We talk about optimization a whole lot. There's cloud workload optimization, there's mobile optimization for website presentation and there's every other type of optimization as we move through the ‘full stack' of information technology from the base logic layer all the way up to the Graphical User Interface (GUI).

First, the race for power
You get the picture, there's a lot of optimization going on - but this is a natural thing, i.e., we spent the end part of the last century trying to get more processing speed, better form factors for devices and cheaper memory and storage.

We've achieved a lot of those things now... and with cloud services we have (almost) as much power as we need for most use cases - so now it's a case of finessing it, or optimizing it.

Second, the race for optimization
Naturally then we see the drive toward optimization continuing... and now at the most pertinent surface of all, i.e., information optimization.

But what is it?

Information optimization is all about finding our way through Big Data. Information optimization is all about analytics and insight, but most of all...

... information optimization concerns the Return on Information Investment (RoII) as a measure of the value that any enterprise can generate (and subsequently gain) from an investments into information analytics solutions, services and resources.

A new economics
The economics of Return on Information Investment can only be calculated once we assess the ability to gain insight from the data analyzed in order to make better and quicker decisions. The volume of the world's "digital universe" is expected to reach as much as 8 zettabytes during this year, but that figure could play out to be much higher - this factor makes RoII even more tough to achieve.

Robert Youngjohns, HP's Executive Vice President and GM for the Software division, was quoted on Network World saying that "What most enterprises want is to be able to apply analytics to drive better decisions based on the data they already have."

He also said that firms want to manage an ever-increasing inflow of new data, but that HP's Big Data platform includes both structured and unstructured database options to address those needs.

HP's Big Data strategy is designed to addressing four areas:

• Architecting, deploying and applying analytics everywhere
• Provisioning for a capability to support all data types
• Championing open source, open platforms and open standards
• Empowering developers

When all these factors come together as one and we embrace the new measure of Return on Information Investment (RoII), then we start to make money from Big Data - or at least that's how the theory goes.

This post is sponsored by The Business Value Exchange and HP Enterprise Services.