The Data Warehousing Institute (TDWI) estimates that poor data quality costs U.S Business more than $600 billion a year in postage, printing, and staff overhead. Meager data quality affects customer and vendor relationships, results in poor decision making, missed opportunities, and quality downstream. Anyone engaged with users of ERP or CRM systems quickly recognizes the frantic need to have clean integrated data between systems. Without quality data users are frustrated, make mistakes, and customers are lost. This article will show you several of the classic data errors that contribute to this problem, and how Scribe can be used to supply clean data you CRM system users. Specifically, we will show how we can enforce data quality standards in a SalesForce.com system using Scribe Insight. The integration pattern we use for these types on data quality DTS files is to us the CRM system as both the Source and Target using the Record ID as the Lookup Value. Below is a lead that has incorrectly formatted Names and phone numbers. We will use the format formulas to correct these issues.
Here are 2 tips to address the Data Quality issues. Looking first at the telephone numbers. Let’s build a few formulas to improve the Phone number formatting. Working with phone numbers you need to build formulas that deal with numbers coming in various formats. Sometimes one will expect area codes, and other time you won’t get that.
- 1-234-567-8901 x1234
- 1-234-567-8901 ext1234
- 1 (234) 567-8901
The fax number is 808-947-4198 and we want to add the appropriate bracket to match the desired phone formatting. The most common method is to use the Strip function to pull all the non-numbers out and then add the formatting by using the Format function. So the formula looks like:
FORMAT( STRIP( S14, “N” ), “(###)###-####” )
This will change 808-947-4195 to (808)947-4198
There are many other use cases with phone numbers where one may have extensions included, or the need to add a missing area code or country code. Here are some links to other posts that address these challenges.
Once you have settled on a good telephone format formula it is a great opportunity to utilize our User Formula feature. This is a big time saver as one would want to apply the formula for every time they integrate a phone number.
The second formula is to use the PROPER command. This formula with properly case upper and lower cased text data. So ACME INC. turns into Acme Inc. In the test window one can see the results of the formulas.
Now that we have a workbench file that can run to clean up the data it can be automated in the console to run on an ongoing basis to reach out to correct improperly formatted data.