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When it comes to the launch of a new vehicle, original equipment manufacturers (OEMs) have many questions about the most effective approach to price a vehicle on the market? What are the most appropriate price positions to be considered to fulfill consumer demands?
Historically, the price was determined by a company’s executive board by taking into account results from clinic studies (a small sampled survey) and a range of factors from their own point of view, not from customers’ perspectives. They often don’t comprehend that buyers are only concerned with how much they want to pay, not with the cost of the vehicle or the improvements made over the vehicle’s previous generation. With a large amount of automotive product and market related data accessible, businesses need to understand a host of factors to arrive at the optimal pricing that satisfies both the OEM and the buyer.
Over the years, massive amounts of data have been gathered, particularly with the development of alternative energy vehicles. However, attempts to analyze, filter, and extract usable information from data sets that are too vast to manage using traditional computation have failed. The majority of the time, OEMs are unsure how to use this information. Adding to the woes of huge datasets in any business is the fact that data is generally housed in different organizations, systems and formats, resulting in redundant and misleading data. In a nutshell, the silo problem looms greater with big data making data processing a challenge. If the data is viewed without considering data governance, big data can be deceptive in decision-making. Additionally, in today’s environment, merely having data is not enough; it is critical to understand the what, why, and how of the data that is available in the business decision-making process.
With more than two decades of global experience in analytics and leadership in both new and used, retail, and fleet markets in the automotive industry, Rose Peng recognized a need for a company that can bring value of interconnected data and data-out-of-data to businesses and their decision-makers. This led her to lay the cornerstone of Piston Intelligence, a leading decision intelligence (DI) company focused on integrating applied data science, social science, and managerial science into decision making.
“We can be a driving force in providing more comprehensive, valuable and insightful services that enable businesses to make decisions that are not only wiser, but also more efficient,” says Rose, founder of Piston Intelligence.
Under the Hood of Excellence
By providing a highly integrated big data system, Piston Intelligence is able to deliver full vehicle lifecycle management solutions and products that can help businesses and OEMs cope with the complexity of making significant decisions.
We can be a driving force in providing more comprehensive, valuable and insightful services that enable businesses to make decisions that are not only wiser but also more efficient
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