A recent article published by Tech Republic shows that companies are collecting data, but have not concurrently embraced the tools needed to maximize data insights while minimizing the work effort to do so.
The one aspect of data collection that has not received much press is data relevance. Just because data is collected regularly, doesn’t guarantee that it is the right data or that it is entirely accurate.
Some simple rules of data collection are as follows:
1. Source. Data should be collected at the source. There are many organizations where one department makes a copy and that copy becomes the source for another department. This is one way to make sure the data is stale, inaccurate and incomplete.
2. Ownership. Data should be “owned” by the originator. Ownership includes making sure the data is accurate, timely and relevant.
3. Collection. Data collection methods need to be periodically checked and validated. Business processes change and so does the data associated with that process.
4. Share. Information about how data is being used and analyzed should be centralized so it can be reviewed:
Data queries implicitly contain logical insights. These should be checked, validated and shared.
Eliminate duplicate efforts.
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