What is bad data?
An incomplete data
A duplicate data
Irrelevant data
Old data
Why is it dangerous for your business?
It significantly affects organizational efficiency
It gives wrong insights
It could lead to project failure
Distorted success metrics information
It exponentially increases costs
Decreased customer satisfaction rate
Invalid reports
Statistics on bad data:
Organizations lose $13.3 Million yearly due to poor data
40% leads consist inaccurate data
21% of organizations got bad reputation due to poor data
Near to 30% operating expenses because of bad data
Organizations lose 20% revenue due to dismal data
Inaccurate data affects bottom line of 88% companies.
Percentage of irrelevant information in bad data:
15% had duplicate data
6% invalid mailing address or email address
8% had missing fields
How do organizations find it early?
You’re finding significant information missing
The process not going on right track
Not connecting with desired prospect
Costs have hugely shot up
Teams’ co-ordination in doldrums
Why bad data emerges at all?
You received data from unauthentic sources
Significant portion of bad data already exists in database
You didn’t optimize the data at intervals
Poor data collection methods
How do you clean data?
Data updating on a regular basis
Enable the data management process
Other methods of coping with bad data:
Executing advanced data quality programs
Analysing each set of data in the database
Regular checking to see if data aligns with customers’ information
Cleaning up immediately if any discrepancies
How does bad data affect employees?
They won’t get the desired results
Low morale and inefficient coordination
Blame game starts decreasing productivity
Results to higher attrition rate
Conclusion:
For many years, bad data has affected businesses across the world. They suffered huge losses and the consequences were too harsh where they couldn’t get back reputation they earned. It’s just not the small and mid-sized businesses that have suffered from bad data; large enterprises also fall in this bracket. In fact, they suffer greatest as they invest a significant amount for mammoth results at a targeted time.
The crucial thing that businesses could do here is finding out the bad data at the earliest to mitigate chances of losses. The infographic explains more about the bad data with some relevant statistics to get a better understanding and implement it in process.
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