Introduction
With the trend of ever-increasing data, it doesn’t appear that this growth will be slowing down any time soon, especially for major organizations. The company has to implement bid data initiatives to better manage this data to conduct day-to-day business and anticipate future trends. Big Data was developed on the premise that specialized data could be combined from various sources and extracted from massive data warehouses. Information gathered in this manner can be used in decision-making systems to bolster the worth of intelligent services and expand the scope of research. Examples of Big Data-based instruments in widespread use today include data mining, data analysis, machine learning, and many others. As a result, in this article, we’ll talk about Tesla’s Big Data Initiative.
Tesla Organization Description
Tesla’s meteoric growth from its founding in 2003 to its status as a global commercial behemoth that has made its longest-serving CEO one of the world’s wealthiest people is unparalleled in corporate history. As Tesla Motors, the business set out to transform the automobile industry by developing affordable, environmentally friendly electric vehicles. When Elon Musk was appointed CEO in 2008, Tesla began diversifying its offerings to include renewable energy sources like solar farms. The company has been at the forefront of the electric car industry for several years. However, thanks to acquisitions and its manufacture and invention, Tesla has been more active in sustainable energy production and storage, including batteries (Chen et al.,2019. p.48). Furthermore, the firm has grown involved in the vast industry of buying and selling tax credits, using that money to earn a profit, and becoming further active in a popular secondary market. Most of Tesla’s customers are families with children, young or teenagers. Most of the people in these families are professionals, executives, senior managers, or have other high-paying jobs.
Current Data State
On July 1, 2003, Tesla Motors was founded. The company became a major electric car manufacturer. The corporation designs, manufactures, and sells cars. The company creates 2-5 terabytes of data per week. Putting cameras in cars gathers data. The company’s ultrasonic sensors collect data. The company collects data using forward-facing radar. After using sensors and high-tech cameras, data can be used for machine learning and mapping. Software keeps the data current. The software keeps the company’s data safe for future use. Tesla Motors offers many ways to collect useful data. Company data trains machine-learning and AI machines. The collected data helps improve corporate research, make vehicles function better, and keep customers satisfied.
The corporation uses the data it collects to develop future products. Thanks to its data, the company can forecast and prevent difficulties. Business strategies and data collection are linked in numerous ways. The obtained data helps the organization tackle challenges. Data ensures the business employs successful strategy. Without data, the company can’t succeed. Once the strategies are in place, the corporation can develop good products, increasing sales faster. The company can’t run without data and strategies.
Key Problems or Decisions
Even though Tesla has been known for being a successful manufacturer for over a decade, it still faces numerous challenges that are solved currently and others in future. The major problem that Tesla is facing is cashflow issues that have turned into net losses according to the constant colossal investment in research and development of new vehicles. The Tesla 3, the company’s best-selling vehicle, has been a drain on resources due to the continual production of new units (Bhardwaj et al.,2020. p.83). However, the company’s policy of reducing its price by 8% to make it affordable led to actual cash flow problems. This change led to the employees’ unhappiness as they lacked an incentive for each sale. The company had to lay off some employees because of a cash flow problem.
To boost the profitability of selling affordable vehicles, Tesla had to lay off 7% of its employees in 2018 due to increased employment. According to sources, several Tesla employees were reportedly laid off this year after the company converted many storefronts into museums and visitor centres (Tosesarij,2020). Furthermore, in 2019, roughly eight per cent of the personnel was laid off, resulting in disillusionment among the staff and broken communication due to the attitude of the higher management. The turnover affected the lower team, and there were also terminations in the executive department. Chiang and Chen (2021) state, “Within the past year, the company has lost its chief financial officer, vice president of global recruiting, and general counsel” (para. 10). If a corporation is unable to prevent people from leaving, it raises doubts about the viability of the industry.
Manufacturing was another challenge that Tesla had to face. The company is committed to excellence and invests heavily in the research and development of new cars. Despite having successful quarters every year since 2010, Tesla has never turned a profit for the entire year. The company can’t afford to wait for the Model 3 to begin making a profit because it’s losing money on sales of other models in the meanwhile. According to (Tosesarij,2020), the firm intended to use the proceeds from selling its high-end vehicles to fund the development of more reasonably priced automobiles.
Unanswered Questions
Elon Musk, CEO of the company, is not to be trifled with. He has publicly stated his desire to acquire Twitter and has indicated that he will pay $43 billion in cash to the company’s shareholders. Musk’s admission, part of a filing with the Securities and Exchange Commission, sent shock waves through the political and media worlds (Duffield,2022). However, some conservative pundits have praised Twitter for its purported dedication to maintaining free expression. In contrast, others have warned that removing Twitter’s efforts to restrict harmful content could ignite a fresh rise of disinformation and online harassment. However, with his last action, two major questions remain unresolved.
To begin, we must ascertain whether or not he intends to carry out a hostile takeover with all its attendant risks and repercussions (Duffield,2022). Despite his best efforts, Wall Street is still not convinced by his pitch to acquire Twitter. Speculation abounds on Wall Street over Musk’s ability to pull off the acquisition without disclosing his funding strategy. According to the Bloomberg Billionaires Index, he has an estimated $250 billion, making him the wealthiest person in the world. Even with Musk’s immense wealth, it would be impossible to acquire sufficient funds to purchase Twitter. His principal asset is 172.6 million Tesla shares, while he also has collateralized loans (Duffield,2022). As for his future Twitter endeavours, that is also a mystery.
Tesla priorities
Musk, CEO of Tesla, claims his company is focused on two key areas. It is of utmost importance that all vehicles be delivered to their respective buyers before the end of the year. Priority number two is to dramatically speed up the installation of solar panels (Lambert, 2019). Moreover, the firm focuses on advancing its vehicles to full-time self-driving.
Value of Data
As a manufacturer, Tesla is known for producing state-of-the-art vehicles that employ many innovative features. To further differentiate this model from the competition, Tesla installed its autopilot system. According to international SAE regulations, a level five vehicle’s automated driving system can handle all aspects of dynamic driving in all conditions, including heavy traffic and adverse weather. To that end, Tesla has been working to improve the autopilot technology so that every vehicle it produces has a perfect 5-star rating (Dreme et al.,2017).
An ex-CEO of Tesla says that for self-driving cars to work for just eight hours, they will need 40 terabytes of data. Data is essential to the development and success of autonomous vehicles. So, Tesla Inc. and other automakers like Ford and Audi must collect data to train machine learning models and develop AI for autonomous cars. The company also uses the information collected for research and development and to develop ways to get cars to customers quickly (Dreme et al.,2017). The deadline will also give the company time to plan to speed up and improve the process of installing solar panels, making the company more productive and efficient. Since the data is collected almost in real-time, Tesla can predict problems and fix them before they happen.
Data types and sources
Tesla motor company contains different types of data that the company utilizes for its success. The types of data that tesla motor company uses include weather data, real-time traffic condition data, GPS data, and object map data. The types of data are said to be essential to the company as the company utilizes the data to ensure that no problem occurs in the company. The information comes from the cars and the customers. When a camera is put in a car, the company gets information and the people who use the car give feedback on the product. The customer may decide to give their honest opinion concerning the company’s product once they have utilized the product
Conclusion
Tesla Inc. has made a name for itself as an industry leader by developing and producing electric vehicles equipped with an auto-pilot system. Tesla’s autopilot technology has made considerable progress toward producing an autonomous vehicle, even though it does not yet satisfy the threshold for level 5 autonomous driving established by SAE International. Both a challenge and an opportunity for innovation in the form of big data are presented by the large amount of data produced by Tesla vehicles and uploaded to the Tesla cloud rapidly.
References
Bhardwaj, S., Pandey, R., Sharma, S., Sejal, S., Iyer, G., Sharma, S., Ranjith, P.V. and Kulkarni, S., 2020. Problems Faced by Automobile Industries: Case Study on Tesla. International journal of Tourism and hospitality in Asia Pasific (IJTHAP), 3(2), pp.78-88.
Chen, Y., Chowdhury, S.D. and Donada, C., 2019. Mirroring hypothesis and integrality: Evidence from Tesla Motors. Journal of Engineering and Technology Management, 54, pp.41-55.
Chiang, T.R. and Chen, Y.N., 2021. Why Can You Lay Off Heads? Investigating How BERT Heads Transfer. arXiv preprint arXiv:2106.07137.
Dremel, C., Wulf, J., Herterich, M.M., Waizmann, J.C. and Brenner, W., 2017. How AUDI AG established big data analytics in its digital transformation. MIS Quarterly Executive, 16(2).
Duffield, W., 2022. What Can Elon Musk Do with Twitter?.
Lambert, F. (2019). Elon Musk announces Tesla’s ‘two most critical priorities’ by end of year. [online] Electrek. Available at: https://electrek.co/2019/12/04/tesla-two-most-critical-priorities-elon-musk/ [Accessed 29 Sep. 2022].
Tosesarij, C., 2020. DISCOUNTED CASH FLOW VALUATION OF TESLA INCORPORATED (TSLA) (Doctoral dissertation, Mahidol University).
