- Ted Nelson

Systems Theory for Designers

Equifinality, Multifinality, Unifinality, and Counterfinality

Introduction

Part of what makes methods from Psychology useful in design is that the goals for a psychologist and human-centered designer have a lot of over-lap. A shared high-level goal is that they both aim to model and predict human behavior. Open Systems Theory would call this relationship equifinal. The words equifinality, multifinality, unifinality and counterfinality are used to explain relationships, or links, between things. They are employed across a variety of different studies including psychology, business, archaeology, and geomorphology but are not used explicitly in the field of design. This article aims to provide an overview of these words as well as examples of how they can expand on designer vocabulary and be identified and used within existing systems ranging from Means-End Chains to Conceptual Models.

Equifinality : One event leads to multiple outcomes.

: One event leads to multiple outcomes. Multifinality : Multiple events lead to a single outcome.

: Multiple events lead to a single outcome. Unifinality : One event leads to a single outcome.

: One event leads to a single outcome. Counterfinality: An event that unlinks another event from an outcome.

“Information architectures become ecosystems. When different media and different contexts are tightly intertwined, no artifact can stand as a single isolated entity. Every single artifact becomes an element in a larger ecosystem.”

― Peter Morville, Intertwingled: Information Changes Everything

Equifinality and Unifinality

In Psychology, equifinality refers to the observation that in any open system a diversity of pathways may lead to the same outcome. This is a framework for viewing a persons behavior as a byproduct of many different circumstances in their lives (their living situation, ethnicity, biology, etc.). The principle of multifinality suggests that any one component of a system may function differently depending on the organization of the system in which it operates. In layman’s terms, equifinality means that multiple things are linked to the same thing, and multifinality means that one thing can be linked to multiple things.

Figure 1: Examples of Equifinality and Multifinality.

Put short- every pattern between events and outcomes are different depending on the context of the system- or the user. For example, the way someone selects a means might also be effected by values, beliefs, attitudes, or memories. Values guide actions and develop and sustain attitudes towards objects and situations. (Leão et al, 2007) Equifinal and multifinal relationships are not mutually exclusive as an event may be both equifinal and multifinal at the same time e.g. “get sleep” in Figure 1. These webs, or constillations, of multifinal, equifinal, unifinal and counterfinal relationships create systems, or ecosystems.

We can extend the terms equifinality and multifinality into product design by considering how they might fit in to goal systems. We can start with an overview about Don Norman’s gulfs of execution and evaluation to understand the relationship between Means and Goals.

Gulfs of Execution and Evaluation

Don Norman wrote in his book “The Design of Everyday Things” about two gulfs- The Gulf of Evaluation and The Gulf of Execution. He states that there are two parts to an action: executing the action then evaluating the results. Both execution and evaluation require understanding: how the item works and what results it produces. Both execution and evaluation can effect our emotional state.

Figure 2: Don Norman’s gulfs of Execution and Evaluation.

Users start with a goal and take from what’s available in the world (or, information system) to accomplish it. They then enter a, more or less, subconscious state of evaluation to determine if their goal was accomplished the way they expected (Figure 2). How can these means-goal relationships be studied from a top-down perspective in order to bring light to smaller goal systems existing within a greater system? For example, we can study how a user interacts with different information systems with the goal of finding entertainment e.g. Netflix vs. Hulu.

“Design is concerned with how things work, how they are controlled, and the nature of the interaction between people and technology.”

― Donald A. Norman, The Design of Everyday Things

Semantics in goal systems using Means-End Chain Theory

Dr. Sabine Matook, an information systems researcher, shared a similar mindset to Norman’s theories in her article “Conceptualizing means-end chains of user goals as networks” (2009). She validated the conceptualization and abstraction of goals in systems theory through the quote — “individual behavior is driven by personal motives which can be conceptualized in the context of an IS as user goals.” (Gutman, 1982) She stated that the use of an Information System (IS) depends on the value that an IS provides to the user by achieving a goal and went on to explain how an information system provides multiple means for a user to accomplish a variety of low, medium, and high-level goals.

Below is a model of a means-end chain for the online auction system, eBay. I should point out that all of these data-points (and the clustering of them) are drawn from user data available in Dr. Matook’s article. That is, the construction of this model is completely data-driven unlike the previously modeled chains.

Figure 3.2: Means-end chain network of user goals based on degree centrality for all participants (Matook et al, 2013). Each node represents a goal with it’s size

Within the model we can see a vast number of equifinal and multifinal relationships shared between nodes, similar to those seen explicitly in Figure 2. The network is structured based on importance and centrality. In Figure 3, we can see how the goals that are most important to the user are the largest in the model. The purpose of measuring importance (the size of the nodes) and centrality (their position/connections to other nodes) allowed Dr. Matook to gain an understanding of the immediate linkages a goal has with its direct neighbors. Thus, they were able to identify the goals that were most central in the local neighborhood.

What this provides is a method for mapping user goals when interacting with a system. Like a mental model, the relationships within this hierarchy are still subjective- as there may be differences in goal importance and goal positions per user or structure. That being said, the purpose of these models is to help understand and predict patterns in user behavior when interacting with a system.

Dilution and Unifinality

More important to the purpose of this article is how equifinality and multifinality are applied in Motivation Sciences. There is an article in the journal “Advances in Motivation Science, Volume 2” titled “The Architecture of Goal Systems: Multifinality, Equifinality, and Counterfinality in Means-End Relations” by Kruglanski et al (2015). This article references studies by Zhang et al., 2007 that were pivotal to how the user’s interpretation of things helps them choose a means, or system, toward achieving their goals.

One particular term of importance from the aforementioned article is the dilution effect which states that a multifinal means is perceived to be less instrumental due to it’s linkages with multiple goals. For example, a pen with a laser pointer is usually perceived to be less instrumental to the task of writing than a regular pen. It’s strength of association to any single one of it’s goals is diluted. A pen that is associated with only one goal is part of a unifinal relationship (e.g. writing), and is perceived to be more instrumental at achieving one single goal than a multifinal means.

Figure 4: If a user has a single goal (e.g. writing) then they are more likely to select a unifinal means

These notions were supported by six experiments by Zhang et al. (2007) including the pen example mentioned above. Kruglanski concluded from this research that although multifinal means may offer more value by serving more goals at the same time, if one cares about a single goal more than the others, multifinal means may be perceived as less instrumental than unifinal means and would ultimately fail to be chosen when pursuing that particular goal. (Arie W. Kruglanski et al., 2015)

Counterfinality

As designers we are often faced with the task of making something complex easier to use. One way to do that is by introducing counterfinality into a system. Counterfinality intentionally (or unintentionally) shatters links in a means-end chain. It is defined by Kruglanski as “the case wherein a means that serves a focal goal also undermines an alternative goal.” More important to this article, there is sometimes a need for a counterfinal means precisely because of its detrimental effect on other goals.

Figure 5: (a) Multifinality. (b) Equifinality. (c ) Counterfinality. Kruglanski et al. (2007)

The implications are that counterfinality may be able to reduce means-goal dilution. By introducing counterfinality you are able to make a multifinal system unifinal. It is like minimalism. Removing static or friction, or anything else that might grab at our attention while trying to accomplish a goal.

Implications

Counterfinality and Attention Capture

Attention capture is a phenomenon where a stimulus essentially captures our attention, affecting our response latency when completing a goal. “This thing captured someone’s attention”- simple enough to understand, right? In design, we have the ability to influence a system in a way that reduces (or improves!) attention capture from different stimuli. We can see this all the time in design, especially in the theory of visual hierarchy for U.I. or graphic design e.g. blinking advertisements on a webpage, or a shiny Call-To-Action that grabs our attention.

Consider the example from Figure 4. It’s possible that awareness of the laser pointer on the pen is the catalyst between choosing the regular pen over the one with the laser pointer. If the user were not aware of the laser pointer, it is possible that it would not have grasped their attention and they would be more likely to select the multifinal pen (the one with the laser pointer).

Mike Ambinder and Daniel J. Simons wrote about the theory of attention capture in their article “Attention Capture: The Interplay of Expectations, Attention, and Awareness” (2005) . Their study analyzed the influence of expectations, goals and strategies on both implicit and explicit forms of attention capture.

The purpose of addressing the aforementioned research is to state the hypothesis that if attention capture is quantifiable, then we can measure it’s effects on Means-Goal selection.

By this logic, I recommend research on the correlation between multi finality, counterfinality and attention capture. I hypothesize that if counterfinality is introduced into a multifinal system then attention capture will be reduced from stimuli unrelated to the focal goal.

Counterfinality and Progressive Disclosure

Progressive Disclosure is an concept from design where counterfinality is introduced to a system for the purpose of exposing the user to only essential information early so they do not get derailed during a process- revealing all content to them later once the process is complete. Counterfinality removes all means of achieving any goal but the focal goal, turning a multifinal system into unifinal. If you would like to see an example of Progressive Disclosure then check out the onboarding process for a MyNintendo Account. I conducted a heuristic evaluation on this system which can help explain how it functions (link).

Visual Vocabulary of Conceptual Models

In order to model high-level means-goal relationships we must first develop a visual vocabulary for defining these phenomena.

Jesse James Garrett of Adaptive Path wrote that a visual vocabulary is a set of symbols used to describe something (usually a system, structure, or process). In our case, we are trying to put a visual vocabulary around equifinality, multifinality, counterfinality, means, and goals- and they definitely already exist (as seen in the previous examples in this article). We have established a good starting point, and it is possible that we could build the architecture off of the visual vocabulary for conceptual models, mental models, mind maps, or even wireflows. We can already see how equifinality, multifinality, and even unifinality already exist in the visual vocabulary of conceptual models:

Figure 6: An example of Multifinality, Equifinality, and Unifinality being explicitly used in a conceptual model I created about the Semantic Web. (@ Kent State University)

By tinkering with these relationships e.g. by adding a new child to a multifinal parent, or reducing a multifinal or equifinal system to unifinal, we can examine different outcomes of the system. These systems would ultimately provide a different value to the user’s experience.

“Experience design is the design of anything, independent of medium, or across media, with human experience as an explicit outcome, and human engagement as an explicit goal.”

-Jesse James Garrett

Conclusion

Equifinality, unifinality, multifinality and counterfinality, if introduced to design, would open up new methods of ideation and innovation. Using top-down processing we can break an information system into a model that would allow us to toggle the relationships between means and goals. Reaching back to Don Norman’s model (Figure 2) we can develop a system that is more capable of helping a user reach their goal, improving the usability, or expanding on the abilities of an existing product.

Furthermore, having a name for the “arrows” in the “boxes and arrows” models that we as designers are familiar with, will allow us to talk about them at a high level. This vocabulary is also shared between other sciences (e.g. business and psychology) which makes it even more useful to apply these names. Knowledge can be more easily shared, and relationships between things more easily understood.

As designers, it’s important in our process to communicate a system’s design in a way others can understand. It would be especially useful if we are able to better communicate a system’s design in tandem with user goals. I have no doubt that with the onset of the semantic web, machines will be able to develop models of equifinal, multifinal and counterfinal relationships on their own. This makes it all the more important for us to be able to study them on our own in order to create better systems.

“Your customers don’t care about you. They don’t care about your product or service. They care about themselves, their dreams, their goals. Now, they will care much more if you help them reach their goals, and to do that you must understand their goals, as well as their deepest desires.”

-Steve Jobs

Sources

Ambinder, M., Simons, D. (2005). Attention Capture: The Interplay of Expectations, Attention and Awareness. Neurobiology of Attention. 69–75

André Luiz M. De Souza Leão, & Mello, S. C. (2007). The means-end approach to understanding customer values of a on-line newspaper. BAR — Brazilian Administration Review, 4(1), 1–20. doi:10.1590/s1807–76922007000100002

Garrett, J. (2002, March 6). Jjg.net. Retrieved February 12, 2018, from http://jjg.net/ia/visvocab/

Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of Marketing, 46(2), 60–72.

Kruglanski, A. W., Chernikova, M., Babush, M., Dugas, M., & Schumpe, B. M. (2015). The Architecture of Goal Systems. Advances in Motivation Science, 69–98. doi:10.1016/bs.adms.2015.04.001

Matook, S. (2013). Conceptualizing means-end chains of user goals as networks. Information and Management, 50(1), 24–32. https://doi.org/10.1016/j.im.2012.12.002

Norman, D. A. (2013). The design of everyday things. London: MIT Press.

Zhang, Y., Fishbach, A. (2007). The Dilution Model: How Additional Goals Undermine the Perceived Instrumentality of a Shared Path. Journal of Personality and Social Psychology, 2007, Vol. 92, №3, 389–401