FAW Volkswagen

Tableau Helps Faw-Volkswagen Upgrade Management And Improve Productivity, Empowering Digital Transformation of The Traditional Automobile Company


Tableau is easy to use for everyone, motivating employees to engage in data analysis and build up confidence in analyzing business data conveniently and efficiently.

It simplifies the data analysis workflow, saves human resource and time cost, and allows the employees to focus on mission-critical business.

It enables visualization of daily work reports, helping organizations capture opportunities and the future. Dig out the potential value in data to give powerful insight for marketing plans and job arrangement.

FAW-Volkswagen Automotive Co., ltd. ("FAW-Volkswagen")is a joint venture and a large passenger vehicle maker, owning 3 major brands: Volkswagen, Audi, and Jetta. After 30 years' development, FAW-Volkswagen now has production capacity in several major provinces and cities in China, with 6 saloon car factories, a powertrain business unit, and a stamping center. Noticing that accelerated digital transformation has became an inevitable trend in the post-covid times, FAW-Volkswagen accurately seized the emerging opportunity and decided that it should further open up and embrace changes in data utilization and data potential releasing. This is why the company introduced and encouraged use of Tableau to facilitate data-based communication and data-driven decision-making.

With Self-Help Data Analysis, Tableau Improves Productivity And Analysis Autonomy

Pushed by the wave of digital transformation, traditional industries represented by vehicle manufacturers are facing a landscape that changes quickly. They generate and come into contact with tons of data during operation and management. However, as automobile makers are generally running in the traditional way, their data assets are excluded from business conversion. With this background, digging out useful information from the data and empower added business value has become an important topic as for FAW-Volkswagen to maintain their core competitiveness.

FAW-Volkswagen realized that to maximize the value of data resource, automobile makers need the hand of a great business intelligence (BI) assistant. As a result, they introduced Tableau in 2015 and has been extending deployment and promoting adoption since 2018, under the support of DKM ECO, a Tableau distributor. Tableau was favored by FAW-Volkswagen for its ease of use and friendliness to beginners when they were choosing the right BI platform. Since Tableau is easy to use, they could analyze their data conveniently without having to recruit data professionals, and this advances digitalization of the company.

DMK served as a housekeeper during the process, providing tailored technical support and services, while making suggestions based on the current state, helping them to build up an internal community and service system.

Tableau is used by FAW-Volkswagen in marketing and sales of Audi, Volkswagen, and Jetta cars, to visualize daily work reports. Their people use Tableau to analyze sales data, so that they get and insight of monthly and quarterly sales, to figure out how to increase sales volume, save cost and improve productivity. Previously, 90% of FAW-Volkswagen workers use traditional data analysis methods, which required a lot of repeated operations and provided poor visualization. It was very difficult to improve efficiency. For example, analyzing data collected from training sessions required a whole week's work of 2 people. Using Tableau, each of them were able to save 2-3 days, reducing 50% of working hours.

Assisted by Tableau, FAW-Volkswagen's business workers could carry out self-help data analysis, allowing IT to focus on platform deployment and administration, instead of struggling with specific operations. The workers can get an insight of the business by understanding data and the information behind. With the capability to explore data, the company managed to optimize their workflow and free human resource, and now, their productivity and management are on a new level.

Help Employees to Develop A Data Analysis Mindset Based on Tableau, to Optimize the Production Process And Focus on Details During Implementation

Digital transformation evolves all respects of an enterprise, which means relying on a few data specialists is not enough. They need to help employees to build up a data analysis habitat, to get used to think about data, and to figure out solutions based on data. Tableau does not require data background and provides powerful visualization, which satisfies the company's rigid demand of urgent digital transformation. FAW-Volkswagen recognizes Tableau as an excellent data analysis platform, for it provides prospective modern BI analysis capabilities to facilitate digital transformation.

As a result, more and more FAW-Volkswagen employees started using Tableau for data analysis. Tableau inspires data-based thinking, so the employees are now making data-driven decisions everyday. The company managed to optimize workflow of the production units, assign production activities and focus on details, to improve productivity and empower digital transformation.

Great organizations must use and understand data, and that's what we do. Tableau encourages business users who don't have a technical background to analyze data by themselves, which is highly efficient and agile, helping business units to reduce cost while improve productivity. Practicing and carrying on Tableau's learning and analysis mindset, they developed a data culture and abundant data masters, preparing human resource for digital transformation.

At first, Tableau was only applied at a small scale, in Audi dealerships. As the outcome owned accumulated credit, it was gradually rolled out to most FAW-Volkswagen dealerships. Three years later, FAW-Volkswagen had been working with Tableau to hold in-house training camps, to help employees build up and develop data analysis skill sets. The FAW-Volkswagen Academy also used Tableau to analyze how much the students learned in each empowerment project, to improve course quality. Data source of the Academy were spreadsheets exported by multiple business units from multiple platforms. With Tableau, more than ten thousand pieces of data from 20+ business units were analyzed each day, and the average daily page views (PVs) reached 10000+.

More than 2000 employees engaged in deep learning through data analysis camps, and now, there are 400+ frequent users and 30+ BUs use data analysis powered by  Tableau to optimize and improve their workflows. As FAW-Volkswagen's important self-help BI platform, Tableau was utilized and promoted by various BUs; it changed how employees think about data.

Tableau Drives Business Decisions, Facilitates Cost Saving and Productivity Improvement, Helping Enterprises to Gain An Competitive Edge

Digital evolution is changing the competition landscape of the manufacturing industry, leaving the mainstay of manufacturing, automobile makers, to ever-changing opportunities and challenges.  FAW-Volkswagen believes that data analysis can help with workflow optimization effectively, and it enables the company to discover and solve problems, in addition to conducting business and improving management. As a self-help data analysis platform, Tableau is there with every employee as they grow, helping the organization to get a head start.

For example, during the covid-19 pandemic, employees were not able to work together at one place, and work from home brought some inconvenience to the business. Tableau helped the company to breakthrough geographical limitations. They brought up an online business system, and got a head start. Using the daily analysis platform, employees could publish monitoring reports they developed to the server, allowing their colleagues to remotely sign in to share and view the production data, so that everyone could get on the same page in time.

Beside, Tableau Dashboards drove many important decisions at FAW-Volkswagen, especially during workshop production downtimes and vehicle selling. The Audi Claim Team used to have 8 people work for 8 weeks to analysis the massive data. In 2020, the team turned to Tableau,  analyzed data in regard with dealership and component failure by 13 metrics. Tableau analysis brought forward the company's strategic adjustment, contributed to cost saving of more than 10 million CNY. Besides, the Audi Claim Team also used Tableau to build up an agile analysis system, saving 4 hours for analysis each weak, allowing them to predict custom claims and provide better service for the customers even before claims really happen.

Jiang Hongbo from the Training Strategy And Management Department at FAW-Volkswagen said, "Great organizations must use and understand data, and that's what we do.Tableau encourages business users who don't have a technical background to analyze data by themselves, which is highly efficient and agile, helping business units to reduce cost while improve productivity. Practicing and carrying on Tableau's learning and analysis mindset, they developed a data culture and abundant data masters, preparing human resource for digital transformation."

As digital transformation becomes an inevitable trend of the future of manufacturing, traditional automobile companies including FAW-Volkswagen are seizing emerging opportunities, and prepared to cope with every opportunity and challenge with unmatched keen insights. Tableau data analysis activated FAW-Volkswagen's data assets and enabled data-driven decisions, which improved the agility of the company's business and operation management.  FAW-Volkswagen believes that Tableau will help more organizations to build up their data culture, lay a solid foundation for digital transformation, and improve industrial competence.

 

DKM ECO  is devoted to provide comprehensive solutions including business intelligence, data integration, and big data platforms for international and local companies in the Greater China.Our customers from Retail, Healthcare, Communications, Finance, High-Tech has benefited from these services and seen improvements in business revenue and profit.