12 - The Science Behind This Book

Описание: This chapter explains the "why you should believe" the book's findings: how to distinguish plausible stories from evidence, and what it means to evaluate transformation practices with rigor. The authors summarize primary and secondary research approaches, and how qualitative and quantitative methods combine to understand complex phenomena in organizations.

Primary research involves collecting new data directly—through surveys, interviews, observations, or experiments. Secondary research analyzes existing data collected by others. The State of DevOps research combines both: primary data from annual surveys supplemented by secondary analysis of case studies and academic literature. Qualitative methods explore "why" and "how" through rich descriptions and patterns in non-numeric data. Quantitative methods test "how much" and "what relationships" using statistical analysis of numeric data.

The chapter introduces three types of analysis: descriptive (what happened), exploratory (what patterns exist), and inferential/predictive (what causes what, what will happen). Descriptive analysis summarizes data—for example, showing the distribution of deployment frequencies. Exploratory analysis reveals patterns and relationships—like how deployment frequency correlates with change failure rate. Inferential analysis tests hypotheses and establishes causation—demonstrating that continuous delivery practices cause improved delivery performance.

Critical distinctions are emphasized: correlation does not imply causation. Just because two variables move together doesn't mean one causes the other—there may be a third variable, reverse causation, or coincidence. The research uses rigorous statistical techniques including structural equation modeling and regression analysis to test causal hypotheses while controlling for confounding factors.

The chapter prepares readers to interpret findings with a scientific lens rather than accepting comfortable narratives. It underscores that the book's recommendations are evidence-based, tested across thousands of organizations, with statistical confidence behind the conclusions.