Kenny
Bangudu

The measure of a study is not its rigor, its sample size, or its readout deck. It is whether the product, the roadmap, or the organization did something different because of the evidence. If not, the research failed — regardless of how well it was executed.

Qualitative research explains the why. Quantitative research establishes the how many and how much. Neither is sufficient alone. I default to mixed methods not because it is fashionable but because converging evidence from multiple sources is how research earns the right to influence decisions.

Every study I design starts with the decision it needs to support, not the question a stakeholder initially asks. Understanding the business stakes, the product timeline, and the organizational dynamics is part of the research brief — not a distraction from it. Research framed in business terms gets acted on. Research framed in user terms gets appreciated.

AI tools accelerate synthesis, pattern detection, and documentation. They do not replace the researcher's judgment about what questions to ask, which participants to recruit, or how to contextualize findings for stakeholders. The speed gain is real. The accountability for insight quality stays with the researcher.

The most expensive research mistake is answering the wrong question rigorously. Upstream generative work — understanding the actual problem space before solutioning begins — is where research creates the most leverage. Evaluative testing at the end of a design cycle can only catch what has already been built wrong.

Presenting findings is the midpoint, not the finish line. I partner with product, design, and engineering to translate insights into specific actions, track whether recommendations are being adopted, and follow up when they are not. A research readout that produces no change is an expensive status update.