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Cloud computing involves collecting data from multiple sources to a centralized location. This data is used by data mining tools to try and get critical analytical information on organization performance. The first move that Volvo took towards making a cloud infrastructure was purchasing a 2-node Teradata warehouse in 2007.
Data about each vehicle on its operations and the warrant is stored in this warehouse. The dealer shops worldwide are networked to the data warehouse to provide data collected on vehicles.
Every vehicle has a chip integrated into its engine and some software that collect data. Once the vehicle is taken to the dealer shop data is read and transmitted to the data warehouse through the internet.
Data collected from the fields need to be analyzed to help decision makers within the corporation to make the right decision. Correct data analysis tools provide the best information on the car market and problems facing consumers.
Mechanical problems are discovered early enough before the release of more vehicles into the market. An example would be launching a new vehicle with an automatic gear box. Such vehicle might have errors that are not noticed during factory testing period which might arise upon its launch.
The clients’ vehicles having devices that are continuously collecting data on the status of the gear box would display errors in the gear box. The discovery of the problem might be noticed after selling the first 1000 vehicles which might be easier to rectify.
Rectification will be carried on the cars waiting to be sold before reaching the intended market (Global Intelligence for the CIO, 2011). Volvo has been able to analyze data to establish changing taste of clients on vehicle types and brands.
The data is used to come up with new brands within the company that will meet customers’ satisfaction. All this information on causes of accidents on vehicles and market changes trend is knowledge to Volvo Car Corporation.
Volvo adapted the Teradata system in its warehouse to automate data analysis. The system enabled the company to integrate data on vehicle life cycle, warranty and design. The integration helps in diagnosing the root problem of a mechanical problem within the engine leading to development of satisfactory solutions.
The company has been able to identify the rate in which a certain problem keeps on occurring in different vehicles. The rate of occurrence will help in identifying what problems clients keep on facing and what might be the root cause.
The system is able to store data on the geographical location of the vehicle, and it can match mechanical problems with different geographical locations (Tobey, 2010). This is important because vehicles in China might be facing different problems from those vehicles in the United State of America.
Matching problem with geographical location will allow the company develops solutions that will solve problems for specific regions. The system is able to prioritize issues according to their fatality and need of response.
Prioritization of issues will allow management to decide on what problems to solve first followed by what. The system is able to hasten the process of problem solving within the organization. Lastly the system has provided corrective measures to the problem in the design and production of vehicles.
Volvo corporation collecting huge data on diagnosis and market gives it an advantage compared to its competitors. Consumers would like to drive vehicles that are fuel efficient and safe to drive. Safety comes first, where the company’s vehicles are diagnosed to identify causes of accidents.
The diagnosis and data collected by the Teradata system provide corrective measures early before more problems occur. Companies’ without data on their vehicles will continue making mistakes leading to loss of clients. Profitability of the company will increase with increased sales generated by having good products.
Teradata system has led to reduction in cost of storing and sorting data within the company. The money saved on data storage can be invested in other business related issues like improving on quality of vehicles. Data on changing consumer preference will allow the company to improve on production.
The system is able to show which vehicles customers purchase according to geographical regions. The data will enable the company to know what vehicle to export to which market. The company will not deliver to a market in Africa 1000 vehicles while such a vehicle has never been purchased in that market.
The data from the market can be used to determine which market requires new marketing strategies to improve on sales. Companies without such data will not make decisions regarding their markets in real times (Mueller, 2010).
The company ability to solve customers’ problems on real time will keep it ahead in the market. Customers will prefer a company that will solve their problems with minimum time to allow them continue enjoying their vehicles.
References
Global Intelligence for the CIO. (2011). Converting data into business value at Volvo. Web.
Mueller, E. (2010). Agility: Competing and Winning in a Tech-Savvy Marketplace. Wiley: New York.
Tobey, B. (2010). Teradata Magazine Online, Volvo Car Corporation realizes core values through data-driven decision making. Web.
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