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Building cars in a changing world: Audi’s Integrated Approach with IBM Planning Analytics

Building cars in a changing world - Audi’s Integrated Approach with IBM Planning Analytics

Audi, a renowned German automobile manufacturer, stands proudly as a symbol of luxury, performance and cutting-edge automotive technology. Founded in 1909, Audi has evolved over the years into a global leader in the automotive industry. The brand’s iconic four interlocking rings represent the merger of four independent carmakers in 1932, solidifying Audi’s commitment to excellence and unity.

Audi is known for its meticulous attention to detail, elegant design, and unmatched engineering. These qualities have earned them a dedicated following worldwide. However, the Audi team acknowledged the growing difficulty in developing a successful solution for integrated planning, given the unpredictable and multifaceted influences affecting the modern business landscape.

In a world marked by volatility, uncertainty, complexity, and ambiguity (VUCA) building a holistic planning environment is inevitable for successful steering.” Integrated Planning Team @Audi

These include CO2 emissions regulations, the COVID pandemic, and driving bans in Europe. Additionally, there’s a push towards electric vehicles, competition from other brands and countries, and existing internal company solutions.

The search for a comprehensive solution for a complex process

As a manufacturing organization, they faced numerous challenges in their contemporary setting. According to the Integrated Planning Team at Audi: “Complex planning can’t be done in an efficient way in Excel.” As they faced the issues of complexity and efficiency, Audi attempted to mitigate these problems by using analytics and other platforms.

Previously, Audi was confronted with the absence of an efficiently integrated, across-the-board solution for planning and analytics. To manage its multifaceted operations, it was critical for the company to ensure that as many as possible individual business entities within the organization were operating from a uniform base. This meant utilizing the same integrated planning infrastructure. It was equally important that this infrastructure contained consistent metadata and data structures across all entities, preventing data redundancy and streamlining processes.

The primary goal of adopting a planning and analytics solution was to link data and processes across departments. This aimed to improve communication, speed up decision-making, and boost efficiency.

Different departments have varied needs and priorities, so agreeing on a single data structure that would suit everyone’s needs was a challenging task. However, overcoming this challenge was crucial to the successful implementation of the Planning Analytics solution and its benefits throughout the company.

Implementing IBM Planning Analytics: One integrated planning platform

To address these complexities and revolutionize their planning practices, Audi turned to IBM® Planning Analytics. This solution helped to improve Audi’s business planning and analytics practices. Up to this point, reaching a unified, cross-business view for short- and long-term planning was a time-consuming, inconsistent and error-prone process.

Recognizing the need for a comprehensive solution, Audi embarked on a two-phase development and deployment strategy.

  • In the first phase, the team established and scaled the “One Integrated Planning Platform”. They found synergies through a uniform IT governance and support structure.
  • In the second phase, they expanded the integrated planning. This was done by incorporating mathematical optimization and machine learning algorithms, completing the holistic approach for more efficiency.

This two-phase plan offered a structured yet flexible approach, meeting Audi’s unique needs while ensuring efficiency and accuracy in planning and analytics.

Working closely with Audi’s stakeholders, the Integrated Planning Team and its development partners customized solutions for each department’s planning needs. They pinpointed ten distinct use cases, like sales planningfinancial planning and reporting.

The solution’s most valuable feature is its comprehensive planning capabilities. IBM’s Planning Analytics powerful engine (TM1) allows the use of multiple data cubes to operate in one application. A data cube is a multidimensional model of data for the purpose of performing analysis. This structure enables complex analytical and ad-hoc queries with a rapid execution time. The platform also makes transferring data between department applications easy, which is vital to achieving efficient planning continuity.

Managing complexity more effectively

With the implementation of Planning Analytics Audi has seen considerable improvements and benefits. The most significant advantage has been the ability to handle more complex analyses and planning, which previous systems couldn’t do. The Planning Analytics Workspace (PAW) has become the preferred interface, and the number of users, which currently stands at several hundred, continues to grow steadily.

Using analytics, has enabled Audi to delve into complex planning and analytic tasks. Over time, the handling of these tasks has consistently improved, a development that has been appreciated by many users.

For organizations that are considering implementing Planning Analytics or similar solutions, understanding different planning tools is key to helping them find the best fit. Having a clear objective for what they aim to achieve with their planning platform is also crucial. Without a well-defined goal, there’s a risk of the platform developing in a direction that may not align with their needs or expectations.

Smooth operations and enhanced user experience

Going forward, Audi’s primary focus is addressing system bugs quickly to reduce user disruption. As they expand their use of Planning Analytics within the organization, their aim remains operational excellence.

The platform’s proactive monitoring, intuitive interface and data visualization capabilities ensure prompt issue detection and resolution. This commitment underscores Planning Analytics’ role in smooth operations and streamlined problem-solving.

Audi’s journey serves as a guiding example for organizations navigating the labyrinth of complex planning and decision-making. Implementing flexible, powerful solutions like IBM Planning Analytics not only brings structure but also makes business processes smoother, faster and smarter. Breaking free from outdated practices and embracing innovative change helps businesses thrive.

The story of Audi’s success shows the power of using the right solutions and strategies. They started early, set clear objectives and tailored solutions to their needs. This reshaped Audi’s planning and analytics operations, boosting efficiency and productivity. Their journey encourages others to turn challenges into opportunities for growth and innovation, creating their own unique narratives of success.


Source: Building cars in a changing world: Audi’s Integrated Approach with IBM Planning Analytics – IBM Blog


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