Cleanliness of streets and the local environmental is a key indicator which impacts upon people’s quality of life and as such is an essential front line service. Ensuring appropriate street cleansing frequencies is the core element in designing front line street cleansing operations, but how can these frequencies be designed to meet the need of the local area?
It is estimated that streets cleansing activity in the UK costs in the region of £800 million per annum. In the current economic climate where financial savings are required, new and innovative ways of identifying front line service efficiencies is critical. In this case, can Performance Monitoring of street cleansing services be used to identify where service efficiencies can be made.
Street cleansing schedules can often be a combination of historically designed rounds, ‘ad hoc’/ reactive work, inappropriate zoning (e.g. residential streets classed as town centres) or local knowledge. This can sometimes mean cleansing schedules are reviewed on an infrequent basis. Often the key driver to these schedules is ensuring reaction times are achieved, which is certainly effective in town centres but may not truly reflect the surrounding housing areas.
Up to and including the financial year 2009/10, National Indicator (NI) 195 was used by local authorities to monitor street and environmental cleanliness. NI195a and NI195b were used to show the levels of litter and detritus, while NI195c and NI195d related to graffiti and fly posting. As NI195 is no longer a statutory indicator it is important that local authorities continue to not only monitor service performance, but also use the data generated to inform service design. It may be that local authorities can now design internal monitoring regimes to reflect the make-up of their areas to provide monitoring that meets their operational needs and local surroundings.
Although keeping streets free from litter is a key responsibility for local authorities, it is an area where monitoring techniques can be easily introduced to improve service efficiencies and reduce costs while maintaining a high standard of service. Efficiency saving is all about either reducing budgets while maintaining service levels, or achieving a static budget with an increase in level of service.
For example, it could be that by simply following historic cleansing schedules a number of housing estates receive a mechanical sweep on a four weekly basis. Upon review of performance data it may be possible to identify that these streets are consistently viewed as high performing. It may also be that this high performance could be maintained even if street cleansing frequencies are stretched to, for example, every six weeks. Local authorities may look to use performance monitoring data to trial such changes in services.
In addition a re-zoning exercise can help to identify where streets are wrongly classified and provided with an over (or under) intensive sweeping frequency. By monitoring performance data it may be possible to see where services are over-resourced and allow for either service efficiencies to be achieved or for resources to be deployed elsewhere in order to meet demand. This can lead to either a reduced resource requirement or financial saving by reducing the frequency of cleansing. Clearly, this regular and structured monitoring is needed to ensure affected areas do not fall below the required standard.
Essentially, utilising performance monitoring can help local authorities address the question “Why Sweep Clean Streets?” If an area is clean, why sweep it when this has a financial cost to a local authority and resource could be targeted at areas that are not performing as well. The Code of Practice on Litter and Refuse clearly lays out anticipated response times for street cleansing activities. This information is often used by local authorities in order to design street cleansing schedules, but as important as this is ensuring that a front line street cleansing service reflects the needs of the public and the local geographical area. By using performance data to map an area this is achievable. By targeting resource to meet need and performance levels it is possible to provide a cost-effective service through the development of a database on service performance and on the operation of the system itself creating a tool that enables service improvement through analysis of the data.
