% non-mechanicalsweepers

% other (inc.Tippers)

90

CONFIDENTIAL

A street cleaning blueprint? PlantThere appears to be almost no correlation between the proportion of mechanised vehicles used and BV199a performance. This suggests that the optimum level of mechanisation is dependent on the local environment of the Borough.

Correlation between reliance on mechanised sweepers and BV199a

0

5

10

15

20

25

30

35

40

0% 10% 20% 30% 40% 50% 60% 70%

Proportion of fleet that are mechanised sweepers

BV199a -

% o

f st

reets

wit

h u

nacc

epta

ble

le

vels

of litt

er

and d

etr

itus

BrentBromley

HarrowLambeth

RedbridgeSouthwark

Tower HamletsWaltham ForestWandsworth

91

CONFIDENTIAL


Local Environment


People


Plant


Outputs



issued

Context

Inputs & Structure

Outputs & Outcomes

Service Spend

Activities


Outcomes


92

CONFIDENTIAL

A street cleaning blueprint? Activities

In each ease to serve category, the top-performing Borough is that which is collecting the greatest tonnage of arisings per km of road…

Tonnage of arisings per km of road

0

10

20

30

40

50

60

70

80

0.0 3.3 6.6 9.9

Ease to serve

Tonnage o

f ari

sings

per

km

of ro

ad


93

CONFIDENTIAL

A street cleaning blueprint? Activities

…and similarly is the authority that provide its residents with the highest number of litter bins per km of road

Number of litter bins per km of road

0

1

2

3

4

5

6

7

8

0.0 3.3 6.6 9.9

Ease to serve

Num

ber

of litt

er

bin

s per

km

of ro

ad

BromleyRedbridge


WandsworthSouthwark


94

CONFIDENTIAL

A street cleaning blueprint? ActivitiesEffective enforcement is not necessarily the correct approach to waste minimisation in every Borough, however, there are wide variations in the activity of enforcement teams across the services considered

Relationship between the number of Enforcement officers employed and the number of Fixed Penalty Notices issued

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 5 10 15 20 25 30 35 40

No. of Enforcement officers

No. of FP

Ns

issu

ed Bromley

RedbridgeWandsworthSouthwarkLambethBrentTower Hamlets

Capital Ambition and LEDNET Street Services Productivity Review: detailed analysis March 2009.

Documents

money street cleaning

money services

visible services

data appendix slide

drivers of value

possible slide

head of service

good value