This data was originally featured in the April 3rd, 2024 newsletter found here: INBOX INSIGHTS, APRIL 4, 2024: AI DATA GOVERNANCE, GENERATIVE AI LANGUAGE TASKS
HOW GOOD IS YOUR DATA GOVERNANCE?
Last week, Harvard Business Review asked the question, “Is your company’s data ready for Generative AI?”
Because I work with a variety of clients, I would say a resounding, “No!”
You can read the full article here.
You need at a minimum, decent data governance before you can use your data in a generative AI system.
Before we get into that, let’s all get on the same page about where generative AI fits into the Data Analytics Hierarchy.
Say, what?
You’ve never heard of the Data Analytics Hierarchy? That’s surprising. The name totally just rolls off the tongue.
For those that don’t know, the hierarchy consists of five stages: Descriptive, Diagnostic, Predictive, Prescriptive, and Proactive. Think of it like rungs of a ladder. You start on the bottom rung and climb your way up to the top.
This is what it looks like. Forgive me, I’m not a designer:
Here’s why I say that your company’s data is not ready for generative AI. Most companies, whether they recognize it or not, are still at the bottom of the hierarchy. They cannot confidently say, “What happened?”. If they can say what happened, they need to determine if they can also say, “Why did it happen?”. Generative AI doesn’t enter the chat until the at least the third rung.
“But I’ve used generative AI to analyze my data!”
Using generative AI to make sense of your data is not the same as having solid data governance.
I get it. This is the not-as-fun stuff. Think of it like eating your vegetables so you can have dessert. Data governance is Brussels sprouts. You either love them or hate them. Either way, they are really, really good for you and you’re better off if you eat them.
(Stops to dig around in the produce drawer of the fridge for a snack)
Back to the point. If you don’t have good data governance, you won’t have good data analysis. How do you set up good data governance? I’m so glad you asked!
The 5P Framework!
- What is the Purpose of collecting and using the data?
- Who are the People responsible for and that have access to the data?
- What is the Process for collecting, cleaning, and maintaining the data?
- What are the Platforms use for data collect, storage, and analysis?
- What is the Performance of the data? Are we confident in it?
Think about your Google Analytics 4 data as an example. I’ve heard numerous complaints from users that the data is different from Universal Analytics and they don’t believe the numbers. If this is the case, why are they still trying to make decisions from it? Generative AI won’t help. You have to get to the root of the issue, and that’s your data governance.
Once you have a solid foundation, the rest should come “easily”. I put that in quotes because maintaining and analyzing your data for insights isn’t easy. If you have repeatable processes in place and people who can maintain your systems, you can ensure data quality.
The moral of the story is eat your vegetables.
Well, the real moral of the story is to have a strong data foundation through your governance. When you have that piece in place, you can keep moving up the hierarchy and confidently bring generative AI into your company.
Quick plug – if you want help with your data governance, we can do that. Give us a shout!
Is your company’s data ready for generative AI?
Reply to this email to tell me or come join the conversation in our Free Slack Group, Analytics for Marketers.
– Katie Robbert, CEO
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