By breaking down applications and systems into loosely coupled services, service oriented architecture has paved the way for enterprise architects to support smaller, more numerous, and even more "experimental" projects within their organizations.
That's the view of Forrester analyst Jeffrey Hammond, speaking at the recent EclipseCon 2013 conference in Boston. A summary of Hammond's talk is provided in a new post by TechTarget's James Denman.
One of the advantages SOA brings to organizations is the ability to abstract important parts of applications as reusable, standardized services that can be run in any and all connecting systems. The emergence of these flexible service layers means architects, developers, and even business users can more readily put together new business workflows and processes without the need to rewire or rewrite underlying applications.
For example, marketing may want to try out a new promotion, and require access to the CRM and financial system to provide special discounts. If the promotion fizzles after a couple of weeks, the only labor lost was in linking interfaces to the services —versus the time IT may have spent writing new code.
Hammond pointed to such capabilities in his talk:
The cost of starting up a software architecture improvement project has gone down significantly, and that means large application development organizations can afford to start more projects on a shorter budget ... Even the projects that have to be shut down will teach the organization something, if the company is prepared to learn from its mistakes.
Such testing may even include sophisticated analysis, such as "multivariate testing and examining the interactions of complex traffic routes". As a result, Hammond said enterprise architects are increasingly expanding their roles from artists to engineers to scientists.
Indeed, as more organizations embrace analytics, they are turning to data science to explore and understand the results of their experiments. And enterprise architects are finding themselves working side by side with data scientists. The greatest innovations are a result of a lot of failures, and if organizations have the ability to fail —cheaply —they won't fear innovation as much as they do.
(Thumbnail photo credit: Joe McKendrick.)