Technology advances at such a fast pace, it is hard for businesses to keep up. However, those that are ready to undergo a digital transformation need to work out how to maintain their data, so they do not lose any of it in the move.
Here are some tips on how to make sure you do not lose any valuable data when going through a digital transformation.
1) Integrate data
The main challenge is trying to connect data from across a variety of platforms. As reports and records might be held on different channels, apps or departments, it can be exceptionally difficult to pool these together.
In order to have all this information, they need to be found first. By organising the data and extracting them from various sources, this will reduce the chances of any documents becoming lost.
Then you can have a unified data management programme whereby all the important records are all in one place.
2) Move offline data online
Both online and offline data needs to be consolidated if all the siloed documents are to be together.
If these are kept separate, no analysis or insight can be gained from the information available. However, by moving all data on to the same digitised programme, this helps to highlight trends and patterns
In order to move all offline documents online, it is essential to consider the types of data your organisation has, such as reports or surveys. Businesses also need to remind themselves what type of data they are collecting from customers and in what format.
This will tell them where to look for these documents, including emails and questionnaires.
Pay attention to what data might be missing from the records, so these do not get left out during the digital transformation process.
3) Prioritise data entry
Digitising data can be a long process, but this does not mean it should be rushed. Businesses should make sure data entry is a priority, so it is given the time and consideration it deserves.
If the information inputted is inaccurate, this could result in false results following analysis. Therefore, wrong trends or patterns will emerge that do not give a true representation of the data gathered.
As it is inevitable that some human error will occur, it is sensible to consider automated data entry, as this reduces the chances of inaccuracies.
This also means staff have more time to spend on other tasks, such as collating all the offline data from different sources.
4) Data cleaning
Of course, it is also important to consider how valuable the information is, as not all data needs to be stored.
That is why it is essential to clean the data from time to time, which means the records saved are the most important and accurate ones. This improves the quality of the data, and makes the analytics more reliable.
