INFOCLUTCH | MARCH 29, 2022
You heard data is useful for businesses. It helps generate insights, streamlines process, further increasing revenue and sales.
And all these happen only if the data is good; what if the data is bad?
It would reverse the results. A decayed data is worse than no data, as you would spend your precious time focussing on leads, processes that won’t deliver desired results. It would also lead you down the rabbit hole with huge losses.
USA loses $3.1 Trillion yearly because of poor data.
An incomplete data
A duplicate data
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
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.
15% had duplicate data
6% invalid mailing address or email address
8% had missing fields
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
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
Data updating on a regular basis
Enable the data management process
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
They won’t get the desired results
Low morale and inefficient coordination
Blame game starts decreasing productivity
Results to higher attrition rate
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.