Failed IT major projects: why, individually adapted IT solutions with AI are becoming increasingly important for the future-picture: xpert.digital
The key to digital transformation: adaptable and individual AI solutions
Why tailor-made AI solutions will shape the future of companies
The digital transformation presents companies with enormous challenges. In a world that is constantly changing, the ability to adapt quickly and implement innovative solutions is crucial for success. An IT area in which this becomes particularly clear is the implementation of Enterprise Resource Planning (ERP) systems. In the past, many companies have had painful experiences with failed ERP major projects. These failures are highlighting the need to rethink traditional approaches and instead rely on individually adapted solutions with artificial intelligence (AI).
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The failure of ERP giants: a warning
The list of failed ERP major projects in Germany is long and painful. Companies of a wide range of industries have invested millions and still miss their goal. Some of the most prominent examples are:
Lidl
With “Elwis”, the discounter wanted to introduce a tailor -made merchandise system to revolutionize its processes. However, the project was stopped after seven years and investments of around 500 million euros. The reasons were diverse: exploding costs, too little benefits and massive complexity problems that made the project an uncontrollable monster.
Haribo
The introduction of a new SAP system should optimize production and increase efficiency. Instead, there were significant problems that led to delivery failures and loss of sales. The changeover turned out to be much more complex than expected, and the company fought with start -up difficulties that undermine trust in the project.
Otto
With “Passion for Performance”, the mail order company planned the standardization of his IT landscape. The project was considered the largest IT project in company history, but failed due to immense complexity and resistance within the company.
German postal service
With the “New Forwarding Environment” project, a new IT system should be introduced to increase the efficiency of the logistics processes. After investing a total of 345 million euros, the project was canceled in 2015, since the goals set could not be achieved and the costs were out of hand.
German bank
The “Magellan” SAP project to integrate Postbank should create synergies and increase efficiency. According to costs of 1.6 billion euros, the project was discontinued in 2015 because the strategic goals changed and the implementation was too complex, which led to significant delays and additional costs.
Liqui moly
The introduction of Microsoft AX failed, among other things, due to missing process experts and a lack of project transparency. The management publicly expressed its frustration with the failed implementation that the company had cost a lot of time and money.
These examples clearly show 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 errors in ERP projects
The causes of the failure of ERP projects are diverse and are repeated across industries. It is important to understand these mistakes to avoid them in future projects:
Poor planning and unclear goals
An ERP project without clear goals is like a ship without compass. Missing or imprecise target definitions lead to misunderstandings, wrong expectations and ultimately to a project that loses its direction.
Inadequate resources and missing process experts
ERP projects require an interdisciplinary team with experts from different areas. Qualified key users and process experts are often missing, or they are integrated into the project too late, which leads to wrong decisions and delays.
complexity
The introduction of a new ERP system is a change management process that requires the support of everyone involved. Resistance of the employees and the lack of support from the management lead to delays, conflicts and ultimately to the failure of the project.
Lack of acceptance and support
The introduction of a new ERP system is a change management process that requires the support of everyone involved. Resistance of the employees and the lack of support from the management lead to delays, conflicts and ultimately to the failure of the project.
Lack of transparency and control
An ERP project requires effective project controlling to monitor progress, identify risks and initiate countermeasures at an early stage. A lack of project controlling and unclear responsibilities make it difficult to control the project and increase the risk of failure.
Technical and organizational overwhelming
Large ERP projects often overwhelm the organization and blow up time and budgets. It is important to realistically assess the complexity of the project and plan the resources accordingly.
The paradigm shift: Why are individually adapted AI solutions the answer are
The experiences from failed ERP major projects show that classic, monolithic systems are often too rigid and inflexible in order to keep up with the dynamic requirements of modern companies. Here individually 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 error sources and make processes more efficient. For example, AI can be used in invoice processing to automatically record, validate and record invoices. In warehouse management, AI can be used to optimize inventory, automate picking processes and to shorten delivery times.
Data -based and forward -looking decisions
AI-based ERP systems analyze large amounts of data in real time, recognize patterns and provide well-founded forecasts for production, sales or maintenance. For example, AI can be used to predict the demand for products, optimize production plans and plan maintenance work with foresight.
Flexibility and scalability
Modern, AI-based ERP solutions are modular and can be flexibly adapted to individual business processes and industry-specific requirements. This enables companies to adapt the system to their specific needs and to expand or reduce it if necessary.
Improved user experience
Digital assistants and chatbots enable more intuitive operation, faster answers and higher acceptance among users. For example, with the help of chatbots, employees can ask questions about business processes, call up information or do tasks.
Continuous optimization
AI learns from past events and continuously adapts processes, which enables constant improvement and adaptation to market changes. For example, AI can be used to optimize marketing campaigns, dynamically adjust prices or to develop new products.
Fulfillment of regulatory requirements
AI supports in compliance with compliance and data protection requirements with automated monitoring and documentation. For example, AI can be used to recognize suspicious transactions, prevent data protection violations or prepare audits.
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The advantages of AI in detail
In addition to the points mentioned, AI offers a variety of other advantages:
personalization
AI enables companies to personalize their products and services and to tailor 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 to stand out from the competition.
Increased efficiency
AI can help companies increase their efficiency and reduce costs.
Risk management
AI can help companies identify, evaluate and minimize risks.
The challenges in implementing AI solutions
Although AI offers many advantages, there are also challenges when implementing AI solutions:
Data quality
AI systems need large amounts of high-quality data to work effectively. Companies must ensure that their data is clean, complete and up to date.
Skilled workers
The implementation of AI solutions requires specialists with specific knowledge and skills. Companies must invest in the training and further education of their employees or consult external experts.
Cost
The implementation of AI solutions can be expensive. Companies must carefully calculate the costs and ensure that the return on investment (ROI) is positive.
acceptance
The introduction of AI solutions can lead to resistance to employees. Companies must involve employees in the process at an early stage and clarify them about the advantages of AI.
The future belongs to the intelligent, tailor -made solutions
The high quota of failed ERP major projects illustrates that classic approaches reach their limits. Individually adapted, AI-based ERP systems offer companies flexibility, efficiency and innovative strength that are required for successful digital transformation and sustainable competitiveness. Companies that rely on AI can optimize their business processes, better use their customers and get a decisive competitive advantage. The future belongs to the intelligent, tailor -made solutions that help companies be successful in a constantly changing world.
It is important to emphasize that implementation of AI solutions is not a sure-fire success. Companies have to prepare carefully, select the right partners and actively tackle the challenges. If you do this, you can fully exploit the advantages of AI and make your digital transformation successfully.
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Konrad Wolfenstein
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