Taqelah-2026

Most test analytics efforts work backwards. Teams measure what is easy-pass rates, coverage, execution time—build dashboards, and hope the data leads to better decisions. In practice, this often results in more numbers, less clarity, and decisions still driven by instinct.

As systems grow more complex and release cycles accelerate, this approach becomes increasingly risky. High pass rates can mask shallow testing, coverage targets can pull focus away from real risk, and improving trends can create confidence without understanding. The problem is not a lack of data, but analytics that are disconnected from the decisions they are meant to support.

This talk reframes test analytics as a decision-support practice rather than a reporting activity. Through three real team examples, it highlights common analytics failure patterns and the blind spots they create,where teams appear informed but remain uncertain about release readiness and risk.

The session introduces a simple, decision-first approach to analytics, start with the decision that needs to be made, identify the uncertainty blocking that decision, and design minimal metrics that reduce that uncertainty. The goal is fewer metrics, clearer risk conversations, and analytics that help teams make better decisions, not just produce better dashboards.

Three Key Takeaways :

Three common ways test analytics fail to support real testing decisions

A practical, three-step decision-first approach to designing test metrics

Real examples of minimal analytics that inform release readiness, risk prioritization, and testing effectiveness

Read more in details : Taqelah Lightning Link