Software Asset Management as a trigger point for Data Management
In today's digital era, data management is crucial, especially when it comes to structuring IT data. Companies are faced with the challenge of managing a wealth of information efficiently, not only to keep track of software in use, but also to ensure compliance and optimize the cost of software deployment. In this blog post, we take a look at why data management is an important prerequisite for SAM and how a structured approach can help companies to manage their IT resources effectively.
The complexity of Software Asset Management
The challenges in SAM have not become any smaller in recent years. In addition to the "classic" on-premises world with the corresponding variety of software solutions used - from operating systems and office applications to specialized tools - the proportion of cloud solutions is growing steadily. In SAM departments, it is important to maintain an overview of both commercial data (licenses, contracts, etc.) and technical data, i.e. the actual use of the products.
Why Data Management is crucial
A SAM tool is often sold as the solution to get a good overview of the license inventory and software usage and thus license compliance. But what use is the best tool if the data that is imported is not valid or is out of date? Data management is generally the key to avoiding data chaos and gaining useful insights from data. Structured and well-maintained data is a key prerequisite for successful SAM.
SAM provides impetus for Data Management
Structuring IT data means that information is recorded and organized in a uniform format. SAM departments rely on data that is as complete and up-to-date as possible in order to achieve their goals. The lack of availability of reliable data often only becomes apparent when SAM managers ask for it. If, for example, a license balance for a software product is created for the first time and it is discovered that it is not possible to map the usage data ad hoc, there may be various reasons for this: Active Directory groups are not maintained, individual devices are not scanned or the installation data is not available in an up-to-date form.
Recommendations for a structured approach
Both SAM and data management are constantly on the move. The more complex a company's IT landscape is, the more important it is for the two areas to work well together:
- Process optimization: In license management, there are often points where data is not available or not consistent. This is a great opportunity to approach the right contacts and change processes so that data is available in the required quality in future. This often means that data is recorded where it is initially generated.
- Awareness: Raising employee awareness of the importance of SAM and data management as well as training are important in order to improve the quality of the data entered and promote compliance with processes.
- Integration with other systems: Linking data from the SAM with other company systems helps to provide a holistic view of IT resources. This makes it easier to identify correlations and enables better planning.
- Data quality: An important step that can be controlled by license management is to formulate the requirements for the data and define which systems are leading. The completeness of the data (what is the baseline) and regular reconciliations and checks must then be checked.
- Automation: The use of automated tools, and increasingly AI tools in the future, helps to optimize the process of data collection and updating. Automation minimizes human error and provides (near) real-time information.
Conclusion
In the world of SAM, data management not only has a supporting function, but is a decisive success factor. Structuring IT data is a prerequisite for meeting the challenges of the increasing complexity of software licensing with confidence. By implementing best practices in data management, organizations can not only optimize their software licensing, but also reduce compliance risks and save costs in the long term. Well thought-out data management is therefore the basis for effective SAM in the digital era.
Author: Anne Pinke