Are you truly leveraging AI, or is your data holding you back?
1. Generative AI Demands Clean Data
– Clean data isn’t optional. Generative AI relies on accurate, complete, and current data.
– Poor-quality data leads to unreliable AI insights and decisions.
2. Identifying and Tackling Bad Data
– Common culprits include duplicates, inaccuracies, incomplete records, and outdated information.
– “Hoarded data” is a challenge; organizations must clear out unused data.
3. Steps to Ensure Data Readiness for AI
– Document workflows to identify critical data entry points.
– Engage stakeholders to understand the importance of clean data for AI.
– Prioritize cleaning data in key areas where AI impact is crucial.
– Utilize tools like Salesforce’s “Clean Your Room! Dashboard” to make data cleaning engaging.
4. Proactive Strategies to Prevent Bad Data
– Use paths and dynamic forms for efficient data entry.
– Highlight crucial fields in layouts to ensure they receive attention.
– Integrate tools like Einstein Activity Capture for up-to-date data.
– Customize user interfaces to reduce data entry errors.
Salesforce technical debt can become a barrier to growth, as outdated and inefficient systems consume resources and limit agility. Proactively managing this debt maximizes Salesforce ROI by ensuring systems remain streamlined and responsive to changing business needs. Helping managers understand and address technical debt is crucial for supporting long-term strategic goals.
Start building your data governance policy today. It’s not just about fixing reports; it’s about future-proofing your business for AI.
You can read it here: https://sfdc.blog/usqey
Source from admin(dot)salesforce(dot)com