Transport infrastructure priority development for the Australian dairy industry

Transcription

1 Transport infrastructure priority development for the Australian dairy industry Overview of project approach Methodology An evidence-based study to identify investment priorities to improve transport infrastructure and regulations to benefit the dairy industry. The terms of reference were: 1. develop a methodology for identifying and prioritising transport infrastructure projects, and provide a model for assessing the infrastructure needs, which may also be relevant to other industries. 2. use the methodology to identify and prioritise transport infrastructure projects for each of Australia s eight dairy regions. 3. identify regulatory reforms that would improve transport efficiency and reduce costs. 4. undertake a preliminary cost-benefit analysis of the top three regulatory projects in each dairy region. The methodology Figure 1 summarises the project methodology at a high level. The methodology in each section is described in more detail below. The methodology took a bottom-up approach, relying heavily on the cooperation of industry processing companies to provide data and identify about specific transport issues and challenges. Figure 1: High level project methodology Define regions of focus Supply chain mapping Transport infrastructure and regulatory needs High level benefit cost analysis Define Regions of Focus Regions of focus were defined using the following criteria and in consultation with industry: Major commodity production areas feeding into major processing facilities and markets. Minor production areas at the industry s request to check for potential infrastructure or regulatory issues in common with major production areas. 1

2 Using this criteria, this study covered dairy regions 1, 2, 3 and 5 in Figure 2. Regions 1 and 2 incorporate: all of Victoria; the Bega part of NSW; the south-eastern part of South Australia; and Tasmania. This equates to around 76% of total Australian milk production. The focus was on six processors in these regions: Murray Goulburn, Fonterra, Warrnambool Cheese & Butter, Lion, Burra and Bega. These companies make up more than 90% of milk production in these regions. Regions 3 and 5 covered Queensland and Western Australia, with the focus on three processors: Norco in region 3, and Harvey and Brownes in region 5. These are the only major processors operating in these relatively small milk-producing regions. Figure 2: Milk production regions (% of total Australian milk production) Region 3: Around 15% Region 5: Around 4% Region 4: Around 5% Region 1: Around 68% Region 2: Around 8% Supply chain mapping The focus milk companies were asked to identify their key transport routes from farm to processors, and from processing facilities to warehouses and major customers, including ports. Individual farm to processor routes were not mapped; this component was limited to aggregate transportation movements from particular regions to processors. Companies were also asked to identify impediments on these routes. Estimates of transport movements were based on: Dairy Australia milk production data; the consultants data on processors milk production; and information from the major processors. The supply chain map would illustrate the volumes of raw product produced and processed at various points along the chain and at various locations. This included: farming regions; processing plants; warehouses; and major customers (including export ports). The methodology would attempt to disaggregate and classify the supply chain movements according to key characteristics and factors that would affect the benefit-cost assessment. In terms of transport movements on either key transport routes from farm to processors or from processors to the next point in the supply chain, this included identifying (based on available data as discussed above), by processor, volume/tonnage data on: aggregate annual movements and seasonality/variability in movements; 2

3 intra and inter regional movements; raw milk, drinking milk and manufactured milk product movements; and the class of roads these movements occur on. The type of information sought from processors on transport movements include: the vehicle configurations (e.g. semi s, b-doubles); the length and mass of the vehicles; and the payload capacity of the vehicles. The type of mapping undertaken is illustrated in Figure 3. Note that this is illustrative and the route of each individual farm to processor was not mapped. Rather the approach was to map each sub-region within Regions 1 and 2 and for the three companies listed above (Norco, Harvey and Brownes) for regions 3 and 5. Figure 3: Supply chain mapping: illustrative example Dairy farms Processing End use customer Domestic customer Processor Processor/ Warehouse Port (for export) In consultation with processors, opportunities for changes to transport infrastructure and/or regulations in regions 1, 2, 3 and 5 would be tested with consideration of supply and demand factors: regions 1 and 2: identify two to three significant issues within four sub-regions that make up regions 1 and 2 (e.g. four of South East Vic/SA, Gippsland, North/North East Victoria, South East NSW (Bega region) and Tasmania). This equates to 8 to 12 transport issues. Regions 3 and 5: identify one to two key transport issues in both Queensland and Western Australia. This equates to 2 to 4 transport issues. Factors driving the demand for transport resources and the implications for transport needs was examined. Supply chain mapping was used to illustrate milk production and processing volumes at various points along the chain. Additionally, the implications for transport resources were examined. A key part of this analysis was to consult with milk processors and make a distinction between the characteristics of the current transport task (e.g. vehicle configurations, loads) and what could be considered by processors to be optimal if they were able to improve transport infrastructure or have changes made to current regulations. 3

4 The supply side factors reflect the current capabilities of the transport infrastructure and the constraints imposed by current regulations. In assessing the supply side issues, a range of factors were considered, including: road geometry (lane widths, bridge widths, gradients, overtaking opportunities, turning circles) all feeding into road classification level; pavement strength and condition (affects axle group loads); bridge strength and condition (affects axle group loads and gross combination mass); and loading and unloading facilities, which may have throughput constraints or may not be able to physically accommodate larger vehicles. On the demand side, the potential for next generation vehicle configurations along the supply chain was considered, with the need for these types of vehicles taking into consideration feedback from processors in terms of their transport needs. Whether the current infrastructure and regulations in the relevant region would allow for access to this type of vehicle was investigated. High level benefit-cost analysis Three benefit-cost analyses (or case studies) were undertaken from the eight to 12 transport issues identified across regions 1 and 2. Cost-benefit analysis for regions 3 and 5 depended on the transport issues identified; in this study, it was decided the issues were too diffuse to separate out a couple of priority actions that would make a clear and significant difference or cost-saving. Challenges were also generally already being addressed or could be by company decisions, without the need for changes in regulations or upgraded public infrastructure. Case studies incorporated multiple processor supply chains since some processors operate out of the same region. The benefit-cost analysis considered benefits in transport productivity savings, estimated in consultation with processors and consultants expert transport sector knowledge. The relevant road authorities (e.g. VicRoads in Victoria, local councils) were contacted to establish the costs of upgrading infrastructure and/or changing regulations. The aim was to gather information relevant to the case studies on the cost of issues such as: evaluating roads against the network classification guidelines ( per kilometre ); upgrading roads to a higher classification ( per kilometre ); upgrading bridges from MS18 (or earlier) design standard (i.e. pre-1976 construction) to T44 or SM1600 standards that allow B-doubles and larger combinations ( per unit deck area or per lane-metre ). The cost to upgrade fleets to next generation higher-productivity combinations was estimated based on the consultants expert knowledge. 4

5 Methodology shortcomings The supply chain mapping of transport movements was limited by the information provided by processors on transport movements. This limitation affected the consultants ability to provide comprehensive analysis of transport movements across the supply chain. The quality and quantity of data supplied by companies varied widely, as did the degree of their cooperation with and responsiveness to the consultants. The company data supplied was commercial in confidence in almost every instance, particularly from companies competing against each other for milk supply in the major southern production regions. Each company believed their transport logistics solutions provided a competitive edge, and did not want this information shared even when the adoption of some solutions would the benefit the industry as a whole. This meant the final report could not be released, and a publicly available summary of key findings was of a more general nature with few specific recommendations for actions of common benefit. 5