The digital transformation has prompted companies worldwide to fundamentally rethink the way they work. In particular, the increasing importance of artificial intelligence (AI) and modern analytics tools highlights the need to base decisions increasingly on data and not just on gut feeling. However, the path to a successful data-driven organization is anything but easy. It requires profound changes in the corporate culture, technology, and processes to create the basis for successfully using AI and optimizing the supply chain.
1. Create the right conditions: the basis for a data-savvy culture
The first step on the path to becoming a data-driven organization is to create a culture- and structure-bound bedrock that enables using digital information as a strategic asset. A “data-savvy” culture must be fostered on several levels.
Operationally: Effective data management is essential. This includes clear processes and policies that place a strong emphasis on “data quality circles” – the continuous improvement of data quality.
Strategically: Equally important are a sound architecture and “data governance” that ensure that all relevant company data is accessible, understandable, and secure. Without clear guidelines for handling information, it will be difficult to create a reliable database.
Process-oriented: The company must ensure that relevant data is made available for and within business processes in order to enable efficient decision making for sustainable success.
2. Ensure data quality: eliminate data silos
A common obstacle on the path to a data-driven organization is the presence of data silos. These isolated repositories make it difficult to access information comprehensively and prevent companies from deriving the full value from their data.
Breaking down data silos means bringing together all the information from different departments and systems and making it accessible to the relevant parts of the company. This is where cloud technology comes into play. Cloud computing is the key to creating a shared data environment. This platform enables all areas of the company to have access to the same, always up-to-date information.
In such an environment, document management systems (DMS) play a crucial role. They not only enable the secure storage and processing of data and documents, but subsequently also the automated collection and analysis of information using AI-supported processes.
3. Successfully integrate AI: data is the key
The use of artificial intelligence is closely linked to the quality and availability of company data. AI only works effectively if it can access relevant and high-quality information.
Another major problem is the availability of data along the entire supply chain. Especially when it comes to achieving the goal of “predictive quality” and making reliable predictions, AI must be able to access real-time data from the entire supply chain. To do this, it is crucial to create a digital infrastructure that enables the easy exchange of information across all company boundaries via interfaces.
4. The cloud as a key technology: flexibility and scalability
The cloud is more than just a technology trend – it is the cornerstone of a data-driven organization. Without cloud services, it is almost impossible to store, manage and exchange the information needed for AI-supported analysis. In particular, collaboration across different departments and companies is greatly simplified. All stakeholders access the same data without delays or misunderstandings.
In addition, cloud-based systems offer the highest security standards, which is a prerequisite for handling sensitive company data. An intelligent rights and role concept ensures that only authorized persons can access certain content, and two-factor authentication further increases security.
5. Integrate processes and people: establish data-driven decisions
The last step on the path to becoming a data-driven organization is to integrate data into daily decision-making processes. Companies must ensure that employees not only have access to the right information but also have the tools they need to analyze it and convert it into informed decisions.
An important part of this is training employees in how to use data and AI tools. It is not enough to simply implement new technologies; employees need to learn how to use them and which benefits they enjoy in their day-to-day work. Low-code/no-code, in particular, plays a role here. This enables even less tech-savvy employees to create simple digital applications.
Conclusion: a clear data strategy is an indispensable competitive factor
In today's business world, it is inevitable that companies will move towards becoming data-driven organizations. The advantages are clear: companies optimize their internal processes, strengthen customer loyalty, and significantly increase their competitiveness.
With a solid database, the right technology such as the cloud, and the integration of AI into all relevant processes, companies are laying the foundation for long-term success in an increasingly digital and data-driven world.
