Business Process Management for a Motor Vehicle Company
In the current competitive business environment, businesses must be able to reduce their manufacturing costs by eliminating all non-value adding processes, ensuring compliance to industry standards, ensuring proper storage of data, and fostering innovations in the industry. Various processes are entailed in the manufacture of vehicles, such as designing of new products, manufacturing, provision of after sales, and recycling of old vehicles. Currently, the automotive industry accounts for about 15% of the world’s gross domestic profit. Further, it has a new product introduction rate of about 34% per annum (McGarrahan & Harris, 2008). As such, businesses in the automotive industry must have a competitive production process to reduce their manufacturing costs, enhance the level of compliance with industry standards, increase their business opportunities, and foster innovation. This paper shows how motor vehicle manufacturers can use the business process management (BPM) to optimize solutions.
As the automotive industry grows, the challenges and opportunities within it continue to increase. In particular, the original equipment manufacturers (OEM) in this industry are now required to adhere to new regulations, become more innovative, and receive flexible solutions that provide them with insight into business processes. In the European Union, for example, there have been an emergence of new laws, such as the Directive 2000/53/EC on end of life vehicles (ELV) and the one on the use of hazardous substances (RoHS) (Directive 2002/95/EC. McGarrahan & Harris (2008), note that businesses that do not comply with the new regulations will lose about 1 billion euros annually. Accordingly, the business process management in the automotive industry will increase companies’ business opportunities, enhance the level of their innovations, and reduce their operating costs.
The Company’s Activity
My company will work on the development of an automated business process for organizations in the automotive industry. Currently, the automotive industry is growing, primarily driven by the increase in demand in middle-income countries. The huge demand has resulted in the increase in the number of competitors for the available buyers, which is coupled with the increased demand for unique and fuel-efficient vehicles. There has also been an increase in the outsourcing of various products in motor vehicles, which has resulted in the need for increased coordination between car manufacturers and their suppliers. Additionally, most current car buyers require reliable vehicles that use sophisticated technologies. For example, they require cars that are fuel efficient, those that have sophisticated safety equipment, and also have digital infotainment systems (McGarrahan & Harris, 2008). Given the increased complexities in the manufacture of vehicles due to high demand from both customers and motor vehicle regulators, enterprises in this industry require an automated business process that will assist them in ensuring that they meet our requirements and can perform their operations in an economical and sustainable means.
Position of the Business in the EDRM
The primary importance of this business in the automotive industry is in the provision of detailed analytics of various aspects of the company. In particular, the business will provide car manufacturers with information on demand levels of various car brands. This information is critical to the success of any business since its shows it the optimal number of vehicles that should be manufactured for each region. More importantly, a detailed analysis of this data is essential in enabling the company to identify the optimal production levels and also the optimal location for the manufacture of an assembly plant (Ferreira, Marques, Faria, & Azevedo, 2016). Regarding the most optimal output, businesses can know their economic order quantity, which helps them to identify its optimal order quantities and re-order levels for various outsourced items. Moreover, a business can identify where to establish its assembly plant having factored its logistics and manufacturing costs.
Besides enabling companies to have information on the demand levels of the cars ordered by customers, the business process management will help companies ensure that their vehicles comply with the established safety standards. The business will require engineers to follow a set of systematic steps for it to achieve its goals. In the first step, engineers will have to record once they install a safety feature in each car. Secondly, there will be a test of the safety equipment installed in each car. Lastly, there will be a random simulated test of each car made by a manufacturer. In most cases, one car will be tested for its safety. This test will be necessary for providing car manufacturers with actual information of their safety kits. Further, this information will ensure that carmakers comply with safety laws, which will in turn cases of litigations due to the manufacturing errors.
Finally, the information provided by the business management system will be essential in enabling car manufacturers to develop the best car designs for their customers. The business management system will always customer’s demand for specific products based on their unique characters and market trends. This information will be necessary for ensuring car manufacturers remain competitive by developing, modern, affordable, and stylish cars.
Decision Making in the Company
When making various decisions, the company will consider various factors that will be important to its success. The following are some of the key decisions that will be considered:
- Type of information that is confidential.
- Objectives of the business.
- The target market for the business (Its target clients, car manufacturers).
- Source of finances for the company’s operations.
The identification of confidential information will help the business to know the type of data to encrypt and store safely. Importantly, it will reduce the cases of leakage of sensitive information of individuals, such as their credit numbers, identity numbers, names, and account number. Since the process of data analysis may result in the discovery of sensitive private information, this policy is essential in preventing the business from lawsuits due to reckless handling of such data.
The predetermined decision on the objectives of the business will inform it on the type of data to collect. Typically, raw data contains ‘noise,’ duplicated information, and other unnecessary content. Accordingly, the predetermined decision on the objective of the business will inform it on the data to collect and the one to ignore. Additionally, it will inform it of the appropriate sample size. Finally, the pre-determined decision on the company’s objectives will ensure that it is not distracted by unnecessary ‘noise’ in the data (Ferreira, Marques, Faria, & Azevedo, 2016). The primary objectives of the business will include the following; demand levels for each car, features needed in each car, a price that customers can afford, safety features demanded each car and buying behavior of each customer group.
To ensure that the company succeeds in its endeavors, I will provide high-quality, timely, professional, and affordable services. In particular, all the analytics services provided by the company to businesses in the automotive industry will be accurate and will be provided within a reasonable time. The high-quality of services offered by the business will enable it to succeed in the data analytics market. Further, the business will be distinct from its competitors in that buyers will be able to make online purchases of various analytics works. This feature will be essential in ensuring the company’s services can be accessed from any part of the world in a fast and convenient manner. Additionally, unlike other players in the industry, which provide analysis in different fields, the business will specialize in automotive (Ferreira, Marques, Faria, & Azevedo, 2016). Accordingly, it will have profound insight and knowledge in this industry, which will make it offer the best services.
Currently, many service providers provide analytics services to various businesses including those in the automotive industry. The common ones are:
- Cogito Dialog
From the analysis, business process management is vital to the success of companies in the 21st century. In the current information age, the quality of analytics that a company has can determine its success or failure. Usually, business use analytics to make their decisions. Therefore, those with successful information always make the best decisions. Since the business will provide specialized high-quality analytical information on various issues in the automotive industry, its service will have a high demand, which will result in its success. Although the company does not expect to fail, it can still underperform if it fails to win customers who are being served by its competitors or those who also want analytical information of other market segments besides the automotive industry.
In conclusion, today’s manufacturing in the automotive industry is moving towards customer-driven production and knowledge-based manufacturing. These changes are coupled with the reduction in the life cycle, which have increased complexities in process design, product operations, factory deployment, and partnership with suppliers. To overcome this challenge businesses must now use a business process management system that is guided by proper data analytics. Importantly, such a system results in more predictability in workflow, a reduction in uncertainties and manufacturing costs, and proper decision making by the management.
Ferreira, F., Marques, A., Faria, J., & Azevedo, A. (2016). Hybrid process management: A collaborative approach applied to automotive industry. Procedia CIRP, 56, 539-544.
McGarrahan, J., & Harris, M. (2008). Business process management for automotive end of life processes. IBM Business Paper: Business Process Management Series, PP. 1-20. Retrieved from https://www.redbooks.ibm.com/redpapers/pdfs/redp4451.pdf