1. RIMMS Data Collection Workshop #2 Christopher R. Bennett Stephen Vincent Scott Wilson U.K.

2. Outline Data collection: why bother? Principle outcomes from last workshop Evaluation of workshop results Priority data types and automated equipment Data collection options Recommended forward path

3. Today’s Objectives Confirm outcomes from previous workshop Prepare draft recommendations on –Data items to collect –Appropriate technologies –Priorities

4. Data Collection - Why Bother?

5. Road Management Issues Delivering a defined quality of service Allocating resources of people, materials and equipment Determining appropriate activities and procedures Where on the network are the needs and when should activities be done?

6. Impacts Level of service and road condition National development and economy Road user costs Accident levels and costs Environmental degradation Road administration costs

7. Road Asset Management Defining activities Planning Allocating resources Organising and motivating personnel Controlling work Monitoring and evaluating performance Feeding back results to seek improvements

8. Goal? A safe and efficient road infrastructure which contributes to the successful social and economic development Improve the management of road assets to optimise total road system costs and functional performance

9. Objectives Strategic –Allocate adequate funding to road sector –Balance development and preservation allocations Tactical –Program priorities and strategies which optimise costs and timing –Evaluate impacts - on users, safety, environment

10. Assisting the Road Manager Require decision support systems which fit the management cycle: Planning Programming Project Preparation Operations

11. Data are Important! Required as input to the decision process Data are the foundation of key information for the manager

12. Good information does not guarantee sound management but bad information makes sound management difficult Information

13. Deciding What to Collect What decisions do we need to make? What data are required to make these decisions? Can we afford to collect the data initially? Can we afford to keep data current over time?

14. Principle Outcomes From Last Week’s Workshop

15. Voting on Main Data Users

16. Obstacles Lack of Funds18 Lack of Appropriate Skills14 Lack of Adequate Tools13 Maintenance/Sustainability7 Resistance to Change5 Donor Driven Priorities3 Lack of Updated Standards2 Changes in Legislation1 Lack of Internal/External Co-ord.1

17. Success Factors Adequate funds to implement and sustain Data collection recognised as high priority Commitment Appropriate importing of technology Phased implementation to minimise impact and risk Optimise local involvement (market) Continuous staff training and education

18. Success Factors... Appropriate continuous updated standards Applicable to local conditions Political support Established co-ordination, consensus and linkages to other appropriate organisations

19. Summary We need to have: –Funds to cover acquisition and ongoing costs of data collection –The appropriate equipment –Strong training programme We must: –Ensure that management recognises the importance of data collection –Provides the necessary support for ongoing sustainability

20. Technology Strong preference for low and medium technology solutions Two groups recommended against any high technology solutions One group recommended some high technology solutions but were also very clear on potential problems with these

21. Data Types Total of 111 identified Inventory Data - 41 –physical elements of road network that do not change markedly over time Condition Data - 16 –elements of the road network that change over time Bridge Data - 17 –data pertaining to bridges

22. Traffic Data - 22 –data on traffic flow and speeds Accident Data - 11 –data on accident type and locations Other Data - 4 –businesses, socio-economic, registration, weather Data Types

23. Evaluation of Workshop Results

24. Objectives To establish –The most appropriate technology for collecting the data –The most important data items

25. Process

26. Grouping of Data

27. Methods of Collecting Data Four Basic Groups From Other Records –other departments, existing drawings, etc. Manually –Visual: estimate or counting –Equipment: use common or dedicated equipment

28. Methods of Collecting Data Automated Equipment –Low Cost: Simple and relatively inexpensive –Medium Cost: Moderately complex and/or expensive –High Cost: Complicated and expensive Video –Data which could be obtained/verified from a video taken from moving vehicle

29. Options for Collecting Data Allocated the 111 data types to the four groups (Other/Manual/Auto./ Video) For manual/automated assessed technology options Results: Most data will come from other sources or be manually collected

30. Video Logging Increasing in popularity overseas due to inexpensive storage and playback hardware Recent centreline and video logging surveys in N.Z., South Africa and expected soon in Indonesia

31. Video-logging Vehicle

32. Example of Video Log

33. Group Exercise: Method Verification Break into groups Review the list prepared and assess whether or not the assignments of the 111 types are correct For example … –are there low technology solutions for measuring water current? –should some of the manual items be collected with equipment or vice versa?

34. Priority Data Types and Automated Equipment

35. What is REALLY Important? Although 111 data types, only some are critical to management process Emphasis should be on these critical items as opposed to the total number of potential data items

36. Process ?

37. Group Exercise: Priority Data Break into groups What are the most important data for management decisions Review the short-list prepared and: –are there items here which don’t belong? –have some from the longer list been incorrectly omitted?

38. Automated Data Collection Decision upon appropriate technology depends on the end use of the data and cost of collection/ processing Automated data collection is not always the best answer

39. Technology Short List Based upon feedback we have prepared –a short-list of key data items with technology options –a description of the technologies What is missing? What should not be here?

40. Data Collection Options

41. Previous Workshop Recommendations Should not necessarily adopt high technology solutions for data collection Emphasis must be on sustainability Must address institutional issues –Support for data collection –Appropriate method of executing surveys –Quality assurance

42. Feedback Australia Canada Chile Finland Italy New Zealand South Africa UK USA

43. Data Collection Short-term: –Should organise road centreline survey with differential GPS –At same time, record video of pavement right of way Medium-term: –Look at data requirements for making management decisions –Consider issues such as contracting out

44. Organising Data Collection

45. Issues to Consider Survey Components Planning Execution Quality Assurance Executing Survey All done centrally All done locally Combination central and local Sub-contracting Localised Decentralised Combinations of above

46. How is it done elsewhere? NO single ‘answer’ which is perfect for everyone Need to carefully consider local issues and capabilities and institutional issues Different solutions in different countries

47. Who Does What?

48. Quality Assurance VITAL to the successful execution of the work Must have in place good quality controls before project commences Must have independent verification of data during surveys

49. Everything Centralised

50. Centralised Operation –Road administration head office would have a small number of its own teams that go out and do all major data collection Advantages –Improved quality control –Lots of work for head office personnel Disadvantages –Lots of travel –Lack of local ownership of data –Not popular with districts –Lots of work for head office personnel

51. Localised - Thailand

52. Localised - Argentina

53. Localised Operation –Road administration head office or local office would plan surveys using local staff –May do some specialised surveys themselves (eg roughness) or may support local special survey units Advantages –Local involvement in data collection helps ownership –Reduced work load for road administration head office Disadvantages –Quality assurance more difficult to ensure –Greater training requirements

54. Limited Sub-Contracting - India

55. Limited Sub-contracting Operation –Road administration plans surveys and do QA but uses private sub-contractor(s) Advantages –Competitive tendering may reduce true cost from having administration do surveys –Reduced QA requirements since sub-contractor involved Disadvantages –Requires budget for outside sub-contractors –Lack of local ownership of data

56. Specialist Sub-contracting Operation –Use sub-contractors to collect data in specialist surveys (eg Roughness) Advantages –Sub-contractors must maintain and calibrate equipment –Specialist skills likely to be maintained Disadvantages –Reduced work load for admin. staff –Requires budget for contractors

57. Full Sub-contracting - New Zealand

58. Full Sub-contracting Operation –Road administration completely contracts out planning and execution of data collection Advantages –Minimises the head office work involvement in surveys –Probably lowest true cost of data collection –Road administration can focus on information systems Disadvantages –Reduced work for road administration staff –Requires budget for outside contractors –Lack of local ownership of data

59. Devolution - Finland

60. Devolution Operation –Road administration completely devolves responsibility for everything to local office –Local office may use own staff or subcontractors Advantages –No head office work involvement in surveys Disadvantages –Reduced work for head office staff –Requires honest and diligent local offices –Possibility/likelihood of poor data due to local QA

61. Sub-contracting and Jobs Use of sub-contractors does not necessarily mean loss of jobs Possible to form independent trading enterprise owned by which acts as a consultant in this area Very successful in New Zealand

62. Is Sub-contracting Always Better? Depends on: –Sustainability –Technology –Availability of internal skills to do job Agency needs to fully consider the long- term ability to maintain data collection Sub-contracting works best in fully competitive environment

63. Issues if Not Sub-contracting Capital costs of equipment Ongoing maintenance over extended period Security and insurance of equipment Do staff have adequate skills Training costs Staff retention Running costs

64. Group Discussion List advantages and disadvantages in Philippine context of: –Centralised –Localised –Limited Sub-contracting –Full Sub-contracting –Devolution