Whereas the current SaaS offerings are dominated by the automation of standard workflows such as CRM, HR, and Accounting, the demand for information processing is quickly outstripping the capabilities of the processor offerings by Intel and IBM. The SaaS space will become much more competitive as compared to the old software industry that relied on on-premise installations. In the on-premise days, an IT staff had to become familiar with the installation, configuration, and maintenance of that software instance. The IT department had to amortize this investment in skill and in doing so became more and more intrenched with a particular vendor. With SaaS, that skill is no longer part of the equation and thus customers can more quickly move to a 'better' workflow. This implies that the SaaS providers need to differentiate through product value more so than before.
All business SaaS workflows manage important information assets that need to be leveraged to its fullest extent for an organization to be competitive. The computes to leverage this information have exploded due to maturity of data base management systems but also due to the sheer availability of competitive information available on the internet. Most of the current database research is about query languages and systems for querying non-stationary data and federated systems. Fully automated machine learning systems like Google's web index are only the tip of the iceberg. Compute requirements for optimization techniques in inventory management and logistics are much more severe.
This explosion of compute requirements creates a huge problem. Since SaaS relies on multi-tenancy to offer profit margin for its provider the end user actually gets less hardware to work with. Secondly, the demand for computes handily outstrips the offerings by Intel and IBM. At the end of 2007, Google computes were up at the rate of 10,000 CPU years per month and that rate has been tripling every year since 2004. All this implies that we are in for a bumpy ride with SaaS providers having to scale out their data centers rapidly due to customer growth and compute demands and Intel and IBM not doing their part to keep up with the compute needs. This will inevitably lead to an increased rate of innovation on the hardware side that the successful software organizations will leverage to differentiate. Virtualization of these hardware assets will be the name of the game to remain nimble and not get stuck when you bet on the wrong horse.
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2 comments:
Very astute observations. The question remains of large scale viability of SaaS given the proprietary requirements of mid-large companies. Will the company of the future be willing to ship critical, business-critical data "offsite" to a third party vendor for "processing" in the cloud? My experience tells me that is a tough (but not impossible) sell... Agree wholeheartledly that with increasing data processing needs under your scenario, the SAAS vendors will likely have an infrastucture problem related to how to successfully deal with the geometric data growth and increasing sophistication of required to drive business competitiveness.
Afterglow:
I think the adoption of cloud computing will come from the bottom up, not from the high-end. Outsourcing of critical data to IBM and EDS is done all the time but the SLA is then focused on reliability and accountability not price. Cloud computing on Google and Amazon is all about use cost reductions for SMBs. And typically with technology disruptions that focus on expanding the market, more dollars are available that will lead to the disruptive technology overtaking the high-end technology in terms of innovation to the point where the old high-end technology gets absorbed.
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