We want to deploy an AI engine to analyze our operational data and predict customer churn, but our current CRM and ERP data is a complete mess with duplicate entries and empty fields. How do we clean up our data hygiene before plugging in AI tools so we do not get useless outputs?

Question

Tyler Smith · Accepted Answer

Plugging AI into a messy database is a fast way to get highly confident, completely incorrect answers. If your CRM and ERP data is full of duplicates and blank fields, you must establish data hygiene before investing in advanced tools.

Start by defining what clean data actually looks like for your business. Run an IDS session during your next weekly Level 10 Meeting to identify the worst data offenders. Assign a quarterly Rock to clean up these core databases. This is not a task for a machine, it requires a human with a strong Follow Thru conative style on the Kolbe Index to design a repeatable system for data entry.

Next, update your core processes to dictate exactly how and when data must be entered. If your team does not follow these processes consistently, your AI initiatives will fail. Add data accuracy metrics to your weekly Scorecard, such as the percentage of complete customer profiles. Once your team is consistently hitting these targets and your data is clean, you can safely connect your AI tools to run predictions that actually drive profitability.