Recently, I had a conversation with a well-known industry analyst—a very creative guy drawn to big ideas. He got me thinking about a big idea that has been rattling around in my brain to some degree of distraction. In my estimation, the idea is nothing short of transformational to the economics of enterprise computing.
It’s a story about taking back control of IT and truly rationalizing costs.
The story has two parts:
Part 1: Returning control and flexibility to IT by making system workloads autonomous, self-healing and portable across deployment environments.
rPath, for example, does this today.
Part 2: Allowing IT leadership to make dynamic decisions about where workloads should run based on optimizations for price and service levels.
Think of this as the logical evolution of IT financial management.
In combination, these two concepts have the potential to change everything.
IT has long been beholden to outsourced service providers for managing systems. In some cases, the comparative cost of outsourcing system management is lower due to scale economies and other built-in efficiencies. But, more often than not, it’s the predictability of a contract relationship that IT leadership covets: fixed bid contracts are easily forecast and service level agreements allow IT to share some risk.
But the cost of admission is exceptionally high—for a very large company a contract may exceed $40 or $50 million … a year.
Why have CIOs been willing to spend this much?
• Efficiency—traditionally, it has been more efficient to throw systems “over the wall” due to service providers’ comparative cost advantage through specialization.
• Switching costs—once your systems are deployed, it has been too expensive to move them to a new provider; you’re locked in—and so is your price.
• Liquidity—or the absence thereof. Traditional pricing models have forced enterprises to engage in onerous, long-term commitments, removing the liquidity that drives market-efficient pricing.
But this is changing—fast:
• Efficiency—emerging approaches to automation make system scale and complexity far less prohibitive and intimidating for enterprise IT organizations to handle in house.
• Switching costs—deep automation also allows you to regenerate systems that are ready to deploy to new environments, setting workloads free to run anywhere.
• Liquidity—At the same time, elastic computing models allow you to pay as you go. Systems can be moved and capacity can be consumed on demand.
IT efficiency increases, switching costs decrease, liquidity emerges, and a true market is born. Then, introduce decision support for driving price and SLA optimizations and CIOs can dramatically improve the efficiency of IT spending.
As context for what is possible, consider the achievements we’ve seen in modern manufacturing. Supply and capacity are dynamically shifted to the highest-yield demand. Capacity is allocated based on contract values, delivery commitments, and the on-hand availability of raw materials. Raw materials are procured based on competitive bids. Production runs are scheduled against available capacity.
The entire manufacturing process is automated and dynamically optimized.
Why shouldn’t this be the inspiration for the future of enterprise IT?
