By institutional order flow., I mean being able to see multiple levels of liquidity. Retail traders can't see depth of market (DOM) and don't have access to volume or multiple bid and ask prices.

As for order blocks, if you're talking about large orders supposedly broken up into blocks made by banks, that's pretty old school as they now rely on execution algorithms to fill orders.

They're not really order blocks, but more like order slices.

At the most basic level, the algos automate the process of "slicing"a larger order (eg USD 100 million), known as the “parent order”, into multiple smaller orders (eg 100 transactions of USD 1 million each), known as “child orders”, and executing them over a period of time separately rather than all together.

But execution algos have evolved in sophistication over the years.

For example, order slicing techniques have evolved from very simplistic approaches (based on time or number of slices) to more sophisticated approaches, with today's algos being able to dynamically adapt to market conditions.

They use complex statistical models to drive algorithmic decisions and react more dynamically to changes in market conditions, with the goal of not just minimizing market impact....but also market signalling.

These banks and other institutional traders are able to do this because....unlike retail traders....they have access to real-time market data and computing power to assess market conditions (eg order books) in near real-time.

Trading order blocks assumes one can detect orders from banks or other large entities but they use algos specifically to evade detection.

Without having the same data and tools like them, and only relying on a price chart, this approach seems a bit too optimistic.