The term "fake news" is being tossed around a lot lately. It points to the general opinion that it's becoming increasingly difficult to trust what we read online or even in our local newspapers.
Reading "alternative facts" from seemingly honest news sources is disturbing, but what's equally damaging is reading a news article that omits important details.
Likewise, in software business systems, such as Dynamics 365 and Salesforce, fake news is the result if those using the system aren't careful to consistently provide accurate and complete information.
Examples of bad data include duplicate records, inconsistent field entries (e.g., US, USA and United States in the country field), data in the wrong place (e.g., mixing customers with leads), fat-fingered values that go unverified and data entered in the wrong place.
In addition to bad data, another common problem is missing data -- data that is omitted for a variety of reasons: it's too difficult to enter, takes too much time, not sure where the data goes, difficult to import, getting an error message, forgot to update it, etc.
Just like with fake news, consumers of the data will start to question the content of the records and reports they view. This will eventually erode confidence in the system and people will find alternative ways to do their jobs, which usually means creating another Excel file and storing the data on their local machine.
To prevent bad data from making its way into your Dynamics 365 (CRM) system and to keep it clean over time, Microsoft provides features in the base product that can help. Those features include duplicate detection (real-time and scheduled), form-based business rules and scripting for data validation, processes and plug-ins to validate, correct and complete data, and bulk import and deletion tools.
Just as the New York Times and the Wall Street Journal are careful about publishing accurate news stories to at least maintain their subscriber base (and avoid the "fake news" label), it's also essential for CIO's, system administrators and end-users to treat their business systems in the same way. Otherwise, once trust is lost, it's difficult to get back.