Fbp1107 Primary Distribution Benchmarking Survey
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    Fbp1107 Primary Distribution Benchmarking Survey Fbp1107 Primary Distribution Benchmarking Survey Document Transcript

    • Primary Distribution Benchmarking Survey 2009 Benchmarking Guide
    • Acknowledgements The following companies took part in the benchmarking survey outlined in this guide and are thanked for their kind participation: Aspray Transport Ltd. Bandvulc Tyres Ltd. Fridays Ltd. Gist Ltd. Global Manufacturing Supplies Ltd. Howdens Joinery Co. Knights of Old Ltd. Norfolkline Ltd. PD Logistics Ltd. Pilkington UK Ltd. Roadways Container Logistics Ltd. Robert Wiseman Dairies plc. Tesco plc. i
    • Foreword Freight Best Practice is funded by the Department for Transport and managed by AECOM to promote operational efficiency and reduce environmental impact within freight operations. Freight Best Practice offers FREE essential information for the freight industry, covering topics such as saving fuel, developing skills, equipment and systems, operational efficiency and performance management. All FREE materials are available to download from www.freightbestpractice.org.uk or can be ordered through the Hotline on 0845 877 0 877. Additional free copies of the guide can be obtained by calling the Freight Best Practice Hotline on 0845 877 0 877. It can also be downloaded from the programme’s website www.freightbestpractice.org.uk Disclaimer: While the Department for Transport (DfT) has made every effort to ensure the information in this document is accurate, DfT does not guarantee the accuracy, completeness or usefulness of that information; and it cannot accept liability for any loss or damages of any kind resulting from reliance on the information or guidance this document contains. iii
    • Contents 1 Background 1 1.1 Measuring Performance in Your Own Business 1 1.2 What Should the Key Performance Indicators Be? 1 1.3 Which KPIs are Right for Me? 2 1.4 External Benchmarking 4 2 The Primary Distribution Benchmarking Survey 5 2.1 The Nature of the Primary Distribution Sector 5 2.2 The KPIs 5 2.3 How the Data was Collected 6 2.4 Survey Participants 6 3 Survey Results 9 3.1 Miles per Gallon (MPG) 9 3.2 Number of Incidents per 100,000 Kilometres 12 3.3 Empty Distance Run 12 3.4 Vehicle Fill 14 3.5 Vehicle Time Utilisation 16 3.6 On Time In Full Deliveries (OTIF) 18 3.7 Damaged Deliveries 20 3.8 Delivery Complaints 20 3.9 Interventions 21 4 Summary 23 4.1 Accurate Data Collection 23 4.2 Vehicle Fill 23 4.3 Empty Running 23 4.4 Damage 23 4.5 Fuel Saving Interventions 24 4.6 Regular Benchmarking 24 5 The Primary Distribution Transport Efficiency ‘Road Map’ 25 v
    • Operators in the sector, whether survey participants or 1 Background not, can use this benchmarking guide to identify real Every successful organisation needs to manage its opportunities to maximise transport efficiency, reducing assets effectively and can benefit from benchmarking its both their running costs and environmental impact. performance against that of similar operators, especially those deemed to be ‘best-in-class’ in their sector. 1.1 Measuring Performance in Your The Department for Transport, through its Freight Best Own Business Practice programme, has supported a series of If you want to make well-informed tactical and strategic benchmarking surveys that have developed a range of decisions about your operation, you need to be able to key performance indicators (KPIs) in a variety of accurately measure the performance of the resources industry sectors. you use to deliver your services. Only then can you identify areas for improvement and assess how effective any operational changes have been. Already published are KPI survey guides for the following sectors: The starting point for any performance improvement Key Performance Indicators for programme should be to understand the current Non-food Retail Distribution performance of your operation. This means collecting data on key aspects of your operation and turning this Key Performance Indicators for the into specific measurements that can help you identify Food Supply Chain areas for improvement. Examples of such Key Performance Indicators for the measurements include how much fuel each vehicle Pallet Sector uses, how many miles your vehicles run empty and the number of late deliveries you make. Those measures Key Performance Indicators for the most critical to your operation will be your firm’s KPIs. Next-day Parcel Delivery Sector They may, of course, be supported by other, less critical Key Performance Indicators for the measures. Builders’ Merchants Sector A KPI on its own will not tell you much. Individual All of these publications are available FREE measurements and raw data need to be turned into of charge from the Freight Best Practice information that can help you to make decisions. This programme website means setting a target and measuring and monitoring www.freightbestpractice.org.uk and from KPIs over a period of time to see how your operation the Hotline 0845 877 0 877. performs against target. Weekly, monthly and annual reports allow you to identify trends, monitor progress and see which areas need the greatest improvement. Producing graphs or charts will often be the best way of This particular KPI benchmarking survey covers the showing progress in performance. primary distribution sector. KPIs used in external benchmarking are essential tools 1.2 What Should the Key Performance for the freight industry to understand and then improve Indicators Be? its performance. They provide a consistent basis for measuring transport efficiency across different fleets, There are many different KPIs that can be used to comparing like with like. measure performance in a freight transport operation and it can be difficult to know which ones might be right This guide aims to: for you. This section is intended to explain the Show companies how their own performance characteristics of some useful KPIs that can be applied compares with that of others in various types of operations. However, there are a number of things you should consider beforehand in Measure performance across a range of KPIs order to decide which ones are actually right for you. A Identify recommendations to improve efficiency KPI should be relevant to your particular operation and it should also be SMART – Specific, Measurable, Achievable, Realistic and Timed. 1
    • Specific needs of a particular business. Some information may have to be collected on a daily basis, such as staff KPIs should be specific, simple to use and easy to absence levels in the warehouse, daily delivery drops or understand. Complicated statistics and formulae can nightly trunking volumes. If certain measures are not lead to confusion about what is actually being measured recorded and presented to the agreed timescales, the in the first place. If KPIs are specific and simple, they risk of changes in performance going unnoticed rises. can be easily communicated across the business and there is no need for staff to have an in-depth knowledge of the area being measured. 1.3 Which KPIs are Right for Me? The size, type and management structure of a company Measurable are all likely to influence the range of KPIs you might use. KPIs can be used to help managers develop KPIs can show changes in performance over time. For strategy, plan and make decisions, while at an this to happen, it is essential to compare like-with-like operational level they can also clearly show up any data. It is easy, for instance, to fall into the trap of areas that need improvement or a change in approach. comparing two drivers on different routes for time utilisation or miles per gallon (MPG) – but if one route is An individual KPI can tell you how well you are more demanding than the other, it could be misleading. performing at an operational level. However, when Similarly, comparing drivers of vehicles of substantially looked at in combination with other measurements, different age or vehicle type can also be deceptive. KPIs can also help build a picture of how well you are performing in terms of revenue, profitability and overall There are ways you can resolve these problems, such fleet efficiency, or in relation to customer service. as rotating drivers on different vehicles and different routes and then monitoring both driver and vehicle Figure 1 shows a basic, step-by-step process for performance, to identify consistently high and poor measuring your performance. The checklist that goes performers. with it shows some important questions you can ask to help set up a performance measurement system in your Achievable organisation. Any targets set must be achievable. It may seem beneficial to set high targets in the hope that this will See the Freight Best Practice Guides lead to greater improvements in performance, but remember that people often become disillusioned if they Performance Management for Efficient continually fall short of their targets. Regularly reviewing Road Freight Operations performance towards targets and then resetting the This guide explains the process of targets to encourage smaller, incremental (but measuring performance effectively. It cumulative) improvements may work much better in the includes advice on how information is best long run. collected and interpreted to allow informed decision making in order to achieve Realistic operational efficiency improvements. Remember that important decisions will be taken as a result of the data collected and presented so the data collection method needs to be realistic, reliable and The eight KPIs used by the companies that participated consistent. It is important that the data required to in the primary distribution benchmarking survey are produce a particular KPI can be collected easily and on detailed in Section 2.2 of this guide. a regular basis, as comparison over time forms the basis of benchmarking and then improving performance. Timed Frequency of monitoring is an important consideration. Weekly or monthly monitoring is recommended for many KPIs but this can depend on the measure and the 2
    • Figure 1 The Process of Selecting and Measuring KPIs Performance Management or Checklist: Have you reviewed your existing KPIs or Select KPIs looked at those that might be appropriate for your type of operation? Are they Specific, Measurable, Achievable, Set and Review Targets Realistic and Timed? (SMART) Have you set targets for these KPIs? Do you know how well your operation is Data Collection performing against your targets? Do you need to raise or lower them? Have you considered external benchmarking Review/Evaluation to compare your operation’s performance with (Including Benchmarking) that of others? Have you reviewed or set up a data collection system to give you the information you need? Reporting & Feedback Do you have a good system in place for analysing and reporting your KPIs? Results Yes Do you use information technology systems Targets to help you? met? Have you considered actions that can be No taken to improve your operation’s performance and meet new, higher targets in the future? Targets Yes too high? No Identify Strategy for Performance Improvement Take Action Implement Strategy 3
    • 1.4 External Benchmarking The benchmarking survey described in this guide was designed to highlight the performance of some of the The basic process of measuring operational best-in-class operators in the primary distribution sector, performance internally is extremely useful, but to fully enabling you to compare the relative efficiency of your understand how your operation compares with that of own fleet and operation and identify measures you can your peers, you must benchmark against the take to improve your performance. best-in-class performers in your sector. This process of external benchmarking will enable you to understand the characteristics displayed by the best-in-class performers across a range of KPIs. In other words, understanding exactly why some operators perform better than others in certain KPIs will help you to decide the best measures to implement in your own operation to improve efficiency. 4
    • Primary distribution commonly involves the bulk 2 The Primary Distribution movement of goods – often a single commodity – often Benchmarking Survey over long distances and tends to be carried out by larger sized heavy goods vehicles (HGVs). 2.1 The Nature of the Primary There are many product-dependent variations in the Distribution Sector types of vehicles typically used for primary journeys, from curtainsiders and box-bodied HGVs for palletised There are a number of definitions of primary distribution, goods to bulk tankers for liquids and skeletal trailers for with perhaps the most accurate being from the container movements. Department for Transport, which describes it as “the transport of goods from the point of production or port to the wholesaler, primary consolidation or import centre”1 2.2 The KPIs Transport operators often define primary distribution as In any benchmarking survey, it is essential to use the the final delivery of product to their customers or the most appropriate set of KPIs and that everybody in the distribution of products to distribution centres and survey can accurately measure them. processing sites. However, the term is entirely dependent on the transport operator’s perspective and The five core KPIs used in previous external its end customers. For example, the delivery of finished benchmarking surveys – namely vehicle fill, empty products to a Regional Distribution Centre (RDC) will be running, time utilisation, deviation from schedule and regarded as primary distribution by the manufacturer of fuel consumption – were all considered alongside other those products, but for the RDC, delivery of those same measures for this survey, but not all of them were finished products from the RDC to their end customers deemed to be relevant. The eight KPIs detailed in Table will be the primary distribution element. 1 were deemed most relevant to primary distribution operators in this survey. Table 1 The KPIs Measured during the Survey KPI Description Total distance run per vehicle divided by the total fuel consumed per Miles Per Gallon (MPG) vehicle to calculate miles travelled per gallon. The average number of incidents that take place per vehicle pro-rata’d per Number of Incidents 100,000 km travelled with an incident being defined as “damage to vehicle, property or people”. Empty Distance Run Distance run empty per vehicle as a percentage of total distance run. Number of hours each vehicle is in operation as a percentage of its Worked Hours theoretical maximum (24/7 operation). Average total gross weight of each vehicle when fully loaded as a Vehicle Fill percentage of its theoretical maximum (maximum gross weight of the vehicle as taxed). Total number of deliveries made on time and in full compared to the total Deliveries On Time In Full (OTIF) number of deliveries overall. Total number of deliveries where damage to products occurred compared Delivery Damage to total number of deliveries made. Total number of delivery complaints that were not damage or OTIF-related Delivery Complaints compared to total number of deliveries made. 1 Department for Transport, ‘Delivering a Sustainable Transport System: The Logistics Perspective’, December 2008. 5
    • 2.3 How the Data was Collected The eight KPIs used in this survey were deliberately chosen to offer consistency with the KPIs included in The primary distribution benchmarking survey was the On Line Benchmarking system. This was to based on a 48hr period in February 2009. Survey encourage participants to provide their data using OLB participants had two options in terms of providing data and to allow data not entered this way to be transferred for their operation. simply into the OLB system for data aggregation and reporting purposes. Option 1: The next section of this guide introduces the types of Six of the transport operators involved in the survey transport operators and vehicles covered by this survey. used a benchmarking spreadsheet to enter their operational data, inputting relevant KPI measurements manually for each vehicle involved. 2.4 Survey Participants Thirteen transport operators (as detailed in the Option 2: Acknowledgements page on page i) using a total of 794 vehicles in primary distribution operations participated in The other seven transport operators used the recently this external benchmarking survey. launched On Line Benchmarking (OLB) tool. OLB is an external operational performance comparison tool The following information provides a general overview offered through Freight Best Practice. of the types of transport operators involved, illustrating from an aggregated and anonymised perspective where they were located and what types of primary distribution The Department for Transport On Line vehicles were covered. Benchmarking (OLB) system provides an internet-based resource that can be used Geographical Spread by transport operators to externally and anonymously benchmark the performance The geographical spread of the operators involved is of their vehicles. Vehicle types and shown in Figure 2. operating characteristics can be selected quickly and easily to compare In terms of geographical spread, 30% of the surveyed performance data from your fleet against vehicles were located in the North West and 60% in a other operators nationally. corridor running diagonally from the South East to the North West. OLB can be accessed from the website www.freightbestpractice.org.uk/benchmarking Figure 2 Geographical Spread of Vehicles in the Survey 6
    • Primary Distribution Transport Sub-sectors Vehicle Types As previously stated, primary distribution covers a large The vehicle types involved in this survey, their gross and diverse range of different road transport operations. vehicle weights (GVW) and their route types are all The spread of transport operators involved in this detailed in Figure 3. survey is detailed in Table 2. ‘Motorway’ refers to vehicles mainly used on motorway Table 2 Breakdown of Primary Distribution Sub-sectors journeys (e.g. trunking work). Involved ‘Single’ refers to vehicles mainly used on single/dual Number carriageways (e.g. A roads). Number of % of Sub-sector of Companies Vehicles Vehicles ‘Urban’ refers to vehicles mainly used in built-up urban areas (e.g. inner town/city). Construction 2 22 3% Containers 1 60 8% As the chart below shows, the most common vehicles involved in the survey were rigids of 18-26 tonnes GVW. Engineering 1 1 0% Rigids in this survey were particularly heavily employed Food/Drink 5 586 74% in ‘urban’ and ‘single’ transport operations, while artics were more commonly employed for ‘motorway’ work. General haulage 1 13 2% Manufacturing 1 5 0% Table 3 Vehicle Route Types Non-food retail 1 87 11% Operation Type Percentage Parcels 1 20 2% Motorway 29% Total 13 794 Single 3% Urban 68% Food and drink is the largest primary distribution sub-sector covered by this benchmarking survey in terms of vehicle numbers, followed by non-food retail and containers. Figure 3 Vehicle Operational Diversity 7
    • The body types of vehicles involved in the survey also Figure 4 Transmission Type of Vehicles varied, as shown below in Table 4. Table 4 Vehicle Body Types Body Type Number % Box 3 1% Container 60 7% ARTIC Curtainsider 138 17% Flatbed 16 2% Refrigerated 104 13% Total 321 40% Box 7 1% Cranemounted 1 0% RIGID Curtainsider 23 3% Figure 4 illustrates the transmission types for all vehicles in this survey. Most vehicles (69%) had manual Refrigerated 442 56% transmission, meaning that the driver had direct control Total 473 60% over gear selection and a more direct effect, therefore, on fuel consumption performance. For articulated vehicles, curtainsider and refrigerated Figure 5 Emissions Standards of Vehicles trailers were the most prevalent, making up 17% and 13% of the survey sample respectively. For rigid vehicles, refrigerated bodies were the most popular, making up 56% of the survey sample. Refrigerated bodies and trailers therefore accounted for a total of 69% of all the vehicles surveyed. Table 5 Nature of Fleet Analysis Nature of Fleet No. of % Description Vehicles Hire and Reward 111 14% Own Account 683 86% As shown in Table 5, the largest number of vehicles in Figure 5 illustrates that the majority of the vehicles in the survey belonged to ‘own account’ operators. this survey had a Euro III emission engine type (62%). A small number of operators (6%) were unsure as to their vehicles’ emissions standards. 8
    • Odometer readings and fuel consumption were 3 Survey Results recorded for each vehicle from all fleets during the This survey’s 13 participants provided data using the survey period. methods detailed in Section 2.3 of this guide. From the survey’s total pool of 794 vehicles, 450 Collating data from all the survey participants in order to vehicles provided accurate MPG data. The remaining report on an aggregated basis proved difficult because 344 vehicles were excluded as data recording of a consistent issue of accuracy. The data was inaccuracies meant their MPG scores were not valid. checked and cleansed where inaccuracies or The 450 vehicles were segregated into their respective inconsistencies were identified. GVWs as presented in Table 6. One of Freight Best Practice’s over-arching messages Table 6 Gross Vehicle Weights has always been “if you can’t measure it, you can’t manage it”. The word ‘accurately’ may now have to be Gross Vehicle Total No. assessed added to this message! Weight (GVW) for MPG Each KPI is summarised, where possible, in three 3.5-7.5 tonnes GVW 30 different ways: RIGIDS 7.5-18 tonnes GVW 40 By gross vehicle weight (GVW) By operational type 18-26 tonnes GVW 106 By primary distribution sub-sector 26-32 tonnes GVW 6 In some cases, KPIs have also been analysed by ARTICS geographical region. 33-40 tonnes GVW 32 3.1 Miles per Gallon (MPG) 40-44 tonnes GVW 236 MPG analysis is perhaps the most common key Grand Total 450 performance indicator (KPI) used by transport operators to determine their operational efficiency, as it is widely Due to the diverse nature of primary distribution, a understood and easy to calculate. simple MPG figure may be misleading if vehicle types are not considered. The average MPG performance achieved for different vehicle types in the survey is shown in Figure 6. Figure 6 Average MPG by GVW 9
    • The MPG analysis in Figure 6 shows that generally, The 26-32 tonne rigid vehicles in this survey were larger, heavier vehicles have a lower MPG, with the involved in motorway operations, which would help to exception of the 26-32 tonne rigids and the 40-44 tonne explain their higher MPG figure compared with the 18- artics. 26 tonne rigid vehicle category, which was mostly involved in urban operations. This is no surprise since MPG performance generally deteriorates as gross vehicle weight increases. The overall average recorded during the survey across However, this is not to suggest that these vehicles have all vehicle types was 8.54 MPG. lower overall efficiency since other aspects may also affect MPG, such as type of route. Figure 7 shows MPG performance by type of route run. As might be expected, the MPG performance of Artic vehicles, as shown earlier in Figure 3, tended to be vehicles running on the motorway correlates with the involved in motorway operations, which returned a MPG performance of 40-44 tonne artics, as these reasonable MPG for the size of vehicle, possibly related vehicles tend to operate on motorways. to the need for fewer gear changes and less fluctuation in speed. The 33-40 tonne artics, however, were mostly Single carriageway running showed the best average involved in urban operations in this survey, which would MPG. This may be because smaller vehicles are more help to explain why these vehicles show a lower MPG likely to be found on this type of road. than larger artics. Figure 8 indicates that the engineering sub-sector had the worst fuel consumption performance of the Figure 7 Average MPG by Route Type sub-sectors surveyed (an average of 4.91 MPG). This is perhaps because such vehicles often tend to be left idling to run on-vehicle plant or machinery, such as Average 8.54 cranes. The best performing was the parcels sub-sector, whose Route type Urban 7.79 MPG performance was 78% better than the next best performing sub-sector, non-food retail. This could be explained by the types of vehicles involved in parcels distribution, as a greater number of smaller and lighter Single 13.02 loaded vehicles in this sector would help generate a better overall average MPG performance. Motorway 8.65 Figure 9 confirms the average MPG per region, with all vehicle weight types for each region aggregated together. 0 5 10 15 MPG 10
    • Figure 8 Average MPG by Sub-sector It can be seen that the North West region provided the For example, a higher concentration of vehicles highest MPG performance in this survey, with the East involved in urban type primary distribution would result Midlands region providing the worst return. This could in lower average speeds, with more stop-start traffic be purely the result of different terrains affecting fuel conditions and repeated gear changes. performance – for example, the number of hills in the various areas. However, a lower MPG may also be This could certainly help to explain the MPG related to the type of operation undertaken in each performance for the London area, which came out as region. the second worst region. Figure 9 Average MPG by Region Geographical Region 11
    • 3.2 Number of Incidents per 100,000 3.3 Empty Distance Run Kilometres The survey required each operator to record the This KPI refers to the total number of incidents per distance travelled empty per vehicle. Empty running vehicle per 100,000 kilometres (KMs), averaged across was defined as when the vehicle was carrying no cargo a fleet. and for the purposes of the survey, ‘cargo’ was taken to include empty packaging and the necessary re- Participants were told to include any event where positioning of other equipment, such as an empty damage to vehicles, property or people occurred. This container. allowed for all types of incidents to be considered. The empty distance run KPI compared empty distance The KPI calculation reflects the total number of travelled with total distance travelled per vehicle. The incidents recorded during the survey period in relation to results are presented in Figures 10, 11 & 12 and include distance travelled to arrive at the number of incidents data by vehicle type, route type and sub-sector per 100,000 KMs. respectively. This indicator provides an overview of safety Figure 10 shows that large articulated vehicles were performance per vehicle for an operator to benchmark subject to the most empty running. against, whether they operate with a single vehicle or multiple vehicles. This could be due to them being commonly used for motorway routes, where empty running might be For the 48hr survey timeframe, only two incidents were associated with the return journey after a long distance reported across all of the participants and both were delivery. from the same operator. This operator recorded total distance travelled across all vehicles of 121,897 KMs, Smaller vehicle types in the survey experienced very resulting in a KPI of 1.64 incidents per 100,000 KMs for little empty running, something which can in part be that particular fleet. explained by these vehicles frequently being involved in the carriage of empty packaging back to their base Taking all 794 vehicles from all 13 transport operators depots. into account, the total distance travelled by all vehicles was over 507,000 KMs, against which these two incidents resulted in an overall KPI of 0.39 incidents per 100,000 KMs. Figure 10 Average Empty Running by GVW 12
    • Figure 11 Average Empty Running by Type of Route A container vehicle can be re-routed after a delivery to fill an empty container with a back-load on its return journey to the container depot. But the 47% empty running rate thrown up in this survey suggests that most containers delivered to customers were returned empty. However, as Table 2 demonstrates earlier in this guide, the sample sizes for these sub-sectors are relatively small and therefore this data may not be truly representative of the sub-sectors as a whole. Empty running appears to be less of an issue in other sub-sectors, possibly as a result of implemented operational changes and initiatives. General Haulage has an empty running figure of 26% which compares accurately to a commonly referred to industry average figure of 25%. It is entirely possible that the transport operators involved in this survey in the Manufacturing and Parcels sub-sectors may not have recorded empty running, Figure 11 shows that motorway routes involved a however this could not be confirmed after the survey, significantly higher rate of empty running than either therefore they are included in the graph for single or urban routes, something which could be completeness. explained due to vehicles returning empty from long- The average empty distance run per vehicle during the haul deliveries where there was less requirement to survey equated to 13%. carry empty packaging back to the base depot. Figure 12 illustrates that vehicles involved in the construction, containers and engineering sub-sectors incurred substantially greater levels of empty running than those in other sub-sectors. Figure 12 Average Empty Running by Sub-sector 13
    • 3.4 Vehicle Fill Figure 13 shows that the fill of vehicles varied considerably between different vehicle weights with the An important measure for all operators, and in particular best utilised vehicles being the smallest. primary distribution operators, is how well vehicles are being filled when compared to the maximum theoretical Artics exhibited high levels of fill, which was to be load. expected as these tend to complete longer distance, motorway work. Smaller vehicles, meanwhile, tend to There are two options for transport operators looking to reach their weight limit quickly, helping to raise their record vehicle fill – fill by weight or fill by volume. For level of average vehicle fill. the purposes of this KPI, vehicle fill by weight was used. There is some fluctuation in the average vehicle fill for Each survey participant was required to provide an other vehicle groups, with 7.5-18 tonne rigids coming average vehicle utilisation figure during the survey out as the least well utilised. timeframe. This was then calculated against the maximum possible weight each vehicle could legally Figure 14 provides a breakdown of average vehicle fill carry to determine average vehicle fill as a percentage. by type of route and shows that vehicles on urban and motorway routes were the highest filled during the Vehicle fill by weight was recorded at the beginning of survey. Vehicles on single carriageway routes were the each vehicle journey. No account was taken of changing worst performing, either because vehicle load space levels of vehicle fill in the course of multi-drop tended to be filled before maximum weight limits were operations. reached or because vehicle fill was sacrificed in order to achieve specific customer delivery requirements. Figure 13 Average Vehicle Fill by GVW 14
    • Figure 14 Average Vehicle Fill by Type of Route The parcels sub-sector also experienced a poor rate of fill which could be related to the light weight of parcels or vehicles being sent out irrespective of fill, as customers in this sector tend to require collection or delivery within a certain time limit. The manufacturing sub-sector achieved the best level of vehicle fill. This may have been due to operators in this sector only sending deliveries out once their vehicle fill had been maximised, thanks to having direct control over both the goods produced and their related transport requirements. Further details on the balance between vehicle fill and delivery performance are provided in section 3.6 of this guide. Figure 15 highlights average vehicle fill by sub-sector and shows that the engineering sub-sector had the lowest rate. This may have been due to load size and shape restrictions preventing a high level of utilisation. Figure 15 Average Vehicle Fill by Sub-sector 15
    • 3.5 Vehicle Time Utilisation Figure 16 shows large artics leading the field with a time utilisation KPI of over 50%, indicating that these Another good KPI for measuring vehicle utilisation is the vehicles worked either overnight or on multiple shifts, amount of time that a vehicle spends actually out on the with their results equating to more than 12 hours per road. day out on the road. This would be consistent with their routes being primarily motorway based and would help A tractor/trailer combination is an expensive asset so it ensure that the higher costs of such vehicles were is important to keep the wheels turning and get covered by a higher-than-average level of utilisation. maximum productivity out of the vehicle. Rigid vehicles worked, on average, between six and 10 Of course, vehicle time utilisation is heavily dependent hours per day, according to the time utilisation on the type of transport operation involved – for percentages. This would be compatible with single shift example in terms of the number of shifts run, any operation, which is unsurprising given their primarily particular customer requirements, and any operational urban or single-carriageway running, where more restrictions that might impact on vehicles, like night-time delivery restrictions may be in place based on customer delivery curfews. requirements or regulations. This indicator looked at the proportion of time each vehicle spent out on the road during the 48 hours in the survey timeframe. Figure 16 Average Time Utilisation by GVW 16
    • Figure 17 Average Time Utilisation by Type of Route Figure 18 shows that the construction and engineering sub-sectors had the lowest level of utilisation in terms of hours worked. The economic downturn at the time of the survey may explain this. The non-food retail sub-sector proved to have the highest level of time utilisation. Figure 17 shows that, unsurprisingly, vehicle utilisation in terms of hours worked was greatest in motorway running, where longer trips are often involved. The time utilisation for single and urban running vehicles suggests that these are not used as intensively. Single and urban delivery points tend to be open only during the day, for one thing, restricting operators to single shift operation. Figure 18 Average Time Utilisation by Sub-sector 17
    • 3.6 On Time In Full Deliveries (OTIF) Figure 19 demonstrates no correlation between GVW and OTIF performance. Overall, the level of OTIF Getting it right first time is the simple message related to performance was extremely high, with an average this performance indicator. If a transport operator can across all 774 vehicles of 99.27%. In isolation, this KPI deliver an order first time, on time and in full, this helps would suggest a high level of efficiency in the primary to achieve optimum delivery efficiency. If they cannot, distribution sector, however, as detailed at this end of additional costs will be incurred. this section, other KPIs should be considered alongside OTIF to determine an overall level of operator efficiency. The results for this KPI are based on 774 vehicles as some of the survey participants did not record data for this area. The OTIF KPI is calculated per vehicle as the percentage of completed deliveries made on time and in full within the survey’s 48 hour timeframe. For example, if a vehicle completed 100 deliveries during the period covered by the survey of which 90 were recorded as OTIF, the KPI measurement would be 90%. Figure 19 Average OTIF Deliveries by GVW 18
    • Figure 20 Average OTIF Deliveries by Route Type Motorway and urban routes provided the highest levels of OTIF delivery, indicating that operators in this survey experienced few external delays on such routes or built contingencies into their delivery schedules. Figure 21 illustrates average OTIF delivery performance by sub-sector. The parcels sub-sector did not record OTIF data for this survey and is therefore not shown. General haulage shows below average performance. Specific reasons for this were not captured in this survey. 7 out of 8 sectors achieved a 99% or better performance level. Figure 21 Average OTIF Deliveries by Sub-sector 19
    • 3.7 Damaged Deliveries Table 7 Delivery Complaints by GVW Quality is just as important as quantity when it comes to deliveries, with damaged goods impacting on customer Vehicle Type GVW % satisfaction levels. 3.5-7.5 tonnes GVW 0.00% Definitions of a damaged delivery vary, but in this survey damaged deliveries were defined as those declared as damaged by the customer. 7.5-18 tonnes GVW 0.20% Rigid Where a delivery is declared as damaged by the customer, it often results in a need to re-manufacture 18-26 tonnes GVW 0.82% and re-deliver the product, invariably leading to increased costs, increased freight requirements and 26-32 tonnes GVW 0.00% reduced efficiencies. This KPI was calculated as the number of deliveries 33-40 tonnes GVW 0.46% declared as being damaged by the operator’s customer Artic compared to the total number of deliveries made. For example, if a vehicle completed 100 deliveries of which 40-44 tonnes GVW 0.36% two were declared as being damaged, the KPI would be 2%. The types of vehicles with the highest number of During the survey timeframe, all operators reported nil complaints were 18-26 tonne rigids, at 0.82%. Rigids of damaged deliveries. This could be because no 3.5-7.5 tonnes and 26-32 tonnes received no delivery damaged deliveries took place during the survey, or complaints during the survey timeframe. because damaged deliveries did take place but were not recorded by operators during the 48hr timescale of Urban route deliveries produced the highest number of the survey, or because complaints about damaged complaints during the survey, with the other two route deliveries made during the survey timeframe were not types receiving far fewer. received until much later. Table 8 Delivery Complaints by Type of Route 3.8 Delivery Complaints Route Type % This KPI was based on the number of complaints Motorway 0.34% received by operators as a percentage of total deliveries. Single 0.31% Delivery complaints were defined in this survey as Urban 0.62% complaints from customers relating to deliveries other than those relating to non-OTIF deliveries and damages. Examples of delivery complaints would be where the delivery had been made too early, which can obviously impact upon the operation of a customer (particularly if working to just-in-time schedules), or where there were issues relating to the conduct of the driver or operation of the vehicle. If a particular vehicle completed 100 deliveries, one of which led to a complaint due to being delivered 24hrs early, the KPI measurement would be 1%. 20
    • Table 9 Delivery Complaints by Sub-sector Within the survey period, the general haulage sub-sector had the highest number of delivery complaints. Sub-sector % It may be that, as with delivery damages, reports of Construction 0.00% complaints did not reach the operators during the survey timeframe. Containers 0.00% Engineering 0.00% 3.9 Interventions Food/Drink 0.59% Operators were asked to indicate whether their vehicles had any fuel saving interventions fitted. The General Haulage 7.46% interventions are listed in Table 10, including the proportion of vehicles which had them fitted. Manufacturing 0.00% Table 10 confirms that the most common type of Non-Food Retail 0.00% intervention used by primary distribution operators was some form of aerodynamics. Parcels 0.00% Table 10 Summary of Interventions Used by Surveyed Vehicles Rigid Artics Total number 3.5 - 7.5 7.5 - 18 18 - 26 26 - 32 33 - 40 40 - 44 Intervention Description of Tonnes Tonnes Tonnes Tonnes Tonnes Tonnes vehicles GVW GVW GVW GVW GVW GVW 794 42 101 323 7 85 236 Includes cab, roof and 756 42 80 315 0 83 236 Aerodynamics body fairing (95%) (100%) (79%) (98%) (0%) (98%) (100%) Includes driver training 667 41 78 319 7 83 139 Drivers and driver motivation / (84%) (98%) (77%) (99%) (100%) (98%) (59%) incentive schemes Measures to increase 567 41 76 313 0 72 65 Operation vehicle fill and reduce (71%) (98%) (75%) (97%) (0%) (85%) (28%) empty running Includes anti-idling schemes and the use of 701 41 94 314 0 73 179 Other approved engine (88%) (98%) (93%) (97%) (0%) (86%) (76%) lubricants and synthetic oils Includes vehicle routing and scheduling systems 28 0 0 0 0 1 27 Telematics and satellite navigation (4%) (0%) (0%) (0%) (0%) (1%) (11%) systems Includes regular wheel alignment checks, fuel 644 41 76 313 0 76 138 Tyres efficient tyres, tyre (81%) (98%) (75%) (97%) (0%) (89%) (58%) pressure management and regular re-grooving 21
    • The least popular type of intervention was telematics As can be seen in Table 10, there were very few which, considering this category includes computerised vehicles with no aerodynamic equipment fitted. The artic vehicle routing and scheduling systems and sat-nav 33-40 tonne category did, however, include vehicles systems, is perhaps a little surprising in light of the both with and without aerodynamic interventions. general increase in the popularity of such systems in recent years. Figure 22 shows that there was an improvement of 9% in average MPG for vehicles in this category fitted with aerodynamic interventions on motorway routes. The Fuel Efficiency Trials Guide provides a generic 12-step process for operators to A 9% improvement in MPG translates into a saving of consider in implementing fuel efficiency almost 5,748 litres of fuel over 100,000 miles, equating interventions within a vehicle fleet. to around 15,117 kg of carbon dioxide (CO2). The Effects of Aerodynamic Interventions A common way of assessing the benefits of fuel saving interventions is by measuring MPG performance. This section of the guide looks at the effects of aerodynamic interventions, as the most common type of fuel efficiency intervention reported in the survey, on the MPG performance of the vehicles involved. Only the 450 vehicles with valid MPG measurements as described in Section 3.1 were included in this analysis. Figure 22 Variance in MPG for Vehicles in the Artic 33-40 tonne GVW category 22
    • 4 Summary Vehicle tachographs Telematics systems This survey of the primary distribution sector confirms that operational performance can vary greatly between operators, due to the dynamic make-up of the sector. 4.2 Vehicle Fill A number of positive recommendations can be made as It is important to find the right balance between some a result of this survey on ways in which primary KPIs, for example between vehicle fill and on time in full distribution transport operators can improve their (OTIF) deliveries. operational performance, save fuel and ultimately save money. They include: A transport operator needs to be careful not to jeopardise vehicle fill for the sake of a better OTIF Ensuring accurate data collection, for example rating. MPG performance, for the purposes of subsequent decision making Lower vehicle fill may have a positive effect on vehicle Ensuring vehicle fill matches the size of the MPG performance, but total fuel spend and number of vehicle as consistently as possible journeys are both likely to substantially increase as a result of lower fill levels. Reducing empty running, for example, through greater use of back-loads Vehicle fill levels can also be affected by the size of vehicle specified. An operator specifying a vehicle that Keeping damage levels during deliveries to a is too large for their typical loads, whether by weight or minimum by volume, is always likely to achieve a low vehicle fill Exploring the use of relevant fuel saving level. interventions Establishing regular benchmarking activities 4.3 Empty Running These points are explored further in the rest of this Empty running is an issue throughout the freight section. industry, as this survey underlines. Genuine empty running (where vehicles are running 4.1 Accurate data collection with no cargo, including any empty packaging returns) can have a significant impact on a transport operator’s The fact that valid fuel consumption figures were efficiency. recorded for only 450 vehicles out of the 794 involved in this survey suggests that many operators do not have Empty running may prove difficult for a transport an accurate picture of fuel consumption per vehicle. operator to solve alone, but collaboration can prove the key to dealing with it, for example by providing more Accurate MPG analysis is vital to determine how much back-loads on a regular basis. fuel is being consumed by each vehicle and to allow operators to target less fuel efficient vehicles for Finding regular back-loads across an entire vehicle fleet improvement. can prove difficult for a single transport operator but the recent growth of pallet networks and the introduction of To achieve accurate MPG figures, the following haulage exchanges offer operators greater opportunities elements need to be measured accurately: than ever for working together to consistently fill Vehicle odometer readings vehicles and increase operational efficiency. Vehicle fuel consumption figures 4.4 Damage There may be existing data sources in your company that already provide this information, including: This survey suggests that the level of damages among primary distribution transport operators was negligible Fuel cards and that damage to goods during delivery is not really Driver job sheets an issue. 23
    • It is important however, that this performance is 4.6 Regular Benchmarking maintained. To this end, operators should: This survey has highlighted the importance of carefully Ensure the correct loading of all items, with lighter collecting the necessary data to analyse current items placed on top of heavier ones operational performance and plan for further Feed any cargo packaging issues back up the improvements. supply chain – products may be shipped in packaging not specified by yourself, causing your If you can’t measure it accurately, you can’t manage it delivery performance to be affected accurately! Use stretch-wrap or shrink-wrap to secure pallet The survey has also made clear that operational stacks performance indicators should not be considered in isolation. A suitable range of KPIs should be adopted Use cargo support straps or bars to secure loads that fit the business model of the transport operator and in the vehicle offer a comprehensive overview of overall operational Avoid excessive braking or acceleration during performance. driving (something which will also have fuel consumption benefits) The Department for Transport On Line Benchmarking (OLB) system provides an 4.5 Fuel Saving Interventions internet-based resource that can be used by transport operators to externally and There are many fuel saving interventions available for anonymously benchmark the performance transport operators to consider. of their vehicles. Vehicle types and The data collated in this survey generally confirms that operating characteristics can be selected when interventions have been used, which are relevant quickly and easily to compare to the vehicle type and type of operation, there are performance data from your fleet against significant fuel savings. other operators nationally. OLB can be accessed from the website The Fuel Ready Reckoner, can help you www.freightbestpractice.org.uk/benchmarking determine types of interventions available. It is a FREE web-based tool that can be accessed by logging on to the Freight Best Practice website at Once the right internal KPIs have been established, you www.freightbestpractice.org.uk can compare your current performance not just against your own previous performance but also against other operators in your sector. Measuring performance against other operators can add real value in terms of understanding how efficient your operation is and provides further indicators as to what other initiatives could be adopted to improve your efficiency, with the ultimate aim of achieving a best-in- class rating. 24
    • 5 The Primary Distribution Transport Efficiency ‘Road Map’ The Primary Distribution Transport Efficiency Road Map The measures in the action plan are set out under six shown below is an action plan of measures that can be key categories: considered by anybody in the sector looking to improve Saving Fuel their efficiency. Equipment and Systems It identifies the measures that can be ‘owned’ and initiated by those managers responsible for transport Developing Skills within the business, for example, fuel management and Performance Management load preparation. Fleet Performance It also shows wider strategic measures, such as Supply Chain Reconfiguration customer-related initiatives, which would require the close involvement of other parts of the business, for Specific actions are identified for each category, example the sales, marketing and procurement together with signposts identifying relevant guidance departments. and support material from the Freight Best Practice programme. 25
    • Efficiency Measures for General Consideration General Specific Action Ownership or Initiator Appoint Fuel Champion. Audit current fuel management processes. Fuel Management Implement effective fuel management programme Purchasing Saving Fuel Fuel Management Stock Control Guide Dispensing In-use control Data collection Routing and Scheduling Audit order processing routing scheduling process. Computerised Vehicle Review potential benefits of computerised routing and Routing and scheduling. Scheduling (CVRS) for Optimise journey planning. Efficient Logistics Equipment Telematics Consider benefits of in-cab telematics and Telematics for Efficient communications’ systems to enhance expected arrival Road Operations times, traffic avoidance and performance monitoring. and Systems Review vehicle specification and potential benefits of Depot Manager the introduction of vehicles with increased: Vehicle Specification Payload Truck Specification for Load bed Best Operational Cubic capacity Efficiency Consider fitment of auxiliary equipment to reduce loading/ unloading time. Driver Development Conduct training review audit. Developing SAFED for HGVs: A Implement driver development programme. Guide to Safe and Fuel Consider implementation of driver league tables and Efficient Driving for rewards scheme. Skills HGVs Monitoring Performance Establish relevant key performance indicators and ctor Performance Fleet Performance measure performance:
    • Management Tool Set targets Management incorporating CO2 Benchmark across depots Emissions Calculator External Benchmarking On Line Benchmarking Increase pre-loading of vehicles with next day’s loads to ensure maximum productive delivery time. Load Preparation If operations are short distance, preparation by yard staff of second trip loads whilst vehicle is on first trip. If operations are short distance, encourage customers to accept pre-8am deliveries, allowing second run loading during morning peak traffic congestion and Delivery Windows post-peak second run. Sales staff to ‘lead’ customers to available delivery Supply Chain / Logistics Dir Fleet times. Increase pre-loading of vehicles with next day’s loads to ensure maximum productive delivery time. Performance Pricing Mechanism Consider rate discounts for off-peak deliveries. Consider delivery of less than full loads on nominated Zoning days by geographical area. Consider rate discounts for off-peak deliveries. Establish standardised customer service levels and Inter-Depot serve customer from most appropriate depot for the Co-operation delivery site. Sector Initiative Supplier Direct Investigate benefits of supplier direct delivery. Deliveries Establish economic thresholds. Back-loading Review opportunities for reducing empty running by Make Back-loading back-loading. For example, collect parcels for delivery to Supply Work for You depot on return trip. Chain Review industry-wide opportunities for trip reduction Reconfiguration Consolidation Centres through the use of consolidation centres. Unitisation of Investigate market opportunities for further unitisation Customer Orders of deliveries and consolidation of orders.
    • Freight Best Practice publications, including those listed below, can be obtained FREE of charge by calling the Hotline on 0845 877 0 877 or by downloading them from the website www.freightbestpractice.org.uk Saving FUEL Performance MANAGEMENT Fuel Efficiency Intervention Trials Performance Management for Efficient Road This guide describes a 12-step standardised process Freight Operations for transport operators to use when considering the This guide explains the process of measuring trial for a fuel efficiency intervention – an important performance effectively. It includes advice on how starting point in understanding the operational information is best collected and interpreted to allow efficiency savings that could be possible for your fleet. informed decision making in order to achieve operational efficiency improvements. Developing SKILLS Transport Operators’ Pack - TOP Sound Advice! The Fuel Efficient Truck Drivers’ TOP provides practical ‘every day’ support material to CD help operators implement best practice in the Featuring professional truck drivers and fuel experts workplace and acts in direct support of tasks essential this 25 minute audio CD explores safe and fuel to running a successful fuel management programme. efficient driving techniques and the benefits to you, your company and the environment. Equipment & SYSTEMS Case STUDIES Telematics for Efficient Road Freight Operations There are over 25 case studies showing how This guide provides information on the basic companies have implemented best practice and the ingredients of telematics systems, highlights how to savings achieved. Check out the following selection of use this technology, the information obtained from it Scottish case studies: and how to select the right system for your needs. • Tesco Sets the Pace on Low Carbon and Efficiency • Engine Idling – Costs You Money and Gets You Nowhere! • Power to Your People - Motivation Breeds Success November 2009. Printed in the UK on paper containing at least 75% recycled fibre. Performance MANAGEMENT FBP1107 © Queens Printer and Controller of HMSO 2009.