"To ask the right question is harder than to answer it" - Georg Cantor
At Lindus Health, we want to build great products.
To build great products, we need a set of underlying principles grounded in hard reality. We can start by asking ourselves: What matters most in clinical trial delivery? Is it regulatory approval? Is it patient safety? Of course, these are non-negotiable, hard requirements. But to answer our question fully, we need to take a step back to get a broader view of what is at the heart of running a clinical trial.
One way to answer this question is to look at a clinical trial as if it were a factory. The most important thing when running a factory is producing good-quality output, and this is equally true when running a clinical trial. In our case, both the input and output of a clinical trial is clinical data. Everything in between is simply applying trial design to produce the best possible outcome data.
Considering this, we can answer our initial question with a simple syllogism:
· Premise 1: The success of a study relies on the quality of the outcome data;
· Premise 2: The quality of the outcome data relies on the time and effort put in by the study team;
· Conclusion: A study’s success relies on the time and effort put in by the study team.
With this in mind, the next question that should be asked is: What steps can be taken to reduce the time and effort burdens on study teams, while also improving output quality? Saving study team time means more subjects can be processed per day/week/month which, in turn, means faster, cheaper and more efficient trials.
The simple answer, one which has been tried and tested in product development, is to build excellent user experience into the product. So how do we do this?
A well-trod debate exists in the field of product development around whether qualitative or quantitative research leads to the best product decisions.
On one hand, as product user numbers grow, we can collect huge amounts of quantitative usage data, and use tools to visualise and generate insights from it. It is perhaps unsurprising that this method is so prevalent in product development, particularly in B2C/B2B SaaS products, where such quantitative data is so abundant and easy to track.
On the other hand, qualitative data comes in the form of user insights. Generating these insights is a laborious effort requiring careful planning and consistent follow-through on feedback from clinical research teams. There is a lot of value in this work, though, as it provides an important understanding of why study teams are doing what they’re doing. In other words, this data tells us, clearly and in detail, what matters most to our users.
One of the most common challenges we face is when users are unsure which features will make their lives easier. Of course, in clinical research, where time and effort are key, it can be unreasonable to expect users to pull together and condense careful thoughts about the best features to build in a short amount of time, so how do we go about getting the best possible user insights for our feature development?
To do this, we follow a process best described by my tennis teacher: Plan Fast, Act Slow. Prepare what you’re going to do fast, but take the shot slowly.
This is exactly how we do user insight research. First we plan fast: we use our intuition and ongoing informal user feedback (from interviews, training sessions, demos, all-hands, sales calls, or a combination of these) to generate decisions around what we should work on. Then we act slowly. We take our time reviewing our research evidence, then validate or invalidate those initial decisions when figuring out the details within the regular product development process (product discovery, prototyping, usability testing).
With all this in mind, it’s unsurprising that qualitative user insight research is aligned with every single one of our company’s values:
· High Agency: Find the right person to ask questions, and escalate immediately
· Stay Curious: Ask as many questions as your curiosity allows
· Go Fast: We don’t do A/B testing – instead, collect information quickly and make fast decisions
· Be Transparent: Build a rapport with your user and be clear about your goals for user research
· Have Fun: Both user-want ideation (product and design) and implementation (engineering) can be extremely fun!
Check out how we use technology, processes, planning and rituals to build great products.
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