Case study:
Harrow Council

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Residents often judge a Council by the quality of its bin collection service and are quick to condemn inefficiency. By combining Experian’s data and customer insight with new technologies, the London Borough of Harrow has demonstrated how to effectively deploy this insight within their waste management services and in turn transform their delivery. This award winning strategy has resulted in significant cost efficiencies – an estimated £3.2 million over the next 10 years.

Waste management is a key issue for local government. There are strict targets to hit, with 40% of waste to be recycled by 2010 and 80% of all waste to be recycled by 2020. Along with the significant increases in landfill charges, there is an urgent need for Councils to become smarter and more effective in encouraging their communities to recycle. As a result, Councils must ensure both that households are actively recycling, and that residents are fully educated on how and what to recycle. If residents put rubbish in incorrect recycling bins, whole truckloads of contaminated recyclable rubbish (e.g. plastic bags in a garden waste bin) can be rejected from recycling plants and sent to landfill. Every extra tonne of rubbish sent to landfill costs a local council £32 and is set to increase by £8 each year, reaching a charge of £72 per tonne in April 2013.

As part of the waste management project, bin lorries in Harrow were installed with GPS information systems, with mobile working, route planning and CRM technologies. Each lorry has a touch-screen computer with GPS links and communication capability between crews, managers and Harrow’s contact centre. Crews collect waste and log when they finish each road. This technology allowed the crews to log which households have not recycled their waste correctly. From day one, usage of this system was high with 35 crews reporting 21,000 logs daily. On average there were 551 contaminated bins daily, leading to 1,653 opportunities each week to target residents about improving their recycling behaviours.

Harrow used bespoke customer insight segmentation, built and delivered by Experian using public and private data, to inform the business case for this waste management project. The Council was able to use this customer insight to gain a detailed understanding of those repeat non-recyclers and residents guilty of ‘contaminating’ waste bins, including their lifestyle behaviours, characteristics and likely engagement and communication preferences.

With this, Harrow could deploy effective marketing campaigns that would target hotspot areas of poor recycling through appropriate communication channels, to educate residents and help them get it right. With an understanding of which types of people are more receptive to certain methods of communication (e.g. by phone, post, internet), Harrow also plans to contact residents automatically by text or by phone if their bin was not collected for reasons of ‘contamination’. In turn this will enforce better recycling behaviours and ultimately reduce landfill costs in the long term.

To date, the amount of ‘contaminated’ waste sent to landfill has been reduced by 18.8%.

Over the next 10 years it is forecast that this shift in recycling behaviours underpinned by Experian’s customer insight will save Harrow Council £2, 682,260 (£19.5k in year one). In addition a 15% reduction in fuel consumption (£11,000 in year one) generated by creating the most efficient collection rounds possible for bin lorries, contributes to an estimated overall saving of £3.2 million over the next 10 years.

“I am delighted with the efficient way Experian’s Customer Insight process has run, and from which the London Borough of Harrow is now able to make better informed, cost efficient and customer centric decisions. We are now looking to extend Experian’s relationship with Harrow, in terms of partnership working and future challenges to the Borough over the next 10 years.”

Carol Cutler, Director of Customer Services and Business Transformation,
London Borough of Harrow
Summer 2009

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