Within the global automotive industry, the figure Hours per Vehicle (HPV) is advancing to become an increasingly important key indicator for the analysis of personnel productivity of a production plant.
Because price-based competition in the automotive market has led corporations to launch initiatives on maintaining profitability, HPV has become not only an internally used measurement tool of personnel productivity, but has also transformed into a key indicator used to compare vehicle manufacturers against one another. Jim Harbour, who retired in 1980 as Chrysler's director of manufacturing engineering, used his background, knowledge, and interest to establish Harbour Consultancy, the firm responsible for publishing the annual Harbour Report (Vasilash, 1997). The report, depending on the region in which the participating companies are situated in, may be openly published, as for example in North America, or may only be released to the participating entities, as for example in Europe. “It is a tool used to benchmark performance, develop strategies, and improve operations” (Priddle, 2007). The Harbour Report measures the participating car manufacturing companies against many key performance indicators, therefore also including an analysis on the production efficiency through personnel Hours per Vehicle.
Hours per vehicle, simply stated, is the quotient of the number of hours worked in a specific time period in relation to the quantity produced in the same period (Weyer, 2011).
HPV=(Paid hours of attendance in a certain time period)/(Quantity of vehicles produced in the same time period) (1)
Although the equation above seems simple and straight forward, one will notice throughout the course of this report that the calculation of HPV itself may not be too difficult, however, clarifying the boundaries and parameters of this calculation is highly complex. One must clearly define and understand the characteristics of the key figure and the interdependencies among the influencing factors.
3 Scope of Hours per Vehicle
3.1 Principle Scope of Hours per Vehicle
Generally speaking, all paid hours of presence of all employment groups are relevant for the calculation of HPV. As easy as this may sound, breaking down this topic and looking into each and every one of these employment groups that a large corporate entity such as Daimler AG has, and then identifying to what extent each of these groups dedicate their work directly to the manufacturing of vehicles, made this the most extensive and time-taking part of preparing the Hours per Vehicle calculation for the MBV plant in Charleston.
Of the many different employment groups that count into HPV, the main employment categories that contribute with their working hours to an increase of the HPV are direct production employees of the body shop, paint shop and assembly, as well as indirect production employees, this being logisticians, maintenance technicians and quality engineers. (Weyer, 2011) The administrative staff of an operation, including management, must also be taken into account and effectively increase or decrease HPV. Additionally, light duty and limited workforce, as well as temporary workforce get counted into the HPV of a manufacturing plant, as well as an intern, thesis-writer, apprentice, or student-worker that is employed in the production or supports the body shop, paint shop, assembly shop or logistics (Mercedes-Benz PP/MIEC, 2017).
As stated above, all paid hours of presence of the valid employment groups count. To back this statement with precise data, one quickly notices that in a large, diverse corporation with many rules and regulations, this must be closer examined in order to achieve a precise Hours per Vehicle calculation. Training the workforce in their tasks, which is of special importance during a ramp up of a new manufacturing plant, as well as workshops and meetings, all increase the HPV of a plant. If the above stated employment groups get paid for working overtime or receive payment during break time, this too gets counted into HPV. However, inactive work contracts due to occupational disability, parental leave, or similar long-term reasons will not count into HPV, as these employees are not actively contributing to the value creation of the manufacturing plant (Treston, 2016). Unpaid overtime, breaks and sickness are also irrelevant for the consolidation of HPV.
Before getting into the specificity of every department and their influence on the efficiency of a plant, it is important to mention that any work contributing to an increase in Hours per Vehicle must be directly related to the ongoing series being produced (Priddle, 2007). This means, planning new products, planning the facelift of the current model, spare part production for older models, as well as rework at the expense of a third party do not get accounted for in the HPV calculation. However, any rework necessary at the fault of the manufacturing plant itself, or the spare part production of the current, running model, and also the provision of parts for other plants, as for example when one plant has the sole competency of creating a part for the current model, then these factor into the HPV calculation and cause it to increase or decrease accordingly.
Lastly, before the Mercedes-Benz Vans plant in Charleston was declared to expand into a full, part-by-part (PbP) production site, meaning it would produce vehicles entirely, it was a semi knock down (SKD) production, which therefore only consisted of an assembly shop producing the 2012-2018 Sprinter and the Metris models. Semi knock down, which means reassembling vehicles at the foreseen destination in order to achieve an economic benefit in regard to customs, is a production method not counted into the HPV calculation, as the vehicles are only partially built in the originating plant, and are then reassembled in the receiving plant, not newly produced. As the assembly shop at MBV in Charleston continues to produce some vehicle models in SKD and now adds the new 2018 Sprinter into its production in PbP, meaning this vehicle model will get entirely produced in Charleston by first travelling through the body shop, then the paint shop, and then meeting the SKD vehicles in the assembly line to be completely assembled, it is an alert to the plant that we must carefully depict the amount of time an assembly worker contributes towards the SKD production and the PbP vehicle production, as well as the amount of time an indirect production employee and an administrative employee dedicates towards each vehicle classification, as this can easily offset the Hours per Vehicle calculation.
3.2 Specific Scope of Hours per Vehicle
Illustration 1. The considered scope of HPV relevance adjusted to the Mercedes-Benz Vans, LLC plant in Charleston (Klein & Schnell, 2012).
As mentioned above, many different departments with different sizes, roles and responsibilities get counted into the HPV calculation. However, not all employees of a department have a role that is of significance to HPV. In order to prepare the calculation of HPV and to make it valid and most true for the Harbour Report and in the comparison of different automobile manufacturers, the department in charge of controlling HPV at Mercedes-Benz must obtain specific information from the Harbour Consultancy, to then pass this information to each plant's HPV representative to examine the department-specific guidelines of HPV and depict the relevant employees.
As Illustration 1 above shows, the press shop that provides the metal parts of the chassis is not relevant for HPV. This is because a so called “Stamping-Index” already exists, which combines five KPI's into one index that compares different workstations within the press shop based on their productivity (Harbour Consulting, 2007). However, even if the press shop would be relevant for HPV, the Mercedes-Benz Vans, LLC plant in Charleston does not have a press shop on site, as this is outsourced to Europe. So even if the press shop was generally relevant for Hours per Vehicle, the fact that the plant in Charleston does not have one at its disposal would be another reason not to include the hours of work done in the press shop in the HPV calculation.
Consecutively following the press shop is the body shop in a vehicle manufacturing plant. This shop is of relevance for HPV. Since the SKD production in Charleston only occupies the assembly shop, determining the relevant factors counting into HPV for this shop is far less strenuous and time consuming. It is of importance that not only the work being done on the body of the vehicle in the body shop on site gets counted into this plant's HPV, but also the time taken to produce the parts that are produced in other plants. For example, if the side doors of the vehicle are produced in a plant in Germany but are mounted onto a vehicle here in Charleston, all the hours worked for the production of these doors get counted into the HPV of the plant in Charleston, rather than into the HPV of the German plant.
The paint shop is the next destination for the vehicle in its production phase. This shop's production output is also generally relevant for HPV, as it too does not provide any work for SKD vehicles in the Charleston plant. This is because the vehicles that are rebuilt here have already been painted in the plant that once produced it PbP, so the hours produced there can be neglected. Based on the Mercedes-Benz internal HPV Guideline (2017), the only HPV non-relevant paint jobs are chassis painted for internal usage, e.g. corrosion testing or similar checks. Also, the additional expenditure of time spent on specialized coatings of vehicles based on customer demands do not count into HPV (Mercedes-Benz PP/MIEC, 2017). Nonetheless, any correcting activities needed to enhance the quality of the paint job, done by the rework area in MBV's paint shop, for example, does remain HPV relevant.
Lastly, the vehicle proceeds through the assembly shop, where it gets assembled entirely. Here, everything, including the engine dressing line, counts into HPV. It is, however, important to mention that any working hours spent on the production of certain pre-assembled vehicle parts, such as the production of a seat or assembling of the axle, do not get accounted for in the efficiency measurement. The Metris that will continue being produced in SKD in Charleston in the future is also categorized as non-relevant in this plant's HPV calculation. Lastly, any additional expenditure caused by a ramp-up, as for example the additional personnel costs caused in the plant in Charleston, are not relevant for the HPV calculation (Mercedes-Benz PP/MIEC, 2017).
Logistics also plays a large role in the calculation of HPV, however, does come with more restraints. Generally spoken, all logistics functions directly involved in keeping the production line running are HPV relevant. As Illustration 1 shows, this involves any intra-plant logistics activities such as material procurement, goods receipt, materials handling, sequencing, production scheduling, supplier management, and material transportation on site (Klein & Schnell, 2012).
As quality plays a vital role in the modern automotive industry, partly due to the shortening of the time to market launches of vehicles, they too become a relevant department for the calculation of HPV. For the quality department, all activities that concern the series production are seen as HPV relevant (Mercedes-Benz PP/MIEC, 2017). This means that any tasks that can be charged back to the suppliers, or the Development Liason Office, or even the materials laboratory where sample parts are tested upon their quality, are not relevant towards HPV.
Another department closely tied to the production and therefore relevant for the HPV calculation is the maintenance department. This department mainly focuses on providing services to other departments when needed. Therefore, all services provided by maintenance to other HPV relevant departments get counted into HPV, however, any other work done by them that does not provide service for HPV affected departments is not valid for the efficiency calculation, such as services for the heat and power plant.
Last but not least, certain administrative departments play a major role in increasing HPV.
Any production planning task that involves the planning of the series, industrial engineering such as MTM or workforce-planning, and even the KVP shop all fall into the HPV calculation. The project management's partner department here in Charleston, in charge of the Mercedes-Benz Production System, a derivation of the well-known Toyota Production System that was implemented throughout all Mercedes-Benz plants, also shows relevance towards HPV if their tasks can be directly allocated to the running series.
According to the Mercedes-Benz internal HPV Guideline (2017), the human resource department also impacts the HPV efficiency calculation, as all employee administrative topics, recruiting, as wells as qualification trainings count into HPV, and also services that boost employee satisfaction such as running the dining facilities, security services, the company doctor, and the administration of sport programs are HPV relevant. Lastly, while the payroll and other budget-related processes in HR are not HPV relevant, any controlling task of the finance department concerning budget or departmental controlling is HPV relevant.
4 Methodology and Reporting
4.1 Method of Hours per Vehicle
With all relevant factors determined, the next step towards a successful implementation of the Hours per Vehicle efficiency measure in a new automotive plant was able to be made, by taking a closer look at the methodology. Since all relevant employee working hours were now able to be defined, it was important for the plant in Charleston to decipher these relevant employee's and find a way to store this data. A data-based IT tool from IBM Cognos, called “TM1”, that includes a data orchestration environment for accessing external data and systems, as well as capabilities designed for common business planning and budgeting requirements (Cubewise, 2016), was decided on by top management. This is the standard reporting tool used throughout all Mercedes-Benz Vans, Mercedes-Benz Cars, any many other corporations, as it has the capability of syncing with other IT applications such as KRONOS, the time-keeping tool that is used to retrieve data on employee hours at MBV Charleston.
4.2 Reporting of Hours per Vehicle
Along with the implementation of this IT tool, the reporting style and future steps must be determined. Research shows that the reporting style for HPV is most effective when done in the most detailed manner (Klein & Schnell, 2012). After many alignment meetings with upper management, the plant in Charleston decided on a monthly internal tracking, as this would enable a close look on the efficiency of the workforce and a quick reaction to deviations from the target HPV, but would not enforce an entire team or employee's capacity to be solely invested in the HPV topic. Secondly, it is a common practice of large automotive enterprises to create a quarterly business review, in which plants review and compare their efficiencies and other performance indicators, which would make the quarterly calculation of HPV also a standard. Lastly and most importantly, the calculations made on a monthly or quarterly basis can then be consolidated into an annual calculation, which would then be reported to the Operation's Efficiency Department, which then combines the HPV calculations of all plants and then creates the overall Mercedes-Benz Vans HPV measurement for the annual Harbour Report.
5 Calculating the Hours per Vehicle
As shortly noted above, a key element of the efficiency measurement is the creation of a target HPV. After implementing the IT tool and evaluating the scope and relevant factors of the plant, a target HPV has to be created and approved by upper management. The creation of the target is just as extensive and complex as the actual calculation of HPV, as the plants' equipment and features, the employee groups involved, and the product diversity must all be taken into account. As the body and paint shop facilities were just recently built in Charleston and, along with the assembly shop, have incorporated recent technological advancements such as 182 robots and many aiding tools for workers to ease their workload, the HPV target would be assumed as lower than of a plant with limited technological advancements. This is due to the fact that aiding production tools and other technologies increase the efficiency of workforce, which enhances a workers job, makes him/her more efficient, and therefore leads directly into the HPV calculation by decreasing the hours worked per vehicle. As elaborated before, the diversity and complexity of the employment groups would affect the HPV target calculation for the MBV plant in Charleston conversely, as this would increase the HPV. For example, MBV Charleston employs approx. 10% light duty and restricted workforce as direct production employees. Lastly, the product portfolio being manufactured at the plant also gets acknowledged when creating the HPV target. However, this can be neglected in MBV Charleston's calculation of a target HPV, as only one vehicle model is built as a PbP, making it relevant for HPV, whereas the other model is imported SKD and is therefore left out of the calculation.
The challenge faced by not only the automotive manufacturing plant in Charleston, but also by all sister plants manufacturing the Sprinter Van, and a challenge that caused the research for this paper to increase drastically, is that the Mercedes-Benz internal HPV Guideline (2017) states that the HPV target for new models must be based on benchmarks. This means that the launch of the new 2018 VS30 Sprinter Van, with which the MBV plant in Charleston is starting its PbP production for the very first time, needed to either be based on the HPV calculation of a similar, competing model, or on the preceding model, the 2016-2018 Sprinter Van. To create this target, as shown in Illustration 2, a comparable vehicle's HPV is used, and adjusted according to the new model's variance, product content, quality, and service level or integration type. Consecutively, an annual improvement of the benchmark is applied to the Hours per Vehicle, which typically ranges between two and five percent, and then factors such as the consideration of volume of the normal year program, adjustments for local specifics, and additional content such as a mixed production or similar factors are taken into account.
Illustration 2. The HPV target setting for new models are based on benchmarks (Mercedes-Benz Vans, LLC, 2016)
After all relevant factors of HPV are determined, the foundation in regard to IT tools, applications, and any other necessary tools needed for the creation of the Hours per Vehicle measurement is set, the scope of responsibilities within the plant are defined and a target is created, the first calculation of Hours per Vehicle can be made. The diagram below shows a standard, monthly calculation of the HPV for a certain vehicle model, displaying the amount of hours invested by production workforce (MP), production support workforce (MPn), and the salaried employees (MV). Below the bar chart, a table displaying the Hours per Vehicle invested by each department is shown. Such a demonstration as below is typically retrieved from the IT Tool TM1.
Illustration 3. Diagram indicating the total monthly Hours per Vehicle, with an allocation based on MP, MPn and MV subcategories (Mercedes-Benz Vans, LLC VAN/OL, 2017)
Table 1. The detailed, department-specific allocation of HPV on a monthly basis (Mercedes-Benz Vans, LLC VAN/OL, 2017)
Although the intention of the Hours per Vehicle measurement – measuring workforce productivity – is not a new technique used in the automotive industry, the HPV variable has become one of the most established indicators in the industry (Rumpelt, 2009). As any other established key performance indicator, critiques have taken a closer look at this variable and have brought awareness to some downsides to this efficiency measurement. As Illustration A.1 of the Appendix shows, especially the complexity, variability, and details involved in running a modern automotive corporation and in the vehicles that are being produced can cause a great extent of criticism towards this performance indicator.
The most obvious conflict about the HPV comparison is that model variant numbers differ drastically between vehicle brands, and even between vehicle models of the same manufacturer.
Illustration 4. Product Complexity displayed through the total number of variants for a variety of car models (Pil & Holweg, 2004)
As the diagram above displays, Mercedes-Benz Cars offers many more variations to a vehicle model than, for example, Toyota does. This makes processes such as the feeding of a production line by logistics, as well as the assembly line itself, more complicated and time-extensive, directly impacting HPV. Although then in turn, workplace improvement measures such as the one shown in Illustration A.2 of the Appendix, can be implemented to speed up a process, the time taken by engineers or the Mercedes Production System team for improving the efficiency, also count towards HPV and thus, the HPV of such a manufacturer will always be higher.
The vertical range of manufacturing, meaning the volume of production that has been outsourced, differentiates drastically between automotive manufacturers, causing an offset in HPV between the different brands and car models (Klein & Schnell, 2012). For example, the Opel Astra produced in Antwerp has an HPV of 18.7 (Rumpelt, 2009). Comparing this to the Volkswagen Golf produced in Wolfsburg with an HPV of 37.1 (Rumpelt, 2009), will make Volkswagen look very inefficient, although it has been neglected that Volkswagen may only have outsourced a minimal amount of production compared to Opel. This shows that although a manufacturer with a low vertical range of manufacturing may look more efficient in the Harbour Report due to a much lower number of involved workforce, the company may still have higher expenses due to the additional complexity, the logistics costs, and many other expenses involved in the outsourcing of vehicle parts.
A prominent concern involved in the comparison of HPV's for different vehicle manufacturers is that the efficiency measurement tool is indifferent towards the lifecycle stage of a certain vehicle model, therefore also disregarding the planned production volume of manufacturers in a given year. As shown in Illustration 5 (Claessens, 2017), the demand for a new vehicle model is significantly higher in the first half of its lifecycle than in the second half. Since all paid hours of work in a certain considered time period are relevant for HPV, quantity-independent employees, indirect production employees and the administrative staff, will increase HPV if the quantity of produced vehicles in the considered time period was smaller, such as typically in the second half of a product lifecycle.
Illustration 5. Indication of the rapidly increasing sales in the first half of a product's lifecycle, and a declining customer demand in the second half of its lifecycle (Claessens, 2017)
As a typical lifecycle duration of a vehicle lasts between seven and ten years, the Hours per Vehicle calculation will fluctuate tremendously throughout the span of production. This is because the product calculation is usually based on the entire lifecycle, and a fixed cost degression is always assumed (Klein & Schnell, 2012). With this in mind, the quantity variation creates enormous fluctuations of the HPV, which in turn induces offsets in the comparison of companies' HPV's, as the stages of the vehicle model's lifecycles differ within companies and also between different companies, and rarely two comparing models are launched at the exact same time.
The last and most prominent issue for the Mercedes-Benz Vans, LLC plant in Charleston, is that the production facility may run many different models and model variants on one production line. This often leads to resources being used jointly. Any logistics effort invested in the feeding of the production line must now be allocated correctly, meaning proportional to the quantity of vehicles of a certain model being produced. This complexity can quickly cause errors and can offset the true HPV for a certain model, which seems like an insignificantly small issue, yet when paired with all other above mentioned HPV offsets, can cause a tremendous shift in the true value of the efficiency measurement.
Within a corporation, it has become apparent that working hand-in-hand and creating a general, joint understanding of the Hours per Vehicle and the expected target HPV, makes the implementation of it most successful. As the ramp up of the manufacturing plant in Charleston continues, the emphasis on creating a cooperative business culture is of great importance, as this provides the basis of a common goal oriented entity and consecutively leads to a lower HPV. Research shows that especially European automotive corporations focus their core business on the development, design and marketing of a vehicle. Toyota, on the other hand, lays their main business focus directly on the production of vehicles. (Weyer, 2011) While each practice is vital in modern competition, implementing yet another performance indicator in a plant like Mercedes-Benz Vans in Charleston, which is currently focused on getting the production running yet belongs to a mother corporation that has a generic focus on running its business, is more difficult.
Research shows that many corporations with a well-rounded view on business have had difficulties convincing non-production employees on the importance of such key performance indicators. (Weyer, 2011) Especially when the responsibility of a HPV result is analyzed, departments typically point their fingers towards production. This is the exact and most prominent reason for a large corporation such as Daimler AG to have to create a joint understanding of the Hours per Vehicle measurement and other key performance indicators, so that subcultures that typically exist in these large companies do not cause an offset in HPV just by blaming one another.
Overall, implementing this efficiency measurement at Mercedes-Benz Vans, LLC has turned out to be a bigger challenge and a more time consuming process than expected. While upper management stresses the implementation of the Hours per Vehicle efficiency measurement tool, the complexity of gathering precise data, as well as the implementation and training needed to implement a new IT tool and getting all involved employees on track, caused a great deal of resistance towards the topic and made the implementation more time consuming than expected.
In summary, it can be stated that while implementing a new key performance indicator, the research and training required to effectively manage Hours per Vehicle is vital before introducing its scope and starting the consolidation of data and the actual calculation of the indicator. Although HPV can be seen critically and this performance indicator may reach to conclusions that are not backed by fully precise data, it has helped facilitate the sharing of competitive benchmarking among all of the world's major vehicle manufacturers, and through this, has helped the entire automotive industry raise its level of competitiveness and pursue creative solutions to remain one of the most innovative and efficient industries.
...(download the rest of the essay above)