Salesforce and Customer Master


Are you connected to your Enterprise Data?

Salesforce is a boon for companies which can’t take a number and wait for IT to prioritize the implementation. However if adequate data architecture planning is not done, it can end up as a siloed application with Data Quality issues. Many companies don’t have the time to engage the Enterprise team for CRM implementation besides some basic back up, or data feeds. Also it starts off as a small group of users using it to track customers, prospects and sales opportunities only to confront the bigger problems when mergers and acquisitions happen.

It is a great opportunity to take a step back and engage the appropriate Enterprise Architecture team (or outside help) during consolidation of multiple Salesforce instances. Defining the architecture and taking the opportunity to integrate and create Sub-Pub (Subscriber, Publication) model to share the key Customer Data will address Data Quality issues and make the latest customer data available to the Enterprise.

Salesforce - Make Salesforce Stick
Make Salesforce Stick

To ensure your Salesforce implementation or migration goes as planned, our team of change management professionals discuss how to manage the transition process to ensure your team is ready, willing, and able to perform effectively in the new environment.

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Consolidating without a proper Data strategy only will compound the Data Quality issues and partial information.  Many tools are available for creating a solid Master Data program at Enterprise level, or on the cloud. Even simple strategies like creating the Governance policies and integration approaches will go a long way in sharing the most accurate customer information at the right time.


See also:

Reference Architecture – Cloud MDM for Salesforce

Why MDM should be part of the CRM strategy

About the Author

Shankar RamaNathan is a Senior Enterprise Architect with 25+ years of experience in successfully developing and implementing IT strategy and Information Governance ( Master Data Management, Metadata Management, Data Quality and Data Governance) programs.

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