Researchers often get measured on speed. How quickly can you turn around a study? Can you deliver insights in two weeks instead of four? The pressure is increasing, especially with the advent of AI research tools that center speed-to-insight as a key value proposition.
The message is clear: faster is better. But faster isn’t always the right choice.
Speed assumes every question needs an quick answer and that the research infrastructure (recruiting pipeline, representative participants, etc) is a well-oiled machine and, therefore, that every question can be treated with urgency.
It frames delivery speed as the metric of success regardless of whether those insights land when and where they’re needed, whether they’re accurate, and whether they’re deep and rich enough to create market differentiation and a competitive advantage for the firm.
I prefer to optimize for timeliness.
Timeliness means delivering the right insights at the right time relative to the decisions they need to inform. Sometimes that’s fast as with a brief evaluative study to help a team choose between two design directions or a quick gut check on customer priorities. Sometimes it’s slower as with foundational research that runs for months to surface patterns that will de-risk and shape longer-term product strategy.
Both can be timely. Only one can be fast.
When speed becomes the goal, researchers may cut corners to hit deadlines. They may recruit samples that are not representative of customers or segments. They may analyze too quickly and generate superficial insights. A looming, near-immediate deadline may also cause them to whiz past questioning the timing of the information need. Do we need to learn this now? Or can we learn this later so that we can learn something else now?
Timeliness addresses these questions. Is this the right thing to study now is a different way of asking whether a firm is making the best use of its research resources. Timeliness also exposes where there may be operational inefficiencies. What kind of research and prioritization mechanisms are in place to help the team review and prioritize work? What’s the escalation path to resolve competing research priorities?
Questions about timeliness force clarity about dependencies, milestones, and what’s truly blocking progress versus what’s just feeling urgent.
It also creates space for researchers to push back. If a decision isn’t happening for six months, then accelerating research to deliver insights in two weeks doesn’t add value unless the most important value is the speed with which the insights are delivered (quality concerns notwithstanding). If a strategic question requires depth, doing fast and shallow research doesn’t serve decision-makers or researchers.
Ultimately, the goal is to deliver research when it matters, with enough rigor to be useful and enough lead time to inform decisions. Some studies can happen in a couple days. Some can happen in a week. Some need three months. Some need six months. Each of those variants can be timely.
Start optimizing for timeliness.