Risk Based Testing with intelligence

With the proliferation of Digital transformation leading to adoption of Agile methodologies and DevOps, clients need delivery of quality products/services with reduced Time-to-Market and Cost. As there are Time and/or Cost constraints, IT QA is expected to use the time efficiently and effectively with prioritized testing based on risks that impact customers or business, if not tested.

Our experiences with multiple clients has led to believe that Risk Based Testing is ofcourse prevalent, but now requires intelligent inputs in defining the scope for the QA. More and more clients are asking for intelligent driven risk analysis and its being applied for different kinds of engagement models (all-encompassing TCoE to specific testing use cases).  We have seen implementation of this is now being asked for and included within the established testing methodologies and processes and is an example of SHIFT LEFT.

Steps for setting up an intelligent RBT:

  1. Creation of risk matrix and keeping it live with continuous tagging of risks to the scope as early as possible in the lifecycle in the requirements gathering. This requires a very close interaction between the business and IT stakeholders. Business Intelligence provides information about the most critical business functions / modules / transactions or web services that impact business (monetary, regulatory, operational, frequency of use, customer touchpoints) and probability of failure (requirement size, technical complexity). Our FMEA risk register has been used in most instances.
  2. Risk factor values driven test planning, estimation and test execution activities securing critical functionalities. Our customized artefact provides the required focus on the prioritized list of critical requirements/risk items at the module / use case / transaction level that feed into the Test Design.
  3. Categorization of Risk generally seen with the clients are Quality, Cost, and Schedule in that priority order. Also, other ancillary parameters like Test Data, environment, tools usage etc., should be considered.
  4. Leveraging Test Automation for progression, regression and UAT testing for functionalities based on the risk factor values and a detailed due diligence for choice of framework and ‘automatable components’ provides clear wins with RoIs.
  5. Optimized teaming approach generally tapers down over test cycles, on an average is smaller against a non-RBT model and more so pronounced in the back drop of agile scum methodology. Teams should also adopt TDD (Test Driven Development) ensuring higher upfront synergy between development and test teams.
  6. Defect analysis to triage for resolution based on Risk factor of the modules/functions and priority of defects by supplying specific insights through the defect management process and defect details.
  7. Reporting of Test Planning and Test Execution progress with risks highlighted for mitigation and also ensuring how these risks can impact the risk matrix and thereby the scope iteratively.

Benefits realized across different client cases

  • Reduced Time-to-Market by 30%
  • Quality improved by 35% measured through test effectiveness and defect leakage
  • Customer satisfaction boosted by up to 30% – due to transparent customer involvement, reporting and progress tracking
  • 20% reduction in planning effort due to critical functionalities recognized upfront and scope optimized thereby