Big Data Analytics – How does it help the automotive industry?
Continuous development of technologies is inevitably causing a transformation within the ecosystem of the automotive industry.
The increasing demands from consumers coupled with diverse technological features has arguably made decision making a tough process within the automotive industry.
However, with the availability of big data analytics, decision making can be made easier.
These are ways Big Data Analysis can help the automotive industry:
- Maintains smooth flow between links in the supply chain
- Auto manufacturers use huge amount of data from various systems such as Dealer Management System (DMS), Customer Relationship Management (CRM) and customer-satisfaction surveys to gather metrics on numerous values ranging from customer inquiries, sales, inventory levels, customer order patterns on various models to trims and colours selection.
- This process enables manufacturers to understand what their customers actually want in a particular vehicle.
- In addition to that, the data collected allows suppliers to ensure availability of materials needed to manufacture components that customers find appealing.
- Enables strategic marketing planning
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- Other than manufacturing, the automotive industry is also known as a platform for huge businesses.
- Huge sums of money have been invested into the automotive industry and it is only set to increase in value.
- Thanks to the data collected through marketing mix analysis, comprehensive evaluation of customer responses and internal business operations, big data analytics is helping auto manufacturers to strategically manage the use of incentives, rebates, financing deals and other key-attractions in increasing sales and return of investments (ROI).
- R&D made easier
- The designing and engineering process of developing new vehicles involves a lot of decision-making dilemmas, often leading to the waste of time and money.
- Let’s take this scenario as an example – a model in development may have a certain feature used in existing models, for example, a door lock function button.
- If the manufacturer leverages on data monitoring and analytics from industry customer-satisfaction studies, its dealership service departments and its own internal research, concerns with that button based on existing models can be recognised.
- This approach allows designers and engineers to avoid repeating the same mistakes, hence saving time and money.
- The data sample can also enable the manufacturer to smoothen the operational proves, which allows for a more accurate material procurement, manpower planning and vendor coordination.
- Being Data Friendly means being Future-proof
- Think of data as a tool to future-proof the automotive industry – it is a significant enabler of the latest advances in the development of autonomous vehicles.
- The technology behind self-driving cars is machine learning or, Artificial Intelligence (AI).
- A machine “learns” to keep passengers safe through continuous research and development, all facilitated by data collected from real-world driving conditions, environmental study, and so on.
- According to the Center for Automotive Research (CAR), one of the recent applications of big data analysis involved the assessment of cost and effectiveness of powertrain technologies developed to meet global standards in fuel economy and greenhouse gas emissions.
- The research found that there exists discrepancy between what automakers and regulators project it to be when it came to the cost of meeting those standards.
- This shows that data, in addition to being a tool in guiding manufacturers towards meeting these regulations, data also has the ability to inform regulators and policymakers as they make decisions going forward, which could benefit automakers in the long run.
As stated in the article above, the possession of data is not sufficient to ease decision making processes.
Data acquired must also be analysed in order to make full use of its potentials. With the development of autonomous vehicles, connected mobility and artificial intelligence, now is the best time to enable the application of big data systems.
This will not only future-proof the automotive industry but will also be a game changer as to how vehicles are perceived.
It is a revolution.