Bentley Motors, a globally recognized luxury car brand, was facing a significant challenge in the wake of the automotive industry's unprecedented changes. The company, known for its bespoke luxury cars, realized the need for a transformation to ensure its long-term success. This transformation was not only about switching to an all-electric portfolio of vehicles by 2030 but also about implementing effective digital transformation throughout the company. The goal was to streamline operations, improve customer service, and solidify Bentley's position as a global automotive leader. The company also aimed to enhance its customer experiences, which are a key hallmark of Bentley, through a more data-driven approach. However, the challenge was to find a solution that could help them achieve these goals.

BMW Group Germany, one of the largest commercial enterprises in Germany, was facing significant data challenges. The company was dealing with multiple data sources, databases, and in-house systems, making it difficult to collate, analyze, and visualize information effectively. Employees were conducting their own isolated analytics and reporting, leading to data discrepancies. The senior leadership team recognized the need for a unified analytics platform that would provide a 360-degree view of data, support data-driven decision-making, and foster cross-functional synergies within the company.

Anadolu Sigorta, Turkey's first national insurance company, was facing challenges in identifying and investigating fraudulent claims, a process that was extremely time-consuming and detracted from their ability to serve genuine claims efficiently. The company was dealing with disparate data sources, legacy systems, and manual work processes, making it difficult to identify and eliminate fraudulent claims. Additionally, as a 95-year-old company, Anadolu Sigorta had many legacy systems and applications throughout the business, creating a fragmented ecosystem that was hard to work with. They had multiple production environments for the same process, leading to problems with data quality, reliability, and effective governance. The company also faced cultural challenges, with employees and external distributors resistant to modern data visualization trends.

Belcorp, a Latin American beauty corporation, faced a significant challenge due to the COVID-19 pandemic, economic turmoil, and drastic changes in consumer behavior. The company, which operates in 13 different countries, had to rethink its line of beauty products and business model that had been in place for the past 53 years. The pandemic also posed a challenge to Belcorp's traditional direct selling model, as face-to-face interactions were no longer possible. The company had to quickly adapt to these changes and find a way to continue its operations and maintain its growth. The challenge was not only to survive the crisis but also to take advantage of it and transform the business to become more digital and consumer-centric.

Belcorp, a leading beauty and cosmetics company in Latin America, was facing a challenge in its business intelligence model. The company was struggling with a high demand for business cases and was seeking solutions to empower its business areas and generate immediate responses to questions that previously took weeks to address. The traditional BI model was not serving the company's needs, and there was a need for a tool that could introduce the Self Service BI concept at Belcorp. This was part of the digital transformation initiated by the company's CTO & CDO, Venkat Gopalan. The company was also looking to involve its business areas in the selection of the new BI tool, a first in the company's history.

Bridgestone Sales Thailand, the local trading business for Bridgestone, was facing challenges with its data analysis process. The teams were heavily reliant on spreadsheets for data analysis, which had its limitations. The process was time-consuming, taking two to three hours to extract insights from data. The data had to be consolidated from different sources, including Bridgestone’s ERP, which added to the complexity and inefficiency of the process. The company was in need of a solution that could streamline this process, make it more efficient, and enable informed decision-making in line with the corporate philosophy of Bridgestone.

Clintel identified a growing need in drug development: enabling clinical development organizations to comply with FDA draft guidance on risk-based monitoring principles. They saw the potential to develop easy-to-use tools that could also improve quality and significantly reduce costs. The FDA advocates alternatives to regular, frequent onsite visits and verification of all data, which involve costly travel and provide little added benefit. Instead, they recommend approaches that identify risks to patient safety by utilizing critical data elements gathered in clinical data systems as a method of determining which sites warrant additional attention from clinical research associates (CRAs). The problem lies in getting that information to the right people at the right time, and in their language. Despite these issues, spreadsheets have become the default report technology for many business users because they have simply had no other option.

AREVA Group, a renewable energy company, was looking for a tool to help present data to their executive committee. They needed to analyze and visualize data to strategically meet the demand for delivering more wind turbines. The initial project that Tableau helped them to analyze was the production of 100 windmills a year at their plant. They needed to know when a 2nd and 3rd plant would be needed. They asked themselves when should they build? Where will they build? How many jobs will they create?

American Family Insurance (AmFam), a private mutual insurance company, faced challenges in providing data support to its local and regional agencies. These agencies, organized as independent contractors, are a crucial part of the AmFam data ecosystem, utilizing corporate data to optimize their sales and customer service contributions. However, the existing system was siloed and offline, making it difficult for agencies to access and analyze data. AmFam sought to improve the delivery of analytics to its agents, particularly around product availability, performance metrics, and expected business results. The challenge was to replace the siloed data sources and offline workflows with a secure portal that integrates insights into existing user interfaces (UI).

PT Bank Rakyat Indonesia (BRI), one of the largest banks in Indonesia, was facing a significant challenge in its data analytics process. The bank, which is data-driven in its approach, was struggling with a centralized system where data analytics was considered a task for the IT department only. Business teams had to put in a request to IT every time they needed a new report or dashboard, and then wait up to four weeks for a response. The reports and dashboards were prepared using complex queries and coding, which often led to requests for changes and further delays. In some cases, the dashboard was no longer required by the time it was complete. BRI wanted to enable faster delivery of data to business teams and build a foundation for self-service analytics.

Basware, a global provider of SaaS solutions, helps businesses digitize their financial processes to drive compliance, facilitate better process automation, and optimize overall data quality. The company supports over 2,500 customers across more than 175 countries. However, the challenge was to provide these customers with a complete overview of their financial data, from procurement-to-payment (P2P), via a single, central platform. The goal was to enable customers to make faster, more informed decisions and streamline payment processes. The ongoing COVID-19 pandemic further emphasized the need for organizations to have complete visibility of both direct and indirect spending, making accurate analytics essential.