In a company that employs many people, a large number of programs and applications quickly accumulate. Every employee needs individual software for his or her daily work. For the acquisition of such work tools, however, it is usually not enough to download the program, but various licenses must be purchased and renewed from time to time.
As a private person you may still keep track of your existing programs and their licenses, but as an administrator of a large company, this is an enormous administrative burden. The license inventories must be recorded and afterwards updated again and again.
But thanks to new technologies, the overview of licenses is easier than ever, even within the company.
A significant contribution was made by Data Analytics, which was developed in the course of digitization 4.0. By definition, data analytics is the science of analysing raw data with the aim of drawing conclusions from it. Many techniques of data analysis have been computerised in various processes and algorithms, allowing to process raw data for human use automatically.
Surely you have already come into contact with the effects of data analytics while browsing the Internet: Once you have searched for a new pair of headphones on the Internet, you will subsequently be constantly presented with advertisements and ads for headphones when visiting other websites. This method of advertising is therefore based on Data Analytics. Needless to say, this is only one of many examples where Data Analytics is used.
Data Analytics is a very useful contribution because it eliminates the need for manual collection of large amounts of data and is therefore used in many areas. In the IT industry, data analysis is the core of the so-called usage statistics which are used in many programs or on the smartphone today.
These usage statistics allow an easy collection, analyzation, and visualization of the program usage. In order to get a quick and clear overview of the inventory, the data is visualized not only with concrete figures, but also with adapted diagrams. This stocktaking is important and helpful to determine further actions to be taken. By listing the frequently used and less used programs, additional licenses can be purchased or the number of licenses for less used licenses can be reduced. This way, efficiency can be increased by individually adapting the program licenses to the demand, and at the same time high expenses for unprofitable licenses can be saved.
The statistics cover all employees, even those who have left the company. Thanks to the statistics, administrators can easily and quickly identify the " leftover" licenses, pass them on to other employees or terminate them directly to close security gaps.
Further monetary advantages are provided by the usage statistics integrated in programmes.
Since the data is evaluated where it is generated, patterns and interrelationships become clear. Furthermore, the need for expensive external parties, such as data scientists, for analysis is eliminated.
In addition, the statistics can also be used to predict trends and thus to take appropriate action at an early stage. This enables more foresighted and agile planning for the company.
Advantages of usage statistics programs:
- Overview of the programmes
- Differentiated views of frequently or rarely used programs
- Discover trends: Which programs lose their effectiveness over time?
- How active are the employees ? How productive are they?
- Which programs are used most by employees / groups ?
- Identify need for action
- Determine cost requirements & time requirements
- Data-based forecasts enable realistic predictions
The advantages of usage statistics are not only reserved for companies, but also individual employees can benefit from them. The employee gets an overview of his working methods and his time management in relation to the programs used. Strengths and weaknesses can be identified and appropriate measures can be taken.
You may also be aware of these statistics from your mobile phone where statistics about your services can be viewed. The usage time of the services and the consumption of data volume, storage space and battery power are displayed, for example. This allows you, to identify applications that should not be used on the road, with mobile data volume, or whose data volume access should be limited.
Usage statistics have a general objective: they should help to adapt the use of the programmes to available resources and to monitor the effects of changes.
CONCLUSION: The usage statistics is a simple-looking but efficient tool with great added value. Its benefit applies to the individual as well as to a company, because clarity about the current situation enables focused improvements through action.