Predictive analysis when testing software

In today’s world, there are many companies experiencing sudden cost increases, production delays and operational risks due to a lack of Predictive Analytics in Testing. Predictive Analytics is a data-driven technology that can be used to predict test failure points and determine the future. It has the power to optimize project data and enables business leaders to make very quick strategic decisions.

There are roughly two types of companies. In one type there are software test companies that perform tests with the internal test environment and in the other type there are software development companies that easily outsource the entire test activities to preferred suppliers.

• A software testing company focuses on timely product launch using its own testing team.

• A software development company outsources testing and expects deliveries on time.

Test companies typically follow a lengthy process for each test project to reduce operational problems and costs. These companies encounter many problems during this new project.

Let’s take a look at some of the challenges that come with internal testing.

Internal test challenges

• Finding the right testers and matching them to the project

• Fix time and budget for the project

• Need for multiple testing tools and infrastructure

• Meeting productivity goals

• Current testing issues leading to unknown future challenges

• Different stakeholders expecting different reports

Test companies should run Predictive Analytics at the operational level to avoid productivity slowdowns and issues, while addressing the root causes at an early stage. The development companies that outsource all testing activities would prefer to focus more on core activities and avoid the increasing cost of testing, but these companies are experiencing many delivery delays and the costs remain higher.

Let’s take a look at some of the expectations of outsourcing testing.

Customer expectations of supplier testing

• Complete required understanding of the projects

• Flexible to quickly adapt to changes in requirements

• Compliance with timely delivery

• Communication and coordination

• Testing effectiveness, consistency and satisfaction

• Test coverage

• Timely delivery of products

The development companies must run Predictive Analytics at the company level to avoid slow results by identifying the right supplier and the right team for the right project.

Predictive analytics is quickly becoming one of the most discussed topics in software testing projects because it can reduce operational risk and aid planning, quality and delivery. Predictive analytics are widely used today in many industries such as healthcare, life sciences, insurance and finance, but it is not limited to just these industries. It can be used in software testing to improve things significantly.

Advantages of Predictive Analytics when testing software

• Predict test problems at the earliest, which can lead to unknown future challenges

• Forecast deliveries

• Reduce communication and coordination problems

• Predicting the right environment / the right supplier

• Improving planning, quality and delivery

• Meeting business needs

Conclusion: Predictive Analytics helps development and testing companies identify the root causes of all issues and make proactive decisions at the earliest.

Source by Pavan Kumar