In 2006, Jeanne W. Ross, Peter Weill, and David C. Robertson famously published “Enterprise Architecture as Strategy” and it still provides a great way to think of how to best structure IT to align with wide variety of business needs. As the name suggest, it’s an expose of how different IT Enterprise Architectures can be structured to support different Business Operating Models. One important message is that not all companies need to structure IT in the same way. However, IT should be structured to align with the business strategy. While in retrospect this may seem self-evident, it was a new and very powerful idea and the authors demonstrate clearly how the right thinking about IT can drive competitive advantage.
In this blogpost we will try to employ a similar approach to shine light on the business of testing. But first let’s dive a little bit deeper in the Enterprise Architecture as Strategy model. In the model 4 archetypical business operating model are defined: Diversified, Coordinated, Replicated, and Unified. They are distributed along an x-axis representing Business Process Standardization and a Y-axis depicting Business Process Integration.
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Background: Enormous amounts of data are processed every day. 8 million mobile payments were made in Q1 2015 at Starbucks, 3 Million – 5 Million trades are completed at NYSE on a daily basis, and 26.2 Billion credit card transactions were done in United States 2012.
Weekly # of mobile app transactions processed by Starbucks stores in the US as of Q1 2015 (in millions)
A lot has been written on how to measure various aspects of software development. The metrics range from lines of code, security defects to user satisfaction. In any scientific measurement effort, you must balance the sensitivity and the selectivity of the measures employed.
No metric is perfect. We need to understand which of the metrics make the most sense and contribute to a well-balanced and informed decision making. Software quality is a multi-dimensional concept. The views of a developer vary vastly from those of a business sponsor to an end user. One way of defining software quality is - Quality is a measure of how well the product serves its customers.
The business imperative for faster enterprise applications development has never been stronger. Competitiveness and ultimately business survival depends on enterprise capability to not only create the right software but also to deploy it fast. At the same time, quality cannot be compromised as the business costs of launching bad applications also has sky-rocketed.
In this climate, it is no wonder that a lot of effort has been devoted to creation of good tools for test automation. However, an overwhelming number of these tools tend to concentrate on the test scripts and not doing very much to solve the test data problem. And still, even the best test script does little to secure quality unless it is executed with quality test data that truly reflects the business reality the application will run in. Scripts without the right data is like a car without fuel.
Mobile applications have now become a part of life. It’s common for users of smart phones, tablets and other mobile devices to download applications from the online store. The focus has considerably moved from the web to the mobile.
As it stands, most mobile devices use one of the two dominant operating systems: Google-developed Android and the Apple-developed iOS. The difference between these operating systems and their related devices isn’t just aesthetic: Just as your MacBook won’t run a Windows application, an Android phone can’t run an app built for iPhone — in most cases at least.
The purpose of testing is to ascertain that the product is built to its specifications and a quality product is released to the consumers.
Testing is an important step but we seem to be caught up in the cost, ROI, and measuring quality of the testing organizations to the extent that the basic premise of why we test is lost.
The goal of testing is to ensure the product is built to its specifications, not to run all tests and find tons of defects. Techniques, technologies and process can be employed to test faster, better and more accurately.