Investments In Technology Increasing Investment Thesis

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Investments in Technology

Increasing Investment in Gasoline Production

As a leader of any corporation or organization that faced the decision of whether or not to invest in the continual improvement of processes and systems that would make gasoline production more efficient, I would. In making this decision, the fluctuation in gasoline prices attributable to the unique oil market dynamics would be of secondary concern relative to the streamlining of the value chain the entire industry is based on. From the initial mining and exploration to the refining and sales of oil-based products including gasoline, there is significant room for improvement at the process and system level. Concentrating on process flow-based manufacturing analysis there are many opportunities in any company to see significant gains from business process management and business process re-engineering (Lin, Fan, Newman, 2009). These gains in efficiency can be driven first through process improvement and re-engineering with technologies integrated into these processes secondarily. By taking this approach the processes themselves will be as efficient and automated as possible. Take for example investments in quality management as part of the industry-wide supply chain. Process re-engineering of these areas could dramatically reduce the amount of shortages and overages in the supply chain of not only gasoline but the key chemicals and raw materials necessary for its production. Second, the processes of gasoline refining could be made more efficient through process re-engineering and then automated to make them more cost effective over time. The bottom line is that the fluctuations in gasoline prices should not be a decision factor in investing in improving gasoline production efficiency. Rather, the continual pursuit of greater efficiencies in the entire process of gasoline production must first be considered if the entire industry is going to stay profitable and have the potential for longer-term growth. (Lin, Fan, Newman, 2009)

Huiping Lin, Yushun Fan, Stephen T. Newman. (2009). Manufacturing process analysis with support of workflow modelling and simulation. International Journal of Production Research, 47(7), 1773. Retrieved March 6, 2009, from ABI/INFORM Global database. (Document ID: 1645330821).

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