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Using Predictive Analytics to Mature IT Production

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How to Reduce IT System Testing Costs and Speed Delivery of Critical Systems

by Rudolf Schmandt and Nabil Abu el Ata

EXCERPT: “Predictive analytics supports a test driven development approach by collecting business functional and non-functional requirements early and providing an accurate picture of end-to-end system performance at any point in the lifecycle. With this knowledge, development teams can understand the outcome of system design decisions, define the best-fit infrastructure and production methods, and design to avoid the dynamic factors that destabilize IT systems in production—before any investments in technologies are made.”

ABSTRACT: Today many companies face escalating costs, production delays and operational risks due to testing inefficiencies. In the quest to meet tighter schedules and budgets, IT systems are frequently accelerated into production without sufficient testing—at the cost of quality. A strategic opportunity exists for companies that adopt predictive analytics mature testing processes and cut production costs. By harnessing the predictive power and improved efficiency of analytics throughout the SDLC, companies can expand the scope and depth of system testing to lower risks and better meet business requirements.

This paper provides an overview of the advantages of using predictive analytics to execute model-based IT system testing and identifies which traditional system testing tasks can be replaced with new model-based methods to increase testing effectiveness, efficiency and coverage. Additionally, it presents reasons why companies should leverage predictive analytics throughout the SDLC to streamline processes, mitigate risks and avoid long-term maintenance issues. Companies that adopt model-based methods, like Accretive X-Act OBC Platform, and operationalize analytics through the creation of a test organization—a.k.a. Test Factory—can create competitive advantage, cut testing budgets by up to 60% and speed the delivery of high performance systems.