Before you walk.

You crawl before you walk.

I talk with companies almost weekly and hear something like "we want to do advanced analytics, AI/ML, LLM Models, etc."

I love to hear companies passionate about the transformation data can have on their business.

But as the conversation goes on, it's clear they are trying to run a marathon before they have figured out how to lace up their shoes.

The path to advanced analytics, with very few exceptions, goes through this progression.

✅ Step 1: Do you have Batch ETL with a well-model data warehouse with operational reporting? Have you implemented basic data cleansing and quality standards in place? Is there any governance or data dictionary deployed?

Great. This is your descriptive analytics. You now know what’s happening in your business.

✅ Step 2: Do you have the talent and the tools to perform root cause analysis? Is your data stored so you can meaningfully look at historical trends, perform data mining and review A/B analysis?

Good work. This is your diagnostic analytics. You know why something is happening in your business.

In most organizations, these two steps will take several months to a few years.

This work will have a much larger ROI than trying to jump into predictive or prescriptive analytics without a good foundation.

If you are working on these first two steps and not making the progress you hope for, hit reply and tell me about it.

I help companies take the first step.

Thanks for being here,

Sawyer