Here a few common kinds of dirty data:
Duplicate Data: Various users in your org unknowingly create three entries for the same account. Confusion reigns and time is wasted when users try to track down the account and its correct related records.
Missing Data: Busy users leave fields blank in their rush to move on to other tasks. Reports become inaccurate and automatic processes are derailed as critical information is missing in action.
Incorrect Data: Human error results in inevitable typos or data entered in the wrong field. Poorly enforced data entry policies mean one rep might enter a country as "USA" and another enters it as "U.S." As a result, filtered reports and list views are missing essential data.
As a result of dirty data, your business cannot make good decisions because your reports and forecasts are incorrect. Your customer service reps lose their edge because they can't find accurate or complete information on customers who call in. Your Salesforce.com user adoption goes from bad to worse as your employees feel that their Salesforce.com data is inaccurate and unhelpful. The bottom line is wasted time and money.
The good news is this does not have to happen! Tune in next week to learn Cloudy's favorite strategies to clean up, and better yet, PREVENT dirty data in your Salesforce.com org.
If you can't wait until next week and want help cleaning up your dirty data today, Contact Us.
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