Supercharging your business means building a number of key superpowers.
In a previous post, I talk about SuperOps and the power of having superpowers to collectively combat those archaic principles that live within massive organisations.
To truly empower and supercharge your business, you need these 4 abilities:
- Strength (CloudOps)
- Speed/Agility (DevOps)
- Flexibility (DataOps)
- Cognition (MLOps)
Let’s look at them in a bit more detail.
The Power of Strength
First, you need a solid cloud foundation behind your AI.
You need to be living in a cloud-based world. You need the power of strength. And you need good infrastructure.
If you’re on-prem, you’re not in the cloud. If your infrastructure is your strength layer and is unable to scale and grow on demand, it means that you lack the very foundation that enables you to supercharge your AI.
The Power of Speed/Agility
Then you need the power of speed.
Which is essentially DevOps.Your code is everywhere, but without the right practices and capabilities to release code fast and efficiently, you’re unable to move with true speed.
If you’re building code with pipelines that release quickly, then you have the agility to launch innovation and keep up with the changes and trends in technology.
The Power of Flexibility
Flexibility is your ability to extract and turn data to a usable state.
When you look at the power of flexibility, your data pipelines are a key factor in
The problem with most enterprises is that data is siloed. It’s not usable. It’s broken. Without flexibility, bringing data into a state that makes it readily usable is (and will continue to be) a big challenge for enterprises.
The Power of Cognition
Lastly, you need the power of cognition. The ability to analyse and predict.
Simply put, your MLOps.
Machine learning represents the power of foresight and accelerated cognition. If you’re not able to predict customer patterns and understand behaviour through data, then it’s not truly AI.
How Are You Enabling SuperOps?
Are you truly building out the foundation layers of your AI journey, and embracing the end-to-end stack that drives innovation?
Or are you just investing in one particular area hoping for miracles to happen?
