Making decisions as a UX designer is not an easy task. There are many things involved when it comes to decision making and, in this article, The Art of UX Design Decision Making, we will discuss in in-depth how decisions in UX design unfold and what are the components involved in this process.
This article will also tap into the following topics:
What is decision making
Most of the time, making decisions requires the evaluation of at least two alternatives that are different in several attributes. For example, you make decisions whether to place a bid on eBay or not, you are deciding which mobile plan you will be getting for yourself.
These are examples of selecting an alternative, which requires a person to combine multiple sources of information in order to form an overall evaluation for each of the given alternatives. How people search for information will provide UX designers with evidence of these decision strategies.
What Research Tells Us About Decision-Making
When it comes to decisions, quite often people do not have well-informed objectives and their preferences are quite influenced or adaptive in nature. Because of this, we can say that the way people decide is quite different from the common assumptions about how UX designers decide.
Science has greatly advanced our understanding of how human decision-making actually works. Luckily, we got a lot of advances in technology that enables us to see the brain at work while people make decisions. This technology provides us with research from different fields such as behavioral economics, behavioral finance, behavioral decision theory, neuroscience, cognitive psychology, and social psychology.
A lot of this research revealed that people’s decisions greatly differ from our common assumptions about how we decide in UX.
Several UX professionals observe that people are typically goal-oriented with very specific preferences. Thus, the task of UX researchers and designers is to remove the barriers between users and what they want.
However, research on user’s decisions shows people often do not have well-formed objectives, and their preferences can be easily influenced.
In this sense, we also need to be aware of the connection between decision outcomes and context, where users’ decisions are dependent upon the contexts within which people make decisions.
Context includes factors like the complex decisions, how experienced a decision-maker is, the number of options available, how the available options compare and relate to one another, and many others.
The Goal of Decision-Making
The goal of decision-making is to come up with the best outcome possible and with the least effort possible. These two factors: effort and outcome are pretty much connected to one another. The best decision outcomes usually require more effort
People, in general, are sensitive to the whole process of deciding because people find decision-making a piece of work. People tend to be lazy when it comes to exerting effort in making decisions. Unless given some incentive, people without a compelling reason for expending effort on a decision, will likely not be going to decide.
How decisions affect UX Design
When it comes to decisions, humans decide using the head and gut. And it is important to know how the head and gut function, keeping the following facts in mind:
The head and gut function in different ways.
The head is sometimes the active participant; but also, sometimes it is not.
Decision outcomes are largely dependent on the contexts in which people make decisions.
Since context is very involved in decision outcomes, it is essential to get things clear that there is no such thing as a neutral design since every design has an effect on decision making and usability.
How can we use this knowledge in user experience design?
Since context is very important to decision-making outcomes, it’s essential to be clear and confirm that there is nothing like a neutral design. UX professionals should be aware that every design affects usability and decision-making. This means that when no one proactively takes responsibility for designing for a good user experience, then expect to have poor usability as the result.
The same can be said in decision architecture. That in every web design affects users’ decision-making. Thus, to get good decision outcomes, UX designers should create designs focused on humans.
Additionally, a successful decision architecture also requires a consideration of both the head and the gut, knowing each difference and how they both interact with each other.
In the coming sections, we will look at the popular decision models or medium without considering probabilities, because we assume that a person has all the information needed to make a good and informed decision.
We will also discuss the steps in which the steps involved in decision making in user research design so you can get more sounding decisions.
Informed decision models
There are four models of decision making, which differ in terms of how
There are four models of decision-making that mostly differ with respect to how people search for relevant information that helps them make a choice.
They are:
Elimination by aspects
The elimination-by-aspects model has the advantage that it does not require any calculations – the cognitive load is low. The decision-maker simply selects an attribute (price, color, feature, etc.) according to some probability that depends on the importance of that attribute. Model #1 and #2 fall both into the basket of non-compensatory models, which are decision strategies that generally reject alternatives that have negative attributes, without considering their positive ones.
Example: of Elimination by aspect: Consider you are looking at digital camera or camera medium on Amazon and have only a certain budget to spend. You start eliminating the ones that are over your budget. By continuing to select attributes and reject those that do not satisfy some of your minimum criteria, you will soon arrive at your desired item.
Conjunctive model
The conjunctive model is an example of what is known as satisficing search. It is a strategy that follows the conjunctive model and therefore selects the first alternative that satisfies the minimum criteria for each attribute.
Example of Conjunctive model: Consider you are looking at cameras again, but this time notice that there are so many cameras available within your budget that you are just simply overwhelmed. You adapt swiftly your decision-making strategy by starting to go through each search result and selecting the first camera that satisfies all your minimum criteria.
Additive model
One problem with this decision-making model is that the rating of the attributes does not account for how the attributes might interact. A single product benefit or attribute from the examples listed above might be so important, that it compensates for a weaker rating of another attribute and vice versa.
Example of Additive model: Consider you are about to sign up for an online service such as Dropbox for file storage or Spotify for streaming music and are comparing two similar product offerings from two different companies (e.g. of app tools like Spotify vs. Apple Music, Dropbox vs. Box). You list all your important attributes and then rate each systematically with stars or numbers. You then pick the one that has the higher rating in summary.
Additive-difference model
This decision strategy is fairly similar to the additive model, but instead of summing up all scores to determine the relative attractiveness of each alternative, you determine the difference for every single score on each attribute. The sum of these differences determines which alternative is more attractive. Model #3 and #4 fall into the basket of compensatory medium models, which are decision strategies that allow positive attributes to compensate for negative ones.
Step process in decision design
Let us focus on Dr. Pam Brown's model of decision making, mainly due to the fact that this 7-step process is the most recent and widely used, in fields outside of design as well. The seven-step process is:
- Define the Problem
- Gather required log user data
- Develop alternative solutions
- Selecting the best type of alternative
- Implementation of the decision
- Follow up
- Learn and reflect
Define the problem
The first and foremost step in the process is to identify and define the real problem or risk. A problem can be explained as a question for an appropriate solution. Defining a problem statement in a human-centric way is essential, this requires you to frame your problem statement according to specific users, their needs, and insights that you have gained.
Gather required data
After defining the problem, the next important step is a systematic analysis of the available data. Understanding the context and its elements heightens awareness of the intensity of the situation. This involves consulting experts to find out more about the area of concern through observing, engaging, and empathizing with people to understand their experiences, interaction, and motivations, as well as immersing yourself in the physical environment so you can gain a deeper personal understanding of the issue or risk involved.
Develop alternative solutions
After defining and analyzing the problem or risk, the next step is to develop alternative solutions. You’ve grown to understand your user and their needs and you’ve analyzed and synthesized your observations. With this solid background, you can start to “think outside the box”(or inside) to identify new solutions to the problem statement you’ve created. The main aim of developing alternate solutions is to have the best possible decision out of the available alternatives.
Selecting the best type of alternative
After developing various alternatives, you are ready to select the alternative that seems to be the best for you, the context, and the company. Evaluate whether the need identified in the first step would be met or resolved through the use of each alternative. Evaluation should be based on a few selection criteria, and you should rank the ideas to how they meet the published criteria. These ideas selection criteria may help you frame your own
- Does it fit with the user’s needs?
- Does it really meet the goals set initially?
- Do we have access to the budget — enough to implement even partially?
- Is the technology or medium available?
As you go through this difficult process, you’ll begin to favor certain alternatives: those that seem to have a higher potential for reaching your published goal.
Implementation of the decision
Once you’ve made your decision, act on it! Develop a plan to make your decision tangible and achievable. Develop a project plan related to your decision. Planning the implementation is a sign that largely determines the project’s success because, without it, your strategic goals remain unactionable.
Follow up
A follow-up system ensures the achievement of the objectives. It is exercised through control. Simply stated, it is concerned with the process of checking the proper implementation of the decision. Follow-up is indispensable to modify and improve upon the decision at the earliest opportunity.
Learn and reflect
One of the most important steps of this process is learning through reflection. As human beings, we build up understanding through our experience and interaction in the world. But until we reflect — i.e, until we engage in explaining not just what we do, but why we do what we do — this understanding just remains “intuitive”. A mechanism should be built which would give periodic reports on the successes and failures of the implementation which you use to reflect and understand what went right or wrong and learn from it to make yourself a better designer.
Conclusion
Good product design decisions come from the balance between data and design intuition. That’s why it’s important to use both data-driven and data-informed approaches in product design. Think of data not as numbers but as something that supports your design decisions. Collect, analyze, and make design decisions in accordance with the data you have. However, do not forget to validate those decisions by testing them with your target users.