Tension modeling as a UX research and strategy tool | by Stacie Sheldon | Mar, 2024


Who are we designing for? Let’s look at our personas

These days, personas take place in many different forms and under many different names. Archetypes, proto-personas, qualitative profiles, and just “personas” are used to identify who we are designing for and to what degree. However, being complex beings, we also have opinions, thoughts, beliefs, and needs that can not only oppose other’s, but also sometimes our own. This is where creating personas can get tricky. If two users have the same goal or are doing the same tasks, but have different needs, how might we better identify and understand the needs of each user, yet also account for the tradeoffs that come with it?

“How might we better identify and understand the needs of one user, yet also account for the tradeoffs that come with it?”

Inspired by the urban planning work of Richard Saul Wurman in the 1970s, The Understanding Group uses In/Tension modeling to document and visualize stakeholder priorities on a continuum to help inform architectural design and strategy alignment. Then they use voting sessions to identify where strategy and business tensions (or consensus) arise in the group and show the stakeholders’ anonymous votes as a visual to see where their opinions/priorities/thoughts lay among the group.

Conducting workshops and voting sessions are one way UX experts collect feedback and gather alignment, but they can be time and resource intensive. A more common method of collecting information is conducting stakeholder interviews. While conducting our own interviews, we saw an opportunity to evolve TUG’s concept of In/Tension modeling beyond creating real time alignment among stakeholders, and to use the technique to discover and visualize how data points across interviewees and across the research session can vary. During interviews, we noticed that there are always trade-offs and that these trade-offs are often not thought about by users. For example, in a modern digital experience users often want customization, and yet they also want privacy. Common in persona creation, these trade-offs often become the sacrifice of one user and a win for another, creating tension within a persona.

Implementing In/Tension modeling for a law enforcement agency helped us to uncover a ripple effect — when you solve one problem, other problems are naturally created. Our client experienced tensions when they implemented a take-home car policy in their agency. The intent of the policy was to give employees more flexibility in their schedule by allowing work cars to be taken home at the end of their shift instead of dropping them off at the station. During interviews a ripple effect emerged; the younger employees loved the perk of getting home sooner, while more senior employees thought it was a threat to culture and comradery. Using In/Tension modeling during our analysis allowed us to map out these layers of a decision and ask ourselves how we might balance out the In/Tension scales without hindering their progress, while also maintaining their spirit or sense of camaraderie.

These trade-offs often become the sacrifice of one user and a win for another, creating tension within a persona.

Two scales illustrating imbalance during moments of tension.
Above is a visual of the take home car example mentioned earlier. Research uncovered two opposing sentiments, “I want to take my car home from work every day” and “I want to go into the station to pick up my car.” The arrows show when one decision is made, there is a trade-off (or at least a compromise) that must be made. If employees can take home a car every day, they can get home sooner; however, the trade-off or compromise must be made to not have as much time spent with your squad with the possibility of not even seeing your squad each day. Source: Naman Mandhan

Asking ourselves ‘how might we’, paired with In/Tension modeling, gave us the following insights:

Insight #1: Through research, we were able to hear multiple points of view on how policy has affected employees. For some, it enhanced work-life balance, for others that same policy hindered camaraderie. Through In/Tension modeling, we were able to track these opposing insights, helping us to uncover that take-home cars are not the problem that needs to be solved. Rather, the real problem that needed to be solved is, how might we maintain camaraderie while still implementing the take-home car policy.

Insight #2: In/Tension scales provide us with a holistic perception of progress. As solutions to our ‘how might we’ questions were tested, we could start to see the scales even out. Helping the organization and its stakeholders see take-home cars was just a ripple effect from the real problem.

A scale displaying two conflicting viewpoints. ‘Take home car’ is on the left end, while ‘Building camaraderie with coworkers by not going to the office’ is on the right end.
Source: Naman Mandhan

Going a step further

In our law enforcement project, we found the In/Tension modeling to be an effective tool for communicating divergent points of view and addressing the ripple effect. In a subsequent project, we were not only able to scale this tool fourfold, but also leverage it to increase stakeholder engagement with the work. These scales provided a visual and approachable tool that brought along product and UX customers in synthesis of the findings and building of qualitative personas from interview data over 120 customers in 6 different countries.

The team started off by conducting the interviews with the goal of understanding current attitudes and behaviors towards vehicle technologies and features. As expected, we found several differences in how customers used and perceived the technologies in their vehicles, owing to variations in cultures, socio-political factors, and infrastructures. However, we also gained insight into several commonalities that existed between customers from different countries — these hinted at the core human beliefs that transcended the boundaries of countries.

As we gathered more voices, we started unearthing themes that the voices fell into. These included beliefs around the role of a vehicle in a customer’s life, attitudes towards privacy, and how customers felt about the future of autonomy in vehicles. The deeper we dug, the more we uncovered conflicts that existed within these themes — while some customers expressed a desire for more autonomy in vehicles, others didn’t want anything to do with it. While some didn’t pay attention to privacy, others wanted full control of it. Additionally, we uncovered a softer, but just as important middle voice. These were the voices that could see themselves in a future with autonomous vehicles, as long as certain practical considerations were met, or ones who understood what they were gaining when they gave up their privacy.

In/Tension modeling added structure to these conflicting viewpoints and visualized our understanding of the spectrum of attitudes and behaviors that customers had across different categories.

A scale illustrating two polarizing viewpoints on the role of vehicles in life. Emotional attitude is depicted on the left, while conflicting utilitarian attitude is on the right.
Source: Naman Mandhan

And this unlocked something truly powerful.

Unlock #1: It built a bridge between the qualitative nature of research synthesis and persona building, by providing an intermediary step that illuminated the conflicting viewpoints that can exist between personas. Now, instead of showing two distinct personas with conflicting viewpoints, we were able to show our customer how and why these personas came to be.

Unlock #2: It provided a path for Product Managers to see what solutions could help move the needle from one end of the scale to the other. For a Product Manager who was responsible for bringing more autonomous vehicle features to the road, it showed what practical considerations would help accelerate adoption. For the Product Manager who was responsible for the governance of privacy in vehicles, it illuminated what factors would make someone more accepting of technologies by addressing their privacy concerns.

Unlock #3: It allowed personas to become actionable and dynamic. Each In/Tension scale becomes a spectrum to identify each persona’s attitude toward a particular product. This keeps personas dynamic by tracking the possible evolution of each persona and identifying opportunities to support their transition of behaviors/mindset.

The solution to one problem is simply the creation of another. Because humans are inherently complex, there will always be something on the other side of the scale. As UX professionals, our goal is not to be right, but rather; less wrong. The best way to be less wrong is to continue identifying the ripple effects of a solution. That’s why using In/Tension Modeling is so powerful, especially in the analysis phase. For both automotive and public sector clients, this methodology helped us to visualize and communicate these In/Tension moments, ensuring that all perspectives were heard and represented in a variety of personas.

These visuals not only aligned us as researchers to identify different personas but also helped us recognize that conflicts exist within personas, holding true to the human condition.

However, that’s not where this method’s powers stop. Gaining insight into these differing perspectives, through personas, allowed stakeholders the opportunity to identify their larger goal and uncover the gradual steps needed to guide each persona to that goal. Paired with continued research this methodology also has the power to detect when some personas may have taken a few steps away from the larger goal, allowing stakeholders to identify the level of success of a product and assess the appropriate steps forward.

Harness the power of In/Tenson Modeling in your UX Work

In your reports

Let’s imagine that you are doing some stakeholder interviews within an organization about their Intranet. It is not just a fun or shopping website, it is an essential core tool for their organization. You find that stakeholders are willing to open up during the interviews and are straightforward about not liking change and not wanting the website to change. And on the other hand, you have people openly disparaging it and wishing it to change. Both of these voices are interesting and memorable. And when sharing research readouts it can be tempting to only note these strong voices. But as you can see here, when we really looked at the results and loaded them onto the scale, plenty of middle ground emerged. And this itself is an interesting story to share with your clients. It can also help identify opportunities for considering the impact to those who are resisting change and how the experience of a redesign could accommodate their needs.


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