Tackling Data Overload: Strategies for a Leaner Salesforce Org

Is data overload bogging down your Salesforce org? As the new year unfolds, it’s time to shed the burden of unnecessary data that clouds decision-making processes. But, how do you sift through the digital clutter to determine what stays and what goes?

Taking Stock of Your Data

Begin by assessing the volume of records in your Salesforce instance. Are you juggling 1,000 accounts or struggling under the weight of 300,000? Understanding the scope of data is your first step towards a lighter, more efficient database.

You can easily see this from the Company Information section in Setup. Click “View” next to the field label Used Data Space.

Identifying Core Data Objects

List the objects that are critical for your organization's operations. Typically, these include accounts, contacts, opportunities, tasks, events, and cases. However, custom objects might be holding even more significant data than these standard ones. Pinpointing these essentials is crucial for the next phase of cleanup.

Organizing Your Cleanup Process

Set up a report folder — let's call it 'Data Cleanup' for memory's sake. Generate foundational reports for each important object, focusing on creation dates, last modified data, last activity, object owner, and object ID. Do this for all the core ipbjects you’ve identified above.

Data Usage Analysis

Now, dive into the usage patterns. Group records by last modified date to get a snapshot of activity. You might discover large swathes of data that were imported but never utilized. Identifying inactive data is key to understanding the overall health of your Salesforce org.

Active Data Evaluation

Flip the script and assess what data is actively engaged with. What percentage of your total data is regularly used? This doesn't require precision but aims to provide an overview of your data's vitality. A high percentage of active data is a good sign, but a low percentage indicates an issue that needs to be addressed.

Data Governance Considerations

Once you've got a grip on your data's landscape, it's time to decide who should oversee the culling process. Agreeing on the value of data is imperative before any cleanup can occur. In our next post, we'll explore how to assemble your data governance team and equip them with the right tools.

Engage with End Users

Start conversations with your end users about how poor-quality data affects their daily tasks. Inquire about incomplete accounts or excessive duplicates. Gathering feedback on data quality will be invaluable as you move forward.

Stay tuned for our next post, where we'll delve into rallying your data governance team and setting the stage for efficient data management.