4.4.1. Good UX Research Practice Versus Organization Orientation
It is possible to witness good UX research on the genius and participatory side of the data spectrum. Clearly delineating the difference between good UX research practice and
organization orientation, however, is problematic. The line between providing strong facilitation to drive UX deliverables and acting on behalf of the users is not easily drawn. The key to
understanding this challenge lies in making the distinction between facilitation of processes that lead to UX deliverables and business decisions about the contents of the UX deliverables. It is therefore necessary to differentiate three dimensions where facilitation and decisions about content may take place: collection, interpretation, and implementation. (Table 4.1).
Table 4.1.
Three Dimensions of User Data Handling That Occur Within an Organization
Dimension Process
Collection Gathering user data
Interpretation Translating data to system requirements
Implementation Integrating data & requirements with system
However, this differentiation is not obvious; interviews with user researchers employed by companies participating in the survey design indicated confusion about the difference between orientation and the common practice of doing user research. For example, a genius company may collect user data early on in the design process. The way it approaches and interprets user data will differ from how a participatory organization does these tasks. Both, however, are facilitating a research engagement. The confusion apparent in the interviews with UX research employees indicates that it is important to define the practice of facilitation before examining the three areas of collection, interpretation and implementation. Facilitation is a
structured process that is repeated, irrespective of the system that is being designed. It is a structured way to get data, a structured way to interpret data, and/or a structured way to implement data. Thus, it is related to the UX methods that are used to generate UX outcomes. Good UX research practice requires good facilitation. For example, using a card sort method is a form of facilitation to improve information architecture design. In the card sort method, data is obtained through asking users to place variables into categories (open or closed). This is a structured process that is repeated regardless of the system that is being designed. After users have placed variables into categories, the next step is to look at tree graphs or item-by-item matrices to interpret the data. Then, the last step in the card sort process is to generate some form of communication artifact to give recommendations on design direction to the development teams. This process demonstrates the concept of facilitation.
Facilitation takes place during all three dimensions where decisions about content may take place: collection, interpretation, and implementation. Collection occurs when the
organization gathers data about the user. Interpretation occurs in the act of translating the data collected into system requirements. Implementation occurs when the data and interpretation of the data is integrated into the system. Table 1 lists the three dimensions of user data handling.
How facilitation manifests in each of these three different dimensions reflects where an organization may fall on the User Data Spectrum, because it indicates how inclined an
organization is to interpreting on behalf of versus interpreting in collaboration with end users. For example, how might the card sort facilitation description differ in a genius design type of company and a participatory design type company (as described in Chapter 3)? During the collection phase of card sort, both a genius and a participatory company ask the user to place variables into categories (open or closed). A genius company may create the variables and prefer
a closed method because it will have made decisions on behalf of the user as to which variables needed to be considered. However, a participatory company may work with the users to create the variables that need be grouped and may prefer an open method.
Interpretation of the data is the next part of the process. After users have placed variables into categories, the practitioner looks at the tree graph or item-by-item matrix. A genius company may look at the tree graph and make a determination about the best information architecture to implement based on the analysis of data processed. However, a participatory company may include the users as it reviews the tree graph or item-by-item matrix and ask for confirmation of what the data is suggesting for the desired information architecture.
The last step in the card sort process is implementation. The goal here is to generate some form of communication artifact to give a recommendation on design direction to the
development teams. A genius company determines when, how, and where to implement the new information architecture. A participatory company may involve the user in deciding when, how, and where would be best to incorporate the new information architecture. In both cases, the company follows the card sort method. The difference is the degree to which end users are involved in the actual interpretation and implementation of decision making throughout the process.3
3 During the collection phase, the distinction between genius and participatory is less clear as
very few companies would collaborate with users to determine the collection items.The
propensity of an organization to involve the end user in those decisions is at the heart of the organization’s orientation.
4.4.2. Systems Knowledge Versus Content Knowledge
When looking at best practice, there is another dimension of design with versus on behalf of that needs to be considered. A user’s ability to effectively design with depends on two
variables, making four dimensions. The two variables are their knowledge about the system and their knowledge about the content of the system. Table 4.2 illustrates these four dimensions. Table 4.2.
System Versus Content Knowledge
System knowledge Content knowledge
Singular Global
Singular System singular
Content singular
System singular Content global
Global System global
Content singular
System global Content global
Note. These are the two variables that affect a user’s ability to participate in design. Users in the lower right corner are best for participation.
For example, if a company were developing a text-editing tool and wanted to take a
design with (more participatory) approach, then it would first need to consider whether the users understand the system of word processing. For example, do they understand the basic
functionality of text editing such as cut, copy, and paste functions? This is a purely technical understanding of these things. The other issue to consider is their content understanding. For example, do they understand the concept of cut, copy, and paste and how a user would need to use those functions? If the answer is yes to both of those questions, then the second variables need be considered. Do the users only know these things relative to their own experience with text editing tools or do they know them on a more global scale? For example, do they have an understanding of the 20 text editing tools in the industry today, their code structure, and the functionality they offer? I call this differentiation the singular versus global understanding. In summary, the two variables on four dimensions are system singular, system global, content
singular, and content global. If a company wants to pursue a design with approach (i.e., full participatory), it will be more successful if the users with whom it wants to design have a high global understanding for both system and content. The more the end user tends toward singular understanding, the more the company may need to consider less design with and more design on behalf of, moving it to the left on the User Data Spectrum.
To recap, orientation on the User Data Spectrum needs to consider the degree to which the organization’s philosophical perspective is collaborate versus create, in other words
designing with versus designing on behalf of the end user.