The current state of the UX experimental design process & the learning cycle CARI
What is experimental design?
When formulating an experiment, we consciously change one or more variables of the process in order to recognise the effect that the changes create on one or more hypothesis. The design of experiments (DOE) is an effective procedure to obtain data that can be analyzed and will serve for optimization not only of an initial hypothesis but also, to the evolution of the process in itself.
DOE begins with determining an initial hypothesis for an experiment and selecting the appropriate factors aiming to reach established outcomes for the study. The power of Experimental Design relies on a detailed plan in advance of undertaking the experiment. Well chosen experimental designs maximize the amount of information that can be obtained for a given amount of experimental effort.
How can DOE be applied to the UX Design process?
There are many factors to keep in mind when boarding a design challenge, from the initial question of: Is this a new product or the redesign of an entire and fully functional digital solution?
Departing from this initial course of action, many digital companies take on the approach that has proven to be valid and efficient on the past for their product cycle, and by doing so, they oversee the most important truth constantly present on the digital ecosystem.
Digital technology is morphing and evolving exponentially. We are currently on the threshold of experiencing new technologies like Machine Learning (AI), Virtual Reality (VR) and multi-device experiences, is the fourth revolution currently under progress. Automated physical systems connected through the IOT will define our society and eventually the way we take on our daily activities.
Based on this fact, the approach to planning and executing the creation of digital user experiences should be based on collaboration and learning about meaningful experiments that will gather critical data and information to support the delivery of an optimal, intuitive and efficient solution as the result of a well-structured design process.
By understanding there is no single path that will lead to an optimal result, but instead, there are multiple methodologies, processes, and strategies that can be mixed-matched according to the challenge being undertaken to aim towards fulfillment of information gaps and successful outcome delivery, any company can ignite the iteration of a cycle that will deliver compelling solutions.
The CARI cycle [Challenge — Action — Result — Iteration]
Many factors are to keep in scope when studying on a human-centred process build upon collaboration and inclusion for product investment that will conclude on continuous learning assisted by artificial intelligence, yet there are a few areas that can be explored and analyzed on the process of achieving a meaningful solution.
Only learning can match the current drive of technology progression.
In Conclusion
As digital intellectuals, we should apply our knowledge and curiosity not only to the challenges that we receive every day but also while questioning our own processes and strategies, implementing lateral thinking and aiming for more compelling results on the next iteration of our human-centred approach should be on the top of our to-do list.
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