Ask an Architect: 5 Steps to an Effective Salesforce Data Management Strategy (Part 2)

“We have millions of records and constituents with high expectations around service and engagement; how do we develop an effective data management strategy?”

In Part 2 of this blog post, we continue the discussion of effective CRM data management as an integral part of delivering a remarkable constituent experience across all channels, particularly for organizations with large data volumes. 

And the Salesforce platform offers a number of features that make it easy to develop a common sense approach to data management that can deliver happier constituents, a more effective user experience, improved organizational agility, and reduced maintenance and cost.

An effective CRM data management strategy is founded on a solid understanding of your business process, user behavior and technology, and succeeds when you combine it with governance and disciplined execution.

Consider these 5 steps when building your Salesforce Data Management Strategy:

  1. Take Only What You Need: CRM-Relevant Data
  2. Optimize your Big Objects: Large Data Volume Optimization
  3. Use Data Where it Lives: Federate and Integrate Non-CRM Data
  4. Travel Light: Data Archiving
  5. Govern with Discipline: Master Data Management

In Part 1 of this blog, we explored Steps 1 and 2. In this second part of the blog, we’ll explore the remaining steps.

3. Use Data Where it Lives: Federate and Integrate Non-CRM Data

    Federation and integration options enable data access from external sources, embedding of external web apps, and syncing of data with Salesforce.

    The following is a table of various Salesforce solutions to align your data.

    Result: Enriches end user view and capabilities, and may reduce cost.

    Technology Options What is it? When to use it?

    Configuration based, uses oData services for Read/Write access to external data through Salesforce external objects

    Display/modify constituent’s transactions/asset records stored in another system via oData services or a custom connector
    Supports mobile/Salesforce1

    Syncs up data from Heroku Postgres database to Salesforce Objects. Can also expose Heroku data as Salesforce external objects

    Access data from a Heroku app (such as Event Management, public facing mobile app etc.) and display / sync it with Salesforce
    Supports mobile/Salesforce1

    Custom visualforce / apex code or lightning component to access data via web services, or UI mashups via Canvas and iFrame etc.

    Enable access to other systems such as degree planning, online coursework, registration/SIS from a portal style UI
    Supports mobile/Salesforce1*

    Embed structured and unstructured (chats/tweets) data insight, analytics and exploration capability for large data sets

    Access to Salesforce and non-Salesforce data that runs into Millions of records such as system generated (IoT, Sensor data, Web Analytics)
    Supports mobile/Salesforce1*

      Here is some additional information on integration and federation options.

      Technology Options Level of Effort/Complexity Examples

      Complexity: Medium – High
      Effort: High (Weeks – Months)Creating oData-compliant services can take time. If they exist, or can be easily created via Middleware, the rest is configuration based.

      View the shipment status of promotional items sent as thank gifts on a Contact record in Salesforce as a related list.

      Complexity: Medium – High
      Effort: High (Weeks – Months)Creating the Heroku app / UI can take time. It is exists, the rest is configuration based and can be relatively quick.

      Sync of LMS / event attendance data from a Heroku-based app.

      Complexity: Medium – High
      Effort: High (Weeks – Months)Depends on the technical design, iFrames are quick to implement, but custom components and Canvas can take time. Authentication can also increase complexity.

      View grades from SIS on a Contact record in Salesforce as a related list.

      Complexity: High
      Effort: High (Weeks – Months)Importing data into Wave, testing and configuration may take a few weeks. Embedding Wave UI in Salesforce is relatively quick.

      Website traffic, community posts, and donation comparison/correlation.

      4. Travel Light: Data Archiving

        Relevant data is the key to successful CRM. The rest is history. Determine relevance by identifying how data is driving insights and behavior.

        Result: Reduces data volume, improves performance, and may reduce costs.

        The following is a table of various archiving tools and information on what each of these options may take to implement.

        Technology Options What is it? When to use it?

        Simple data extract data, usually as .csv files, directly from Salesforce or with another ETL tool.

        To extract historical data out of Salesforce to an external system or store it as flat files.

        A Salesforce API to extract and delete large number of records in a batch mode.

        Used for large sets of data, programming batch jobs to regularly extract and delete.

        New Salesforce feature to store billions of record in a read-only format on the same trusted Salesforce platform.

        Used to store billions of records from an existing object onto a Big Object for direct data access.

        Heroku Based Solutions (e.g. Cervello)

        Partner and Open Source Solutions to archive Salesforce data on Heroku/Postgres platform

        When archiving and unarchiving records into Salesforce is needed, and the archiving platform needs to be tightly integrated.

        Chatter or Attachments Archive.

        When archiving records from Salesforce to an external platform.

        Others / Custom Solutions – Data Lakes, Data Warehousing etc.

        Custom solutions that archive/merge CRM data along with other system data.

        To access large amounts of data for historical reporting with a BI tool.

          Here is some additional information on what each of these options may take to implement.

          Technology Options Level of Effort/Complexity Examples

          Complexity: Medium
          Effort: Medium – High (Weeks-Months)Programming skills required.

          Old activities and case records are extracted and deleted via a daily batch process.

          Complexity: High
          Effort: Medium – High (Weeks-Months)XML and Apex skills required.

          Legacy information about direct mail campaigns sent and received by individuals.

          Heroku Based Solutions (e.g. Cervello)

          Complexity: Medium – High
          Effort: High (Months)Analysis, configuration, and testing can be lengthy.

          Very old student data is preserved mainly for future compliance and legal reasons.

          Complexity: Medium-High
          Effort: Medium-High (Weeks-Months)Analysis, configuration, and testing can be lengthy.

          Archive Chatter posts and Attachments and other data that is outdated / not in use.

          Others / Custom Solutions – Data Lakes, Data Warehousing etc.

          Complexity: High
          Effort: High (Months)Typically, enterprise-wide efforts require specific skills.

          Donation records, contacts/volunteers inactive over the years, and financial transactions that are 4-5 years old.

          5. Govern with Discipline: Master Data Management

            Creating formal governance procedures will direct the alignment of CRM data collection and analysis with business requirements designed to achieve the enterprise’s goals.

            Result: Define procedures for data management to build a strong, high-performing CRM.

            The following is a table of teams to consider creating to build a comprehensive governing strategy.

            Team Purpose

            Center of Excellence

            Ensure CRM changes support business goals and follow IT best practices and processes.

            Release Management

            Design and document a complete release management process

            Design Standards

            Follow key standards for coding, testing, integration, large data volumes, and other areas that affect services

            Quality Control

            Create a regular cadence of code reviews, data quality inspections, and analysis for code improvement.

              This is part 2 of a 2-part blog series on data management for large data volumes. Refer to the first installment of this series. Join us for our “5 Steps to an Effective Salesforce Data Management Strategy” webinar on February 27, 2018.


               

              This blog is also part of our larger “Ask an Architect” content series. To learn more about engaging a Salesforce.org Customer Success Architect in your organization, please contact your Account Executive.

               

              Saurabh Gupta

              Saurabh Gupta

              Saurabh is an Enterprise Architect and seasoned entrepreneur spearheading a Salesforce security and AI startup with inventive contributions recognized by a patent.

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