The need is identified. The problem is targeted. There are inefficiencies, sub-optimal performance, and engagement or utilization issues. We’re confident these problems can be addressed by creating a digital solution.
The digital solution will help compensate for the performance aspects that are slowing things down, diminishing uptake, or resulting in errors. Our digital solution will be able to send information or notifications, take in content, track, monitor, personalize, automate, scale. We can do all of this to make the user’s experience smoother, more efficient, and with enhanced outcomes.
This is where Design Thinking1 must enter the process. We know that a technology that doesn’t account for the psychological, cognitive, and behavioral factors associated with the end user will be less than optimal. As we are laying out the technology we must work iteratively to consider how this solution will interact and impact the user. Design Thinking “forces” us to not jump to a functional endpoint without considering all the factors in the environment that can have a significant effect on the solution itself.
We’ve accounted for the preferences of our direct users, down stream users, key stakeholders, and the clients. We have done A/B user testing, gotten feedback and it all seems to look good to go. We are ready to deploy the technology. But could we be forgetting something? Even with the careful solutioning, are we possibly missing an important factor?
The Curve of the Learning Curve
When we leverage a Design Thinking process, it’s common in the development and deployment of a technology to account for concepts like time and efficiency factors in implementation and user training. We may even specifically account for solutions that have small learning curves and others that require extensive training. Collectively, the time and efficiency curve that goes along with adoption of a new system or approach is the user’s learning curve. We know there will be one but one aspect of the learning curve that is sometimes missed is the impact of the curve itself. Does the process of adoption of the new solution cause the user stress and productivity issues as the user is forced to exist in two worlds (the new system and the old system)? Does the design shift the way the users physically work? Does it require them to do their work in a different order, at a different speed, with different steps? Yes, these are all factors our Design Thinking process accounted for and we can answer the questions. But all of these factors actually create a new factor that can be missed. Learning means we are asking the user to do things differently, not simply “learn.” We are asking them to pull in knowledge and work in a different manner. No matter how small, we are asking the user to engage in a phenomenon that is central to human behavior: Change.
Humans and Change
As adventurous as we may like to think we are, when it comes to our daily activities we enjoy predictability. As far back as 1967 Holmes and Rahe2 described how “good” and “bad” change could be disruptive in terms of producing stress. They coined the metric “life change units” to show how everything from going on vacation to getting fired, to having children, to experiencing a change in job requirements, to experiencing the death of a loved one, to celebrating a holiday could produce stress. The idea was that at the core change drove the stress. Pleasant and anticipated events still could be disruptive and thus result in perceived stress. Thus, even a “good” solution can have negative consequences in the short run because it results in a period of change. If that change period is not accounted for it could misrepresent how the solution is likely to be received, adopted, and utilized.
Solution Designs and Change
Even a solution that is well planned out, uses core principles of Design Thinking and accounts for the user’s psychological, emotional, and behavioral make-up may not account for the element of change itself that is being introduced. The duration from the introduction of the desired change to adaptation and adoption of that change is a period where inefficiencies, lower engagement, and misunderstanding of the solution can occur. Why should we care? So often we are not prepared for the level of disruption that a change can result in. Change itself can create an environment that is less than comfortable for the user, less than desirable despite the qualities of the solution and can result in a misunderstanding of the solution’s benefits. We may be prepared for the instruction, the training, the problem solving but we are not prepared for resistance, the struggle, and the slower than anticipated adaptation to change.
When we are designing a solution we need to be acutely aware not just of the efficiencies the solution will have once adopted, and not just how intellectually challenging adoption may be. But also the degree to which it will require users to do things differently than they are doing now. Afterall, even if different is easy- it is still different, and different means change. We need to map out exactly what the solution will require a person to do that is different than what they are doing now. We need to map out further how the change in design will change downstream behaviors. No matter how efficient a new solution is relative to the legacy solution – it is a shift in behavior set which means there is a decent probability there will be resistance to the change and an efficiency factor that is driven by the change itself, not only the intellectual learning curve. What we have to be highly cognizant of is that any change that “disrupts” even temporarily the flow of a routine for the provider, the patient, the caregiver, the support staff, the payer has the potential to create a fundamental shift in human behavior.
So, how can you apply this knowledge to your real-world Design Thinking?
- Account for the oft unaccounted for change variable.
- Design with change as a byproduct in mind.
- Design in a manner that gets to the end solution in an incremental fashion.
- Design with the understanding that in addition to the individual acquiring knowledge and information about what to do, they must do things differently.
In the end, doing something differently (i.e. change) is a variable that if not actively managed can reduce or even remove the efficacy of a new solution.
About the Author
Joshua C. Klapow, Ph.D. is a licensed clinical psychologist and behavioral scientist. Dr. Klapow’s research focuses on the study of health care products, services, and delivery systems and how the design of each interact with human behavior to drive health outcomes. He is the author of more than 100 professional articles, abstracts, and book chapters in the area of behavioral medicine and health psychology. He has made guest appearances on The Weather Channel, The BBC, and NBC Nightly News and is a contributor to Shape, Readers Digest, The Huffington Post, Men’s Health and a variety of print media outlets.
(1) Tim Brown. Design Thinking. Harvard Business Review, June 2008.
(2) The Social Readjustment Rating Scale”, Thomas H. Holmes and Richard H. Rahe, Journal of Psychosomatic Research, Volume 11, Issue 2, August 1967, Pages 213-218.
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