The Bane of CRM – Data Quality | DM Review | Industry Led, Industry Read

The Bane of CRM – Data Quality | DM Review | Industry Led, Industry Read
Quite frankly, most sane people don’t find cleansing data anymore fun than cleaning the toilet. When given the time, analysts are happy to look at data to find patterns of error, programmers are happy to code validations when they are requested and users try to enter things correctly, but mistakes still happen. Only the most compulsive among us will take the time to research a data problem, determine if and where bad data elements might be in use and find a way to correct it. So, clean data moves in and out of the system smoothly, but dirty data hangs around like laundry on a teenager’s floor.

System implementation projects are planned without allocating enough time to cleanse dirty data. Often the existence of dirty data is acknowledged, and cleanup may be attempted at some level. Most often though, most dirty data is converted, loading new systems with all the old data problems, soon to be joined by a whole crop of new data anomalies. New operational systems simply create bad data faster. Often, CRM systems sitting on top of them are, at best, no improvement over old systems and, at worst, they are dismal, expensive failures.