Published on: April 26, 2025 / Updated on: April 26, 2025 – Author: Konrad Wolfenstein
Failed large-scale IT projects: Why individually tailored IT solutions with AI are becoming increasingly important for the future – Image: Xpert.Digital
The key to digital transformation: Adaptable and customized AI solutions
Why tailored AI solutions will shape the future of businesses
Digital transformation presents companies with enormous challenges. In a constantly changing world, the ability to adapt quickly and implement innovative solutions is crucial for success. One IT area where this is particularly evident is the implementation of Enterprise Resource Planning (ERP) systems. In the past, many companies have had painful experiences with failed large-scale ERP projects. These failures highlight the need to rethink traditional approaches and instead rely on customized solutions powered by artificial intelligence (AI).
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The Failure of ERP Giants: A Warning
The list of failed large-scale ERP projects in Germany is long and painful. Companies from a wide range of industries have invested millions and still missed their targets. Some of the most prominent examples are:
Lidl
The discount retailer wanted to implement a customized merchandise management system called “Elwis,” which was intended to revolutionize its processes. However, after seven years and investments of around €500 million, the project was halted. The reasons were manifold: exploding costs, insufficient benefits, and massive complexity problems that turned the project into an uncontrollable monster.
Haribo
The introduction of a new SAP system was intended to optimize production and increase efficiency. Instead, significant problems arose, leading to delivery failures and lost revenue. The transition proved considerably more complex than anticipated, and the company struggled with initial difficulties that undermined confidence in the project.
Otto
The mail-order company planned to standardize its IT landscape with “Passion for Performance”. The project was considered the largest IT undertaking in the company's history, but failed due to its immense complexity and internal resistance.
German postal service
The “New Forwarding Environment” project aimed to introduce a new IT system to increase the efficiency of logistics processes. After a total investment of €345 million, the project was cancelled in 2015 because the set goals could not be achieved and costs spiraled out of control.
Deutsche Bank
The SAP project “Magellan” for the integration of Postbank was intended to create synergies and increase efficiency. After costs of €1.6 billion, the project was discontinued in 2015 because the strategic goals changed and the implementation proved too complex, leading to significant delays and additional costs.
Liqui Moly
The implementation of Microsoft AX failed due to several factors, including a lack of process experts and insufficient project transparency. Management publicly expressed their frustration with the failed implementation, which had cost the company considerable time and money.
These examples clearly demonstrate that ERP projects do not always lead to success. They illustrate the risks associated with the implementation of complex, monolithic systems.
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The Roots of Failure: Typical Mistakes in ERP Projects
The reasons for ERP project failure are varied and recurring across industries. Understanding these errors is crucial for avoiding them in future projects
Poor planning and unclear goals
An ERP project without clear goals is like a ship without a compass. Missing or imprecise goal definitions lead to misunderstandings, false expectations, and ultimately a project that loses its way.
Insufficient resources and a lack of process experts
ERP projects require an interdisciplinary team with experts from various fields. Often, qualified key users and process experts are lacking, or they are brought into the project too late, leading to poor decisions and delays.
complexity
Too many individual customizations increase the complexity of the standard system, drive up costs, and make maintenance more difficult. It is important to find a balance between standard functionalities and individual customizations.
Lack of acceptance and support
Implementing a new ERP system is a change management process that requires the support of all stakeholders. Employee resistance and a lack of support from management lead to delays, conflicts, and ultimately, project failure.
Lack of transparency and control
An ERP project requires effective project controlling to monitor progress, identify risks, and initiate countermeasures early on. A lack of project controlling and unclear responsibilities make managing the project more difficult and increase the risk of failure.
Technical and organizational overload
Large ERP projects often overwhelm the organization and exceed time and budget constraints. It is crucial to realistically assess the project's complexity and plan resources accordingly.
The paradigm shift: Why individually tailored AI solutions are the answer
Experience from failed large-scale ERP projects shows that classic, monolithic systems are often too rigid and inflexible to keep pace with the dynamic demands of modern businesses. This is where customizable solutions with artificial intelligence (AI) are increasingly coming to the fore. These solutions offer companies the opportunity to optimize their business processes, increase their efficiency, and strengthen their competitiveness.
Automation and process optimization
AI can automate routine tasks, minimize errors, and make processes more efficient. For example, AI can be used in invoice processing to automatically capture, validate, and post invoices. In warehouse management, AI can be used to optimize inventory levels, automate picking processes, and reduce delivery times.
Data-driven and predictive decisions
AI-powered ERP systems analyze large volumes of data in real time, identify patterns, and deliver well-founded forecasts for production, sales, or maintenance. For example, AI can be used to predict product demand, optimize production plans, and proactively schedule maintenance.
Flexibility and scalability
Modern, AI-powered ERP solutions are modular and can be flexibly adapted to individual business processes and industry-specific requirements. This allows companies to tailor the system to their specific needs and expand or reduce it as required.
Improved user experience
Digital assistants and chatbots enable more intuitive operation, faster responses, and greater user acceptance. For example, employees can use chatbots to ask questions about business processes, retrieve information, or complete tasks.
Continuous optimization
AI learns from past events and continuously adapts processes, enabling constant improvement and adaptation to market changes. For example, AI can be used to optimize marketing campaigns, dynamically adjust prices, or develop new products.
Fulfillment of regulatory requirements
AI supports compliance with regulations and data protection requirements through automated monitoring and documentation. For example, AI can be used to detect suspicious transactions, prevent data breaches, or prepare for audits.
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The advantages of AI in detail
Beyond the points mentioned above, AI offers a multitude of other advantages:
personalization
AI enables companies to personalize their products and services and tailor them to the individual needs of their customers.
innovation
AI can help companies develop new products and services and establish innovative business models.
competitiveness
AI can help companies strengthen their competitiveness and stand out from the competition.
Increased efficiency
AI can help companies increase their efficiency and reduce costs.
Risk management
AI can help companies identify, assess, and minimize risks.
The challenges of implementing AI solutions
Although AI offers many advantages, there are also challenges in implementing AI solutions:
Data quality
AI systems require large amounts of high-quality data to function effectively. Companies must ensure that their data is clean, complete, and up-to-date.
skilled workers
Implementing AI solutions requires specialists with specific knowledge and skills. Companies must invest in the training and further education of their employees or bring in external experts.
Cost
Implementing AI solutions can be costly. Companies must carefully calculate the costs and ensure a positive return on investment (ROI).
acceptance
The introduction of AI solutions can lead to resistance from employees. Companies need to involve employees in the process early on and educate them about the benefits of AI.
The future belongs to intelligent, tailor-made solutions
The high failure rate of large-scale ERP projects clearly demonstrates that traditional approaches are reaching their limits. Customized, AI-powered ERP systems offer companies the flexibility, efficiency, and innovative strength required for successful digital transformation and sustainable competitiveness. Companies that embrace AI can optimize their business processes, better serve their customers, and gain a decisive competitive advantage. The future belongs to intelligent, tailored solutions that help companies thrive in a constantly changing world.
It is important to emphasize that implementing AI solutions is not automatic. Companies must prepare carefully, select the right partners, and actively address the challenges. If they do so, they can fully leverage the benefits of AI and successfully manage their digital transformation.
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Konrad Wolfenstein
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