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Jon Sharkey (HoS – Waste, Recycling & Fleet)

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Presentation on theme: "Jon Sharkey (HoS – Waste, Recycling & Fleet)"— Presentation transcript:

1 Jon Sharkey (HoS – Waste, Recycling & Fleet)
The Application of the WebAspx Route Optimisation Technology in Enfield Jon Sharkey (HoS – Waste, Recycling & Fleet) Striving for excellence

2 Background to Enfield Outer London Borough – Less dense in North, deprived and affluent area In House Service 3 streams from wheeled bins Current consultation on Organics service

3 Background to Routing in Enfield
Previous System – map, list of streets with property numbers, photocopier, several packets of colouring pencils Further Tweaks – made after a review of finish times/tonnage of weeks 1, 2, 3, 4……15, 16 Why Change?! – Efficiency review, future service proposals

4 Why Round Mapping Software and Why WebAspx?
General Benefits – strategic fit; improve quality of information; process improvement and productivity; reduction in fuel cost Internal Solution – timescales prohibitive; shared procurement with PTS Procurement Exercise – 2 bidders; very similar on quality; price deciding factor (licences)

5 Preparation and Data Requirements
Contract – 3 year + support pack Training Days – 2 full days; 4 members of staff Data Requirements – property database, bin types, yield, collection times,

6 Webaspx Outputs – all rounds

7 Webaspx Outputs – 1 round

8 Uses to Date 1 Efficiency Review – round reduction in dry recycling service

9 Dry Recycling Tuesday - Before

10 Dry Recycling Tuesday - Optimized

11 Uses to Date 2 and Future Uses
Commercial Waste Routes – how much capacity? Estates Review – reduced optimization through time as sites added In House Modelling of Service Changes – organic service change Future Service Change – fortnightly refuse or recycling????

12 Lesson Learned Training – close to service change
Data Requirements – do not underestimate, base data for other applications Benefits – fuel, round reduction Flexibility – links with other applications Use By Bid Teams – all built around pick rates (actual vs perceived)


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