Enterprise applications are here to stay; how they work, look, and the means by which they are delivered is constantly evolving. Over the past couple of weeks, announcements from two major vendors, Oracle and Salesforce.com, suggest that the latest battle lines have been drawn, in the form of artificial intelligence.
It is not fair to claim that all enterprise applications, be they ERP, CRM, SCM, or HCM, are created equal; however, it is fair to say that the level of maturity among these applications is high, creating a problem for both the enterprise and vendors alike: how can they be differentiated? Cloud delivery is, largely, old news – users expect the ability to acquire and deploy in the cloud the majority of solutions they consider. That statement comes with an important caveat: not all enterprises can be 100% in the cloud. Flexibility of deployment options – i.e. hybrid – will be an important feature for some customers. So, if the cloud is expected, what else can separate applications from each other? The answer: data and analytics.
Applications vendors have been building or acquiring analytics capabilities for some time, from the early days of the major business intelligence vendors Business Objects (SAP), Cognos (IBM), and Hyperion (Oracle) getting acquired through more recent acquisitions like that of BIME (Zendesk) and Platfora (Workday). These are not the only examples though; more recently, vendors have been adding capabilities in artificial intelligence and, in some cases, the range of data sources they can handle.
The benefits of incorporating data-driven insight directly into applications are clear, but dashboards or tools that require some user knowledge only go so far. Two recent announcements, from Oracle at its OpenWorld event (Adaptive Intelligent Apps) and from Salesforce.com prior to its Dreamforce event (Salesforce Einstein), have helped mark the next step: automating that insight by baking machine learning directly into the application. While this description is a simplification of what these vendors are offering, in reality it is a logical move on their part: taking analytical advantage of the data held within the applications' databases (and from third-party sources in the case of Oracle), and, in some instances, removing the need for users to work directly with the data at all while still benefiting from its analysis. Examples of this could be real-time dynamic web content tailored to the customer’s buying habits, or predictive lead scoring for sales executives – both examples require limited or no input from users.
Ovum expects significant further news on this emerging trend and would suggest that a key theme of artificial intelligence – automation – is one that will come to an ever-greater proportion of the IT portfolio. Some years ago, the industry used to talk about "closed-loop decision-making." At the time, it was largely science fiction. It seems the constant evolution of technology capability has started to make it tangible fact.
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