Data Supply chain is how you intake, structure, and leverage your data. It's not about "how big" or "how much data" you have, it's about the relationships between the information, or the in other words: it's about the context.

Here's the best example I've got. Let's compare Wal-mart, who clearly has the most sales data at $400B, compared to Amazon and its $200B in sales.

But think about the granularity of the data.

Imagine a customer at Wal-Mart walking down the aisle, glancing at products. They pick up three boxes, put two back, and take one to the checkout. Sure, Wal-Mart get's the "success data" about what that customer bought, but Wal-Mart does not know the relationships between the boxes that were glanced at, picked up, or taken to checkout. Wal-Mart is unable to leverage that data to make a more personalized experience for their customers the next time they walk that aisle.

Now think about a customer checking out on Amazon. They spend 30 seconds on one page, 30 seconds on another page, and then 10 seconds on the last one where they click "Buy Now". Well, Amazon was just able to figure out that that customer is Gluten-Free, and can now prioritize Gluten-Free products in their future search results.

It's not about how much data you have, its about what you (can) do with it.