A driving force in cloud adoption is the cost savings one gets from eliminating physical servers, then migrating applications and data into the cloud. This reduces up-front capital expenditures (CAPEX) and enables budget planning that is based around operating expenditures (OPEX) and on-demand service provisioning.
Undoubtedly this propels pricing competition among major cloud service providers. They are striving to reduce their price per virtual machine (VM), which averages 10 percent a year or roughly 5 cents an hour per virtual instance. The continuous pricing reduction derived from multi-tenant public cloud has contributed to the exponential growth of the cloud market for the past five years.
However, from an enterprise user perspective, is the velocity of cost savings enough to be highly competitive in the long term? The convergence of mobile, social, Internet of Things (IoT), cognitive computing and cloud has already disrupted industries by creating innovative solutions around smart cars, smart buildings, smart health care and smart education.
App-based ride sharing companies are now multi-billion-dollar concerns. How can existing taxi service providers around the world sustain their business? Obviously, cost savings from cloud migration is not enough, but they may be compelled to create innovative solutions using cognitive capabilities on cloud.
“Cognitive on cloud” refers to cognitive services running in the cloud and that are available to be consumed via representational state transfer (REST) APIs. These services are available as part of platform-as-a-service (PaaS) offerings such as Bluemix so they can be easily bound to an application while coding.
For example, cognitive analytics such as voice (tone analyzer, speech-to-text) and video (face detection, visual recognition) capabilities enable users to analyze petabytes of unstructured data generated by mobile devices every day.
Developing cognitive applications to run on mobile devices will provide new insights and help organizations create totally new revenue streams. The convergence of cognitive computing and cloud is driving this cognitive-oriented digital economy. The potential return is seemingly unlimited.
From an return-on-investment (ROI) perspective, let’s suppose that there are two organizations, each planning its cloud adoption. One picks the lowest-priced cloud service provider based on cloud commodity services as well as total cost of ownership (TCO) in the cloud (this is Org 1 in the chart). The other picks a cloud service provider based on one more evaluation criterion in addition to the TCO comparison: cognitive capability (Org 2 in the chart).
As shown in the chart above, by leveraging cognitive capabilities in the cloud, Org 2 will achieve a higher ROI through continuous innovation. The difference between the two organizations is that Org 2 sees cloud as an innovation platform for high ROI as rather than a way to cost savings based on a TCO comparison.
Continuous innovation will also include added values, such as IoT and blockchain powered by the cloud. However, the return may not be immediately quantifiable. Therefore, the gap between the two organizations can be enormous depending on how effectively an organization creates innovative solutions via cognitive applications and other value-added services.
When it comes to selecting the right service provider, ROI on cloud requires more than just a TCO comparison based on the number of VMs, storage capacity, hypervisor, operating system and so on. In addition to this basic analysis, an organization must consider which cloud is cognitive enabled or disabled at the PaaS layer. Achieving a high ROI requires a cognitive-enabled cloud as a foundation. More than 30 IBM Watson services on cloud with a supporting foundationhave become key to the solution for organizations across many industries.
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