After the summer break, September also marks the start of a "new" year in many companies. And what better way to start afresh than with a proper tidy-up? In digitalised companies that work on the basis of software, the Chaos today more on the servers than in the filing cabinets. But how do you tidy up digitally? Seven tips on how you can optimise your data maintenance and at the same time quality of the data.
1. make data optimisation possible through standardised processes
Firstly, you should check the data entry processes. If, for example, data is stored in different areas of the system so that it is not (or cannot be) automatically linked, the processes should be corrected here. Software that supports most Processes standardised within the company makes this much easier. Only on this basis does it make sense to clean up the databases, as otherwise a Sisyphean task awaits you.
2. make completeness verifiable
When is a data set complete? This question can be answered differently depending on which processes rely on the data. Does the data record for a product need a picture, for example? Once these criteria have been defined, the completeness of a data set can be assessed on the basis of them and the data checked for defects.
3. check condition
... and this is the next step: checking the data for its status. Prefabricated Analysis tools can help here. In particular, incorrect or redundant data comes to light and can be corrected or archived.
4. archive before
Which brings us to the next step. Parts of the database are often old or have become unnecessary. However, this data cannot simply be deleted due to the obligation to provide evidence, but must be archived. This is an important step, as outdated or superfluous data can hinder processes in the system.
5. automation is data optimisation
As it is now possible to use various Workflows To automate processes, the data records must be reliable in order to ensure an error-free process flow. The criteria for data maintenance should be clearly defined, especially at those points where the automated processes take effect, in order to utilise the benefits of automating the processes.
6. maintenance of the data on the agenda
All the established procedures for data maintenance are of little use if the "data maintainers" concerned do not apply them. You should therefore use the last few hours of the summer break to familiarise your employees with the new Data maintenance-criteria. This also underlines the importance of data maintenance and makes colleagues responsible for it.
7. ... and from the front
The last step and tip is repetition! Both data cleaning and checking the criteria for recording and maintenance should be reviewed regularly. The reward is not only order, but also faster and simpler processes in the company.
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